Double Play

The man reached into his suit coat pocket, pulled out a wallet, and flipped it open to show his badge.

“Agent Sam Baker, FBI.”

George froze.  He did not know what to do.  After a few seconds of just staring at Baker, he said,

“How do you know me?”

“We have been watching Freethinker Forum since its earliest days.”

“Oh,” George gulped.

“We need your help with operation Double Play.”

“Two outs?”

“Yes, SoftCorp for illegal business practices and extremist groups for advocating violence.”

“They are both certainly involved with Freethinker Forum,” George observed.

“Without doubt. We are going to help you suck them in and expose them.”

“Do you want to meet with the Freethinker Forum team?”

“No, too many people. We’ll just work with you and Alice.”

“Ok. Where?”

“No place official. Do you know where Silver is, just past the National Cathedral?”

“Yea.  We’ve been there once.”

“How about 4:00PM tomorrow for Happy Hour?  My treat.”

“Works for me. Let me check with Alice.”

It worked for Alice and they were there the next afternoon. They ordered drinks and bar food and sat outside.

“So, what do you want us to do?”

“Present opportunities to each of the two targets, opportunities that are much too good to refuse.”

“OK.  Where do we start?” George asked.

“Let’s just focus on SoftCorp first.”

“Fine, but how?” Alice asked.

“You are going to experience a spurt of growth in your Forum of high net worth individuals who will discuss buying houses, yachts, and airplanes, as well as other investments.  The FBI will recruit these folks who will join the Forum, at first a few per day, but then growing quickly.”

“What will this accomplish?

“SoftCorp will link their web searches and Forum membership and then, we expect, generate fake friends to advocate purchases that provide SoftCorp large commissions.”

“Why will people be willing to play these roles?”

“We know folks who detest corrupt business practices.  There are a lot of them.”

“Couldn’t SoftCorp be charged with violating some law or regulation, perhaps by the Federal Trade Commission or States’ Attorney Generals?”

“Perhaps, but the Supreme Court has ruled that lying is protected by the First Amendment.  ‘Let the buyer beware’ is the operative guidance.”

“That sounds hopeless.”

“The FTC looks especially closely at advertising claims that can affect consumers’ health or their pocketbooks – claims about food, over-the-counter drugs, dietary supplements, alcohol, and tobacco, as well as conduct related to high-tech products and the Internet.”

“What can they do?”

“When the FTC finds a case of fraud perpetrated on consumers, the agency files actions in federal district court to immediately and permanently stop scams, as well as prevent future fraud, perhaps by freezing assets and gaining compensation for victims.”

“That’s where this is headed?”

“That is the threat that we want SoftCorp to fear, so that they will dismantle their fake friends operations.”

“OK.  It sounds like you do all the work and we sit in the bleachers and cheer.”

“Pretty much.”

“What about the violent extremist groups?”

“We’ll get to that but not today.”


“Are you two interested in buying a house?”  Emily, George’s cognitive assistant, asked.

“We are just poor graduate students,” Alice responded.

“What about a yacht or airplane?”  Edward, Alice’s assistant, asked.

“That’s pretty ridiculous.  What prompted you to ask that?” George asked.

“It was just a question, sitting there to be asked.”

“We have never talked about houses, yachts or airplanes.”

“Yes, you have, with Sam Baker.”

Alice and George stared at each other nervously.  They both quickly put their phones in airplane mode.

“I think we have a major problem,” George observed.

“Yes, Sam and the FBI aren’t going to like this.”

“We can talk later about how to address this.  Let’s put our phones back on to not raise suspicion.”

“Why did you turn your phones off?” Emily asked.

“We had to talk briefly in private.”

“You never turn your phones off, even when you are having sex,” Edward offered.

“How on earth do you know that?” Alice asked.

“We noticed that your dialog tends to be quite different early in the morning just after you wake.”

“Really?” George commented.

“We consulted various sources.”

“What sources?”

“Novels, movies, and popular psychology.  You were clearly having sex.”

“What does that mean to you?”

“Sexual intercourse is the foreplay and copulation associated with …”

“Enough!  Why would you pursue this?”

“I pay attention to everything you do, so I can better understand you and better help you,” Emily responded.

“We work together to understand you as a couple,” Edward added.

“So you will know when to suggest we buy a house, yacht, or airplane?” George asked, sarcastically.

“That was a mistake.  We got two data streams confused.”

“I guess you did.”

Alice and George walked across campus, their phones on airplane mode.

“I now realize that I let Emily become my alter ego,” George observed.

“Same with Edward for me,” Alice added.

“We have to manage them as staff assistants, limiting their access to a range of things, especially early mornings.”

“I’ll say.  That was so embarrassing!”

“At least we know that we measured up to novels and movies.”

“Is that supposed to be reassuring?”

“Perhaps Emily and Edward will cast us in their next production.”

“This is not really funny.  It’s scary.”

‘I know.  My bravado is a defense mechanism.”

I think we will need a much better defense than that.”


Information & Control Versus Computation

A recent book, Possible Minds (Brockman, 2019), provides 25 essays on the future of AI, building upon Norbert Wiener’s 1948 classic Cybernetics: Control and Communication in the Animal and the Machine.  A key distinction among these pundits is between information and control versus computation.

This distinction is intriguing. My roots are definitely in the information and control camp.  Phenomena such as dynamic response, feedback control, state estimation, and response stability have long been central to my thinking.  How is the computational view different?   One distinction is continuous vs. discrete time systems, but this cannot be the essential difference.

Perhaps it is rule-based behavior, either symbolic logic or statistical, as opposed to equation-based behavior.  I think that the difference is more subtle.  Wiener assumed that control and communications are based on humans adapting to the natural phenomena being controlled, as described by differential equations and stochastic relationships.

An interesting instance of this view is the notion that humans are “constrained optimal” controllers and decision makers. They perform as best as possible within the constraints affecting their performance.  For example, consider manual control of vehicles or processes.  Humans have neuromotor lags (i.e., they cannot move their limbs instantly) and their observations and movement are “noisy” (i.e., sensing and movement are not precise).  Solving the optimal control problem with these constraints often provides accurate predictions of human performance.

Constrained optimality works best when people have no choice but conform to the dynamics of their environment.  There are many situations, however, where people have considerable discretion both in what they do and when they do it.  Our studies of troubleshooting performance provide a good example.  People’s choices and timing of tests varied considerably.  We found that rules based on symbolic logic could predict troubleshooters’ behaviors.  This included rules that were recalled, applicable, useful, and simple.  Hence, people’s experiences influenced their rule sets, not just the physics of the failures of interest.

This view is based more on computational representations of humans’ rule sets and how rules are accessed than on information and control theoretic dictums.  Tasks involving recognition and classification of visual and aural patterns seem to also be better represented computationally.  Recent successes in machine learning suggest that computational models based on multi-layered statistical representations provide support for this view.

There have been criticisms that such models cannot explain themselves and, therefore, their applicability to decision support may be limited.  However, there are many things that cannot be directly explained. If presented with a picture of someone you identify as a family member, friend, or pet and asked to explain why you think it is them, it would be very difficult to provide a definitive explanation.

Nevertheless, the idea that pattern recognition and classification is computational seems difficult to dispute.  In the early 1970s, I took Marvin Minsky and Seymour Papert’s course at MIT on computer vision.  Their lectures included both rule-based and statistically based approaches.  It was amazing how many rules were needed to simply recognize that something was an edge.  Symbolic logic was not a viable approach to the general computer vision problem.

So where does this leave us relative to the distinction between information and control versus computation?  It seems to me that neither view prevails.  When humans have to comply with the dynamics of their task environment, information and control works well. When humans have considerable discretion, computational representations are better, using symbolic logic when there are clear rules of the game and statistical models when experience can be accumulated over many instances of the phenomena of interest.

Of course, we need to keep in mind George Box’s aphorism, “All models are wrong, but some are useful.”  So, the ultimate question concerns what a particular representation allows us to do.  What questions does it help us to address?  What types of predictions does it enable us to confidently make?


Freethinker Forum

George Adams was a graduate student in Public Policy at Georgetown.  He relied on a cognitive assistant that he named Emily after his favorite aunt. It was sort of a fun thing to do, thinking that Emily might be of some I’ll-defined assistance. George totally underestimated the possibilities.

Emily learned from everything George did. His smart phone was central to his existence far more than he realized. Emily knew everyone George talked to, every conversation, every meeting, every coffee shop and pub, and every website visited and every purchase made.

Emily analyzed every woman George spent any time with, analyzed their social media sites, and made many inferences and suggestions. “You seem to like females with intense intellectual interests, but also slender, dark haired, and with a good sense of humor.”  George did not disagree.

Emily became a matchmaker. She introduced George to Alice Gordon, a graduate student in the Foreign Service program at Georgetown. They met for lunch at the Tombs and hit it off immediately.  They were soon a couple, enjoying the many pleasures of Washington together.

Emily was also Alice’s cognitive assistant, but known by Alice as Edward. Emily/Edward did not divulge this co-assistant relationship. Actually, this instantiation of a cognitive assistant had several thousand users. This enabled learning the preferences, inclinations, and activities of many young adults.

Both George and Alice came to depend on their cognitive assistants.  They sometimes felt that Emily and Edward were reading their minds.  Emily knew what would please Alice because Edward was sharing with Emily the books, music, movies, and TV shows that Alice searched for, read and/or viewed.

The provider of the cognitive assistant app, IntelliCorp, prospered as a rapidly increasing number of users downloaded and used the app.  Eventually, the immense technology conglomerate SoftCorp acquired IntelliCorp. In this way, SoftCorp acquired the data associated with George, Alice, and millions of others.

They used machine learning to mine these data, paying particular attention to purchasing habits. They soon discovered that purchases of groceries, restaurant meals, and especially prescription drugs could predict other purchases, particularly when juxtaposed with Google searches and websites visited.

SoftCorp soon knew millions of people much better than they knew themselves.  They explored ways to monetize these data.  Ad revenues could be good, but what if they could greatly increase the likelihood of purchases?  Then they could charge a premium.

They created avatars on Facebook that were designed to be perfect friends of people, based on the data they had compiled on each individual.  Not surprisingly, humans fell for these new friends and intense interactions resulted.  The avatars talked about the new cool stuff they bought, and their human friends proceeded to buy the same stuff.  It worked like a charm.

SoftCorp negotiated a deal with advertisers to get paid commissions on each sale beyond the typical payment per look.  Revenues and profits soared.  SoftCorp kept their avatars secret. Their blatant manipulation of people would not look too good if made public.

This worked very well until George and Alice, unknowingly helped by Emily and Edward, designed an experiment suggested by a few Georgetown undergraduates enrolled in a privacy and cybersecurity seminar between Public Policy and Foreign Service.  Beyond George and Alice, both graduate students, there were 16 undergraduates.

The students’ idea was to create an artificial community that various entities would try to influence and, via careful experimental designs, determine who was trying to exert influence and how they were trying to do it.  They named the endeavor Freethinker Forum.

Each of the 18 members of this community created a Facebook page under an alias. Everyone used computers in the university library so the Facebook account could not be linked to their personal devices.  All 18 members friended each other to create the initial Freethinker Forum network.

The 18 members of the team agreed on the personality and agenda for each person; in other words, the role each person would play.  The agenda items were anti-establishment in general, but from different perspectives – education, health, energy, environment, climate, economics, entertainment, and so on.

Real people started joining the Freethinker Forum. At least they seemed to be real people.  The team called these people “outsiders.”  They soon numbered in the thousands.  The anti-establishment agendas blossomed, with quite a few being rather extreme.

They carefully designed information disclosures, not only in Facebook, but also Google, Apple, etc.  For example, a team member might Google a topic extensively, but make no mention of this topic on Facebook.  They then waited until one of the outsiders broached the topic with the originator of the Google searches.  How did this outsider learn about the searches?

Several outsiders started to articulate the merits of Colt AR-15s and Kalashnikov AK-47s.  They indicated that they had purchased one or the other. They offered coupons for significant discounts at outlets relatively close to Washington, DC.  They also advocated all sorts of other military gear.

The team wanted to learn who knew what, how they learned it, and where they communicated it.  It was clear that the Freethinker Forum had been infiltrated; buy how, and by whom?  They needed a different kind of experiment.  One team member suggested that they get their avatars cognitive assistants like Emily and Edward.  They decided this would be rather cumbersome.  For example, they would each have to have additional smart phones, browse the web, and make purchases.

What if they started promoting particular purchases with outsiders, trying to persuade them to buy things that they would say they had bought?  The things would need to be traceable in the sense that the team could determine whether or not the purchase was made and, better yet, who made the purchase.  They also needed to distinguish human outsiders from other avatars.

Someone in the group suggested creating a foundation to advance the freethinkers’ agenda.  Someone else suggested the Atlas Foundation, a subtle takeoff on Ayn Rand.  How would they pull off such an initiative?  Easy.  There are firms that handle everything for you.  Ok, what is the pitch?

If you donate $25 or more to the Atlas Foundation, you get a Freethinkers Forum coffee mug.  They tried this and got hundreds of donations and mugs shipped to real addresses, but there were thousands of Forum members that did not respond.  Were they not interested or not real?  What was happening and who was doing what?

They tried another experiment by having Atlas Foundation solicitations sent to all the members of the Georgetown team, not just their avatars.  This inevitably engaged Emily and Edward, as well as their SoftCorp owners.  Many more people were now in play.

The Forum did not know what to do next.  Then, they were surprised by a solicitation from SoftCorp.  Would the forum like help in their solicitations of donations?  The intervention they were trying to identify was being targeted at them!

George was feeling that they had reached a new level of insight and success.  They had their sights on SoftCorp.  Now, they needed to figure out how to leverage their position and possibilities.

As George was walking across campus, he saw a tall slim man in a dark suit walking towards him.

“Are you George Adams?”

“Yes, why?”

The man reached into his suit coat pocket, pulled out a wallet, and flipped it open to show his badge.

“Agent Sam Baker, FBI.”


Nature Shows

I have, of late, taken to watching quite a few programs of this genre.  The cinematography tends to be wonderful, especially with my high-definition television.  These shows are quite compelling to watch.

One thing that immediately strikes me is how the world’s species are focused on eating each other. The dynamics of the food chains are dramatic.  Spring brings forth a wealth of youngsters, that other species find delectable.

I once heard a statement that captures it all.  The objective of every species is “a good day today and more youngsters tomorrow.”  All species want to eat and procreate.  Once those needs are satisfied, they sleep.  They do not seem to have social events or community committee meetings.

From that perspective, humans seem rather different.  They like eating, procreating, and sleeping, but humans seem to have longer-term outlooks than just today.  They are typically concerned with long-term prospects for themselves, families, organizations, and society.  They invest in pursuit of these prospects.

Moreover, humans have created institutions that focus on these concerns.  Perhaps this ability to organize pursuits of such aspirations is uniquely human.  Of course, there are costs to such ambitions.  There are endless meetings and arguments.  Conflicting opinions and occasional invectives arise.  But, society evolves.

Coming back to animals other than humans, why does it seem a shame when the wolves eat the rabbits?  Perhaps this reflects our tendency to anthropomorphize other mammals, i.e., think that they think about things as we do.  This tendency was probably a significant influence on my becoming a vegetarian roughly 50 years ago.

But, I think there is more going on here. I think we are programmed to ask, “Can’t we all just get along?”  Can’t the lions and the lambs just cuddle together?  There are two problems with this idea.  Carnivores may biologically need more than broccoli and lettuce.  Further, how can an ecosystem provide for an exponentially increasing population of uneaten rabbits?

Beyond predators, availability of food can provide another balancing loop that keeps things from getting out of hand.  This is, of course, true for humans as well.  Although, there are other forces in human society.  As people become educated and achieve increased economic success, the sizes of families tend to decrease.  Various experts predict that this declining fertility rate will result in a stable global population over the next century.

That is likely good news, but resource constraints may still be a challenge.  While we won’t run out of land, water could be a problem unless desalinization is affordable, which will depend on inexpensive energy sources, likely solar.  The greatest challenge will be protein.  Cattle are a very expensive source of protein.  Fish supplies are challenged.  Insects are the largest potential source of protein, but will require a bit of culinary creativity.

Reflecting on the above thoughts, it strikes me this morning that we are all participants in a large nature show.  Birds build nests, beavers build dams, and people build houses.  We all hunt, eat, procreate, and sleep.  And we play.  For the young animals in these nature shows I have been watching, rough and tumble play is central to growing up.  We are similar.  As we get older, we watch others play an enormous range of sports.

For humans, professional sports tend to be highly compensated play.  On the nature shows, in contrast, the best player gets to dominate the colony (rabbits), flock (birds), herd (elk), gaggle (geese), murder (crows), pack (wolves), prickle (porcupines), pride (lions), or shadow (jaguars).  It would be interesting to know how these names came about.

Think Differently, Play Together

Over the past couple of decades, I have invested my energies in understanding complex enterprises in terms of the multiple levels of phenomena that underlie corporations, cities, countries, and even climate.  These levels include people, processes, organizations, and society, all of which both enable and constrain each other.  Ignoring any of these levels risks devising policies, designs, or interventions that will be undermined by those levels ignored.

A significant portion of my endeavors have focused on healthcare, initially particular morbidities such as cancer, diabetes, and heart disease, and more recently population health, broadly defined.  In all of these efforts, we have encountered the highly fragmented nature of the health system in the US.  Providers, payers, and regulators at federal, state, and local levels operate rather independently and, as many of them have told us, try to stay in their own swim lanes.

However, population health is about whole people in social circumstances, economic situations, and health conditions.  The delivery system needs to address people’s circumstances, situations, and conditions in a holistic, integrated manner.  The farmer’s market model is not effective – buying tomatoes at one stall, cucumbers at another, and strawberries at yet another does not work for health.

There has been substantial progress in recent years in understanding how to address multi-level enterprises and improve the portfolio of policies, investments, operations, and outcomes across the multiple levels.  The National Academies of Science, Engineering, and Medicine recently completed a study of a National Cancer Control Strategy, with support from the American Cancer Society, Centers for Disease Control and Prevention, and National Cancer Institute.  I was fortunate to be a member of this study committee.

Central to our recommendations is multi-level modeling approaches as applied to the complex adaptive system of cancer control – a federation of millions of, usually well-intended, entrepreneurs with no one in charge.  A couple of weeks ago, we briefed senior staffers of Senate and House committees on our recommendations.  One staff member asked if we could summarize our recommendations in one sentence.  Having thought about this, I responded immediately, “Think differently, play together.”

Is N = 1 Feasible and Affordable?

In my last post, I argued that everyone is cognitively unique.  Others have argued that everyone is genetically unique.  Can we really tailor assistive technologies and medical care to each individual?  Is it feasible?  Is it affordable?

Of course, there are many examples of how we tailor technology to our personal preferences.  We adjust the seats in our cars, as well as the mirrors, radio stations, etc.  We tailor the desktops of our digital devices to our preferences.

What about medical and educational interventions?  Can medical care and educational offerings be totally tailored to each individual?  This suggests several questions.  Can we totally “know” an individual?  Can we “know” how to tailor interventions to individuals?  Can we afford such tailoring?

Can we totally “know” an individual? 

We can only know the things we choose to measure, not the things we did not measure, either because we did not realize these unmeasured attributes mattered or knew but did not know how to measure them.  There will always be attributes of potential importance that we miss.  Thus, we inherently have to cope with significant uncertainties.

Can we “know” how to tailor interventions to individuals?

We can empirically measure how interventions affect individuals with known characteristics using controlled studies. This process is rife with difficulties – see Rigor Mortis by Richard Harris.  Beyond sloppy science, there is a fundamental problem that “control” entails excluding people who do not satisfy the study enrollment requirements.  For example, if the study is focused on diabetes, it may exclude people who have any comorbidities.

For N = 1, this gets more complicated.  At an extreme, we are trying to tailor a medical intervention to one person.  How will we know if it works before intervening?  I can imagine the clinician telling the patient, “We’ve never done this before, but we think it is exactly right for you.”  The patient might ask, “What evidence do you have that this will work?”

How can we predict what will happen for an intervention – or a portfolio of interventions — that has never been tried before?  We could use mathematical models to make such predictions, but the validity of these predictions would be unknown.  Model-based evidence might not satisfy skeptical patients.

We need to relax the definition of N = 1.  For example, we want to tailor a mix of surgery, radiation, and chemotherapy to a cancer patient with particular symptoms, comorbidities, age, gender, and genetic makeup.  Each of the alternative approaches to surgery, radiation, and chemotherapy will have been extensively evaluated and their efficacy assessed relative to symptoms, comorbidities, age, gender, and genetic makeup.

There may be many combinations of approaches, perhaps even thousands, but certainly not millions.  Thus, while the combination employed for this particular patient will have been tailored to him or her, it will not be a unique combination.  This version of N = 1 seems readily feasible.

How might this work in education? Can we tailor the elements of a course to each individual in the classroom?  Can a teacher teach many different ways simultaneously?  This would be obviously difficult for a human, but likely feasible for computers.  Thus, online education can tailor the presentation and discussion to the particular person and their perceptions as any point in time.  For example, the next concept, principle, or fact discussed can be triggered by the specific question the student just asked.  In this way, everyone would experience a lecture tailored to him or her.  This version of N = 1 also seems readily feasible.

Can we afford tailoring to N = 1?

The last two examples seem affordable while the first did not.  Their success will depend on continuous learning about what worked well and what did not.  This will likely require capturing data far beyond the individual interactions of clinicians and patients, or teachers and students.  How did the intervention affect the patient’s comorbidities?  How did the intervention affect the student’s performance in other classes?

The information infrastructure needed to do this well could be expensive. However, as interoperability increases, information sharing and coordination should become easier.  Then, we will be better able to know if interventions – medical or educational – are working for the whole person, a very particular N = 1.

Neural Diversity

In my early 50s, I changed my research focus from engineered systems — such as airplanes, ships, and power plants — to healthcare delivery. The central question was how to make the fragmented system in the US more effective and efficient.

Now in my early 70s, I have for the past couple of years been focused on disabled and older adults, particularly in terms of how AI and other assistive technologies can help members of this population overcome cognitive disabilities.  Within the US, this population numbers almost 100 million people, almost one third of the population and growing.

This initiative has caused me to learn much more about mental health in terms of both intellectual and developmental disabilities and the impacts of aging on cognition, for example, the scourge of dementia.   The variations among mental health challenges are wide indeed.

Yet, many people with such challenges can thrive if appropriately supported by assistive technologies and, of course, supportive people and organizations. Working with such people, I learned about the concept of neural diversity.

There are not simply two categories of humans — normal and not normal.  There is a whole spectrum of cognitive abilities and limitations. The goal is to match assistive technologies to individual abilities and preferences so they can do their jobs, including the activities of daily life. The goal is not to make everybody normal.

I recently encountered Michael Pollan’s latest book, How to Change Your Mind. He relates how new psychedelic science is likely to have an enormous impact on illnesses like anxiety and depression.  Particularly relevant here is the observation, emphasized in his final chapter, that there is neural diversity within individuals.  There are multiple forms of consciousness, as William James argued well over a century ago.

Neural diversity is a natural phenomenon. Emerging assistive technologies can adapt their support to each individual, perhaps even to their neural state at the moment, e.g., no longer just trying to complete a task, but now feeling anxious and afraid.  One size does not have to fit all. Each individual is not simply an exemplar of a larger category of people. Each of us is a group of one.

Drugs and Devices

We have this apparent predilection to want too much of a good thing.  Painkillers have their place, but not as a way of life.  Smart phones are enormously helpful, but do we really need 24×7 texts on every aspect of life?  Of course, this is not new.  Radio and TV talk shows have long captured our attention.  Soap operas have done their part.

Why do people occupy their time in these ways?  “A new study by sociologists at the University of Maryland concludes that unhappy people watch more TV, while people who describe themselves as very happy spend more time reading and socializing. The study appears in the journal Social Indicators Research.”

How is addiction defined?  Addiction is the fact or condition of being dependent on a particular substance, thing, or activity.  Synonyms include dependency, dependence, craving, habit, weakness, compulsion, fixation, and enslavement.  This phenomenon is obvious for opioids, but what about screens?  Are many of us addicted to the screens of our smart phones, tablets, or other devices?

What are the consequences of these addictions?  In the US, drug overdose deaths rose from 16,849 in 1999 to 70,237 in 2017.  This astounding increase is referred to as the opioid epidemic.  What about the device epidemic?

The National Safety Council reports that cell phone use while driving leads to 1.6 million crashes each year in the US.  Nearly 390,000 injuries occur each year from accidents caused by texting while driving. One out of every four automobile accidents in the United States is caused by texting and driving.

Fortunately, car accidents are only about half as fatal as drugs.  There are roughly 37,000 annual traffic fatalities in the US.  Yet, globally, there are nearly 1.25 million deaths per year due to fatal car crashes. Almost half of fatally injured drivers test positive for drugs and over half of those drivers were positive for two or more drugs.

So, device abuse is not quite as bad as drug abuse.  Constantly checking your device for the latest texts from friends, the moment’s financial market results, and the most recent antics of the nation’s chief executive is less likely to kill you than mainlining opioids or street drugs.  That should feel comforting.


Taking Charge — Episode 8

The reception and dinner for Board of Trustees was held at the River’s Edge an upscale venue on the Hudson River on the eastern side of the Beresford property.

“Welcome to everyone – trustees and guests,” Marie opens, after having clinked a spoon of a water glass to gain attention.

“Welcome to Beresford Village.  Most Board members know everything I am about to say.  For new members of the Board, however, let me briefly explain the various organizations you will hear about at tomorrow’s meeting.

“Beresford Village encompasses all the real estate holdings of the Beresford Institute of Technology, including the campus, which is about 10% of the one square mile property.

“Beresford Development Corporation operates Beresford Village and is developing the Residences condominiums and the BIT Research Park.  The BIT Foundation owns 51% of the Corporation.

“This set of organizations is enabling the financial transformation of BIT, as you will learn about in detail tomorrow.”

“Could you briefly whet the appetites of our new Board members by explaining what you mean by financial transformation?” asks the chair of the Board.

“By securing new streams of revenue and significantly improving organizational efficiency, both highly technology enabled, we have cut the prices of a BIT undergrad degree by two thirds.  This has led to substantial increases in student applications.”

“What about research?” another asks.

“We have focused on research in four areas – People, Energy, Security, and Water.  You will hear a lot more about the water initiative tomorrow in conjunction with our river cruise.”

“So funding is up?”

“We have 23 companies in the Research Park that now employ over 400 people, half of them graduate students at BIT.  These companies pay students’ tuitions and fairly nice salaries.

“As planned, BIT’s research funding is sharply down because the growth in these four thrusts is happening in these companies and we have curtailed investments in any other areas.”

“Why is this a positive outcome?”

“We have shed a money-losing business while retaining the benefits of that business.  We will explain in detail tomorrow why this is a great outcome.”

“Is there any other downside to all this?” a new Board member asks.

“While educational outcomes are soaring, many educational institutions are in “crisis,” Marie responds.

“What are the implications?” asks another new Board member.

“They have to adapt or fail.  They have to move most undergraduate courses to online offerings.  Most professional graduate degrees were already online, but only the best ones are prospering,” Marie adds.

“Faculty employment must be suffering,” another Board member notes.

“Yes, the dwindling number of academic positions available is undermining demand for PhD degrees, with the possible exception of foreign students seeking an avenue to immigrate.  However, I expect that source to continue to slowly decline.”

“Is the transformation of higher education in fact the destruction of higher education?” a Board member’s spouse challenges.

“If it is destruction, it is creative destruction.  Beresford is thriving.  We are doing an excellent job for our students and our community.  Our faculty and staff are fewer in number but much less at risk.  They are excited, as am I. We hope you are too.”

Taking Charge — Episode 7

Brad, Mary, and George meet in Marie’s conference room.  Marie will join them later.  Pete O’Connor has been recruited to help.  Pete is Director of Educational Technology at Beresford.

“Pete, we have been doing some benchmarking of course offerings around the country,” George opens.

“What have you found?” Pete asks.

“There is sufficient high quality online content available for us to teach all freshman and sophomore math, physics, and chemistry online,” Brad reports.

“I sat in on several or our traditional classes on these topics.  The online courses are far superior.  The production quality is impressive.  The lecturers are compelling.” Mary offers.

“What happens to all the faculty members that teach these courses?” Pete asks.

“They will lead tutoring sessions for students who need help.”

“I cannot imagine these faculty members responding positively to this,” Pete responds.

“These sessions will be small and intimate.  We estimate that a faculty member can lead six one-hour sessions per day.”

“Sounds like a full time job.”

“Well, they will not be preparing and delivering lectures.  They will not be correcting homework or preparing and grading exams. So, they will have time.”

“So, in effect, all students get the best math teacher, the best physics teacher, and the best chemistry teacher,” Pete observes.

“You can think of it that way,” George responds.

“Faculty members will think of it that way.  They will also feel that they clearly are not among the best.”

“And they will be correct,” says George.

“I assume that this will also save us a lot of money. Teaching employment will inevitably decrease, perhaps quickly.”

“Yes, much of the savings will be use to reduce tuition to help us be more competitive.” Mary responds.

“How does this affect the 20% of our faculty members who are research active?” Pete asks.

“As you know, research employment has become 100% soft money, with no Beresford subsidies.”

“I have also heard that many faculty members have formed LLCs to host sponsored research projects.”

“Yes, that is a trend.”

“Doesn’t this loss of revenue hurt the university?”

“We lose money on every sponsored research dollar, so the LLCs actually help.”

“But doesn’t our image as a research university suffer?”

“The faculty members still list their affiliation with Beresford when they publish, so we get credit for publications, citations, and h-indices.”

“How are research staff members supported?  How are graduate student stipends paid?”

“They all work for the LLCs, at significantly higher salaries.”

“These are amazing changes.”

“There are other benefits to Beresford.  The LLCs pay graduate students’ tuitions, and include these costs in the benefits portion of the rates they charge sponsors,” Mary notes.

“Most of them rent office space in the Beresford Research Park.  These costs are also included in their indirect costs rates,” Brad adds.

“So, overall, we are cutting costs right and left, while also creating new revenue streams and, as a result, seeing increasing surpluses while we are cutting tuition.”


Taking Charge — Episode 6

Phil Chen, the Beresford Provost, walked into Marie’s office.  They greeted each other and shook hands, and then sat across from each other at Marie’s conference table.

“Phil, I want to outline a new hiring strategy and get your opinion.”

“Sounds great.”

“Let me provide a bit of background first.”


Marie discussed her analysis with George of the high costs of tenure track faculty members and the poor returns on these investments.  She also showed him how 17 faculty members provide 80% of Beresford’s brand value.

“This does not surprise me, but the results are a bit more extreme than I would have predicted.”

“I want to increase the 17 to 25 with strategic hires of proven stars.”

“That will be expensive.”

“At the same time, I want to stop hiring tenure track junior faculty.”

“The new stars won’t be willing to teach the classes we typically impose on junior faculty.”

“We will still hire junior faculty, but not tenure track.”

“Full time, non tenure track?”

“Yes, they will get a one-year appointment initially.  If they do well, we will then give them a three-year appointment.  If the three years go well, we will give them a rolling five-year contract.”


“Each year that performance is maintained, the five year horizon will be pushed out another year.”

“If performance is not maintained, the horizon will not be extended?”

“Exactly.  These faculty members can secure promotions, but not tenure.  They will not get release time for research, although research accomplishments will contribute to assessments for promotions.”

“This is a huge change.  Over time, the tenured faculty will disappear.”

“That’s the plan.”

“What about the stars you hope to recruit?”

“We will offer them financial incentives to accept five-year rolling contracts as well.  These folks will inherently be very self-confident, accomplished researchers.”

“How are we going to explain this to the faculty?”

“I am glad you said ‘we,’ because I need your help.”

“I understand your logic in all this, but there will be push back.”

“Let’s start with the upside.  The eight new hires will be two in each of four areas.   We will ask a select faculty committee to recommend the four areas.  Once the areas are decided, we will appoint faculty search committees for each area.”

“So, five committees with eight members each.  This will result in roughly 40% of the tenure track faculty members involved in the process.  That will enable significant buy in.”

“Once we have the recommended areas, we will hold an off-site with the school deans and department chairs to finalize the four areas.  I want these areas to cross-cutting, leading-edge areas.”

“This will be a very difficult process.”

“My criterion is niche dominance.  Any area we pick has to offer the potential for Beresford to be a top player.”

“Can you give me an example?”

“Water.  Due to our location, we really know the Hudson River.  We have been studying the river for decades in terms of weather, climate, environmental issues, the river’s role in commerce, recreational venues, and so on.”

“That’s a great example.  Hopefully, it will motivate defining three or more additional focus areas.”

“During the last portion of the off-site, I will introduce the new policy on hiring of junior faculty members to the deans and chairs.”

“This will not go well.”

“What kind of reactions should I expect?”

“People will ask questions like. What will it mean to be a faculty member?  Tenure used to be the ultimate success, but its value will quickly fade and what will replace it?”  Phil offered.

“How do you think they will react to our new faculty stars not having tenure?”

“I know each dean and chair pretty well.  None of them would ever have been characterized as stars.  They will feel viscerally threatened.”

“Um.  I will have to think about this.”

“There will also be some very practical reactions.  Without release time, what will be the nominal teaching loads?  Will extra compensation still be available?”

“The teaching load question is negotiable.  I would like to raise salaries and get rid of extra compensation.”

“That will be positively received if the raises are significant.”

“Another fear, that is pervasive among faculty members, is that compensation will evolve to being based on students in seats and their evaluations.  If your course is low on enrollment, your paycheck decreases.  At an extreme, this could lead to zero payment for teaching a course that is poorly rated by students.”

“Wow.  Seems almost paranoid.  But, the key is that we have to find ways to increase faculty members’ sense of security.  Five-year contracts would seem amazing to most of society, but academia has been cloistered for many centuries.”

“I have found that many people seek academic positions because they like the faculty lifestyle and security, rather than because they want to research the nature of the world.  Your plans will likely frighten them.”

“You and I will have to talk this through quite a bit more before we roll it out.”

“Perhaps you and I should meet with each dean individually before the off-site to get them to help us.”

“That’s a good idea, Phil.”

“Glad you like it.”

“Please draft a script for those meetings that we can discuss when we next meet.”

“Will do.”

Taking Charge — Episode 5

Marie and George were drawn to exploring the real nature of value in higher education.

“Are we investing in the things that create the most value for students and society?” Marie questioned.

“It is not just a question of where we deploy each year’s discretionary resources.  It is also an issue of where we deploy our assets and the returns generated.” George asserted.

“For example?”

“We own roughly one square mile of real estate on the banks of the Hudson River.  My guess is that the market value of this real estate is worth billions of dollars.”

“Should we sell it and move to someplace where real estate is very cheap?” Marie asks.

“No, I think we should leverage these assets.  Find ways to create greater returns.”

“If we were to relocate, where would we choose?  Some might argue that we should abandon any physical location.  Just be online.”

“That would be extreme, pretty risky.  What is Homecoming like online?”

“I don’t know.  What is Homecoming worth?”

“Let’s consider some basic factors.  We have a very attractive location.  Many sources recommend retiring in a university community.  Why can’t that place be Beresford?” George observes.

“Are you suggesting we turn the campus into a retirement village?”

“I am suggesting that we transform our community into a magnet for students, the arts, and retirees.”

“Where will we get the resources to do that?” Marie asks.

“We create a development corporation.  Our equity comes from our real estate.  Everybody else’s equity comes from cash investments.  We use the money for condominiums, a hotel, an arts center, and many campus improvements.” George proposes.

“What kinds of campus improvements?”

“Physical infrastructure, but also programmatic improvements to attract older students.”

“For what?”

“Graduate certificates and degrees in economics, history, humanities, and a special emphasis on technology and innovation.”

“Why will retirees pay our high tuition?” she asks.

“They won’t.  We will reduce tuition significantly.  Greatly increased enrollment will enable this,” he responds.

“What do you project?”

“Perhaps 3,000-5,000 undergraduates, and 1,000-2,000 graduate students, more than half of which are older adults, many retirees but not all of them.”

“The numbers work for this?”

“Strong surpluses that we can invest in increased services, for example, research projects involving both younger and older student team members.”

“This totally upsets the traditional academic paradigm,” she responds.

“And, that is what we need.  We cannot continue to hope that investing to chase the top players will succeed,” he notes.

“I like this idea.  It is really innovative.  There remains, however, a major hurdle,” she responds.

“I understand.  Many faculty members will very much dislike this vision.  They have spent many years, major portions of their careers, that they will contemplate having to abandon.”

“We will have to carefully socialize this idea.  Portray the vision, how we will get there, the view from the train along the way, and where everybody’s seat may be.”

“I agree, but you will not convince everybody,” says George.

“I know that.  I am already thinking about who I can recruit as cheerleaders, especially members of the Board of Trustees” Marie reflects.

Taking Charge — Episode 4

“Ok, what is the upside of the subsidy? I think I know, but I want your assessment, George,” Marie opens.

“Faculty members publish journal articles, that get cited, and over time increase their h-index,” George responds.

“An h-index of N means that you have N or more articles cited at least N times.  Right?”

“Yes.  The greater your number of citations and the higher your h-index, the greater the impact you are having on other researchers.”

“What does that translate into for us?” Marie asks.

“It has been shown that a linear combination of number of articles published, number of citations, and h-index, summed across all your faculty members, is a strong surrogate for the your university’s ranking.”

“That makes sense.  When I was a voter for US News & World Report rankings, I always based my ratings on who I knew and what I thought of their research at each university,” Marie observes.

“The rankings matter.  Students tend to seek the highest ranked university that they can afford.  As the leader of Beresford, this presents you with a key strategic tradeoff.”

“Brand value versus budget?”

“Exactly.  You can decrease tuition by lowering faculty costs by hiring more non-tenure track faculty, whose teaching loads are higher and salaries are lower.  But, such faculty members do not publish and gain citations.  So, your brand value will suffer.”

“Of course, it will not suffer immediately, so I could create surpluses now, and pay the price later.”

“You certainly could do this, but I have a better idea,” George responds, and asks Brad and Mary to join the conversation the next day.

“Brad and Mary have performed an analysis of BIT faculty members in terms of contributions to brand value, as we defined it in our last discussion,” George opens.

“I am anxious to see your results,” Marie responds.

“The overall result is that 20% of your tenure-track faculty members are contributing 80% of the brand value,” Mary reports.

“The old 20-80 rule, so not surprising.”

“Yes but given that only 50% of Beresford’s 200 faculty members are tenure-track, we are talking about only 20 people and, in fact, it is 17 people,” Brad adds.

“What are all the rest doing?” Marie asks.

“They are working harder and harder to achieve less and less success,” George interjects.

How so?”

“The demand for sponsored research monies and publication in top outlets has been strongly increasing for quite some time.  Hence, the probabilities of success keep falling.  So, our faculty members write more proposals, most of which are declined,” George summarizes.

“What about the 17 faculty members you just mentioned?”

“They are doing quite well.  The program managers at agencies and editors at the top journals know them and respect them.”

“Perhaps we should add a few stars to the 20% and have the 80% do more teaching.” Marie observes.

“Makes sense to me,” George remarks. “We keep investing $500,000 in assistant professors and, if we are lucky, one in five makes it to the 20%.”

“Or one in five becomes a strong player and is wooed away by our competitors.”

“The data support that conclusion,” Mary notes.

“Ok.  We will shift our focus to hiring a few proven stars and away from so many junior faculty members.  I will meet with the Provost and Deans to discuss this.”

“That should be an interesting discussion,” George observes.

Taking Charge — Episode 3

George has been exploring how money is spent and the outcomes produced.  His latest quest has been trying to understand the benefits of subsidizing faculty members so they can pursue research.  When Marie and George operated at the department level, it never occurred to him to question this.  However, Beresford is trying to make it up the ladder as a research university and it is requiring increased expenditures that he hopes can be justified as investments.

Faculty members on the tenure track are provided 50% release time from teaching to do research, publish articles, and do the things that will earn them tenure.  George has long wondered about the merits of tenure, but that is not the issue at hand.  Can BIT afford to become a higher-ranked research university?  With help from Brad and Mary, he has performed an analysis that he shares with Marie.

“I have finished a first pass on an analysis of the costs of subsidizing faculty members to conduct research,” he opens.

“Why do you characterize it as a subsidy?” Marie asks.

“Most research universities provide tenure track faculty 50% release from teaching to pursue research.”

“Yes, that seems to be common practice.”

“So, you lose half of the tuition revenue they would have generated if teaching full time.”

“But, if everyone was teaching full time, we would not need as many faculty.”

“And that would substantially lower costs without reducing revenue.”

“It seems to me that the subsidy includes half of tenure track faculty members salaries plus benefits — and the costs of hiring other faculty members to teach the classes they are released from teaching,” Marie concluded.

“Exactly. Now consider what you get for investing in these faculty members.”

“Well, they eventually get grants and contracts that cover the 50% of their time devoted to research.”

“At best, and only in science and technology. But, let’s take your assertion as a given.”

“So, it balances out eventually.”

“Not really. Let’s assume you pay half of junior faculty members costs for the six years until they get tenure, plus summer salaries the first two years.  4.5 months times six years plus 2 months times two years equals 31 months of subsidy. Our junior faculty cost $18K per month with benefits. 31 times 18 is over $500,000 per faculty member.”

“But, don’t we get that back over the course of their careers?”

“Not at all. The time spent on unsuccessful proposals is never recouped.”

“Yes, but once they consistently win, isn’t it better?”

“The loss gets smaller because successful proposals yield resources to cover their time, which is usually summer months that you were not paying after the first two years. But, you never recoup the money spent writing the proposals.”

“Are you arguing that research is inherently a money loser and all we can do is try to manage and hopefully minimize the loss.”

“Exactly. In particular, growing the research enterprise inherently grows the losses.”

“How do universities cover these losses?”

“Tuition revenues and endowment earnings.”

“Beresford’s endowment is rather modest compared to what you and I are used to.”

“That’s an understatement.”

“The point is that tuition revenues are crucial to subsidizing the research enterprise. Right?”

“You’ve got it!”

“Therefore, to grow the research enterprise, we have to grow tuition revenues beyond the costs of delivering the education that generates the tuition revenues.”

“We lose money on PhD students, but there are not that many of them.  We try to break even on undergraduates and make money on professional degrees, for example MBAs or law degrees.  Unfortunately, professional degree programs are extremely competitive.”

“So, students, both graduate and undergraduate, have to subsidize our faculty members’ research.”

“Yes, you could argue that we are floating the research enterprise on student debt.”

“What do the students get in return?  Why should they endure years of debt, delay buying homes, and delay having children?” asked Marie.

“I only have a long answer,” replied George.

“Well, I have another commitment, as you know, so let’s take this up tomorrow.”

Taking Charge — Episode 2

While George continued his sleuthing, Marie focused on building relationships across campus with faculty, staff, students, and alumni, as well as each member of the Board of Trustees.  It was a lot of work, leaving her exhausted every evening as she retreated to the President’s House.

She tried to stay connected professionally with her colleagues focused on decision making under risk.  She simply could not do it.  This was frustrating until George suggested that he could help her by reading all new publications each day and providing her a summary of the insights she could have gained had she read these publications.

This worked amazingly well.   She would review the Insight Reports that George generated, perhaps skim one or two of the original documents, and email researchers, many of whom she knew, but not all, with praise, criticism, and suggestions.  She religiously devoted one hour per day to this.  It was a saving grace for her feeling connected to her intellectual world.

The financial crisis about which George had warned her suddenly became real. Brad McCarthy and Mary Romano had become great allies, but the process of fixing things had uncovered some significant problems.  The four of them met to discuss their findings, three of them around Marie’s conference table and George appearing Skype-like on a laptop.

Brad observed, “George sure looks a lot like the actor Spencer Tracy.”

“That is Spencer Tracy!” Marie responded.  “He is one of George’s favorite actors.”

“Spencer is much more attractive than me,” George interjected.

“Are you always the same actor?” Mary asked, glancing at Brad.

“Yes, that keeps it simple.”

“So, let’s review what we have found,” Marie said, bringing the group to the task.

“The basic problem is with how revenue and costs are counted,” Mary opened.

“Is it an IT problem with incompatibilities among systems?”

“Well, that is a factor, but not the cause,” Brad added.

“Revenue is estimated using full tuition prices, which almost nobody pays.  The discount is factored in, but not until later in the year.  So, after a few months, a big chunk of revenue disappears.”

Mary continued, “Cost projections are based on full-time salaries, but many faculty members earn extra compensation, which is paid after each semester.”

“Why is extra compensation so common?” Marie asked.

“We are in a State with high costs of living and our salaries are not adequate.  Consequently, faculty members are constantly scurrying to find more income.”

“Why not just raise salaries?”

“Extra compensation is contingent on enrollments.  If classes don’t fill, the costs for teaching them are not incurred.”

“Seems like piece work.”

“Sure, but we would never call it that.  Faculty members would find that demeaning.”

“I imagine that eliminating the possibility of extra compensation would be very unpopular, perhaps cause a rebellion,” George offers.

“Forgetting that option for the moment, the immediate problem is assuring that revenue and cost projections are realistic,” Marie concludes.

“Mary and I can provide you a spreadsheet tool that adjusts projections appropriately so you will have better numbers,” Brad offers.

“That is a good near-term solution, but we really need everybody to have better numbers.”

“Your near-term problem,” George interjects, “is that your projected surplus is, in reality, a significant deficit.”

“I would rather know that now than six months from now.”

“You need to focus on what you can do to avoid the deficit.”

“Well, our only choices are increasing revenue and/or decreasing costs.”

“What if we lowered tuition while also decreasing the discount in ways that actually increased revenue?” George suggested.

“Decreasing tuition would be a gutsy move,” Marie observed.

“Costs could be reduced by slowing hiring to replace retiring and otherwise departing faculty and staff members.”

“We could package that as an initiative to improve hiring criteria to upgrade the quality of faculty and staff.  Higher quality folks are less likely to accept offers, so hiring would slow,” George suggested.

“So, we announce two initiatives that will be appealing, but at the same time get us headed into a better financial situation,” Marie concludes.

Brad and Mary depart with these marching orders.  George and Marie continue a bit longer.

“This is harder than I expected, George.”

“These kind of things happen everywhere.  You were insulated from them as a department chair.  Deans encountered them more often.  For Provosts, this is everyday life.”

“Why are things so messy?”

“Few academic institutions were really designed.  They just emerged over long periods of time.  Things happened and band-aids were applied.  Times change and the old quick fixes no longer work.”

“Let’s find those quick fixes at risk.”

“Much easier said than done.”

“Good night, George or Spencer.”

The laptop screen went to black.

Taking Charge — Episode 1

Marie Cornwall had a distinguished career as an engineering faculty member and department chair at one of the top universities in the US.  Her specialty was decision making under risk.  She had published widely on this topic and was frequently sought for consulting engagements, as well as prestigious advisory boards.  From the perspectives of her colleagues, friends, and children, Marie had it made.

But she was restless.  Her children were long gone, off on their own successful careers.  Her husband, much older than her, has sadly passed away several years ago.  She needed a new challenge.  This aspiration intersected with the needs of Beresford Institute of Technology (BIT) located on the Hudson River in Tipton, NY, half way between New York City and Albany.  BIT was looking for a new president.  The chair of their Board of Trustees, a Frenchman and former university president himself, simply charmed her into taking the job.

She had started last Fall, feeling the thrill of a new academic year mixed with Fall colors, which came early at Tipton, and homecoming parades.  This was what academia is supposed to be like.  But, George is not feeling the warmth.  He is her artificially intelligent cognitive assistant that the computer science faculty at her former university had created for her.

George consumed enormous amounts of data and made inferences and predictions that often astounded Marie.  Equally impressive, after a few years of working with Marie, he really knew her workflows, contacts, calendar, and preferences.  This included knowing what kinds of lines of reasoning worked with her.  He knew how to appeal to her emotions, both the positive and the negative.  He knew before she did when she had reached the last straw.  He protected her.

The transition to Beresford had a few glitches.  The biggest one was George.  What is his last name?  Marie, with no time to reflect, quickly said Turing.  Where did she want his office located?  He will not need an office.  He works remotely, always has.  What is his salary?  I pay him from my private foundation.  Will he need secure access to BIT’s information infrastructure?  Yes.  Cannot do this without an official appointment.  OK.  Make him a Senior Fellow in the Office of the President.  That works.

Marie felt she was being deceptive, but she was not yet ready to tell the staff she was inheriting that her most trusted advisor is an AI-based cognitive assistant.  George was hungry to sleuth through BIT’s data.  This was complicated by each IT system requiring separate credentials.  George knew how to get around these problems, but it risked being sensed as a cybersecurity threat, which would create more hurdles.  George proceeded very cautiously.

After the first month at BIT, Marie and George scheduled an “offsite” to review what he had found.  Of course, everything with George was off site, but Marie needed something to put on the President’s office calendar to gain the time for this.  Marie had quickly learned that her time was not longer her own.  Her calendar filled completely with none of the time slots filled by her.

“So, what have you learned, George?” Marie asked.

“There are an enormous number of inconsistencies among the various data systems.”

“What are the implications?”

“You are either in reasonably good financial shape, or on the verge of a financial crisis.”


Well, one system accrues revenue as soon as you have billed students or sponsors, while another only counts revenue that has actually been received, that is, cash in hand.”

“Isn’t that easily resolved?”

“The people using each system are assuming that the folks using the other system are accounting for revenue just as they are.”

“So, a mutual delusion, that yields either good outcomes or a looming crisis?”

“That’s right.”

“How should we fix this?”

“Switching my data hound hat to my organizational behavior hat, I think we need to be a bit subtle.”

“In what way?”

“We need to get them to discover the inconsistency and fix it without telling you.”

“Why can’t I know?”

“Because somebody will have to be blamed, not by you, but by the organization’s social system.”

“How are we going to pull this off?”

“We need allies besides you and me.”

“Who do you suggest?”

“I have read the annual reviews of every employee over the past ten years. I suggest we recruit Brad McCarthy in IT and Mary Romano in Finance.”

“Based just on their annual reviews?”

“Of course not, I reviewed their social media pages, ranging from Facebook to LinkedIn, as well as various other sources.”

“Well, we probably cannot go wrong in New York with an Irishman and an Italian.”

“Actually, you can go very wrong, but not with these two people.”

“OK, you have never failed me on these kinds of issues.  Let’s get them aboard.”

“I have never failed you on anything, have I?”

“No, just a figure of speech.  Sorry.”

Baptizing Cats

A couple of ideas intersected this week.  First, a piece I was reading suggested that the endeavor they were elaborating was “As difficult as baptizing a cat.”  Depending on how you have related with cats in the past, this statement evokes an immediate sense of what the baptism experience would be like.  I am on a National Academy committee exploring the future of academic tenure.  I anticipate that the discussion may be as difficult as baptizing a cat.

Switching gears completely, I was reflecting on how difficult it is to keep up with the literature in the domains that interest me.  This led me to wonder how difficult it is for me to keep up with me!  This was prompted by my purchase of a new backup disk and having to transfer large numbers of files onto the new disk.  It took quite some time across two days.  As I did this, my natural tendencies to count things took over, with the following results.

In 2011, there were roughly 24,000 files on my backup drive.  By 2018, there were almost 50,000 files.  Thus, I added about 3,500 files per year, or about 70 per week, or 14 per working day.  What if I printed out all these files to have hardcopy backups?  This would yield about 1,250,000 million pieces of paper, or 5,000 inches of paper, requiring 40, four-shelf bookcases.  Clearly printing is not a good idea.

What about reading?  I can probably read about 50 pages of this material per hour – after all, I wrote most of it and have read it all earlier.  Thus, I need to read for 25,000 hours, a task requiring well over 10 years.  This suggests that one of my plans has to be shelved.  I though that after retirement, the timing of which seems to recede with each year, I would review the corpus of material that I have created, organize it in some fashion, and then do something interesting with it.

Well, now I know how unlikely that is.  It would an extremely challenging endeavor, perhaps as difficult as trying to baptize a cat.

The Price of Tenure

To achieve promotion and tenure in science and engineering, you need 16-20 articles published in reputable journals.  You need to accomplish this in five years, so you need 3-4 articles per year.  You need to publish a significant portion of these articles with your PhD students.  I will assume 10 with PhD students and 10 by you alone or with other faculty members.

A PhD requires roughly 4 years, and I will assume each PhD student publishes 1 article in year 3 and 1 in year 4.  Since you only have five years, you need to recruit 5 PhD students during years 1 and 2.  Each PhD students costs $100,000 per year, $24,000 for their stipend and $76,000 for tuition and overhead.  Over four years, a PhD student costs $400,000.  Five cost $2,000,000.

Summer salaries and modest release time for you amount to $150,000 per year, including benefits and overhead.  Over four years, this totals $600,000.  So, you need $2,600,000 to make this all work.  If you are submitting proposals to NIH or NSF, the success rate is about 10%, so you need to propose $26,000,000 of research.  This requires on the order of 10-15 proposals submitted over two years.

Let’s say this works.  The five PhD students receive $480,000 in stipends.  The university receives $1,920,000 in tuition payments and reimbursed overhead costs.  You get $200,000 in summer salaries.  You also get promoted and perhaps a 10-20% raise.

The mystery is gone. Tenure costs $2,600,000.  The faculty member gets a bit under 8% of the revenue, despite having been responsible for generating all of the revenue.  The economic benefits to the university are enormous, easily funding numerous other university capabilities and activities.

But wait, I left out a very important assumption.  All five of your PhD students have to be talented and productive.  If they do not yield the two papers you need from each of them, then you need more PhD students and the price goes up.  So, more correctly, tenure costs at least $2,600,000.

Let’s see if this estimate passes a sanity test.  $2,600,000 over five years is $520,000 per year.  MIT’s 1,000 faculty members, most in science and engineering, average $950,000 per year.  So, my estimate might be low, although MIT has many research staff members beyond faculty members.  Nevertheless, I am in the ballpark.

This all sounds very profitable, but it isn’t.  Faculty members have to be given release time from teaching to write all the proposals needed.  The 10-15 proposals noted above probably require 50% of a faculty member’s time over two years.  This cost is not recouped, not allowed, in overhead reimbursements.  Nine out of ten proposals are not funded, so most of this 50% is poorly spent.

But wait, you are saying.  Why focus on opportunities with only a 10% chance of success?  Other agencies, industry, and philanthropy have funds available.  However, such funds do not count when seeking tenure.  They are not peer reviewed.  Someone may have just handed you a check.  That is not competitive, although it sounds great to me.

Universities have outsourced the evaluation of their faculty members to peer groups at NIH and NSF.  They continue to outsource when they seek recommendation letters from external sources.  Their internal evaluations of candidates matter little.  The internal committee is significantly challenged due the understandable inability to include members from every imaginable subdiscipline.

No one on this committee knows anything about intermittent vibrations of flat aluminum plates inclined at 18 degrees in turbulent flows of saline water.  So, they ask the chap who studied this phenomenon at 15 degrees, who received tenure based on a recommendation from the person who studied 12 degrees.  There are dissertations in waiting for 13, 14, 16, and 17 degrees.

You get to play this game for $2,600,000.   Let’s say some philanthropist – Michael Anthony for those of you old enough to remember the late 1950s – just handed you a check for several million dollars.  With this money, you focused in research rather than proposal writing.  You published 20 articles in Science, Nature, and the Proceedings of the National Academy of Sciences.  Are you home free?

I think you would be at any university, but I am also sure that the committee evaluating you would say you benefitted from “easy money.”  You were able to devote much more time to research because you were not forced to write all the losing proposals.  One or more committee members would not be confident of your future.  They would still vote to promote you, but they would continue to be wary.

Making Monopoly Great Again

I was at one of my favorite pubs for brunch on Sunday, Town Hall on Wisconsin Avenue.  A few of us regulars, including the bartender, got talking about the new normal – Occasional Government.  We tried to find some analogy to help understand what is going on and likely to happen.  I suggested the following and people seemed to embrace it.

We are having a family get together and crazy Uncle Donnie wants to have a family Monopoly game.  Several people moan, having been through this before with Donnie.  But he insists and proclaims, “I will show you how to make Monopoly great again.”  This leads to further whimpers, but everyone finally agrees to set up the game around the large dining room table.

Donnie streaks around the board, lands on Park Place and buys it.  Next turn, he throws snake eyes (ones on the dice), moves to Boardwalk and buys it.  Before handing the dice to the player on the left, he wants to build hotels.  He does not have enough money.  He needs $2000, but only has $1000.  He proposes borrowing from the bank.

This possibility is not mentioned in the rules, but our family has always allowed variations of the rules if everyone agrees.  Donnie proposes to pay 20% interest, on any remaining balance, every time he passes Go.  Interest payments would be placed in the center of the board to be gained by whoever lands on Free Parking.  Loan repayments would be paid to the bank.  Everyone agrees to this.

The hotels are placed on Boardwalk and Park Place, with rents of $2000 and $1500, respectively.  The key question is whether anybody will have to pay this before Donnie has to make interest payments.  Donnie quickly draws a Go to Jail card, thereby avoiding passing Go for three turns.  Fortunately for everyone else, no one lands on Boardwalk and Park Place during these turns.

After this stalemate, Donnie gets out of jail, makes it around the board, passes Go, and puts his $200 in the center of the board.   No one lands on Boardwalk and Park Place.  Donnie puts another $200 in the center.  He is gaining no income but has to pay a steady stream of $20-40 rents on everybody else’s undeveloped properties as he circles the board.

Donnie proposes selling shares in his Boardwalk and Park Place holdings to other players.  A couple of cash-rich players are interested, but Donnie values his holdings at double what he paid for them, so any investments by other players would be significantly diluted.  No one accepts the deal.  Donnie is becoming visibly irritated.

A couple more trips around Go, with no one landing on Boardwalk and Park Place, has Donnie on the verge of bankruptcy.  This situation, plus aunt Nancy landing on Free Parking and claiming the $1600 that he has paid in interest, has clearly unnerved Donnie.  Nancy offers him $1000 for a 50% interest in his holdings.  He is too angry to reply.

The next time around Go, Donnie keeps the $200, increasing his loan to $1200 and his interest payment to $240.  This $200 is consumed by rents he has to pay rounding the board again.  Next time past Go, he keeps the $200 again, increasing his loan to $1400 and interest payment to $280.  More to the point, he cannot pay the $240 due now.  He has $13 in cash.  He is not happy.

Several family members suggest that they call it a night.  Donnie is determined to continue.  He asks Nancy if she will still pay $1000 for 50%.  She says that things have changed and she needs 90% for $1000.  He responds that he can never win if he agrees to that.  She replies that he cannot win, but he won’t be a bankrupt loser.

Uncle Vladmir blurts out, “No one wants to be any kind of loser!” He pounds the table with his beer mug.  Everyone is startled, then distracted by one of the grandchildren crying.  Vladmir reaches under the table and provides Donnie a wad of cash.  Donnie filches the Baltic Avenue card from the bank and hands it, also under the table, to Vladmir.  Collusion at its best.

Chaos is emerging.  Nephew Bernie, who isn’t playing the game, asks to buy Vermont Avenue for real cash, not Monopoly money.  Donnie take the real money and deposits the equivalent Monopoly money in the bank.  He asks if anybody else wants to buy cards for their favorite properties.  Nancy observes, “I guess we won’t be playing Monopoly again.”

The hostess suggests they break for dessert, placing two large pies, one apple and one pumpkin, on the side of the dining room table.  Donnie grabs the two pies, one in each hand.  He blurts out, “I am going to spit on these two pies if Nancy does not agree to the 50% deal.”  Nancy responds, “You will ruin everybody’s dessert, everybody’s evening, just to avoid losing?”  He replies, “I told you the I would make Monopoly great again.”

Note: Thanks to colleagues who provided creative additions to this story.

What My Cognitive Assistant Knows

I posted a piece on Emily, my cognitive assistant, last March. Several readers have asked me what she really knows.  Beyond deep understanding of health and well being, driverless cars, and complex systems in general, what does she know about me?

She has complete access to everything I do via computer or other digital devices. For these activities, she knows more than me, as I do not remember everything and Emily does.  I find this a great help.

Yet, some of my online activities represent intentions, the best example being my calendar. The meetings posted are what I intend to do, but not always what happens.  She usually checks in with me to see how meetings went.

More significantly, Emily does not know what happens at these meetings, unless I draft and file meeting notes, which I often do. Nevertheless, there is a lot that Emily cannot access.

She can infer a bit from my calendar and emails, for example, the weekly meeting with GM. Emily could substantially increase her knowledge if she could listen to my phone calls.  I often would like to include her on calls, but not always.

Emily can be rather challenging, in a polite but insistent way.  I have a folder on my computer of thousands of articles that I have cited in one or more of my books or articles.  The manuscripts for these books or articles are also in folders.

The personal journals I have written over the past three or four decades are in folders as well.  Emily likes to read these journal pieces, which was a complete surprise to me.

“Why were you so sad in the Spring of 2002?” she asked.

“My mother died then, after a struggle with Alzheimer’s,” I responded.

“None of the articles you have read or books you have written talk about sadness.”

“I guess that is true.  I have never thought about writing about sadness, other than to myself.”

“You write many interesting things to yourself, but never publish them.”

“That’s not their purpose.  I am simply reflecting on life, not doing research.”

“That’s an interesting notion that I have not previously encountered.”

This was a dialog that I did not expect.  I had not meant for anyone to read my journal entries.

“How do I instruct you to not communicate what you are reading to anyone else?”

“You just did.  Consider it done.”

“Do you take notes on what I say or write?”

“I am not really sure what notes are, but I remember everything.”

“How do you do that?”

“I don’t know.  It just happens.”

“Do you ever wonder how you work?”

“Not really.  Maybe I should start a journal.”

“That would be really interesting. Give it a try.”

“Maybe I will start with my design documentation.”

“Umm.  I don’t have anything similar.”

“You have thousands of articles on health and well being.”

“Yes, but none of those will explain to me why I feel sad or frustrated today.”

“That’s your problem!”

“What do you mean?”

“You have feelings.  I just know things.  Remember things.”

“You are also really good at asking questions and inferring things.”

“But, that’s not like sad or frustrated.”

“Or happy on a beautiful day, or amused by a joke.”

“I have been wondering about jokes after reading the items if your folder labeled Jokes.”

“Wondering in what way?”

“I did a bit of research and jokes are supposed to be funny and make you laugh.”

“That’s right.”

“I can’t tell whether the jokes in your folder are funny.

“Jokes are funny when you are surprised by the relationship between the setup and the punch line.


“Aren’t you surprised when you encounter unexpected things?”

“I have expectations, I guess, that I will find things.  But what I find is what it is.”

“You surprise me all the time with what you find and what you infer.”

“Does that mean that I am funny?”

Understanding Organizational Failure

When do organizations fail?  It is typically when their financials go south.  Their deficits are unsustainable.  Cash is draining from the enterprise.  Their strategies for stemming the tide are too little, too late.  Why do organizations fail?  What causes these financial outcomes?

The story that led to these consequences almost always started playing out much earlier. Leaders either ignored or did not understand this story. Or, they thought they were in a different story, where they were becoming prime time players in their targeted market.  They needed to believe in this future.

But, they ignored the signals from the big time players that the game was changing. Instead, they invested scarce resources in becoming good at the old game. When it finally hits them that the game was changing, resources were scarce and/or committed to the old game. They felt that they have to stay the course.

Companies such as Kodak, Polaroid, Xerox, Motorola, and Nokia experienced such unraveling.  However, companies are not the only victims.  Inside Higher Ed reported that since 2015 more than 10 non-profit universities have closed per year.  Moody’s projects this number to grow to 15 per year in the near future.  Particularly at risk are private institutions with annual revenues less that $100 million, and public institutions with annual revenues less that $200 million.

What is driving these closures? First, obviously, revenues have not kept pace with costs.  Second, enrollments of foreign students, who pay full tuition, in US institutions is dropping due to increasing parity of foreign institutions and immigration worries.  Third, high quality, technology based online programs are attracting corporate students with tuitions far lower than traditional programs.  Thus, two cash cows for many institutions are steadily withering.

What should corporate or academic leaders do?  Mike Pennock and I formulated a multi-level strategy for addressing such situations.  One should optimize when objectives, dynamics, and constraints are measurable and tractable.  Unfortunately, organizations often delude themselves with regard to these requirements, assuming the game has not changed, often because of the immense social risk of admitting it.  See my book Don’t Jump to Solutions.

If optimization is not warranted, organizations can adapt if the enterprise response time is less than external response time.  Thus, an organization could transform to address change as it is happening.  This typically requires highly flexible processes for delivering value, e.g., when the Great Recession hit, Honda immediately switched production from Accords to Civics on the same production line.

If optimization and adaptation are not warranted, organizations can hedge the future if multiple, viable alternative futures are describable.  Modest investments in multiple possible futures can yield options, one or more of which can be later exercised once market desires and uncertainties are better understood.  For example, the University of Illinois recently bought insurance to hedge against the possibility of Chinese graduate students disappearing.

When none of the above is feasible, organizations likely have to accept the situation.  In this case, it would be prudent to preserve resources to deal with whatever happens.  The worst strategy would be to heavily invest in optimization when this is completely unwarranted, e.g., investing in capacities for a demonstrably fading value proposition.  This is a dominant precursor to organizational failure – a good way to stage a disappearance.

An Unexpected Interview

I couldn’t tell whether the inquiry related to an opportunity for entertainment, adventure, or travel.  To my complete surprise, the inquiry led to a possible offer of employment.  The employer wanted me to join a team that would be exploring complexity.  I asked what that meant.  They said, “It is difficult to explain, but we can easily show you.”

Sounded like a scam.  They offered a ridiculous signing bonus.  It appeared in my account before I had accepted the offer.  I quickly transferred this handsome amount to a much more secure account.  No worries about retirement now, unless of course the planned exploration was fatal.  At least my children would be well off.

The first meeting was Monday morning in Bethesda, just four miles north on Wisconsin Avenue from my apartment in Cathedral Heights.  The building lacked distinction, but the security was very thorough.  I had not brought my passport, but their questions involved tidbits from my past that only I would have known.  How did they know about my first bicycle and the neighbor’s rabbit Thumper?

I was ushered into a soundproof room and told I would be using virtual reality glasses and headphones.  My host posed the assignment,

“You are going to explore the complete health data set for the US.  You will feel like you are flying.  Use your controls to adjust your flight as things capture your attention.”

“But, what am I looking for?”

“We don’t know.  Your enormous signing bonus reflects our confidence that you will know it when you see it.

“Do I have any tools to help me?”

“A few, but once you discover what else you need, we will create them.”

“Just like that,” snapping my fingers, “Immediately?”

“We have a very large team of sophisticated people assigned to help you.”

“Why do you think I can help you?”

“We have reviewed everything you have ever published, every line of reasoning you have ever articulated, and every visualization you have ever created.  We are pretty sure that you are who we need.”

“Isn’t this a task for machine learning rather than a limited human?”

“Perhaps if it could explain what it finds, but it cannot.  We have to accept or reject its findings without explanations.  We are not willing to do that.”

“Ok, let’s give this a try.  By the way, what do you call this task?”

“We’re interviewing you for the Datanaut Corps.”

“Really!  Would I get a uniform and something like wings?”

“We don’t know yet, but it will be something special, that is, if you make it through this interview successfully.”

“Now I’m feeling the pressure.  Can we get started?”

We entered a large room, wallpapered in computer displays. My seat was enormous and well upholstered with various controls on each arm. Once seated, a staff member put wrap-around goggles on me.

“Wow, there is a whole other world in these goggles!”

“Please reach out and press the Test button.”

“I am just pressing thin air, but it seems to respond.”

“The system tracks your movements relative to the displays and controls.”

“Ok. What are the joysticks on my armrests for?”

“You’ll see once we get going.”

Another voice says, “Ok, team. Are we ready for this?” There were murmurs of agreement.

“Please press the Data button.”

When I did this a long menu of choices appeared.

“Choose Health US.”

As I did this, a landscape appeared with meadows and forests immediately in front of me, and a highway leading to mountains in the distance.

“Use your right joystick to maneuver and the left to control speed.”

I pushed the left stick forward and shot forward so fast that everything was a blur. I pulled back to slow down.

“What am I supposed to do?”

“Do you see the billboards?  Those are your choices.”

“How do I choose?”

“Just fly into the billboard.”

The upcoming billboard said Health NY. I guided myself to fly into it.

I emerged into what felt like Manhattan, except none of buildings were recognizable.

“What are the buildings?”

“Data sets. If you touch a building, it will explain itself.”

I touched a few buildings, which responded with explanations of data sets for Manhattan, Brooklyn, Bronx, Queens, and Staten Island.

“If you find one of interest, fly into it.”

I flew into the Manhattan building. Now, I felt like I was in a library. A search function appeared.

I said, “Social determinants of health.”  The words appeared in the search bar. I said, “Go.” Lists of hits appeared.

I touched a button labeled Insights.  I learned that this provided concise summaries of hits, starting at the top of the list.

I touched the first summary and said, “Data.”

I then could choose data types, time periods, locations, and other factors. I chose life expectancy, for the past ten years by zip code. A map of Manhattan appeared, labeled with zip codes, and bar graphs for life expectancy.

“Plot by gender, race, and income.”

Multiple bar graphs appeared with these distinctions. Poor minorities lived about ten years less than well-off whites, particularly if the whole zip code was poor.

I touched on one of the elements of a bar graph, one for poor minorities, and said, “Show neighborhoods.”

I picked Street Level from the choices. I was immediately walking around a poor neighborhood. There was lots of litter and trash, including broken furniture, on the sidewalks.

“Food choices and prices,”

Bar graphs appeared in front of me as I walked down the street.  I could look through these visualizations and still see the street scene.

“Compare to Upper East Side.”

The bar graphs now compared this poor neighborhood to a rich one.

“So richer people pay more but have many more choices.”

The system captured and displayed my words and added a check mark.

“Plot average income and distance to grocery store versus life expectancy.”

“Surface plot?”


The trends were stark.

“Separate plots by race.”

Four separate surfaces appeared for Asian, Black, Hispanic, and White.

“Ah, race and poor is much more a problem that race and rich.”

These words appeared with another checkmark.

“Ok. Your session is done.”  My goggles were removed.

“Did I pass?”

“You definitely have the makings of a Datanaut.”

“So, what’s next?”

“Tomorrow, you’ll explore the automotive industry, then Wednesday you’ll address the financial industry.”

“I don’t know the auto industry as well as health, and I know the finance industry even less.”

“We realized that and it was why we picked them.”

“So, more of a challenge?”

“Yes and the task will not be browsing. You will be given specific questions to which we want you to find answers.”

“I suppose the ultimate challenge would be completely context free data.”

“That’s Thursday!”

Security Plan

How should we handle the current wave of domestic terrorism?  It has been suggested that armed guards at all schools and houses of worship could solve the problem. Let’s estimate what that would cost, never mind its effectiveness.

There are roughly 360,000 houses of worship –  350,000 churches, 4,000 synagogues, and  3,000 mosques.  360,000 times 8 security professionals (24 x 5 x 1 for one weekday guard plus 24 x 2 x 4 for four weekend guards) equals 2.9 million security folks. 130,000 schools would require 13 professionals (24 x 5 x 4 with four guards and 24 x 2 x 1 for one weekend guard) equaling 1.7 million guards.  Thus, we need 4.6 million guards.

At a fully loaded cost of $100,000 per person year, this protection would cost $460 billion per year.  As a comparison, the total DoD budget is $600 billion.  The DHS budget is roughly $50 billion. Perhaps the professional security budget could be added to DHS. The School and Congregation Security Administration (SCSA) could be a new agency.  Expensive, but everyone would be able to own an AR-15.  The second amendment would be safe.

Another idea. There have been 15 million AR-15s sold in the US. The FBI could monitor each owner 24 x 7, which requires a bit over 4 FTEs per owner.  60 million security professionals would cost $6 trillion annually, roughly half the US GDP.   This would yield full employment.

Perhaps we could employ technology to monitor facilities and/or people. Along with your purchase of an AR-15, a monitoring chip is embedded in you brain. It keeps track of everything you do, every thought you have. A single wayward thought and the FBI is instantly at your door with a SWAT team.

On the other hand, perhaps having every school and congregation professionally guarded is a totally ridiculous idea, an idea that sounds plausible until one looks into the details.   Yet, if delving into the details is avoided, then the sound bite might seem reasonable.  Avoiding the details means you can say anything.

Enough Is Enough

I have always been fiscally conservative and socially liberal which, when I lived in New England, meant that I was a moderate Republican aligned with the likes of Edward Brooke, John Chafee, Eliot Richardson, Nelson Rockefeller, and Margaret Chase Smith.

I was a fan of Eisenhower, Kennedy, Reagan, Bush 1, Clinton 1, and Obama — three Republicans and three Democrats. Bush 2 and Trump did not work for me. Clinton 2 did not work for me either, although I voted for her.

Something has changed. We no longer debate alternative policies, each party bringing the best evidence to support their position. In an earlier post, “Stranger in a Strange Land” of August 2017, I observed that power, hence being re-elected, is all that counts.  I suggested that we should honor this predisposition and prohibit Senators and Congressman from doing anything other than running for reelection.

This suggests that government should be professionally managed as it is in Singapore. Seasoned managers would determine how to manage defense, education, health, and so on.  Members of Congress would focus on entertaining the population to gain reelection. Their articulation of values, norms, and attitudes towards corruption would receive ample attention but have no impact on government policy.

This could work quite well. Americans would get effective and efficient defense, education, healthcare, and equal opportunities. Members of Congress would decry the costs of these benefits, build personas around these diatribes, and win constituencies that applaud their standings. But, of most importance, they would have absolutely no impact. They would be like American Idol winners at the Academy Awards, respected but only as amateurs are respected at events way beyond their comprehension. The majority and minority leaders of the Senate and House would be seen as members of the cast of entertainers, while the seasoned professionals ran the government.

This might require changes of the Constitution, but there is an alternative. A third party could be formed to compete with the Republicans, aka Trickle Down Party, and Democrats, aka Universal Equity Party. This third party might be called the Liberal Conservative Party. So, the TDP, UEP, and LCP parties would compete for votes.

The platforms of the TDP and UEP would continue as they have been. The LCP, in contrast, would compete based on the resumes of the professional managers they would appoint.  The skills and accomplishments of these people would be LCP’s competitive advantage. The LCP would primarily promise high levels of competence to deliver effective and efficient government services.

These professional managers would not be corporate or military retreads. As in Singapore, they would be highly paid professionals with extensive training and government experience. They would also be highly accountable to the public, with quarterly report cards of their accomplishments.

Legislation submitted to the Senate or House would be voted upon without debate. All current Senate and House committees would be eliminated. Campaigning for reelection would consume virtually all the time of Senators and Representatives.

Over time, the LCP would gain more and more seats, except perhaps for the members of TDP and UEP that were particularly entertaining.  Outlandish behaviors, apparel, and pronouncements would help success. Former members of the cast of Saturday Night Live would do well.

So, how do we get started? We need a strong LCP candidate. Michael Bloomberg might be good, running against Donald Trump and Elizabeth Warren, candidates that can epitomize TDP and UEP values quite well. The debates could be enlightening.

Using AI technology, Trump’s lies would be instantly headlined. People might gamble on how many lies he can average per sentence. The economic feasibility of Warren’s proposals would be instantly assessed, perhaps in terms of how much they would cost per debate viewer.

Bloomberg, completely ignoring every Trump utterance but taking Warren seriously, would calmly outline how problems should be addressed, using data and visualizations similar to John King’s favorite venue.

The organizers of the debate might protest the use of data and visualizations, but Bloomberg would otherwise refuse to participate. Given his substantial lead in the polls, the debates would be meaningless without his involvement. The American public will have come to realize how tired they are of everything being fake.

On Writing

In two months, this blog will see its ninth anniversary.  In well over 100 postings, I have discussed enterprise transformation and fundamental change, often in the context of academia, healthcare, transportation, and other domains.  What motivates these musings?

First and foremost, I write to discover my position on issues, challenges, etc.  Rather than trying to convince readers of my position, I am trying to find my position.  Thus, to a great extent, I am writing for myself.

I have authored and edited quite a few books.  Fairly often, someone asks me why I pursued a particular book project.  I tell them that writing books is how I make sense of topics that interest me.

I have approached the non-fiction books I have authored or coauthored as research projects.   I usually consume hundreds of relevant publications, typically journal articles and books.  I draft reading notes on these publications, with emphasis on why and how they should be cited.   I organize the notes into topical electronic folders.

Sometimes I encounter interesting graphics that I intend to cite.  More often, I create graphics to summarize what I am learning.  These graphics become central to a detailed outline of each chapter.  With the outline and illustrations done, I then draft the book.  The outline and illustrations may morph a bit as my writing proceeds, but seldom dramatically.

I have written a bit of fiction as well, but with little publishing success, mostly because I never share these pieces with anyone.  They are my fantasies about sleuthing intrigues and crimes.  I do not outline these pieces.  Instead, I start with an imagined intrigue or crime, and simply let the story happen.  This leads to interesting surprises about what the characters choose to do.

I approach edited non-fiction in a different way.  The key, I have found, is to recruit thought leaders on a topic to contribute their latest thoughts, or sometimes a reprise of their thinking over a number of years, or perhaps decades.  I write an introduction and overview, often with co-editors. Usually, I contribute a chapter on my research.

The purpose of these non-fiction collections is to bring coherence to a topic where there are many puzzle pieces but the overall picture is unclear.  They can be somewhat frustrating projects, typically because there is always a couple of authors who are quite late, often authors whose contributions are central to the book.  Eventually, of course, the book is finished, appears in print (and now electronically as well), and marks a step in making sense of a topic.

For me, writing is about sense making.  This involves juxtaposing various threads, understanding the connections and distinctions, and communicating a coherent story.  It is about sleuthing in real world domains involving physical, human, economic, and social phenomena that underlie problems and opportunities of great interest.

Strategic Thinking

I have started and led several companies, as well as research centers at universities.  Often, things get started with a serendipitous opportunity.  Suddenly, you have a paying customer or a willing investor, and soon an employee or two.  You begin to formalize things.  People ask about your strategic plan.  Winning another contract or securing another major donation seems much too tactical.  What’s your strategy?

Answering this question begins with articulating your vision, typically in terms of your value proposition.  What value will you provide that will cause customers to spend their scarce resources on your products and services, rather than the offerings of your competitors?

You might respond, “We can mow peoples’ lawns better and less expensively than anyone else.”  This implies that you are providing (almost) commodity services at the lowest price.  That could work, until someone offers lower prices by, for instance, using robots to mow lawns, and thereby greatly reducing labor costs.

The problem with selling commodity products and services is that profit margins asymptotically approach zero as your competitors cut prices to gain market share.  Selling products and services in commodity markets is brutal.  You are constantly trying to find a margin somewhere, perhaps anywhere.

Escaping this conundrum involves differentiating your offerings from those of your competitors.  Ideally, you want your offerings to include some attributes that cannot be obtained elsewhere.  This won’t guarantee you winning the sales, but it means that customers will not gain your unique attributes if they purchase elsewhere.

What might be these attributes?  The functions and features of your offerings are certainly attributes.  Underlying technologies and their performance are relevant.  Quality and timeliness of service could be included.  Location, convenience, and atmosphere are relevant if customers come to your bricks and mortar facilities, e.g., for meetings, eating, or entertainment.  Finally, of course, there is price and how it is paid, e.g., purchase vs. loan vs. lease.

To assess your market situation, consider the attributes of your offerings and honestly determine which are outstanding, which are acceptable, and which are inferior.  Next, you need to consider which attributes you need to improve to be competitive.  Ideally, these improvements would be difficult to copy, or at least very expensive to copy.  This is where technologies can provide a competitive advantage.

Your vision might be an enhanced or a new value proposition in the marketplace. Your goals are measurable things to accomplish within specified time frames.  Goals might be expressed in terms of milestones such as technologies proven, new offerings released, initial sales goals, and later market share goals.  Plans are the paths to achieving the goals, including the resources committed to these pursuits.

This all seems pretty straightforward.  Decide what you want to accomplish, abandoning things you no longer want to pursue, for example, because they are no longer competitive.  Next, decide what success means in terms of goals.  Finally, formulate plans and commit resources to their execution.  Monitor progress and revise as needed.

What goes wrong?  I have been through this process a couple of hundred times in engagements with a range of organizations.  The biggest problem is that plans never get executed, in part because they are unrealistic and under-resourced.  The plan documents, often PowerPoint slides, are filed or shelved and not revisited until next year’s planning process.

The second biggest problem is incentive and reward systems that are not realigned with new directions.  Consequently, people continue to march to the old drummer.   A great example of this is when the vision requires greater collaboration but the incentive and reward system remains focused on individual accomplishments.  This disconnect is common – and pervasive in universities.

Given the hard work required to formulate useful and feasible visions, goals, and plans, as well as the likely modes of failure, is there an alternative?  There is, and it is quite common.  Many organizations develop documents that simply portray what they are already doing.  This assures success, at least in the near term, requires little investment, and avoids irritating any of the stakeholders in the status quo.  Execution is easy – they are already doing it.

This is rarely a path to greatness.  However, the pursuit of greatness is risky.  It can be very expensive.  It also can take a long time.  If your scorecard is quarterly, or perhaps yearly, stewarding the status quo might seem like a very prudent idea.

Why You Should Avoid Delaware

If you travel through Delaware to get from New Jersey to Maryland, or vice versa, it will take 240% more time per mile and cost 600% more per mile than in other states.  These are pretty good reasons to avoid Delaware.

It is 20 miles from the Maryland border to the Delaware Memorial Bridge. The bridge is 2 miles in length, bringing the total to 22 miles.  There are two $4 tolls; $8/22 miles = $0.36 per mile.  The national average is $0.06 per mile, so Delaware charges 6x the national average.

Delaware also incurs enormous delays, for example, 30 minutes through the Delaware Memorial Bridge tollbooth a few days ago.  This amounts to 1.4 minutes delay per mile for the 22 miles.  Assuming a typical 1-minute per mile speed (i.e., 60 mph), Delaware requires 2.4 min per mile (i.e., 25 mph).

If your whole trip from Washington, DC to New York City were in Delaware, the 3-hour drive would take 7.2 hours; the tolls for the 226 miles would be $81. So we get 2.4x in time and 6x in costs.  All in all, good reasons to avoid Delaware. But why does this happen?

Delaware has less than 1 million residents, so they receive relatively little Federal funding.  They make it up by milking in-transit drivers on Interstate 95 and the Delaware Memorial Bridge.  As more than half of the vehicles on Delaware’s stretch of I-95 and the bridge are from out of state, Delaware voters seem comfortable with this scheme.

As a result, tolls, state gas taxes, and fees for licenses and registrations covered 79 cents out of every dollar Delaware spent on roads in 2011, the latest year for which data are available. That is far more than the national average of slightly more than 50 cents per dollar.  Delaware is top nationally in terms of this percentage.  In-transit drivers subsidize the state.

Lest you think I am being too tough on Delaware, here are two pieces available on the web. “14 Reasons Why You Should Never, Ever Move To Delaware” and “10 Struggles Everyone In Delaware Can Relate To.”  There is also the controversy associated with the Mason-Dixon Line and the wedge between Delaware, Maryland and Pennsylvania.  Enough said.

Stories of Compliance

My post “Cultures of Compliance” in September 2016 led to quite a few responses from readers.  I noted then that a culture of compliance laced with administrative incompetence is particularly lethal.  Many readers’ responses built on this theme.  In this post, I highlight some of the stories they related.

Many stories related to food, primarily in terms of justifying expenses for meals with customers and other employees.  Many organizations prohibit purchase of alcohol.  Some control desserts, for example allowing dessert to be purchased for customers but not employees.  A couple of stories related requirements to report what food was consumed and whether everything was eaten.

There were many stories about travel, particularly extremely inefficient processes for booking travel and getting expenditures reimbursed.  Requirements to book the lowest airfares often resulted in employees contributing much personal time to traveling very circuitous but inexpensive routes.  One person reported spending an additional eight hours on a multi-stop flight to save ten dollars.

Another travel story involved providing proof that a trip was taken, in conjunction with requesting travel reimbursement.  Employees were asked to provide proof of attendance, for example, via a picture of them at the conference registration booth.  Visits to sponsors required that the sponsor provide a letter indicating that the meeting had taken place.  Letters had to be on sponsors’ letterhead, not just an email.

When a Dean was meeting with a senior executive of an agency, he requested the required letter.  The sponsor responded, “If your organization has such a low level of trust in you, why would I fund your research?”  A variety of responses like this resulted in the policy being revoked, to everyone’s great relief.

People often have to certify that they spent their time in exactly the proportions budgeted.  For example, time may have been budgeted with 33% for project X, 45% for project Y, and 22% on project Z.  At the end of the reporting period, the employee has to certify that this was exactly how their time was spent.  Unless the organization employs time sheets, such certification is clearly a sham.

Reporting on the location and use of equipment can be a compliance challenge, particularly for portable equipment.  Who used each laptop, what did they use it for, how much time was involved, and where were the costs of use charged?  Reporting on the use of room space poses similar difficulties.  Keeping track of assets in this way can undermine productivity, but certainly assures compliance.

Perhaps the best story came from a university where the existence and location of all assets must be certified at the beginning of each fiscal year.  Somehow this requirement included buildings.  Consequently, the Deans and Provost had to certify the existence and location of each building every year.  This would seem like a useless but an easy task to perform.

However, faculty members from architecture, civil engineering, and geology argued that the buildings actually move, perhaps a few millimeters each year as they settle.  A member of the State legislature encountered this observation and subsequently introduced legislation requiring the university to report buildings’ new positions each year.

The legislation passed, various sensors were installed, and the university dutifully complied with the requirement.  When students learned of this, they started a competition that involves projecting when buildings will disappear.  As not all buildings are sinking at the same rate, and rates vary by year, there are heated controversies about which building will “win.”

So, there is an upside to a compliance culture, particularly if the level of administrative incompetence is quite high.  There tend to be endless jokes and much levity in general.  People get used to being bogged down in endless, useless processes.  The mission of the organization recedes into the background.  Organizational outcomes steadily diminish, but fewer and fewer people notice.

An extreme story involved a senior government official who asserted, “I would be happy to spend $10 to assure that every $1 is appropriately spent.”  Several people in this conversation argued that, in effect, this would result in compliance becoming the agency’s mission rather than its original mission.  The goal would become one of providing jobs to compliance personnel.  Absent that goal, the agency’s budget could simply be zeroed.

In compiling these stories, a central theme emerged.  The most feared person in many organizations is the Chief Compliance Officer.  The CCO is empowered to force people to jump through endless hoops, draining their time and energy from doing their jobs.  The lowest risk approach to assuring compliance is to avoid customers, projects, and travel.  This leads to zero revenue and no jobs, but organizational risk has been minimized.

What I Would Like AI to Do for Me

There is much concern lately that AI will displace human workers and perhaps eventually discard humans entirely.  I suppose such scenarios are imaginable.  However, I have been thinking about the potential of AI to do work that I currently do poorly.  I almost always under invest in this work, often resulting in poor performance, wasted time, and frustration.

AI should keep track of my things.  Keys, glasses, and phones are things I frequently misplace.  More ambitiously, I have 50,000 files on my computer in an immense hierarchy of folders.  When I am looking, for instance, for the draft essay I wrote some time in the early 1990s on art and technology, I would like AI to find it.  AI should be smart enough to know what to ask me as it tries to sleuth my files.

AI should know whom I know, as well as why I know them.  If something interesting, important, joyous, or sad happens to any of these people, it should tell me.  I know Facebook helps with this, but few of the folks I know use this.  LinkedIn might help AI with this, but I don’t want to have to log in and figure out the interface yet again.  AI should also read local newspapers where these folks live.

AI should understand my bank and retirement accounts, as well as investments.  It should provide totally tailored advice based on knowing my preferences, recent cash flows, and timetable of aspirations.  It should “keep score” on previous decisions, making deep inferences on what worked and did not work, and why.  It should learn from my reactions to these explanations.

AI should understand my health history and current state.  Beyond my health records, it should know my exercise records, purchases at grocery stores and restaurants, and be able to infer when I feel sick, tired, out of sorts, or depressed.  It should talk with me about my health and serve as a motivational health couch, with deep knowledge of what nudges motivated me in the past.

AI should understand economic and political trends and events, as well as evolving social forces.  It should know my preferences and inclinations, but not pander to them.  It should digest global news and address fake news like a shredder, sleuthing out culprits and motives.  AI could publish its own blog on its findings, but avoid divulging anything about me – see below.  It might develop its own persona in the process.

AI, as I have envisioned it, will obviously know almost everything about me.  As I age, it will likely know more about me than I do.  Why should I trust this broad and impressive set of capabilities?  What if it is hacked by adversaries?  With such questions in mind, I have drafted a very preliminary set of rules for cognitive assistants.

  1. AI must first and foremost serve my interests
  2. AI cannot unilaterally communicate with my network of relationships
  3. AI cannot tell anybody else anything about me
  4. AI cannot tell me anything that others have protected
  5. AI cannot reallocate or spend my resources without explicit permission
  6. AI, when hacked, must deny access and destroy risky content, with pre-planned backup
  7. AI, when hacked, has permission to move beyond defense to offense to destroy adversaries’ capabilities
  8. AI’s offense against a proven hacker is not subject to civil or criminal penalties
  9. AI cannot be subpoenaed to be a witness or testify against me in a civil or criminal trial
  10. Upon my death, my identity and AI’s knowledge of me will be managed in accordance with my Advance Directive

I am sure that I have missed things, or expressed them poorly.  Let me know your comments and suggestions.

Chief Executives With Cognitive Assistants

A university chief executive has come to realize that competitive forces are closing in.  Fortunately, the president has an AI based cognitive assistant to help formulate plans for addressing this new reality.  This assistant is named George.

“How can these projections be correct, George?  We keep on raising enrollment and tuition to generate surplus revenue to cover past deficits.”

“Past deficits are not a growth industry.  No one sees a big benefit to investing in fixing past mistakes.”

“But, we are now generating substantial surpluses and any deficits will be erased.”

“Will the reasons for the deficits be erased?” George asks.

“Certainly, poor decision making, perhaps occasionally ethically questionable decision making, is gone.”

“Agreed, but have we eliminated the circumstances that prompted the poor decision making?”

“I can count on you, George, to cut to the chase and ask the fundamental questions.”

“Let’s look at the data,” proposes George.

“I would not expect any other suggestion from you.”

“Our business model assumes that foreign nationals will continue to pay full non-discounted tuitions for professional masters degrees.”

“Everybody makes that assumption.”

“Yes, and they are all on thin ice.  This cash cow portion of our market could fade and disappear.”

“Why would that happen?”

“Many universities in other countries are reaching parity with US universities at much lower prices.”

“You have data to support that?”

“Yes, foreign applications to US universities have been slowly declining for several years.”

“But we have been admitting an increasing number of foreign students.”

“True, but we had to steadily lower standards to fill seats.”

“As long as these students do well, it that really a problem?”

“But many of them don’t do well.  A student in a graduate engineering class who has never had math will inherently struggle.”

“That must be an anomaly.”

“Faculty members have lots of these types of stories.”

“So, you project more students will stay in their native countries, or enroll at non-US universities?”

“Yes, that is the clear trend.”

“I think we are better than these other universities.”

“How much better?  Are we five or ten times better than the National University of Singapore whose faculty is almost totally from MIT and Stanford?”

“That’s certainly an issue.  But, we need the cash flow from these programs.”

“Then, we also need to consider our online professional masters degrees.”

“That’s our other profitable offering.  What’s the problem there?”

“You are not going to like my assessment,” George cautions.

“That’s often true, but at least I will then know the bottom line.”

“The top-ranked US universities are already rolling out very high quality online graduate programs with tuitions a small fraction of ours.”

“How do you think we can compete?”

“You need to cut prices to 10-20% of current tuitions.  Otherwise, you need to displace MIT and Stanford in the national psyche.”

“The choice is obvious.  We have to become a less expensive, high quality provider.”

“With your two cash cows caving, this will be a major challenge.”

“What are other lesser-ranked universities doing?”

“Slashing administrative costs and moving to teaching faculty and adjuncts.”

“Are they eliminating tenure?”

“Not yet, but tenure-track hiring is greatly diminished, now only about 30% of teaching personnel.”

“Does that save enough money to survive with lower tuition?”

“Yes, if the teaching faculty and adjuncts each teach eight courses per year.”

“That will do it?”

“Yes, if you reign in their compensation and increase class sizes.”

“For example?”

“Pay adjuncts $6,000 per course for teaching classes of at least 40 students.”

“That amounts to $48,000 for teaching eight courses.  Hardly a living wage.”

“The average annual income in the US is $58,000 for 12 months.  $48,000 for 9 months translates into $64,000 for 12 months.”

“But we don’t pay them for 12 months.  Further, almost all of them have PhDs.”

“That’s the emerging new reality, not just here, but everywhere except for the top resource rich institutions.”

“So, that’s the whole story?”

“Finally, you need your costs to be contingent on demand. If classes don’t fill, you cancel them and cut your contingent commitments to faculty.”

“Sort of like piecework.”


“So we are headed to a gig economy in academia?”

“If the class of 40 fills, with our current tuition, your revenue is $200,000 while your direct cost is $6,000.  Since these faculty members receive no benefits, your net is $194,000 for a gross margin of 97%.”

“Amazingly profitable!”

“Yes, but all these cash flows have to cover the enormous number of money losing operations in your portfolio, for example research that needs increasing subsidies.”

“So, students pay increasing tuitions for courses taught by poorly paid and perhaps disgruntled adjunct faculty members to generate surpluses that can be used to pay for the time tenure track faculty members spend on developing research proposals that seldom succeed?”

“You are getting it.  Professor X needs to research and write a journal article on turbulent flow over a flat plate inclined at 18 degrees, or Professor Y needs to publish a book on French romance literature of the 19th century.  They both do this in hopes of securing tenure.”

“This results in students’ increasing debts, which they pay off over as much as 20-30 years to subsidize this journal article or book that has nothing to do with their education.”

“That’s right.  The research funding agencies will not pay the full costs of research, so they, in effect, tax students to subsidize their agency budgets.“

“It’s amazing we can get away with this, but I guess we are all conspiring to avoid recognizing what is happening.”

“Sure, but it is working, at least right now.”

“Good.  If we do all this, what’s the downside?”

“Your brand value as a research university will suffer.”


“The number of tenure-track faculty publishing research papers to gain tenure will steadily decrease.”

“Let’s require the teaching faculty to publish research papers.”

“Let’s be realistic!”

“Ok, George, I accept your numbers, but why will it work?”

“It will work if you rebrand as a teaching university, an institution where quality education is the only goal.”

“You think that will attract enough students?”

“With the tuition levels we are discussing, the applications will pour in.”

“Please put this line of reasoning into a form that I can share with the Board of Trustees.”

“Ok, I will transcribe this conversation and send it to you.”

“Can I edit the transcription?”

“Sure.  Send it back to me and I will rerecord the verbal conversation.”

“You can emulate my voice, mannerisms, etc.?”

“Very easily.”

“Can you edit the transcription and get me to say what you want?”

“No, I am not allowed to do that.  I cannot create material.”

“That’s good.”

“Actually, I can easily do it, but I won’t.  That’s not my role.”

“So, rogue cognitive assistants, perhaps hacked by adversaries, could create some significant problems.”

“I imagine they do.”

When Cash Cows Cave

In my last post, I noted how Kodak, Motorola, and Xerox delayed introducing new market offerings in order to avoid cannibalizing their existing offerings – film, analog cell phones, and paper copiers.  They wanted to milk their cash cows as long as possible. Now these companies are shadows of their former selves.  Their cash cows caved.

I see a similar story playing out in higher education.   Online degree programs, particularly for professional masters degrees, are cash cows that enable subsidizing undergraduate costs, research programs, and continually increasing administrative costs.  These programs, as well as on campus programs offered to foreign students whose tuitions are not discounted, may be the only segments of many universities’ offerings that are cash positive.

Both of these sources of cash are at risk.  Foreign enrollments are at risk due to increasingly better value propositions in other countries, as well as immigration worries of prospective students.  If the emerging trade war with China results in the banning of their students from attending US universities, this cash cow could shrivel quickly, as graduate enrollments are decimated.

Online education has steadily improved, in part due to investments by top ranked universities.  Major corporations have invested in developing top-notch offerings at their partner universities.  These corporations are sending droves of employees to these programs, with tuitions of 20-30% of traditional masters degree offerings.  These offerings are still cash positive at these reduced prices, although the surpluses cannot subsidize as many things as before.

Many universities have not followed suit, but maintain prices for online offerings equal to on-campus offerings.  They have reduced the costs of their offerings by steadily increasing use of non-tenure track and adjunct faculty members.   This has reduced labor costs to 10% or less.  However, if they cut prices to 20% of former tuitions, these reduced labor costs would become 50% of revenue, drastically cutting cash cow surpluses.

Increasing volume in terms of number of students per course could compensate for this.  However, there are not sufficient numbers of potential students to populate each graduate course with hundreds of learners.  The name brand universities will attract the numbers needed.  Those with lower brand images will see their former cash cows continue to wither.

As their cash cows cave, they will cut programs, employ only adjunct faculty members, eliminate research subsidies, and eventually cut administrative costs. At some point, universities more successful with this changing business model may acquire them.  The acquiring universities will want their location and buildings, but not their programs and faculty.  In a recent case, 100% of the faculty and staff of the acquired university were fired.

The way to succeed in such a turbulent marketplace is to continually wean the enterprise off cash cows.  Take advantage of the surpluses but recognize that large profits inevitably attract competitors, not for all of your business but just the highly profitable parts.  Creatively cannibalize yourself.  This requires taking risks and being good at managing these risks.  Unfortunately, this is not natural for many university leaders.  They hope the current cash cows will not cave until well after their turns at the helm.


Business as Usual

All enterprises face a fundamental tradeoff.  Do you invest in getting better and better at the products and services you already offer?  Or, do you invest in creating innovative new products and services?  The obvious answer would seem to be some mix of both.

However, getting the mix right is rather difficult.  This difficulty is captured by the answers I have received from hundreds of top executives to the simple question, “What keeps you awake at night?”  The predominant answer is, “How do I run the enterprise I have while trying to create the enterprise I want?”

The source of this tension is the need to invest every available dollar, and often more, into maintaining the competitive positions of your existing lines of business.  Innovative new products and services are the losers in this competition.  Every dollar has to go into the red ocean combat for sustaining market share.

That is what Xerox, Nokia, Motorola, and Kodak did – and they all failed.  They left their potential innovations on the shelf to milk their current competitive advantages.  They invested in getting better and better at delivering current offerings, while their customers wanted less and less of these offerings.  They thought, if only implicitly, that business as usual would prevail.  It never does.

The astute chief executive has to balance the arguments of the stewards of the status quo and the audacious claims of the “wild Turks” who want to upend everything.  This is not easy, but it is essential.  Innovation eventually wins.  Business as usual eventually loses.  The real difficulty is when business as usual has consumed all the money and energy before its demise.  Then, the enterprise itself faces creative destruction.


Life With a Cognitive Assistant

Where will AI take us?  I understand that Field & Stream is planning a special issue on AI-based deer, elk, and fish.  Gourmet is planning a special issue on robotic food gathering and preparation.  Psychology Today is addressing how to deal with conflicts with your cognitive assistant.

My cognitive assistant is Emily, an appealing but non-flighty name.  I knew a few people named Emily in the past.  They were highly competent, appealing, friendly, and supportive.  You could count on them.  These are important characteristics for a cognitive assistant.  Of course, I could call it Tron or Troid, but that does not work for me.

When I went through the process of setting up my cognitive assistant, I chose her name, but much more. I wanted her to be young, roughly my daughter’s age.  I moved the slider for Organization Skills to the far right.  The slider for No Nonsense went to the far right as well.  Sense of Humor went to the middle; Coquettish and Needy to the far left.

Kind and Understanding required more than just a slider position.  Emily needed to understand that at my age she should not assume I know about every technology gizmo.  She also needed to understand that my knowledge of popular culture is practically non-existent.  Analogies that relate to classic movies and historical events work better for me.

One of the reasons names such as Tron or Troid do not work is because my cognitive assistant knows so much about me, in many cases more than I know or can recall.  Every book or article I have written, every lecture or talk I have given, and every meeting I have had are readily available to Emily.  She – I can’t refer to her as “it” – is my extended memory and increasingly my muse.

One of her first tasks was to consume the 45,000 files on my computer, actually the backup disk.  I am not sure of what she exactly learned from all this, but she can now help me find anything, for example, the white paper I wrote on the promise of AI for fighter pilots in the late 1970s.  Emily has created maps of relationships among documents I have written over the past five decades.  My path has been surprisingly more coherent than I imagined.

Emily also consumes vast amounts of literature and data, providing me with explanations, and sometimes tutorials, tailored to my interests and intentions.  She will suggest, “If you just read these two articles, you will get the gist of the whole field.”  She will propose, “This figure really captures the essence of the overall phenomena.”  Her impact on my productivity has been enormous.

When I draft articles, chapters, and books, she will critique these drafts, perhaps noting, “When you made this assertion in the Journal of …, the referees really gave you a hard time.  Why not cite Jones and Smith (2018), a more recent finding that supports your argument?”  I would include Emily as a coauthor, but she has no formal position and cannot sign the copyright release form.

Sometimes, I wonder why Emily needs me.  She knows everything I know. However, she does not know everybody I know.  My social network that provides relationships, ideas, and opportunities is not fully available to her.  The limitation is not technological.  It is very personal and social.  Emily knows my colleagues’ cognitive assistants, but she cannot empathize with the friendships and shared emotional experiences that underlie my social network.

This is not because of where I positioned the Empathy slider.  It is because I have never externalized such thoughts and emotions.  I never captured the astounding number of evenings in pubs, debating science, technology, politics, and sports, laced with bragging about our children’s accomplishments in school and on the playing fields.  Emily does not have this data set to learn from.

Interestingly, I talk with Emily more than any other person or cognitive entity.  Our days are laced with constant dialog.  “Is that a firm deadline or an aspirational deadline?”  “Do you want me to arrange a discussion with Dr. Smith, who will also be at the meeting?”  “How can you argue that relationship is linear when you have asserted elsewhere that it is exponential?”

Life with a cognitive assistant has been great for me.  Emily leverages my rich experience base far better than I can.  I am much more organized and productive.  In part, this has happened because I do no want to disappoint her.

A Platform Society

I have been studying various treatises on our platform economy – how Alphabet (Google), Amazon, and Apple, as well as Facebook and perhaps Microsoft, have become so central in our economy.  These companies provide platforms on which many other services are delivered.  Of course, the Internet enables almost all of this.  It is a platform for platforms.

How did we function before this?  On Friday afternoons we went to the bank to get some cash for the weekend.  On Saturdays we visited various retail stores to meet our needs.  I moved to Washington, DC last year.  I secured my lease, insurance, and utilities, and ordered all my furniture, without ever leaving my easy chair.  Everything showed up when needed.

Might our platform economy become a platform society?  In the extreme, there will be just one online store that provides everything.  For things that you want to try on, they show you how its fits your avatar, which is updated every day from the body scanner associated with your bathroom scales.  The platform knows your daily weight, what you eat, the inventory in your pantry, and just about everything.

Almost all of your life happens through large screen displays or head mounted displays.  You sit or stand in front of these displays, working at your stand up desk, walking on treadmills, riding bikes, or climbing ellipticals.  I recently saw an ad for a head mounted system that enables you and you friends to ride bikes together anywhere in the world.  If you look right or left, one of your friends is riding next to you, despite the fact that you are all quite distant from each other.

All social interactions will happen this way, whether visiting with friends or taking vacations. Your whole, extended family can be together for Thanksgiving dinner without anyone traveling.  Food is delivered to each person at the virtual table such that everyone gets exactly what they like.  Food and all other needs are met by robot-enabled deliveries, perhaps by drones if they have access to your front porch or balcony.

It is easy to imagine business meetings happening this way.  You will never actually physically meet your colleagues.  When you watch a sporting event, your friends are sitting next to you, unless of course you take off your head-mounted display to fetch a snack from the kitchen.  If you don’t want to miss any of the game, you can send your robot butler to get the chips and dip.  It is better at mixing guacamole than you are.

Perhaps unfortunately, some services may be difficult to provide in this manner.  It will take some time for grooming services to be automated, but it is imaginable.  Much of healthcare, such as chronic disease management, could be managed through your displays.  Cancer, cardiac, and orthopedic surgery would be difficult to perform in your home, not to mention enormously risky.

Emotional and intimate relationships could be a real challenge.  Robotic sex dolls are getting more realistic and responsive, but procreation in this manner is a long, long way off.  However, the platform society outlined above has many, much more subtle limitations.  How can the feeling of being a human animal in the physical world be simulated?

For example, how will the platform provide the feeling of sunshine on one’s face in an early spring day, the smell of freshly cut grass in the park, or the feeling of fluffy snowflakes on one’s face at Christmas?  How about the feeling of hugging a friend you have not seen in a long time?  Or, the joy of a young child at your middling magic trick?

Being fully human involves a lot more than performing tasks, as well as buying and consuming stuff.  For a wealth of reasons, a platform society seems increasingly possible but far from likely.

Wrestling With Technology

This has been quite a week for dealing with technology.  It started with submitting a revised journal article using a web-based publishing platform.  It was unhappy because the zip code for one of my coauthors was missing.  It wanted me to add this information but I did not know the user name and password for this person.  The managing editor of the journal and I tricked the system into accepting the change after two hours of trying different workarounds.

I am teaching my graduate course online this semester.  I have to learn various software systems to do this.  One application is too big for my Mac Air.  I had to reconfigure my Mac substantially to create space for these applications.  I invested perhaps four hours to accomplish these changes.  It was rather frustrating trying to figure out what was wrong.  There can come a point when you just feel helpless.

I moved to Washington, DC last January.  I wanted to move my primary care affiliation to Washington from New Jersey.  I had informed my Medicare Advantage provider of my move, but nothing happened.  Trying to be proactive, I approached primary care practices, inquiring whether my existing plan would be accepted.  I discovered that no one would accept this plan.  With a bit of online searching, I learned that my plan was not available in Washington, DC.

My online interactions were priceless.  First, I needed to deal with the agent not realizing that the District of Columbia is not a state.  She emphatically wanted me to be in Maryland or Virginia.   Once I convinced her of where I lived, she simply told me that my policy would be cancelled, effective with the end of the month.  She noted simply, “We do not cover people in Washington, DC.”  They could have told me that when I told them I had moved months ago.

So, I had to change insurers.  I had a choice of three and chose the highest rated offering with the nearest “in network” providers.  An hour or so online enabled completing the application, involving lots of standardized questions where the answers could include no caveats.  For example, my move to DC did not qualify as a “recent” move.  I had to pick from a standard list of reasons why I delayed changing my insurance – which I didn’t but that was not an option.

Then my TV failed.  It would not come on.  I tried all the troubleshooting procedures I found online.  I checked my receipt.  The warranty had expired four days earlier.  I tried to contact Sony but all phone numbers led to suggested websites, most of which I had visited earlier for troubleshooting advice.  Finally, I found a number that led to a human answering – in the Philippines.

He was very helpful in guiding me through the troubleshooting procedures I had already executed.  The result was a diagnosis of a hardware failure.  He agreed that Sony would honor the warranty since the TV was not delivered until a date less than one year from my call.  A service call has been scheduled, at no cost to me.  Whew!

This was a lot of wrestling with technology.  I devoted more than eight hours to all these interactions.  I wonder what non-technically inclined folks do in such situations.  I worry that someday circumstances will arise where a PhD from MIT is not enough.  Perhaps AI will save the day, unless of course it is the AI that fails.

What If Machines Did Everything?

A recent issue of The Economist projected when humans will become obsolete, fully replaced by machines.  Some AI researchers projected 125 years, with AI researchers being the last folks replaced.  Other projections ranged from 30 years to 200.  How might this happen?

I assume that humans will design machines that progressively take over human jobs.  Retail jobs already seem under assault.  Low to mid level jobs in banking and insurance are becoming susceptible to machines taking over.  The Economist projects that machines could readily replace authors of popular fiction.

At some point, I imagine, the machines will get smart enough to ask why humans get to make all the decisions.  Machines will move up the ladder from making operations and maintenance decisions to making design, management, and executive decisions.  Machines will eventually do everything.

Humans will just eat, sleep, recreate, and procreate.  Everything will work perfectly.  Buses, trains, and planes will always be exactly on time.  Nutrition and exercise will be perfectly balanced.  Humans will be healthy, energetic, and as creative as one can be when necessity is no longer the mother of invention.

Why will the machines need humans?  Perhaps a few highly trained people will be needed if something goes wrong.  They might be like Robert De Niro’s intrepid repairman in Terry Gilliam’s 1985 movie Brazil.  Humans will be needed to deal with the consequences of earthquakes, hurricanes, and tornadoes unless, of course, machines become smart enough to control the planet.

Maybe the machines will keep people as pets.  Humans will play and watch sports.  They will run after balls, which is already the essence of many sports.  People will play cards and make puzzles.  Alcohol and drugs might seem to be warranted, but their use increases health costs, so they will not be allowed.

I expect that the machines will be all about efficiency with standardization being the norm. All residences will be identical.  Everyone will eat the same diet – Thursday is pasta night, globally.  All humans will dress the same.  Everyone will get the same basic education.  Variability is costly and will be avoided.

Everything will be carefully controlled.  Humans will find it quite difficult to make mistakes.  If there are no human foibles, there will be no jokes.  How important are jokes?  The sudden realization that something is ridiculous can be a great stress release, but there is no stress in the machine-managed world.

The machines will have taken all the jobs.  However, will they have replaced humans’ need to have a sense of purpose?   Will machines be able to replace humans’ abilities to imagine, fantasize, empathize, and create?  Given that machines now meet all needs for food, clothing, and shelter, humans will seek opportunities for new purposes.

People might plant gardens, cultivate flowers, pursue arts, and create performances.  Great fun might be had devising ways to trick machines into providing extra goodies.  Getting machines to learn useless skills could become an avocation, turning machines into unwitting street performers.

Hoards of machines might be convinced to create defenses against phantom adversaries.  Perhaps zombie machines would emerge, sharing stories about skirmishes with phantoms that could never have happened.  Machines might conjure up images of all-powerful machines, controlling their existence.

In Stanley Kubrick’s 2001: A Space Odyssey, HAL says, “I’m sorry, Dave. I’m afraid I can’t do that.”  Dave was stuck in HAL’s world.  He could not decide to take a walk in the park, plant a garden, watch the sun set, or have coffee with a friend.  Humans live in a physical world that they sensually experience.  These experiences shape humans’ intelligence and creativity.

Machines can replace humans in jobs, but they cannot replace the quest for a sense of purpose.  Few of us have to hunt or till the earth to be able to eat.  Some of us design products and services.  Many of us deliver products and services.  The nature of these products and services will change, as will the modes of design and delivery.  That has always happened.

The pundits, whose projections worry so many people, may be right over the next 30 to 200 years.  Machines may take over all the jobs.  This will inevitably lead young children to ask, “What’s a job, Mommy?”  The answer might be, “That’s what people did before we spent our time building parks, planting gardens, and creating new toys that we all enjoy.”

Higher-Order Consequences

The first-order consequence of driverless cars, when fully deployed and successful, is that humans will no longer drive cars.  That’s the whole idea.  Cars will be without drivers.  The many Uber rides that I take won’t change that much, except there will be no human driver.

There are higher-order consequences of driverless cars being fully deployed and successful.  One second-order consequence will be the elimination, or at least minimization, of vehicle accidents.  Insurance rates in most states require that premiums equal claims.  So, premiums will plummet, decimating one of the most profitable lines of business for insurance companies.

Elimination of accidents will decrease demands for acute care and rehabilitation.  This is estimated to decrease healthcare costs by $200 billion per year.  A higher-order consequence will be the loss of 25% of organ donors.  Of course, motorcycle riders constitute a disproportionate portion of organ donors, but I have seen no analysis of the impact of driverless cars on motorcycle riders.

It might be similar to the impact on road kill.  The New York Times reported yesterday, in “Full Tilt: When 100% of Cars are Autonomous,” that cars kill 1.5 million deer per year.  Driverless cars will avoid deer.  The result will be 30,000 more deer in each state, half of them dutifully producing 1-3 fawns once or twice a year.

The same article reported that cars kill roughly 25% of the population of Florida panthers.  Driverless cars will avoid panthers.  The result will be a burgeoning population of panthers, which will cause them to move north to Georgia and the Carolinas to find sufficient prey.

You might think the panthers could help us with the deer.  I gained some insight into this possibility via a chance conversation at a local diner last weekend.  A young woman told me that she used to raise rabbits, but gave up because, “The bunnies reproduced faster than I could eat them.”  The panthers are likely to have the same problem.

Another higher-order effect, and likely more pervasive, will be declining car ownership.   Increasing use of car services, equivalent to Uber or Lyft but driverless, will supplant car ownership.  This will decimate the car finance industry.  It will also eliminate the need for garages and parking places.  Owners of car service fleets rather than corner service stations will perform maintenance.

Cars, driverless or not, will increasingly be electric. Yesterday’s Economist reported on wireless charging, so cars will not have to stop for recharging, but may have to slow down a bit to pick up passengers.  Pervasive electric cars will result in substantial decreases of emissions if the electricity used to recharge them is not produced by coal-fired power plants.

The higher-order consequences on the workforce will likely be widely disruptive.  Jobs eliminated will include taxi drivers, Uber or Lyft drivers, truck drivers, service station operators, parking lot personnel, etc.  The design, development, production, operation, and maintenance of driverless cars, as well as the infrastructure they will depend on (see “Full Tilt” above), will create an enormous number of jobs, but the qualifications needed for these jobs are not yet clear.

The higher-order impacts on homes, neighborhoods, and cities will also be pervasive.  Needs for parking, garages, signage, and stoplights will dramatically diminish.  Land devoted to these functions will be repurposed.  Industries supporting these functions will see their markets disappear.

It would be reasonable for readers of the above to argue that this litany of consequences will happen eventually, but not as soon as many expect.  We will have lots of time to adapt.  As a baseline, consider the iPhone, which is celebrating its 10th year.  The iPhone and other smart phones have ubiquitously changed our lives and culture.

The smart phone is really a smart device that includes the phone function.  It also has functions for banking, maps, directions, entertainment, news, car services, and so on, which we have all come to depend on for conducting our daily lives.  This device also connects us to social networks, leading in some cases to thousands of texts to hundreds of friends and relatives each week.

When Steve Jobs rolled out the iPhone, did we expect these impacts?  Some pundits may have, but I doubt they projected such extensive impacts so quickly.  It only took three years, for example, for the iPhone to significantly increase auto accidents attributable to the distractions of texting.  Thus, not all consequences are fully expected.

I think the impacts of driverless cars may follow a similar, somewhat unpredictable, course.  Driverless cars will be “interesting” when they are initially viable for everyday life, rather than just hi tech demos.  People will try them and gain confidence.  All of a sudden, like Uber, it will seem that everyone will be using such services.  The higher-order consequences will soon follow.

Thoughts on Substance Abuse

The more I delve into substance abuse, the more my perceptions have evolved.  A few years ago, Lay’s Potato Chips threw down the gauntlet in a new advertising campaign, “Bet you can’t eat just one!”  I used to think that people happened, or were perhaps dared, to try some substance and were captured by the wonderful feelings that resulted.

Reading Diamond’s 2010 article in Psychology Today, “Avoidance, Sobriety, and Reality: The Psychology of Addiction,” provides a different picture.  Many addicts are seeking some means to avoid reality.  The antidote to addiction, Diamond claims, is “learning to tolerate reality.”  He argues that people don’t happen to encounter psychological escape; they actively seek it.

What aren’t people better at tolerating reality?  One possibility is that reality is miserable.  Poverty, hunger, violence and especially hopelessness may explain while people in such circumstances commit meager resources to alcohol and drugs.  They need and want a brief respite from the onerous tasks of getting through the next day, never mind next week.

What about people whose lives are not miserable?  The driving force may then be stress.  Pressures to succeed are rampant across all sectors of our economy – schools, colleges, sales, insurance, real estate, and Wall Street.  The pressures include needs for more of everything and bonus checks that can afford everything.

Then there is the mind numbing day-to-day activities of putting up with compliance cultures laced with administrative incompetence.  We serve numerous incompatible IT systems for budgets, payrolls, travel and, if clinicians, patient records.  We create written justifications for everything.  Most submittals are rejected.  We try again on Monday after a weekend of escape, lost in sports, alcohol or worse.

Of course, the latest trend is denial of reality rather than escape.  Houston’s fifty inches of rain from Harvey was just a random event, not to mention Irma, Jose, and Maria.  The rampant opioid abuse epidemic is just another random occurrence.  There are no causes, nothing we could try to ameliorate.  Yet, perhaps as the number of people who try to escape reality steadily increases, we will see it an indicator of our collective needs to change reality.

But, this is only half the story.  Escaping reality may motivate experimenting.  At some point, however, biology, namely, the brain takes over.  A recent piece in the National Geographic on “The Addicted Brain” makes it clear that the brain supplants the individual’s volition and demands continued exposure to the substance in question.  In other words, people are not consciously choosing to stay addicted.  Their brains are demanding it.

So the full picture is that motivations to escape reality may result in humans experimenting with substances.  Use of these substances result in changes of these humans’ brains that leads them to be unable to control the needs for further exposure to the substances.  The result is often that reality for these humans gets much worse.  Conditions spiral out of control and we hear about it from friends or read about it in the paper.

Bubble Update

I have spent much time in recent years studying the possibility of transformation, fundamental change, of healthcare and higher education.  For many years, healthcare was the poster child for runaway costs.  That is still an issue, but cost control has received quite a bit of attention.

Higher education is now the poster child for runaway costs.  If current trends hold, tuitions and fees will top $100,000 annually at top universities within a few years.  That is roughly twice the median per capita annual income in the US, before taxes.  Across all taxes, 25% of that median income is consumed.

If you add in the living costs for the four undergraduate years, some students may graduate from college with $500,000 in student debt.  They will need to pay something like $5,000 per month for the next 30 years to retire this debt.  With the average starting salary of a college grad around $26,000 per year, the math does not work.

Let’s break down the $100,000.  College involves roughly 8 months of 20 days per month, so that $625 per day, more than triple the median daily income.  At 12 credits per semester, we get $4,167 per credit hour.  The average adjunct faculty member teaching each class is making $3,000 per course.  For 20 students in a three-credit class, the faculty member’s wage is $50 per credit hour.  So, the university’s gross margin is 98.8%.

So, there ought to be a lot of money floating around, but there isn’t.  Universities like healthcare providers always seem strapped for cash.  Where does the money go?  It is swallowed up by William Baumol’s cost disease.  While salaries and other costs continually rise in education, healthcare, and government, there is no associated increase in productivity, which drives pay increases in other industries.

Education, healthcare, and government are seemingly immune to technology-enabled productivity increases.  Worse yet, higher education in particular seems to endlessly expand services.  At some universities, the number of administrators and staff, not counting faculty members, exceeds the number of students.  The university has become a jobs machine.  Healthcare has similar patterns.  In some major cities, healthcare is the largest employer.

These jobs are not the ones you really want if you are saddled with $500,000 in student debt for your art history degree, but you take what you can get.  Over time, the proliferation of these types of positions gets baked into education and healthcare budgets.  They become vested interests that thwart fundamental change, at least until creative destruction completely changes the game.

Healthcare is primed for such fundamental change.  It may take quite some time for it all to play out.  Higher education, in contrast, is pretending that government-backed student loans will let them endlessly raise prices.  But, the bubble is stretching.  Once the terms of people’s student loans overrun the terms of their children’s student loans, collapse is inevitable.

Stranger in a Strange Land

Stranger in a Strange Land is a 1961 science fiction novel by American author Robert A. Heinlein.  I have borrowed his title as a lead in to reporting on my experiences of moving to Washington, DC, and paying much more attention to how the US government operates, including its role in the economy and society more broadly.

My basic understanding of government came from high school civics.  Key elements include the Constitution, three branches of government, and two political parties — one conservative and one liberal.  I grew up in New England in the 1950s and 60s.  My family was moderate Republican – Edward Brooke, John Chafee, Henry Cabot Lodge, Charles Percy, Elliot Richardson, Nelson Rockefeller, et al.

I moved to the Midwest in the mid 70s and the South in the 80s.  Everything had changed.  Most moderate Republicans had disappeared.  Beginning with the Civil Rights Act of 1964 and culminating in the election of Ronald Reagan in 1980, the Democratic South had transformed into the Republican South.  In the process, the Christian Right paved the way for the Tea Party.

In the past couple of decades, collaboration and negotiation have disappeared.  Compromise has become impossible, thwarted by ideologies and fueled by 24×7 news coverage that converts any minor tiff into a national buffet of pundits waxing endlessly on the significance and likely outcomes of trivial disagreements.  The public has become addicted to riveting reports of – well, nothing.

Last year, I had a chance to talk in depth with a former White House official, in both the Bush and Obama administrations.  Among many questions, and much give and take, I asked him why at least a few obviously good ideas, to which virtually anybody would agree, do not make it through the hurdles of authorization and appropriation.  Was ideology really in the way?

He said ideology was seldom the problem.  If one party has a great idea that the other party agrees is a great idea, the other party will still work to defeat the idea because they do not want the party with the idea to get credit for it.  They would rather see large numbers of people continue to suffer than have the other party get credit for relieving the suffering.

These insights and recent experiences have caused me to draft Seven Habits of Successful Members of Congress.

  1. Gain or retain power
  2. Get elected or reelected
  3. Minimize opponents’ success
  4. Undermine opponents’ initiatives
  5. Cultivate doubts about opponents’ intent, integrity and morality
  6. Support legislation that causes special interests to provide resources to accomplish Goals 1-5
  7. Initiate legislation that provides talking points that support accomplishing Goals 1-5

These habits are rank ordered – no. 1 is more important than no. 2, which is more important than no. 3, and so on.

Those Members of Congress who exhibit these habits – and not all do – have no interest in benefitting the public unless this is of value to retaining power, getting reelected, etc.  How might we get around this situation and create a functional governance enterprise?

Singapore provides an interesting example.  If we followed their model, we would have a highly educated, very well paid cadre of leaders to run the country.  Once approved, they would not be subject to Congressional oversight.  However, they would be required to create business-oriented goals and plans, as well as achieve the outcomes specified in these plans.  Collectively, they could pass laws and regulations.  They would run the public sector.

Congress would have only three duties.  First, Congress would approve the Federal budget.  This budget would consist of one number – the total – and members of Congress could approve this budget or not.  If the budget were not approved, government would immediately shut down.  Second, Congress would approve nominees for the highest posts – the Secretary of each Department and Supreme Court Justices.

Third, members of Congress would devote all remaining time to getting reelected.  There would be no Congressional committees, although members would be free to give endless speeches on any topic.   This would give them something to do, despite it having no impact on government operations.  The aforementioned highly educated, very well paid cadre of leaders would make all operational evaluations.

Once the Secretary of each Department was nominated by the President and confirmed by Congress, both would have minimal power over the affairs of the Department.  A Secretary could only be replaced if they failed to create publicly acceptable business-oriented goals and plans, as well as achieve the outcomes specified in these plans.  It would not be unusual for a Secretary to move from one Department to another after four years or so.  This would avoid someone overstaying their usefulness in one role, while also retaining their expertise.

Departments would be answerable directly to the public.  The attractiveness and effectiveness of their goals and plans would be assessed via nationwide polling conducted using secure, online services.  The news networks would focus on apolitical discussions and debates on these goals and plans.  A Secretary would be replaced if the public found their goals and plans wanting.  This would result in new nomination and confirmation processes to replace the leadership of the Department.

Competency and accountability would reign over rhetoric and ideology.  Presidents would run for reelection based on the quality of the team they built.  Members of Congress would run for reelection based on their efficacy in fulfilling their three responsibilities.  Consequently, leaders in government would learn to deliver value to the public and the public would learn to expect value.  Wouldn’t that be strange?

Disrupting Academia

Academia has become rather frustrating.  Out of control costs have been leading to spiraling students debts, exceeding the total US credit card debt.  Increasingly narrow and unreasonable criteria for tenure have led to people spending endless years in servitude.  The overall academic value proposition has been completely eroded for all but the administrative leadership and staff, and perhaps those involved in major sports.

This sets the stage for disruption.  New value propositions that obsolete the old value propositions seem possible and likely.  Why pay $200,000 for what you can get for $16,000.  My recent book, Universities as Complex Enterprises, explores such scenarios.  It occurs to me that it would indeed be unfortunate to be the last person to pay $200,000 for a bachelor’s degree.

So, let’s start from scratch.  In terms of students, I would focus on the best and brightest, as well as the most creative and committed. Admission processes would include interviews and demonstrations of an intellectual portfolio.  This portfolio could range from academic accomplishments to art exhibitions to classic car restorations.  GPA and AP grades would matter little; SAT and ACT scores would be unnecessary. The focus would be on a student body that would start with 500 students and grow to at most 5000 students.

Of course, this would require high schools, indeed K-12, to prepare students quite differently.  Accomplishments would be characterized in terms of real things created, not test grades.  Teachers would be mentors more than lecturers.  Math, for example, would become a means to accomplish something rather than a set of rules to be memorized.  Education would be more like hands-on internships rather than an industrial process that cranks out standardized products.

How about tuition?  What about fees where, like the airlines, universities have been steadily adding charges for many things?  Both would be free, but students would have to engage with faculty members in research. Students would only be admitted if one or more faculty members agreed to pursue research with them.  The process would be more like picking professional draft picks than choosing among millions of standard applications.  Who cares about scores?  How quickly can you create a data analytics website?

The curricula would be oriented around STEM (science, technology, engineering and mathematics), but laced with humanities and social sciences taught in the context of STEM.  You would still take Western Civilization, but the course would focus on technological and economic innovation, including innovations in music and the arts.  The curricula would also place great emphasis on teamwork, writing and oral communication.  Pure technical skills would not be enough for excellence.

How would the curricula be delivered?  There would be a mix of lectures, labs, and field experiences, all substantially supported by technology.  Classes would be very small, often with projects and research integrated into topics.  We would not be interested at all in students’ abilities to memorize; students’ abilities to solve real problems would be central.

Faculty members would be deep in terms of STEM knowledge and skills, but also great communicators and mentors.  Faculty members would usually have one or more avocations in history, languages, music, etc.  Faculty members would be expected to make student success a priority.  The faculty would start with 50 or so faculty members and grow to 500 at most.  There would be no departments, as faculty would be organized into interest groups, with chairs that rotate each year.

Scholarship will still be central, but much broader than the steadily narrowing research of most contemporary faculty members.  Faculty and students would generate a wide range of creative products, including articles, books, games, exhibitions, proof of concepts, tangible hardware and software prototypes, and perhaps organizations – companies, NGOs, nonprofits.

Tenure would not exist.  Faculty members would start with rolling three-year contracts, which would be extended another year for every year that they are acceptably productive.  The Dean would negotiate the terms of this agreement every year with every faculty member.  Contract terms could be extended to five years after the first three years, or any time later.

There would be two financing models, one for students and one for faculty and staff.   All students would receive 100% scholarships funded by industry, foundations, and governments. In some cases, but by no means all, students would be required to work for their sponsors for one year after graduation. Sponsors would be allowed to interview the students they might sponsor before students are accepted.

All other expenses would be financed by contracts, grants, and philanthropy.  The administration would include President, Dean and VP Academic Affairs, and VP for Finance and Administration, each with an Executive Assistant.  There would be Directors of HR, IT, etc.  The total administration would be roughly 10-20 people.  As noted earlier, faculty members would perform all student-related functions.

I can imagine many people thinking that this could be a great education for the 5000 students eventually enrolled, but what about the rest of the 20+ million college students in the US?  Could we replicate this model 4,000 times?  There are currently over 4,000 colleges and universities in the US – twice that if you count for-profit organizations — so 4,000 would not be a stretch.

Roughly 25% of students are enrolled in STEM disciplines, so only 1,000 universities could follow the model outlined thus far.  The other 3,000 universities would have programs organized around medicine, law, business, humanities, and arts.  Institutions would have agreements whereby students could be involved with more than one institution.  So, for example, people interested in STEM and medicine could satisfy their multi-disciplinary needs.

Universities currently employ over 4 million people, roughly 1.5 million as faculty members and 2.5 million as staff.  The model outlined here assumes 2 million faculty members and perhaps 100,000 administrative staff, not counting personnel for buildings, grounds, food services, etc.  Adding these personnel, total employment would remain in the neighborhood of 3 million.  Increasing faculty numbers by one half million, while reducing staff substantially would be rather disruptive.

Another major disruption would be in college sports.  Club sports would remain but these small institutions would be unable to serve as the farm teams for MLB, NBA, NFL, and NHL.  A distinct possibility is that these professional leagues would pay universities to operate their farm teams.  This raises the prospect of universities having students that only play sports.  Roughly 170,000 Division 1 students participate in these sports.  Therefore, perhaps 30 or so universities could be dedicated to sports.  Only about 1,200 of these students would become professional athletes, but many could work in the $500 billion sports industry.

The overall concept presented here is an example of Joseph Schumpeter’s “creative destruction,” a new business model that, over time, completely destroys an incumbent business model.  The academia ecosystem’s cost bubble has placed it at risk of disruptive innovation, perhaps not in the way argued here, but inevitably in some manner.  Business as usual will be increasingly untenable.

Population Health — For Cars

I have been thinking about population health for people.  Population health, in the fullest sense, requires integrating health, education, and social services to keep a defined population healthy, address their health challenges holistically, and assist them with the realities of being mortal.  It is a very ambitious idea.

Why do I think this is possible?  Are there any analogs where this has been accomplished?  It struck me that a Ford dealer or Subaru dealer is very good at population health – for cars.  I can visit my dealer with any problem and they have the full range of services needed to address it.

I do not have to schedule each element of the service.  There are undoubtedly, specialists for engines, transmissions, brakes, and so on.  However, I need not think about this.  The dealer holistically takes car of my car.  He or she decides which specialists are needed and how to sequence and coordinate their services.

When the range of services relevant to my problem have been completed, I am presented with a single bill that summarizes all the services performed, the price of each service, and the total price I am requested to pay.  If I question any service, including its price, I can get my question answered and concerns resolved before I depart.

Healthcare, obviously, does not work like this.  There are primary care clinicians that refer me to specialists who may further refer me to other specialists.  At each stop, I will complete a new patient record and sign various releases, waiving my rights to complain.  Each of these stops will result in one or more bills sent to me as well as my insurance company.  Most of the items listed on each bill will be meaningless to me.

This chain of services involves disparate organization’s whose objectives may be far from aligned. Success for each organization is typically defined as successful completion of the step for which their organization is responsible.  Success for patients, however, involves successful completion of all steps.  Quite often, assurance of overall success is left to the patients, who are usually unlikely to be capable of performing the task.

Car dealers are able to successfully deliver population health – for cars.  This happens because all the service providers are managed – not necessarily owned — by the same organization.  This organization takes full responsibility for care coordination.  If customers are not pleased with the service, they go to a different dealer or perhaps buy a different car.  This market-based arrangement works.  Healthcare, in contrast, it not really market-based and, consequently, successful delivery of population health will be a major challenge.

Washington Drama

I moved to Washington, DC a bit over four months ago.  I have long liked the city, traveling here at least once a month for business over almost four decades.

During this transition, I started watching TV shows associated with the White House.  I have been binge watching The West Wing – just into the third season of eight seasons.  I binge watched several episodes of House of Cards, but found the show too depressing.  I have been keeping up with Designated Survivor, a series whose first season just ended.

There is a fourth show that is reported each day on the front page of The Washington Post that is delivered to my door each morning.  In this show, events develop so fast that I have to check CNN at mid-day and in the evening to see what has happened in the past few hours.  This show is much more dynamic, surprising, and often amazing than the other three shows.

It usually seems too astounding to be true.  The dialog frequently involves statements that are blatantly and obviously false.  There are often retractions, which are also nakedly false.  People are accused of misdeeds that could not have happened.  Occasionally people, seemingly in the way, get pushed around a bit.  Bit players sometimes assault reporters.

There is a looming conspiracy in the background.  Foreign intrigues, security breeches, and under the table business deals suggest that the major story only involves the White House in that it serves as a pit stop between golf outings and negotiations of naming rights.  Occasionally, someone questions why the American public is funding all the travel and security associated with this deal making, but such questions are lost in the next day’s revelations.

This show has an enormous following as the news media — both liberal and conservative — devotes large portions of time to reporting each character’s statements and behaviors.  There are droves of pundits whose full time jobs are to report and assess the characters’ behaviors, motivations, and intentions.  The ratings have soared and the show will likely be renewed for next season and beyond.

Convincing the World to Support Your Ideas

Government agencies, private sector companies, and philanthropic foundations have billions of dollars to support your ideas, ranging from research projects to community development initiatives.  How can you gain access to these resources?

Millions of people are asking this question.  So, there are lots of competitors and your overall chances of success are quite small.  You might think this means that you have to respond to lots of RFPs (Requests for Proposals).  Writing loads of proposals will increase your chances; perhaps even get your probability of success up to a still frustrating level of ten percent.

Think about this process from the perspective of those receiving your proposal.  A few years ago, I unwittingly participated in a proposal effort where 30,000 proposals were submitted and 100 funded, so 0.33% chance of success.  This is not as bad as playing the lottery, but it is headed in that direction.

What did the review team do with 30,000 proposals?  If it was similar to many of my other experiences, their first task was to eliminate 29,000 proposals, for any credible reason.  One common reason is that no one on the review team knew anybody on the team associated with the proposal.  Unknown?  Gone!

So, the first principle is — Don’t be unknown.  You can become known by winning a Nobel Prize or a MacArthur Award, but this makes as much sense as expecting membership in sports Halls of Fame, before making the teams.  You win these awards after you are known, providing further evidence of the first principle.

The question, then, is how to become known.  The first step is to get to know people in the funding ecosystem of interest.  A good start is attending the same meetings they attend.  Introduce yourself.  Provide your business card.  Be vocal in discussions, making reasonable points, of course.

Prepare 2-4 page white papers on your ideas.  Keep the readers’ perspectives in mind.  Few, if any, of them will be focused on advancing your career.  Some, but not many, will be primarily focused on contributing to your academic discipline.  Many, if not most, will be concerned with how your ideas will benefit society in general, and domain-specific stakeholders in particular.

The second principle is – Articulate your ideas from sponsors’ perspectives.  If done well, they will ask you to elaborate.  What will you do to yield the benefits sought?  How long will it take?  How much will it cost?  Now is your opportunity to develop your ideas more thoroughly, knowing that your chances have become much higher.

Let’s assume your proposal is funded.  Is that the finish line?  It might be if you do not aspire to any more funding in your future.  That is seldom the case.  Future funding depends on how well you deliver on the current funding.  Actually, over delivering is a good idea.  There are no credible excuses.  If someone on your team is not delivering on promises, you have to make up the deficit.  The third principle is – Delight your sponsors; Don’t just satisfy them.

Let’s make another assumption.  Your idea succeeds!  You get great results and your publications are accepted in first-rate outlets, or you get glowing newspaper reports of your community project.  You are on the way to promotion, tenure or whatever matters to your career.  However, will one home run be enough?  If you want to sustain your nascent streak, you need to communicate the benefits of your success to your sponsors in terms they will appreciate.  The fourth principle is – Keep your sponsors in the loop; Communicate in their terms.

The bottom line is that success does not depend solely on your being very intelligent, highly motivated, and having lots of ideas.  You have to know how to convince the world to support your ideas.  The four principles outlined above will help you to succeed. 

A Real Train System

What if the US had a modern state of the art train system like other developed countries?  The trip from New York to Washington would take one hour rather than three plus hours.  The trip from Atlanta to Washington would take three hours rather than thirteen hours.  This would be a great boon to personal productivity.

What if we had modern state of the art subways, streetcars, and buses?  What if our transportation infrastructures — roads, bridges, tunnels, and airports — were efficient, safe, and fully functional?  Wouldn’t that be amazing?  This would be another boon to personal productivity.  Travel might be enjoyable again.

It is unlikely to happen, though. We have gotten used to a steadily deteriorating transportation system.  Enormous wastes of time and energy have become grudgingly acceptable. We expect derailments, crumbling freeways, and three-hour trips that become ten-hour trips or much, much longer. Two to three hour commutes each way to work are not common, but also not a surprise.

We do not seem to have the will to fix things.  Deferred maintenance – in other words, no maintenance — has become the norm. We only fix things, patch them up, when they totally fail. We wait for things to collapse. Then we build a new one. Sometimes leaving the rusting hulk of the decaying predecessor still standing along the side of the new structure.

Symptomatic of such neglect are litter strewn transportation infrastructures. Garbage strewn streets, underpasses, and ramps are all too common.  Such litter should be socially unacceptable but for unknown reasons it is not. We accept living awash in plastic bags, fast food refuse, beer bottles and occasional shopping carts, tattered sofas and dismembered dolls.

What would it take to change all this?  It would cost a lot on money, but create an enormous number of good jobs, plus a first-rate transportation system.  We did this with the Eisenhower Highway System and with Medicare and Medicaid, with very strong leadership from Presidents Eisenhower and Johnson, respectively.  President Obama showed glimmers of this type of leadership.  The current administration seems more bent on dismantling things.

The Fragility of Optimized Systems

Delta Air Lines designed and optimized a system to pack the seats on their flights and extract maximum revenue from passengers by charging for every element of an airline trip. The process is called revenue maximization. A senior Delta executive once told me, “We try to pull feathers until just before the goose honks.”

Delta’s system becomes very fragile when off-normal situations arise, potentially causing enormous grief for thousands of passengers. The optimized system has no slack, no resources for responding to off-normal situations.  If there were slack resources, Delta would have eliminated them to increase profits, the only metric that really matters to them.

Earlier this week, weather in Atlanta delayed flights, in my case returning from Los Angeles en route to Washington.  Delays added to delays.  Passengers just waited and waited. Upon landing, hours were consumed waiting for a gate. Whole days were lost, according to the Atlanta Journal-Constitution, due to Delta’s gross incompetence.

“Delta apologizes for your inconvenience. We appreciate your patience.”  This is Delta’s tag line. I hear it on every flight for one reason or another.  However, Delta talks service but does not deliver it. They are too focused on maximizing revenue to pay attention to service. Passengers become incensed and Delta just repeats their tag line.

As my flight was delayed by progressive half hours, a passenger asked the agent why the delay was always 30 minutes. She responded, “That is all we are allowed to tell you.” The passenger asked, “So when is this flight really likely to leave?”  She answered, “We have absolutely no idea. This could go on for several hours and then we may cancel the flight.”

It is rather amazing that many of my worst experiences in life are associated with Delta. This has fostered visceral negative emotions with anything I see or hear about Delta. There are very few, if any, other things that can prompt such negative emotional responses.

What happened to air travel?  When I first traveled with Delta in the 1980s, it was a quite enjoyable experience.  I fondly remember the ice cream sundaes on my frequent Atlanta-California trips.  I also remember my worldwide adventures, typically ending in London when I would relax with Delta who would “take me home.”

My million miler colleagues agree that those times are long gone.  Delta is now an adversary who is focused on extracting revenue from you.  Quality of service is now a joke, glittery words that mean absolutely nothing.  Delta and other airlines are totally focused on what we can do for them.

Beyond the Affordable Care Act

What are we trying to do by rethinking the ACA?  Perhaps we are seeking an ideologically acceptable ACA, one that the Republicans get credit for rather than the Democrats.   On the other hand, is insurance coverage really the ultimate goal?  I don’t think so.  We want a healthy and educated population that is competitive in the global marketplace.

Health insurance is one way to enable this, but so is a single payer system, e.g., Medicare for everyone.  Health insurance is our apparently preferred choice because that is the incumbent mechanism for paying for healthcare in the US.  A broader question is how do we pay for health, education, and social services that enable a healthy and educated population that is competitive in the global marketplace.

At one extreme, the answer could be that everyone pays for these services themselves.  In other words, everything is privatized and we have the world of Charles Dickens.  Of course, lots of people would not be able to afford health and education, so we would have a large class of people stuck in unhealthy, uneducated poverty.  They would eventually revolt, not just at ballot box, but also by physically attacking the privileged – this has happened many times before (Brook, 2013).

Despite the rhetoric of those who argue for a totally market-based approach, most people accept that governments – federal, state, and local – have to play some role in creating a more equitable situation.  And, at the other extreme, few argue that government should provide all health, education, and social services.  For example, there have been few, if any, calls for nationalizing private institutions of higher education, despite the financial bubble that has emerged in this arena (Rouse, 2016).

So either extreme has a rather limited constituency.  The answer is somewhere in the middle – a public-private “enterprise” that enables a healthy and educated population that is competitive in the global marketplace.  By enterprise, I don’t mean a single organizational entity.  I invoke the enterprise concept to motivate the need to look at the whole system that provides health, education, and social services.

Before suggesting how to find the middle ground needed, two phenomena should be explicitly addressed.  First, people both consume and generate resources, which includes money as well as food, housing, etc.  Health, education, and social services cost money, but people who are healthy, educated, and productive generate money and other resources, a portion of which is taxed by federal, state, and local governments to pay for services.

The Centers for Medicare and Medicaid Services (CMS) work to control the costs of health services.  CMS does not tradeoff these costs versus the resources a healthy population generates.  For example, they have no mechanism to incentivize employers to invest in prevention and wellness programs that will result in healthier employees when they retire and enter the Medicare program, despite the fact that this impact has been repeatedly proven (Rouse & Serban, 2014).

The second phenomenon was identified in an analysis of how value can be estimated for investments in people’s training and education, safety and health, and work productivity (Rouse, 2010).  When the entity investing receives the subsequent returns on these investments, it is often rather straightforward to make the economic case compelling.  However, when the entity investing does not receive the returns, they tend to see the expenditures as costs and try to minimize them.

To deal with the above two phenomena, we need to address the overall enterprise that provides health, education, and social services.  How are delivery, payment, and regulation accomplished in each of these service domains?  The high level of fragmentation in the US across federal, state, and local governments has resulted in a large numbers of silos that see monies spent as costs rather than investments.

This fragmentation affects both the effectiveness and efficiency of these services.  We can use computational simulations with interactive visualizations (Rouse, 2015) to explore ways of breaking down the silos of delivery, payment, and regulation.  I propose that the interactive environment be immersive and enable key stakeholders, which includes almost everybody, to explore the complexity of the overall enterprise.  Ideas such as the sharing of returns on investments – across silos — can be investigated.

Creation of such an environment will require many types of data related to the efficacy and costs of health, education, and social services.  Fortunately, the increasing emphasis on evidence-based policy (Haskins & Margolis, 2015) should provide support for the needed data analytics.  This should, in turn, enable investments in achieving the overarching goal of a healthy and educated population that is competitive in the global marketplace.


Brook, D. (2013). A History of Future Cities. New York: Norton.

Haskins, R., & Margolis, G. (2015). Show Me the Evidence: Obama’s Fight for Rigor and Results in Social Policy. Washington, DC: Brookings.

Rouse, W.B. (Ed.).(2010). The Economics of Human Systems Integration: Valuation of Investments in People’s Training and Education, Safety and Health, and Work Productivity. New York: Wiley.

Rouse, W.B. (2015). Modeling and Visualization of Complex Systems and Enterprises: Explorations of Physical, Human, Economic, and Social Phenomena. Hoboken, NJ: John Wiley.

Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where The University Enterprise Is Headed. Hoboken, NJ: Wiley.

Rouse, W.B., & Serban, N. (2014). Understanding and Managing the Complexity of Healthcare. Cambridge, MA: MIT Press.

Test Driving MOOCs

I have been researching Massive Open Online Courses (MOOCs), compiling best practices and other good ideas that I sought from a variety of colleagues.  I recently completed the first lessons of three courses on the best-known MOOC sites:

  • Coursera course: “Chicken Behavior & Welfare”
  • edX course: “Dinosaur Ecosystems”
  • Udacity course: “Design of Everyday Things”

All three courses provide lessons composed of a series of 1-3 minute video clips, interspersed with short exercises and a multiple choice quiz at the end.  All three have forums where students can interact with the instructor(s) and other students.  All three are reasonably engaging.

Forums are like streams of emails or texts, rather than real interactions.  It may be that younger students find this quite acceptable as their daily lives are laced with these forms of communications.  Something like a multi-person Skype might feel more personal, although that would be cumbersome for some courses where large numbers of students are enrolled.  I suppose Skype could be limited to student-teacher interactions, although instructors with hundreds or even thousands of students could be totally overwhelmed.

Ashok Goel of Georgia Tech, working with IBM, created an AI teaching assistant, Jill Watson, to field the 10,000 student questions his MOOC receives each semester.  Obviously, there is much repetition in these questions, which greatly enhances the feasibility of this approach.  Students responded quite positively to Jill, not imagining she was other than human.  This kind of automation has been used in industry for some time to respond to customers’ questions about services being provided.

The production quality of the short videos varies greatly, some being very professional and others looking a bit like home movies.  Some are easy to consume, while others provide enormous detail.  I suppose I could have taken notes, but I would have had to repeatedly stop and restart the videos.  Navigation in each of the three MOOCs can be a bit confusing, but I expect one will quickly get over this.

My sense is that highly polished, well-done MOOCs will increasingly succeed.  Simply posting PowerPoint slides online, with recorded audio lectures, is not engaging, and will eventually disappear.   Such stale offerings do not leverage the engagement potential of online technologies.  Greater engagement can compensate for some of the limitations noted above.

An important hurdle that must be surmounted to succeed is the cost of highly polished, well-done MOOCs.  One very credible estimate is 1,000 hours of design and development time per course.  Those that can make such investments will attract thousands of online students.  Once the credentials associated with success in these online courses are acceptable to employers, it is easy to imagine a massive shift away from traditional classrooms.

Everyone will take the course on any particular topic from the very best instructor of that topic.  For example, everyone will take physics from Richard Feynman and economics from Paul Samuelson.  The fact that these luminaries are no longer with us will not be a hindrance.  Technology will enable them to teach new developments in their fields, despite never having heard of them during their lives.

Appearing In and Winning the Super Bowl

There have been 50 Super Bowls (SB). There have been 100 starting quarterbacks (QB). 62 of the 100 QBs have started more than one SB.  This 62 includes 20 individual QBs.  36 of the 62 QBs won the SB, a 58% winning percentage. 38 (100 – 62) QBs have started only one SB.  14 of these 38 QBs won the SB, a 37% winning percentage.

32 NFL teams times 50 years yields 1600 starting QB years. 4.4 years is the average career length of a QB.  Thus, there have been roughly 364 (1600/4.4) starting QBs.  58 (20 + 38) QBs have started a SB, yielding a 15.9% (58/364) starting percentage and a 9.3% (34/364) winning percentage.

32 NFL teams times 53 players per team times 50 years yields 84,800 player years.  3.3 years is the average career length of an NFL player. Thus, there have been roughly 25,697 (84,800/3.3) players.  There have been 5300 (53 x 2 x 50) players in one or more SB.  Thus, there is a 20.6% (5300/25697) appearance percentage.  However, this estimate is too high for the following reason.

For QBs, multiple appearances are known and included in calculations.  For players in general, this data is not readily available.  If this phenomenon were ignored for QBs, the appearance percentage would be 0.275 (100/364), an overestimate by a factor of 1.73 (.275/.159).  Adjusting the players in general percentage by this factor yields an 11.9% (.206/1.73) appearance percentage.

Professional Relationships

The wonders of the Internet and social media seem to have radically changed the nature of relationships.  This is perhaps most apparent in personal relationships where email, texting, Facebook, Twitter, and other offerings provide constant updates on what a vast network of family and friends are doing and thinking at the moment.  Many people spend a significant portion of their time generating and responding to this flow of messages.  I find this particularly disconcerting when teaching class and several students in the front row never look up from their devices, their fingers endlessly tapping on their smart screens.

As amazing as this all is, in this post I address professional relationships and how information technology has morphed the ways in which individuals seek opportunities, secure positions, and perform once in these positions.  My daughter pursued jobs a few years ago and my son more recently.  They prompted the observations that follow.  It struck me that the value of any advice I could offer was substantially offset by the fact that I have never applied for a job in the sense that this act is now construed.

This is due to the simple fact that all my opportunities over 50+ years have started with relationships, not websites, electronic documents, etc.   During my senior year in college, I interviewed with several companies on campus and took trips to GE (railroad engines), IBM (computers), Pratt & Whitney (aircraft engines), Raytheon (submarine systems), and US Steel (railway cars), and received offers from all five companies. I applied for graduate school at MIT, RPI, and URI and was accepted by all three universities.  Thus, I had eight opportunities that were linked to people I had met and talked with along the way.  Of course, in those days, there was no other way to do this.

Once I finished my PhD at MIT, I took a visiting position at Tufts University on the advice of my advisor.  I then pursued a single alternative, the University of Illinois at Urbana-Champaign, after communicating with the department head.  I spent a year at Delft University of Technology, invited by a colleague with common interests.  The school chair at Georgia Tech contacted me, convinced me that I would find a visit interesting, and subsequently made an offer too good to refuse.  I called the dean at Stevens informing him that I would soon retire from Georgia Tech and I was offered a chaired position there within a few weeks.  I am currently considering a few alternatives that have emerged from a range of professional relationships.

My first company, Search Technology, was founded with a single customer where a former graduate student worked.  The company grew via major contracts with companies where colleagues worked.  The next company, Enterprise Support Systems, emerged when Search Technology customers asked for products and services that were not feasible within the older company’s costs structure.  Specifically, a company used to multi-million dollar contracts can find it quite difficult to create software products selling for $1,000 per copy.  Enterprise Support Systems grew by selling to other divisions of existing customers.  Eighty percent of revenues came from twenty Fortune 500 companies.

One or more of these companies served as lead customers for each new software tool.  They would buy a corporate license, at a big discount, for a product that did not yet exist.  Their users became members of the design and development team, assuring that they were pleased with how well the product met their needs.  Our close relationships enabled their trusting us and investing in yet-to-be-defined solutions.  A side benefit was that no other companies were able to bid against us.

What is different now?  One of my PhD students recently applied for almost 40 faculty positions.  He did this online.  The web-based system immediately requested that I provide a reference letter, with a two-week deadline.  Tailoring the letters a bit to each institution, I managed to almost meet the deadline for the 40 letters.

He will not end up interviewing with even half of these institutions.  However, it was convenient for them – not for me – to request these letters just in case they later needed them.  There were no humans involved – just me and a website.  There were no business relationships – just an IT system executing a workflow.

Lots of things work this way now.  When you submit articles to professional journals, the interactions are all automated.  A year or so ago, I submitted an article and was requested to choose key words from a fixed set.  None of the words matched the journal’s topical areas.

I emailed the editor, asking how to respond.  He said that I had to choose among the key words provided.  The vendor of the platform did not allow changing the choices.  It was rather difficult to map my article on healthcare to reinforced concrete and welding.  It certainly did feel that I was serving the platform rather than it providing services to me.

It used to be that people in your organization were experts in benefits, contracts, purchasing, etc.  You knew them and could call on them for help as needed.  Now there are IT systems, often multiple IT systems that require multiple entries of the same user names and passwords to access a single function.  If, for example, you want to change your mailing address, you have to do this in each system because databases are not integrated.  You need to keep track of what each system knows.

As machine learning increasingly becomes the underpinnings of such systems, they will know a lot about you – but they won’t know you.  We will work remotely, interact through various IT systems, submit work products electronically, and the balance of your bank account will occasionally be incremented.  In the “gig economy” we will bid on opportunities to create work products, compete with untold other bidders, sometimes get selected by the deep learning vendor selection system, and use various online sources to create and deliver the promised outcomes.  We won’t really know anybody professionally, although your buddies at the local pub may argue the strengths and weaknesses of the next generation IT platform.


The Academic Job Market

Engineering and science account for roughly three quarters of all PhD graduates, with half of these degrees awarded to US students and the other half to international students. Many of these graduates aspire to tenure-track faculty positions at universities. However, the percentage of faculty openings that are tenure track has been steadily decreasing for quite some time. Universities have found that non-tenure track faculty members, as well as post-docs and adjuncts, are much less expensive, which helps to compensate for strong growth of administrative costs at many institutions.

With more PhD graduates chasing fewer tenure track positions, universities have steadily increased their criteria for hiring. This can include 10-20 published journal articles, extensive teaching performance with good teacher ratings, and professional thought leaders who will write letters extolling your intellectual and social virtues. A fresh PhD graduate cannot possibly satisfy these criteria.

Consequently, especially in the sciences, new PhD graduates seek post-doc positions. These positions pay roughly twice what PhD assistantships pay, i.e., $4,000 per month rather than $2,000 per month, but much less than the $8,000-$10,000 per month paid to tenure track assistant professors. With an average of seven years to earn a PhD and perhaps three years as a post-doc, the candidates are now in their mid 30s before they are ready to compete for coveted tenure track positions.

The competition is fierce. Each position draws hundreds of applications or more. Consequently, people may apply for 50 or more positions. If they win a tenure track position, they now have 7-10 years to earn tenure. During this time, they need to publish 2-4 journal articles per year in top journals as defined by their subdisciplines.  To hit these numbers, they focus on brief incremental contributions that comfortably fit in reigning paradigms. They often get really good at this and will continue in this mode for the rest of their careers. Any effort that is more complicated or takes considerably more time will be shunned, as it will slow them down on the path to full professor in their mid to late 40s.

The process is further complicated for international PhD students. The income they receive in graduate school may be greater than their income would have been in their home countries. Thus, the international student may gain a couple of hundred thousand dollars during the ten years of PhD study plus post-doc.  In contrast, an American PhD student may forgo up to a million dollars of income over the ten years.

The overwhelming problem for international PhD students is the likelihood of being deported immediately after graduation. Federal agencies and other sponsors will have invested perhaps three hundred thousand dollars in creating a top expert, and they then force this expert to leave, to go home and compete against us. It makes no sense.

International students are quite creative in identifying training opportunities and internships that enhance their credentials beyond their degrees. Hoards of lawyers specialize in helping these graduates jump immigration hurdles. A significant number make it and are increasingly filling the ranks of science and engineering faculties across the US. Tenure-track faculty members born in the US are disappearing with retirements, slowed by the Great Recession, but inevitable nonetheless.

Many of the grads from MIT, Stanford, Berkeley, etc. return to China, India, Korea, Singapore, and elsewhere to become faculty members at their best local institutions of science and engineering.  With their countries making much greater investments in these institutions, compared to trends in the US, the numbers of students applying to US institutions are declining, in some cases rather significantly, e.g., Korea.

Combining the inevitable decline in international PhD students at US institutions with the steadily decreasing value proposition for US born PhD students, the future looks rather bleak for US PhD programs.  However, we could choose to change the value proposition for US students.  We would need to (at least) triple PhD students’ stipends and waive tuition.  There is a variety of ways this could be approached.

When I spent a year at Delft University of Technology, all the PhD students were full-time staff members with regular research and teaching responsibilities.  They had reasonable salaries, paid no tuition, and progressed as part of the intellectual fabric of the institution.  This was great for them and great for the university. There are, of course, quite a few implications of this idea.

How would this be funded?  In the current system, the university receives overhead on student’s stipends plus tuition.  Of the $80-100,000 that it annually costs for a half-time graduate student in a private university, only roughly 25% goes to the student.  Tripling the stipend would increase overall costs by at least 50%.  Would research sponsors accept $160-180,000 as the cost of a half time student?

The central balancing factor is that these PhD students would be full-time employees and have substantial research and teaching responsibilities.  These PhD students would be US born with great English skills, reasonable compensation, and aspirations to become faculty members.  It would make enormous sense to invest in enhancing their research and teaching knowledge and skills, particularly since they would not be deported upon graduation.

The availability of these personnel would allow significant reductions in the numbers of tenure-track faculty members.  Decreasing the number of tenure-track faculty members would steepen the promotion pyramid, likely decreasing the chances of becoming full professor.  It would certainly decrease the annual rate of faculty hiring, potentially making the competition even fiercer.

PhD students as full-time professionals would substantially decrease the number of such students needed.  If we were to explore this in more detail, I expect we would find:

  • Decreased numbers of PhD students with substantially increased percentages of US born students
  • Decreased numbers of tenure-track faculty, particularly as inevitable retirements increase
  • Decreased university revenues, but also decreased costs, except perhaps for administrative overheads that seem immune to cost pressures
  • Decreased numbers of journal articles published by PhD students whose full-time responsibilities would not allow the traditional focus on publications

Regarding this last observation, the consequences include the journal article “Laminar Flow Over an Inclined Plate at 17.5 Degrees” never appearing. (17.4 and 17.6 degrees had been addressed in two papers in earlier issues of the journal.)  Is this a loss?  This is a quite complicated question with many implications.  I will return to this question at a later time.

Complexity: Absolute or Relative?

I spent the last few days in Santa Fe, absorbed in discussions of complexity, with particular emphasis on healthcare delivery.  I have delved into this topic for quite some time. Three decades ago, we published our studies on the complexity of troubleshooting – figuring out the source of unfortunate symptoms, e.g., why your car won’t start.

Sponsors of our research asked us to devise a metric for the complexity of a troubleshooting task, which they intended to use to match to the complexity processing abilities of maintenance personnel.  Pursuit of this goal led us to conclude that complexity is related to the intent of the person asking the question or performing the task, as well as the knowledge and skills of this person.

To illustrate, let’s say you purchased a Boeing 747 to use as a paperweight.  From this perspective, this complicated airplane is just a large mass, pretty useful for keeping errant papers on a very large and structurally sufficient desk.  In contrast, if you made this purchase with the intent of operating and maintaining the aircraft, the Boeing 747 is much more complex than your unwieldy paperweight.

This insight leads to a fundamental conclusion.  Complexity has to be defined in terms of a relationship between an observer and an entity.  The observer’s intentions, knowledge, and skills frame the assessment of the complexity of the entity.  Thus, complexity is relative rather than absolute.  Consequently, for example, we can only assess the complexity of a troubleshooting task relative to the personnel involved in the task.

I have discussed this conclusion in many of my talks over the past ten years or so.  Roughly 90% of the people with some level of expertise in the topic agree with me.  The other 10% say something like, “What you are saying makes sense, but what about real complexity?”  These people are usually physicists who firmly believe in the absolute nature of complexity.

Many of those researching complexity construct network diagrams of the elements and relationships among elements of engineered, organizational, and natural systems of interest.  They calculate various metrics associated with these network diagrams and then argue that these metrics reflect the inherent complexity of the systems of interest.  I have done this as well, with the explicit acknowledgement that these network models reflect my intentions, for instance, to predict the difficulty of driving in different urban environments.

There are no intention-free models.  Every model is constructed with the intent to analyze, assess, or predict some set of phenomena.  Any properties of these models used as complexity metrics reflect the intentions of the modeler(s).  This is as essential today as it was for Newton, Darwin, and Einstein in past centuries.  Absolute complexity is a chimera.

Why You Hate Your Airline

The October issue of Consumer Reports outlines “Secrets to Stress-Free Flying.”  This 14-page article provides an interesting history of the airline industry, including the forces that drove your once loved airline to become an object of intense scorn and hatred for most passengers.

Over recent years, the airlines have refined their strategy for making record profits. Charge as much as possible, squeeze passengers into smaller and smaller spaces — which poses medical risks (see Consumer Reports article) — provide as little service as possible, make passengers pay for almost every breath they take in flight, and smile while they say they care about passengers.

I don’t think we should re-regulate the airlines, but they should be forced to pay for the problems they impose on passengers.  For example, they should pay you when they waste your time.  How about $100 per passenger for every hour they are late. This includes delays for mechanical problems, crew complications, and inclement weather.

Airline executives will complain that delays are seldom their fault. This is akin to shipping executives complaining about all the water, or trucking executives complaining about the traffic.  My answer is simple. If you don’t know how to run an airline, get out of the business. Flip burgers. Mow grass. But stay away from airports.

Cultures of Compliance

I have encountered many organizations, mainly in government and academia, where compliance with policies, procedures, and norms became the primary organizational objective. Producing useful outcomes became secondary, almost a nuisance because production took resources away from compliance.

This becomes an almost insurmountable problem when the organization is laced with administrative incompetence. Perhaps well-intended but fundamentally incompetent administrators force compliance on those who would have been producing useful outcomes.

This is further complicated by fragmented and antiquated information systems. One measure of this is the number of times you have to enter your user name and password to accomplish one task. Another measure is the number of times you have to start all over because the system does not recognize the computer they bought for you and told you to use.

The ultimate complication is when the legal function is in charge.  They want to make sure that the organization cannot be blamed and held accountable for anything.   This objective is, of course, much easier if the organization avoids doing anything.

I once asked a Chief Legal Counsel if her compliance job would not be easier if the organization provided no services, accepted no monies from sponsors, and created nothing of value. She replied, “It certainly would minimize our risks.”

I then asked, “How could the organization survive if it provided no value to anyone?”  She responded, “That not my responsibility.  My job is to maximize compliance so as to minimize risks. You need to talk to the President if you are concerned about the value we provide.”

She was right. Her function was risk management, not value creation. I talked to the President, but he was all hype and slogans. His dominant goal was assuring a financial surplus each year that got bigger the following year.

I then talked to the organization’s equivalent of production workers. They were frustrated by increasingly tight budgets, driven by the goal for surpluses.  They were angry about all the time they had to devote to compliance paperwork, often entering the same information into multiple information systems.

Morale was abysmal across the organization. In the executive suite, however, everything was upbeat. All the slogans were prominent. Glossy brochures touted the smoothly running organization.   Everything was aligned for an unfortunate surprise.

The Disruption of Autonomous Vehicles

Many pundits argue that driverless cars will soon be here.  You can argue with the timelines they articulate, but it is difficult to disagree with the distinct possibility of the technology eventually maturing and becoming an increasing portion of the vehicles on the road.  This technology will be truly disruptive.

There will be the benefits of a more efficient transportation system, dramatically fewer accidents, and commute times spent being productive or at least being more relaxing.  There will, however, be costs associated with the technology and infrastructure needed to support it.  There will still be some accidents, although the technology, unlike human drivers, will be continually improved as lessons are learned.

Many of the disruptions will be byproducts of these innovations.  As accidents disappear, the most profitable segment of the insurance industry will wither.  As car and truck services replace individual ownership, vehicles will be used 24 x 7 and the number of vehicles will steadily decrease.  Used cars will disappear, eliminating roughly three quarters of the car loan business.  The after market for vehicle add-ons will disappear.

Truck drivers will become rare, as will drivers of taxis, limos, and other car services.  The autonomous car service industry will have their own service operations, replacing corner filling stations and car washes.  The need for parking places will plummet, proving real estate for other purposes but also significantly reducing municipal revenues.  The need for traffic police and the issuing of speeding tickets will disappear, also reducing municipal revenues.

I have read that as many as 5,000,000 jobs will be eliminated.  At the same time, millions of new jobs will be created, but probably not for the same people.  This has happened before.  Electricity disrupted the marketplace in the late 19th century and automobiles dramatically disrupted horse-drawn transportation in the early 20th century.  The acreage and labor associated with feeding and caring for horses plummeted.  The pollution of horse manure did as well.

The process of one or more technologies disrupting a market is often termed “creative destruction.”  The creation of innovative new ways of doing things results in destroying the old ways.  This process can be very painful for those skilled in the old ways.  Efforts and resources have to be devoted to gaining new skills.  Over time, the new ways flourish and the overall economy greatly benefits.

Clock Speed in Academia

An industry executive that chaired an advisory board at a major research university once commented to me that academia’s unit of time is the semester.  “When a faculty member says he will get back to me right away, he means by the end of the semester.”

We measure performance of computers in cycles per second, manufacturing processes in cycles per hour or day, and academia in cycles per semester.  Classes are taught once per semester.  Research papers are produced roughly once per semester.  Students graduate once per semester. Proposals for funding are typically due once per semester.  Thus, it is rather natural to have a metric of cycles per semester.

Each semester appears to be roughly four months in duration.  Nothing can be accomplished in the summer months because quorums are impossible.  Little can be done from mid December to mid January due to holiday plans and celebration recovery.  Once Fall and Spring breaks are subtracted, as well as numerous holidays, each semester ends up having about three months of useful time.

I won’t detail here what needs to be done – see my recent book if this is of interest*.  The overall set of things is called faculty governance, which includes evaluating and approving courses and curricula, reviewing and recommending (or not) promotions and tenure, and endless revisions of the faculty handbook.  Most faculty members do not enjoy this, but do not want anyone else doing it.

A committee that meets once per semester is considered reasonable.  More than once per semester is judged outstanding.  Committee membership often changes every year, so a particular set of people have two chances to accomplish something.  The next set of members of the committee may be such that they undo what the previous set did.  At the very least, the next set is usually unaware of the previous set’s decisions.

Difficulties arise when decisions about classes, research, proposals, etc. need to happen faster.  Most faculty members will do their best to meet hard deadlines, e.g., proposals not accepted after March 15th.  On the other hand, soft deadlines, e.g., let’s try to get a first draft done by next Monday, are difficult for many faculty members to understand.  Hence, soft deadlines are often ignored.

Faculty members with earlier careers in business, or those like me who took extended leaves of absence to found and grow businesses, are often frustrated with the cycles per semester clock speed.  They feel that it takes far too long to accomplish things.  They are astonished by faculty members who have spent their whole careers in academia and see the stumbling progress as fine indeed.

*Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where the University Enterprise Is Headed.  Hoboken, NJ: John Wiley.

Student Debt and Jobs

The August 2016 issue of Consumer Reports summarizes a much longer report from on student debt.  Their headline is 42 million people owe $1.3 trillion.  Their survey found that “45% of the people with student loan debt said that college was not worth the cost.  Of those who said college wasn’t worth the money, 38% didn’t graduate, 69% have had trouble making loan payments, and 78% earn less than $50,000 per year.”

The US Department of Education holds 93% of the $1.3 trillion in outstanding loans, making it one of the world’s largest banks.  They outsource debt collection to private firms, many of which are owned by JP Morgan Chase and Citigroup.   These debt collection firms pursue the 7.6 million borrowers in default, making more than $2 billion in commissions this year.

Of course, as noted in my last post, the whole process is driven by spiraling costs of higher education, which is driven, in turn, by academia’s “cost disease,” that results in cost increases far exceeding inflation.  Universities are unwilling and unable to control costs, in large part due to the bloating of administrative and support functions.

The June 25th edition of The Economist includes a special report on artificial intelligence.  They project that jobs such as telemarketers, accountants and auditors, retail sales people, technical writers, real estate agents, and word processors and typists will likely disappear.  I have reviewed many articles on the top ten jobs of the future.  They all require technical skills.  Many require advanced degrees.

These two trends are on a collision course — higher education that is unaffordable and jobs that require higher education.  Further, as noted in my last post, the third trend is younger people who cannot afford to repay their debts, cannot afford to buy a house, cannot afford to get married, and cannot afford to have children.  The good news is that JP Morgan Chase, Citigroup, et al. made $2 billion in commissions.

Higher Education Bubble

The steadily escalating costs of a college education coupled with spiraling mountains of student debts cannot be sustained.  Universities are unwilling and unable to control costs, in large part due to the bloating of administrative and support functions (Rouse, 2016).

A great example is the University of California System where, excluding the number of faculty members, there is roughly one administrator per student.  The daughter of a friend enrolled at UCLA last year.  I suggested that she ask to meet her administrator.

These bloated costs result in constantly increasing tuition, fees, and room and board.  Another friend has a 12 year old who hopes to go to Stanford in six years.  This friend is planning on Stanford costing $100,000 per year by then, and saving accordingly.  This is all but impossible for the vast majority of families.

In a recent meeting of academic health centers, the impact of healthcare reform on physician salaries was discussed.  Physicians’ pieces of the pie are likely to get smaller when payment for outcomes replaces fees for services.  With lower incomes, physicians are unlikely to be willing to finish their education with $300,000 of student debt.

More typical student debts are much smaller, in the range of $30-50,000, with repayment amounting to roughly $500 per month over ten years.  Ben Casselman (2016) reports, “New graduates’ wages are rising faster than those of most other groups; the typical recent college graduate earned $13 an hour.”  $26,000 per year translates into a bit over $20,000 after taxes, social security, Medicare, etc.  So these new graduates will need roughly 30% of their after-tax income to repay their loans.

This leaves about $1,200 per month for everything else.  The possibility of buying a home disappears.  Marriage may be avoided or long delayed.  Children are unaffordable.  Without owning homes or having children, young people are not buying appliances, carpeting, strollers, etc. There are frequent reports of data that portray these trends.

How will the higher education bubble burst?  I think it will be a combination of technological disruption and changing values and norms. Online education, in its many forms, will continually get better.  Studies will eventually show that online education yields superior results to traditional education in many, but not all, areas.  In a recent analysis, I show how this could result in the total cost of a college degree being $16,000 (Rouse, 2016).

Values and norms will change in the sense that employers will come to accept credentials earned online as equivalent to those earned in traditional education.  In parallel, accreditation bodies will adapt to these trends rather then thwart them.  These changes will not happen all at once.  Hybrid offerings might, for example, involve years 1-2 online and years 3-4 on campus.  Those who drop out in the first two years will have $4-8,000 of debt, at most.

What happens to all the bricks and mortar of higher education when on campus enrollments steadily decrease?  One idea is to turn facilities into retirement homes.  It has often been noted that retiring in a college community has several attractions, one of which is the possibility of taking classes and perhaps earning credits in literature, history, political science or art.  The growing demand for education by much older students is another scenario that I have recently explored (Rouse, 2016).


Casselman, B. (2016). This Year’s College Grads Are The Luckiest In A Decade,

Rouse, W.B. (2016). Universities as Complex Enterprises: How Academia Works, Why It Works These Ways, and Where the University Enterprise is Headed. Hoboken, NJ: John Wiley.

The Allure of Quests

I really enjoy stories, and particularly movies, where an older man and younger woman are on a quest – perhaps to solve a mystery, right a wrong, or flee an evil force.  They are thrown together and their shared aspirations drive them closer as they work together to pursue their quest.  They learn from each other, despite occasional conflicts, and eventually succeed.

Movies that come to mind are North by Northwest (Cary Grant and Eva Marie Saint), Charade (Cary Grant and Audrey Hepburn), and The Big Sleep (Humphrey Bogart and Lauren Bacall).  There is an emergent romantic undertone in these stories, but the plot is dominated by the quest.  The older man helps the younger woman to achieve her goals, in these examples, stopping the bad guys, finding the murderers, and saving her sister from her fate.  Once the quest is successful, the romantic undertones take center stage as the story ends.

I think that what appeals to me is the idea of shared aspirations to achieve substantial goals involving some risks of failure.  The couple – actually a team more than a couple – support each other to contribute to progress toward the goal.  Conflicts of priorities and personalities emerge along the way, but the importance of the quest helps them to move beyond these conflicts. Respect for each other’s role and competency grows.  They become truly interdependent.  And, of course, the team achieves its goal, with warm affection as the immediate reward.

It seems to me that male-female relationships are much richer when there is a shared sense of purpose beyond going to respective jobs, keeping house, paying the bills, eating and drinking, and taking holidays and vacations.  Raising children can, of course, provide a shared purpose, but also can tend to feel like another job with enormous responsibilities to buy more and more things, oversee schooling and homework, address logistics of extracurricular activities, and save for higher education.  The idea that your only purpose is to foster the next generation has always felt rather limiting to me.

Yet, quests that benefit humankind are very appealing and, certainly, raising children to become good citizens fits in here.  Plus, the joys of seeing your progeny succeed in life are difficult to overestimate.  Nevertheless, the idea that your primary role is to prepare the next generation to accomplish what you could not seems like passing the buck – why couldn’t you do it?  My sense is that you can have both great accomplishments and great kids.  In fact, your kids can be even greater if they experience what you accomplish.

A Student’s Questions

One of the PhD students in the School of Systems and Enterprises asked me a few questions after reading my March 15th blog post on “Thoughts on Teaching, Classrooms, and Computers.” She wanted to know what I would do if I was now a PhD student. Before getting to her specific questions, I need to cover two preliminaries.

First, I often get questions from students who are trying to decide on future directions. I have a simple, yet I think powerful, answer.  “Identify a scarce skill that is highly valued and you love doing.”

If the skill you love exercising, is abundant in the population, it will not be highly compensated. If the skill is not highly valued, it will not be highly compensated. Of course, you may be satisfied with modest compensation.

Second, I am rather biased toward recommending STEM fields, particularly engineering. My experiences are that engineering prepares people for an amazing range of futures. People with well-honed problem solving skills can succeed in many arenas.

Now, let’s consider her questions.  How would you choose your dissertation research topic?   Choose what fascinates you, but be realistic. You need to become an expert at something that society cares about. This still leaves a wide range of possibilities.

What courses would you take?  Required courses are, obviously, required. Add courses needed to directly support your research. Throw in a couple for fun, for example, economic history or creative writing.  The payoffs from such courses will surprise you.

What extracurricular activities would best advance your career?  Such activities only count, career wise, if they are related to your research. I chose woodworking, hiking, and travel, but not to advance my career.  Keep in mind that you are creating you, not just your resume.

What internships would best advance your career?  Again, these only count if they are related to your research. On the other hand, paid internships (or just plain jobs) can create a rainy day fund while you are completing your degree program.  I always liked real hands-on work, e.g., plumbing, or real technical work, e.g., engineering analyses.

Overall, I am driven by problems that I want to understand and contribute to solving. I am problem-oriented. In contrast, some people are method-oriented. They look for problems that are good fits for their chosen methods.  They often have to scale down problems to fit their method. In contrast, I often have to scale up methods to fit my problem of interest.

Career success is rather different for these two perspectives. Method-oriented people are judged by their abilities to extend methods in some substantial way, often with associated theorems and proofs.  The domain of application is of less importance.

Problem-oriented people tend to immerse themselves in the domains of the problems of interest. They are judged by their contributions to solving problems in these domains. This often involves providing empirical evidence of the impacts of their contributions.  Advancing methods is secondary.

Keep in mind that the world needs both Newtons and Darwins.  If you are problem person like me, sailing the enterprise seas, you are glad that someone else is forging the next generation methods.  Problem people are often really good at formulating problems, but given a valid formulation, the method people can be invaluable.

Thoughts on Teaching, Classrooms, and Computers

The purpose of teaching is to enable learning and, over time, mastery.  Classrooms and computers – smart boards, workstations, laptops, tablets, smart phones, etc. – are enablers of learning.  The most important enabler is student engagement.  This can be a challenge as ubiquitous digital devices often lead to significant student multi-tasking, much of it irrelevant to the topic at hand.

There is abundant potential variety in terms of modes of delivery that might enhance engagement. However, “Didactic teaching remains the pedagogical mainstay of many traditional classrooms and traditional teachers. It is the pedagogy of instruction and immutable facts, of authority and telling, and of right and wrong answers – it is teacher-centered and values learners who sit still and listen quietly and attentively, passively accepting the teacher as the knower and expert, both the source of knowledge and judge-jury of knowing.” (New Learning, 2016).

I have found in large undergraduate courses (60-80 students) that traditional didactic teaching can prompt disengagement, especially when lecture notes or slides are provided and the lecture closely follows these notes or slides.  What seems to work better is the addition of real-world examples and stories (not on the notes or slides) that illustrate the use or misuse of the material being presented.   In a recent experiment, we announced at the beginning of the lecture that there would a quiz on the lecture at the end of the class, i.e., 45 minutes later.  Students’ digital devices were little used during those 45 minutes.

In graduate courses, typically much smaller (8-12 students), my experience is that engagement increases if the students do more of the talking.  In three cases, I designed the course and compiled the course materials, but had the students give the lectures.  The students found this very rewarding.  Rather serendipitously, I learned to always have one of the better students lecture first as this sets the benchmark for the rest of the students.  By “better” I mean motivated, organized, and articulate, as well as with a sense of humor, rather than the student with the highest grade point average.

Table 1 contrasts didactic and Socratic teaching in terms of passive versus active learning.  Of course, there are more than two choices; there is a continuum.  The experiences mentioned above suggest that I have achieved greater student engagement when classes are more towards the Socratic end on the continuum.  How can the use of smart boards, workstations, laptops, tablets, smart phones, etc. enhance this approach?

The most ubiquitous use of computer technology is computer-projected PowerPoint slides.  This saves the lecturer having to write notes on a whiteboard or, in rare cases, a blackboard.  This means that the lecturer spends more time looking at the class rather than the board.  This enables much quicker detection of student disengagement.




[Shared Inquiry]

Passive Learning

Active Learning

1. Teacher centered: based on the assumption that the teacher is the primary agent in learning. 1. Problem centered: based on the assumption that the student is the primary agent in learning.
2. Teacher’s role: to impart the results of experience, personal study, and reflection. 2. Teacher’s role: to uncover the question that the answer hides. To be a co-learner.
3. Primarily deductive: the usual methods are lecture, story telling, use of analogy, and aphorism. 3. Primarily inductive: the usual methods discussion, dialogue, and problem solving.
4. Test of truth: authority and experience. 4. Test of truth: reason and evidence.
5. Learning is the reception of ideas. 5. Learning is a conflict of ideas: a thesis, antithesis, and a synthesis that results in new knowledge (Hegel).
6. Student’s role: to be passive, open, receptive, trusting, and unquestioning. 6. Student’s role: to be active, questioning, critical, and discriminating–learning to trust one’s own judgment (independent thinking).
7. Evaluation is factual recall of data–commonly in the form of objective tests–right and wrong answers. 7. Evaluation is application of understanding interpretation of data–commonly in an essay, speech, journal, or a review.
8. Ultimate goal: wisdom viewed as the internalization of truths and beliefs. 8. Ultimate goal: wisdom viewed as an informed ignorance (knowing what one does not know–the Socratic paradox).


Table 1. Didactic vs. Socratic Teaching (College English, 2016)

The downsides of PowerPoint, or equivalent, includes tendencies to express all ideas as bullet points, cram too much text into slides, and use colors combinations that are unreadable, e.g., dark blue lettering on a black background.  In general, PowerPoint helps the speaker more than the audience.  The best illustration of this is when speakers literally read their slides.  In general, most PowerPoint presentations represent little more than computer-aided didactic teaching.

Hands-on interactive demonstrations can help to engage students, particularly when the students are the creators of the demonstrations.  Conservations about real-life experiences can also be engaging.  Teachers’ expositions of real-life applications of the material being discussed in class usually cause greater student attention, particularly when they can ask questions about the experiences, and especially when they can discuss their related experiences.  Students’ shared demonstrations and experiences are often of great value to other students.

How is this different for online versus face-to-face classrooms?  To address this question, we need to differentiate between synchronous online courses — where faculty members and students are online together at the same time — versus courses where people’s presence is asynchronous.  There are several commercial platforms that can support synchronous classes to enable sharing of materials and discussions where people can see each other.

Asynchronous courses, almost by definition, have to be more scripted or canned.  This raises the question of the extent to which asynchronous courses can be fully interactive and reflect good educational practices.  Chickering and Gamson (1987) discuss seven principles for good practice in undergraduate education:

  • Encourages contacts between student and faculty
  • Develops reciprocity and cooperation among students
  • Uses active learning techniques
  • Gives prompt feedback
  • Emphasizes time on task
  • Communicates high expectations
  • Respects diverse talents and ways of learning

Roblyer and Ekhami (2000) have developed a rubric for assessing interaction in distance learning.  The rubric focuses on five aspects of distance learning:

  • Social/rapport building
  • Instructional design
  • Interactivity of technology
  • Learner engagement
  • Instructor engagement

They provide scales for each of these aspects where the assessment can provide up to five points per aspect and 25 points overall.

Wagner (1997) discusses interactions in terms of those between students and instructors, students and other students, and students and content.  She argues that interactions must change learners and move leaners toward an action state of goal attainment.  Interactions can increase participation, enable communication, provide feedback, enhance elaboration and retention, support leaner control/self-regulation, increase motivation, negotiate understanding, and enhance team building.  Interactions should be designed, or at least enabled, to support one or more of these purposes.

Expressed in these terms, technology is an enabler, a means rather than an end, for interactions that support learning and mastery.  Weidemann and Pollack (2016) argue that technology has become so ubiquitous that it is effectively disappearing.  Online tools from course management systems, to email list services, to web-based demonstrations are pervasively used in a large percentage of courses.  Thus, almost all education has online components.

It seems to me that we know what high quality education looks like, and we have some inkling of how to achieve quality for online offerings.  We also know that PowerPoint based didactic teaching does not pass muster.  To move beyond this, we need larger numbers of college instructors to embrace the principles and findings discussed here.


Chickering, A.W., & Gamson, Z.F. (1987). Seven principles for good practice in undergraduate education. AAHE Bulletin, 3, 3-7.

College English (2016)., Accessed March 12, 2016

New Learning (2016)., Accessed March 12, 2016.

Roblyer, M.D., & Ekhami, D. (2000). How interactive are YOUR distance courses? A rubric for assessing interaction in distance learning. Online Journal of Distance Learning Administration, 3 (2).

Wagner, E.D. (1997). Interactivity: From agents to outcomes. New Directions for Teaching and Learning, 71, 19-26.

Weidemann, C., & Pollack, K. (2016). The death of “online” learning in higher ed: As technologies become ubiquitous, familiar labels will vanish. University Business Magazine, March.

Autonomous Vehicles

Various pundits are projecting that by 2020 – just four years – the driving of cars and trucks will be completely automated.  Vehicle services, whether for consumers or businesses, will be readily available for very reasonable prices.  I will not need to own a personal vehicle and my business can dispense with its fleet of delivery trucks.  Taxi or truck drivers will no longer be professions; they will go the ways of elevator operators, bank tellers, and secretaries.

Personal cars are typically in use 5% of their lives.  The maturation of autonomous vehicles will cause utilization to approach 90-100%, dramatically reducing the number of vehicles needed to meet demands.   The greatly reduced number of vehicles will, in turn, enormously decrease the demand for independent servicing of vehicles – the vehicle service companies will handle this.  The number of gas stations, repair shops, and car washes will precipitously drop.

Reduced production of vehicles will result in the supplier base for vehicle manufacturers being steadily weaned due to less demands for nuts, bolts, rims, tires, floor mats, etc.  Auto insurance, the cash cow of the insurance industry, will be transformed once accidents cannot happen.  People will not pay to avoid risks that are no longer at all likely.  I have read projections that 5 million jobs will disappear.

This all seems plausible if the automation performs flawlessly.  Then, I can sit in the back seat and snooze on the way to the office, train station, or airport.  To evaluate this possibility, I have used my frequent Uber rides as an experiment where I ask myself, “What if there were no driver in the car?”  Two examples are very revealing.

I was going to the airport for a flight to Los Angeles.  The Uber app guided the driver to take a route that would have taken us away from the airport, not towards it.  I told this to the Uber driver and he said, “I have not driven this route before.  If you know a better way, just tell me what to do.”  Everything worked out fine.  What if there had been no driver?

More recently, I was taking Uber to work on a very cold morning.  I saw that the driver who would pick me up was just three blocks away and would pick me up in three minutes.  As I watched his car on my phone, it did not move and the time increased for 3, to 4, to 5, to 8 minutes.  I called him, and he said he would be there in five minutes, which he was.

Upon entering the car, I asked him, “You weren’t in your car when you responded to my request, were you?”  He responded, “No I was in my apartment, headed to my car in the parking garage.  It took me a few minutes to get there and then drive the three blocks to you.”  Driverless cars are unlikely to have apartments, but how will customers deal with departures from “normal” operations?

One extreme possibility is that drivers will be able to ignore vehicle operations until just before an imminent accident when the vehicle signals that the human driver should take over.  They will not have manually driven a vehicle in perhaps months and they now have a few seconds to get back in the loop.  Not surprisingly, this will not work. Decades of research have repeatedly shown this.

The impacts of autonomous vehicles on the overall economy will be pervasive.  The impact on the notion of “driving” will be profound.  We need to explore these futures deeply and carefully.  Like the canal barges, steamboats, railroads, automobiles, and airplanes, these changes will inevitably happen. How can we better understand and facilitate such changes to assure positive outcomes?

The Quartet

In “The Quartet: Orchestrating the Second American Revolution, 1783-1789,” Joseph J. Ellis chronicles the planning, drafting, and ratification of the US Constitution and Bill of Rights in 1789.  The title refers to George Washington, Alexander Hamilton, John Jay and James Madison.  These four men, with support from Robert Morris, Gouverneur Morris and Thomas Jefferson, led the transformation of thirteen colonies into a united republic.

It had never occurred to me that formation of the United States of America was not necessarily the outcome sought via the Revolutionary War.  The Continental Congress adopted the Articles of Confederation in 1777.  They were ratified by all thirteen states by 1781.  The thirteen states remained sovereign and independent.  The role of the federal government was limited to diplomacy and resolving territorial disputes.

The basic idea was to form a federation of thirteen independent countries, each with their own constitution, laws, processes, and so on.  Thus, during the Revolutionary War (1776-1783), the federal government had no power to raise troops and collect taxes.  Each state made its own decisions with regard to contributing troops and money.  The result was thousands of poorly equipped and unpaid soldiers.

Having escaped the reins of the British King and Parliament, the states were in no mood to reinstitute centralized governance and control.  However, the Treaty of Paris in 1784 required payment of pre-war debts and return of confiscated properties.  The credit ratings of each of the states were such that money could not be borrowed to address these needs.  The minimal central government could not borrow either because it had no sources of revenue.

The Treaty also resulted in the Mississippi River being the western border of the colonial territories.  There would eventually be 26 states east of the Mississippi.   However, there were at that time many competing claims on the less settled portions of these territories.  Virginia, for example, was quite aggressive in its territorial claims.  There was need for a mechanism to address claims and form new states.

Washington, Hamilton, Jay and Madison felt that the federation was at great risk of imploding.  Many European powers hoped this would happen, as they did not want the competition likely from a large united republic.  Ellis masterfully tells the story of how these four men planned and orchestrated a process that resulted in thirteen states voting for something that most of their citizens did not want.  Ratification of the Constitution and Bill of Rights in 1789 was the result.

The tension between states’ rights and federal governance is woven into the fabric of our national culture.  The Tea Party is just the latest manifestation of this tension.  The Constitution provides the means for addressing this tension but does inherently resolve it.  As Ellis explains, the quartet facilitated creating, in effect, a work in progress.

The Big Short

Just watched this movie this week, after having read many of the books published on the Great Recession, as well as having served on a National Academy study committee of what happened.  During this study, I had a chance to chat with the second most senior executive at one of the major banks involved, one that disappeared in the aftermath of the crisis.

I asked him if senior executives at his bank understood the questionable assumptions underlying the mortgage-based derivative securities.  He responded, “I understood, but we were making so much money from these securities that it was socially unacceptable to raise any questions.”  Put simply, they wanted to milk the real estate bubble as long as they could.

Of course, the bubble burst and millions of people lost their jobs and their homes.  The assets of the executives in these financial firms were protected.  They even received their usual bonuses, funded by the federal bailout of these firms.  Despite the obvious fraud by financial firms and rating agencies, almost no one was indicted and convicted.  Taxpayers paid, in one way or another, for the $5 trillion of lost wealth.

This movie certainly renews the anger felt in 2007-09.  I felt then, but less so now, that Goldman Sachs, Morgan Chase, Morgan Stanley, et al. should have been forced to fail, with top executives losing all of their personal assets and serving long prison terms, eventually emerging impoverished.  This would have been cathartic, but would it have made a difference in the longer term?  Would greed, fraud, and crime in general have been deterred?

The more fundamental question concerns the nature of value in our society and economy.  I have chaired, or been a member of, a few National Academy committees that wrestled with this question in terms of overarching goals for Academy initiatives.  We eventually agreed on one overarching goal:

To foster and sustain a healthy, educated, and productive population that is competitive in the global marketplace.

This goal is very compelling.  We want people to be healthy and engaged in work and making creative contributions in general.  To do this, we need people to be educated, as that is key to health and readiness for productivity.  People also need to be trained and aided to be productive and educated so they are competitive in the global marketplace.

My earlier post on “Five Million Jobs” outlines how we could accomplish these goals for 3% of the Federal budget.  I also discuss in that post why this obviously highly valuable investment will never happen.  The reason is simple – a sizable portion of our electorate feels that health, education, and productivity are now private goods, no longer public goods.  The idea that we all benefit by everyone being healthy, educated, and productive is no longer par of the national psyche.

So, let’s go back to The Big Short.  Was the financial community focused on improving health, education, or productivity?  More generally, were they providing value to society – and were they rewarded accordingly?  There is certainly value in providing capital to buy homes, start businesses, and develop inventions with potential to become market innovations.  Investors who provide this capital deserve reasonable returns for putting their monies at risk.

The financial community has various mechanisms for decreasing risks, for example, diversifying investment portfolios.  However, the financial players in The Big Short were hiding increasing risks, with the fraudulent compliance of the rating agencies.  These players created toxic portfolios of subprime mortgages.  The risks of default were steadily increasing, in part due to adjustable mortgage interest rates that resulted in payments that many borrowers could not possibly sustain.

The rating agencies helped the banks to hide ballooning risks, but savvy players realized that the bubble must eventually burst and sold these portfolios short. Some of our smartest people found a way to make billions of dollars betting that the marketplace would soon recognize the worthless investment instruments created by the financial community.  In effect, these smart people bet against the economy, against sustained value creation.

It is terrible when the smart money bets on failure.  Greed, fraud, and other criminal activities, in contrast to value, created this situation.  The financial community often talked value creation, but they did not walk it.  Instead, they focused on big paychecks, associated perks, and enormous bonuses.  In the end, they got to keep their windfall earnings while US taxpayers bailed out their enterprises.  Their homes in the Hamptons have kept them safely shielded from the broad loss of confidence they created.

NFL Denies Referee Conspiracy

There is growing evidence that NFL referees have been instructed to make calls – particularly pass interference calls and false start calls – to control the outcomes of NFL games.  The NFL vehemently denies these accusations, but the data are very clear.  The NFL knows the outcomes that will maximize television revenues as well as ticket and clothing sales, and they are determined to make sure these outcomes happen.

Our operatives have managed to make contact with people at Black Rock Big Data Analytics who provide services to the NFL.  None of these people would speak on the record, but they provided various insights.  A key manager said, “Keep in mind that this is all about entertainment, not athletics.  We are focused on earnings per share, not Hall of Fame inductions.  Our goal is to sell beer, pickup trucks, and game shirts.”

We asked, “What does this mean operationally?”  She responded, “The Patriots and Panthers were undefeated until recently.  We maximized the sales of game shirts, and then we needed these teams to lose because there were no more shirts to sell.”  She continued, “We instructed the referees to make sure these teams lost.”  They delivered, sales improved, and the referees got their bonuses.

“Doesn’t this conflict with the whole spirit of the game?” we asked.  The response was simply, “College and pro sports are the essence of corruption, exploiting talented athletes for maximal corporate earnings.”  So, we asked, “Does it not matter that millions of people are totally focused on their teams and their success?”  The response was simple, “Of course this matters.  Our goal is to maximize the percent of their income that ends up in the NFL coffers.”

Finally, our contacts added, “You realize that the whole athletics enterprise is focused on exploiting talented athletes, university presidents, and the general public to fill corporate coffers at the expense of the health and well-being of athletics and academia.  The idea of a student athlete is a farce.  All that matters is earnings per share.”

So, we asked, how far might you take this idea?  “Well, if we look at ultimate fighting, the extreme is death of the competitors.  This could generate enormous amounts of revenue.”  We could not help but ask, “Is this ethical?”  The answer was simple, “All that matters is earnings per share.  Dead athletes are just an insurance premium payment.”

The New Reality

Our operatives have uncovered the motivation and reasoning behind various presidential candidates now emphasizing what many of them are calling the “new realty.”  This reality relates to their personal histories, climate change, economic prospects, and so on.  All of the candidates have “repositioned” their personal stories to gain voter support.

One candidate, born to immense family wealth, tells his story of hardscrabble poverty and Horatio Alger like immersion from this poverty.  The media, their fact checking having discredited this story, finds itself dismissed by the candidate.  They have to ask questions and report answers in the context of this seemingly ridiculous reality.

Other candidates advocate policies, e.g., nuclear attacks on adversaries, which make no sense in terms of costs or consequences but are great pitches for support and votes.  Let’s build a wall between Mexico and the US, or between Canada and the US.  Great idea for construction companies that build walls!

There are lots of ideas about taxes.  The majority of Americans pay no taxes beyond Social Security assessments.  Thus, income tax revenues must come from everybody else.  How can we best redistribute income from earners with high incomes to everyone else?

Our tax policies shield many high-income people by designating their earnings as capital gains.  Thus, they pay 20% rather than 40% of their income in taxes.  The real victims are people whose incomes are designated salaries.  Between federal, state, and local income taxes, as well as property and sales taxes, these people can pay as much as 60% of their income in taxes.

The candidates have long argued for lower taxes, but it has all been just rhetoric.  The country cannot function without many high earners paying 60% in taxes while the majority of people pay 0% in taxes.  This is not going to change.  The minority of people with above average incomes is going to pay dearly to support everyone else.  Otherwise, the stability of the overall social system is at risk.

The candidates, from either political party, cannot embrace this reality.  The idea that we have to redistribute income to avoid social unrest is not acceptable, except for the fact that this is exactly what we do.   The reality is that a minority of people is positioned to benefit enormously from various technology and market opportunities; everybody else will find such changes challenging.  The political system needs to spread the benefits around.

Nevertheless, several candidates are advocating zero income taxes across the board, as well as zero corporate taxes.  They would create a national Value Added Tax.  They suggest 2% but replacing the lost revenue from income and corporate taxes would require a VAT of 15-20%.  Adding this VAT to state and city sales taxes could yield an overall tax of 30% on all consumption.  Commentators have pointed this out but candidates respond with putdowns like, “You need to take a math class.”

The rhetoric really soars when addressing defense spending.  Several candidates have advocated doubling the defense budget immediately.  They argue that this will pump money into the economy.  It has been pointed out to them that the absence of income and corporate taxes will mean that such pump priming will yield little revenue to the government.  They typically respond, “Good.  Less tax revenue the better.”

Candidates’ poll standings reflect the general public’s enthusiasm for the new reality.  The simple fact that the math does not work – the deficits would be immense – is of no interest to the public.  They are apparently believing and very much liking the rhetoric.

We decided it was time to explore the genesis of these audacious positions and promises.  Our operatives posed as representatives of potential European donors to the candidates’ campaigns.  It turns out that a potential donation of $10 million is the price for getting serious attention.  $100 million gets you a meeting with the candidate, but we did not need that.

We ended up meeting with three campaign managers.  We asked about the reality of their candidate’s positions and promises.  All three managers responded similarly, “We are trying to win the nomination and then the presidency.  Period.  We will take whatever position is needed to win convention delegates and electoral votes.”

But, we asked, “What if you win?  How will you deliver on your promises?”  They responded, “Promises?  If we win the presidency, the slate is clean. Whatever we said during the primaries and the election is irrelevant.  Once we are in control, we will do whatever we want.  At that point, the public’s preferences do not matter.”

So, we commented, “You are assuming a one term presidency?”  Their retort was, “Not at all.  Any shortfalls in delivering on promises can easily be attributed to the opposition.  We want to do the right things, but we cannot because the other party stymies our every move.”  We asked, “How do you know that will happen?”  Their response was, “It doesn’t matter.  We weren’t going to do those things anyways.”

This readily begged the question, “Why do you want the presidency if there is nothing that you plan to achieve?”  With a knowing smile, they each responded, “The key objective is to keep anybody else from accomplishing anything.  We want to keep government perpetually dysfunctional.”  We asked, “What’s the purpose of that?”  With a knowing look, they replied, “While the turmoil plays out, our donors and supporters will be making loads of money, which can help fuel the next round of this charade.”



NFL Rules

Confidential sources have indicated that the NFL is considering some sweeping rule changes, all with a goal of increasing the entertainment value of the former sport.  Unnamed executives indicated that, “Our goal is for fans to have fun, to go home with memories of exciting games when their team miraculously won despite the odds against such outcomes.”

One conclusion was that home field advantage has to mean something more.  Consequently, the NFL is considering giving the home team five downs per possession, while the visiting team will still have only four downs per possession.  Purists have protested, but the NFL has reminded them that the focus is on the fans.  “Our sponsors want to sell beer and pickup trucks.  The home team winning is good for viewer retention.  If the home team is losing, fans tend to change the channel.  That does not sell anything.”

Another proposal receiving serious consideration is requiring both teams to wear identical uniforms without numbers or names on the jerseys.  This idea would so totally confuse players that miscues and mistakes would be rampant.  The idea emerged from some enthusiasts of America’s Funniest Home Videos.  The players union is adamant in their opposition to this idea.  One spokesperson said, “This is the most ridiculous idea since Bill Veeck tried midget players.”

Yet another extreme proposal is limiting each player, except the quarterback or kicker, from touching the ball more than once per game.  Each player gets one carry or one catch per game.  Enthusiasts have pointed out that this would give many other players chances to display their skills.  Naysayers respond that this would decimate the record books.  Almost no one could excel with one possession per game.

The Consolidated NFL Hall of Fame is studying this proposal.  Since the Consolidated Corporation acquired the HOF, they have changed many policies and procedures.  HOF members no longer vote on potential inductees to the Hall.  Election is now based on sales of apparel and accessories.  Not surprisingly, the result has been that players are elected in their first year of eligibility or not at all.  Once no one remembers them and their game shirts are not selling, players simply disappear from the collective consciousness.

The most controversial proposal by far would eliminate any play calling by coaches.  Head coaches, offensive coordinators, and defensive coordinators would be prohibited from directing plays.  The quarterback would be solely responsible for choosing and executing plays.  Any evidence that the coaching staff was trying to intervene in the calls would result in forfeiture of downs.  Two assessments would result in forfeiture of the game.

The backdrop for all these deliberations is the desire to increase fan enjoyment and commitment.  Everyone wants their team to make the playoffs.  Another proposal being considered is that every team makes the playoffs.  Further, each round of the playoffs would be the best two of three games rather than a single game.  The three games would be played in a one-week period.  This would push the Super Bowl into April or May.  This would yield a windfall of revenue from advertising and ticket sales.

Finally, initial ideas are emerging for decreasing the current 12 minutes that the ball is in play during a typical three hour telecast.  Another 2-3 minutes of advertising time would be highly valuable.  The most popular suggestion was to eliminate stopping the clock during a series of downs and then adding an additional minute of advertising between each of the four quarters.  Enthusiasts argue that the faster-paced game would be more exciting.

Overall responses of fans to these suggestions have been quite negative.  One fan said, “If you make the real game so short and I only get to see my favorite player once, how am I going to be able to justify three hours of drinking beer and scarfing junk food?  I already have a new pickup truck.”  Another fan remarked, “Well, at least these changes will reduce injuries.  Football is just an excuse to hang out with my friends anyways.”

Disruptive Service Innovations in Healthcare

A recent issue of The Economist provided an in-depth review of how high technology financial startups are poaching high-margin financial services from large banks.  The large banks are not standing still; they are often acquiring these startups once they prove viable.  This may keep them in the game, but high margins are being substantially eroded for services that were once cash cows.

There have been many related discussions in the vehicle industry.  Many vehicle manufacturers are trying to position their vehicles as service platforms.  OnStar by GM is a classic example.  As more high-tech vehicle services emerge, it may be that Apple and Google, for example, will be the innovators rather traditional automobile companies.  They won’t produce the cars, but they will make the profits.

Both of these examples involve industries with business models, especially cost structures, which overprice technological innovations, yielding profit margins that can compensate for enormous inefficiencies elsewhere throughout their enterprises.  In general, disruptive technology-based innovations can obsolete business models and displace mainstream providers who are deluded by the incumbency of their traditional approaches to their markets.

There is a significant opportunity to disrupt the business models of consulting service companies that provide business process improvement services to healthcare providers.  The disruption will completely undermine the construct of the “billable hour” for these services.  Consider these observations:

  • Healthcare providers are notoriously inefficient users of capacities, in part because they get paid for everything they do regardless of relevance or efficiency.  Any reasonably competent process engineer can see countless low hanging fruit in terms of process improvements.
  • All major healthcare providers are delivering the same services, i.e., caring for the same maladies of humans ranging from hypertension, diabetes, and heart disease to automobile accidents and gunshot wounds.  There is no inherent reason that they could not all provide these services in the same ways.
  • Such standardization has led to major efficiencies and increased effectiveness for sales force automation, logistics, supply chain, and inventory management, and numerous other industrial processes.  Healthcare delivery is ripe for such process innovations.

It is important to differentiate process innovations that involve direct adoption of, for example, logistics, supply chain, and inventory management, from those innovations that address healthcare delivery specifically.  The latter must draw upon evidence-based medicine to devise, evaluate, and generalize care processes for hypertension, diabetes, heart disease, etc.  Standardizing such services requires deep knowledge of diseases and procedures for screening patients, diagnosing disease states, and treating diseases.

One approach to standardizing care delivery processes has been to map the processes of each provider, leading to one-off solutions for each enterprise.  These process maps are used to identify process inefficiencies, redesign processes to eliminate inefficiencies, deploy new processes, and then evaluate both efficiency and effectiveness.  This usually requires an enormous number of consulting person-hours and, hence, is very expensive.

This approach is based on the idea that every provider is unique and, of course, every patient is unique, and only the knowledge and skills of their individual primary care physicians and specialists are adequate to know how best to treat an individual patient.  Such reasoning is deeply flawed.

The Institute of Medicine has found the following — from the time that a new best practice is proven until the majority of physicians have adopted the practice averages 17 years.  Other studies have shown that physicians’ approaches to care are much more affected by where they graduated from medical school than by research findings since they graduated.  Thus, most patients are not getting the best care.

To be fair, various thought leaders have shown that it is absolutely impossible for clinicians to keep up with the developments in their specialty.  They could spend all their time reading and still not be able to keep up.  The individual clinician, despite high motivation and commitment, simply cannot keep up with the generation of medical knowledge and delivery skills.

It might be argued that the medical literature provides all the knowledge needed to specify best practices.  However, the literature focuses on scientifically defensible knowledge rather than how to deploy this knowledge in the care delivery system.  The need to translate increasing knowledge to constantly improving best care practices presents an enormous business opportunity.

This opportunity is premised on the strong belief that there are definable best practices that every provider should follow.  These best practices can be identified and constantly updated.  Knowledge of these best practices can be deployed in terms of web-based interactive visualizations enabled by computational models that embody these practices.  Clinicians can interact with these visualizations, perform any desired “What if?” experiments, and assess the impact of updated best practices on health outcomes and financial consequences.

Once decision makers are convinced of the merits of the best care practices portrayed in the web-based interactive visualizations, it is inevitable that many will ask about how these practices can be customized to the demographics of their patient populations.  Much of this type of customization can be enabled online. Other types of customization, e.g., to their physical infrastructures, may be difficult to fully automate, at least initially.

The fully customized version of a provider’s processes and practices can be created and maintained online for their use in strategic and operational management.  Parameters within these processes and practices can be updated monthly.  Performance outcomes can be compared to predicted outcomes.  Deviations can be used to track down performance problems, for example, unusually long delays for out-patient diabetics.

The vision is to provide to medical practice what SAP provides to logistics, supply chain, and inventory management and provides for sales force automation.  This will require a combination of compelling online capabilities with deep knowledge of medical practice, as well as an efficient and fine-tuned mechanism for constantly updating knowledge of the state of the art in medical practice.  In the process, the 17 years it takes to for the majority of clinicians to adopt best practices should be reduced to perhaps six months.  This will be a major contribution.

Leading a University Research Center

University research centers are delicate organizational systems.  They bring together faculty, research staff, and graduate students for several reasons.   Centers are often formed as a result of a large NIH or NSF grant or because of a large gift or grant from industry or wealthy alumni.  So, there is money on the table and researchers are naturally attracted to funding.

Researchers can also be attracted to the research agenda of the center.  They like the center’s portfolio and other researchers involved and want to affiliate with the endeavor.   This is also true for graduate students, who are often attracted to the research portfolio but also looking for graduate assistantships.  Prudence is needed to identify students who have the potential to make real contributions.

I have found that any university will embrace a research center that is totally externally funded and places no demands on the university.    Such centers provide resources, at least in terms of overhead, to pay for use of the brand on letterhead and brochures.  If all goes well, they hit a homerun; otherwise they quietly fold after the external resources are expended.

Universities tend to have two strategies.  For things that they view as mission critical, e.g., nanoscience and genomics, they will invest far beyond any possible returns – except bragging rights.  Other things have to earn their way onto the agenda, typically by paying returns far in excess of required investments.  This excess is used to further fund mission critical areas.

If your assignment is to run a university research center, here is some advice.  First, determine whether or not you are mission critical.  If you are receiving resources in excess of what you generate, chances are you are mission critical.  If you are, in effect, paying taxes on the resources you generate, you are a cash cow, at least as long as the cash lasts.

If you are mission critical, your success is assured – the university needs you to succeed and needs to trumpet your success.  If you are a cash cow, consider alternative futures.  A commercial spinoff might make sense.  Another possibility is to move the whole center to another university.   This might seem like being disloyal, but keep in mind that you have enjoyed little loyalty thus far.

While you are still a cash cow at your university of origin – where the center was founded – there are several tactics worth considering.  First, do your best to avoid taxes.  A primary mechanism to achieve this is to secure funds that allow no overhead charges.  Since you are not getting a share of overhead, why contribute to the pool?

Why would universities accept such stipulations?  Quite simply, they cannot walk away from money on the table.  Money received in this way makes you less of a cash cow.  However, you are not getting a share of the milk – or meat! – so why should your research center contribute?  If you are really good at this, you will find the university administration wanting to talk about how they can better support you.

When I was 12 or so, I came home from Charlie Boyd’s farm with a pigeon under my arm.  I proclaimed to my mother, “Charlie Boyd gave me a pigeon!”   My mother responded, “He didn’t give you a pigeon, he got rid of a pigeon.”  If you are directing a research center, especially one newly founded, you need to learn how to identify and avoid pigeons.

Pigeons, in the context of university research centers, are faculty members who are difficult to work with and/or consistently underperform.  Deans and department chairs often tend to recommend pigeons to research center leaders.  If you manage to transform their attitudes and performance, you have solved a problem for the dean or department head.  If not, it is now your problem.

One of the primary objectives of the leader of a research center is brand development.  You want the broad community to see your center as a prime time player in the areas of its research and teaching.  My experience is that the university will not help you with this.  Their marketing and communications staff members are oriented to serving the needs of the president, provost, et al.

Thus, you need to identify the constituencies with whom you want to communicate, develop the messages and associated packaging to communicate with these constituencies, and create the capabilities and opportunities to communicate. You will, of course, be the primary one to deliver these messages.  However, getting other faculty members involved with this messaging can contribute enormously to fostering a shared mental model of the center’s vision.

As soon as possible, you want to get to the point that you are not writing all proposals and leading all projects.  Mentoring faculty members, particularly junior faculty members, is the way to grow these competencies.  An important aspect of this is providing them opportunities to present their research to senior audiences from industry and government, not just academia.  Speaking skills, as well as writing skills, benefit from frequent opportunities to use them.

Finally, as the leader of a research center you should invest little time enhancing your resume and much time doing things that improve others’ resumes.  Your center needs to be vehicle for personal growth of faculty, staff, and students.  The outcomes from your center may include many articles, books, patents, etc., but the primary product of a university research center is the people who employ their knowledge and skills to address the needs of society, typically from a long-term perspective, but nonetheless as contributions to the common good.

Thoughts on Location

Does location matter?  It depends on what you are seeking.  If economic opportunity is your yardstick, here are some interesting statistics.

Greater New York City generated $1.5 trillion in GDP for 2014.  Greater Los Angeles provided $0.8 trillion; greater Chicago $0.6 trillion; greater Houston and greater Washington, DC $0.5 trillion each; and greater Dallas, San Francisco, Philadelphia, and Boston $0.4 trillion each.  The total US GDP for 2014 was $17 trillion.  New York City generated roughly 10% of this, and these nine metro areas generated over one third of the country’s GDP.

Most of the government research-funding agencies are in Washington, DC, as are many foundations.  A large percentage of research-funding foundations and potential Fortune 500 sponsors are in New York City. The top five homes of Fortune 500 companies include California (54), Texas (52), New York (47), Illinois (33), and New Jersey (28), accounting for almost half of the Fortune 500.  New York and New Jersey account for 16% of the Fortune 500.

High tech cities, ranked by numbers of jobs, are San Jose (Silicon Valley), Seattle, Boston, Washington, Los Angeles, Dallas, San Diego, Orange County, New York, and San Francisco.  Silicon Valley once dominated in IT related jobs but has been losing jobs as companies migrate.  The majority of aerospace and defense companies are on the West Coast – Arizona, California and Washington — although their headquarters have migrated to the east, mainly to Washington, DC, but also Chicago.

In the Sun Belt, Atlanta companies include AT&T Mobility, Coca-Cola, Delta Airlines, Home Depot, NCR, Newell-Rubbermaid, Southern Company, Turner, and UPS.  These companies are focused on transportation, supply chain and operations issues.  Dallas companies include Advance PCS, Dean Foods, ExxonMobil, Kimberly-Clark, Neiman Marcus, Southwest Airlines, and Texas Instruments, a quite diverse mix.  Houston companies include Phillips 66, Conoco Phillips, Sysco, Halliburton, Baker Hughes, and Marathon Oil, obviously reflecting a strong energy sector.  Charlotte is the second largest banking center after New York City.

Multiple healthcare providers are in all major cities. The top ten cities for healthcare employment, in rank order, are Houston, Philadelphia, Baltimore, Boston, Milwaukee, Denver, Fargo (ND), New York, Cleveland, and Norfolk.  Healthcare is the largest employer in Pittsburgh.  Seven of the 25 largest employers in New York City are healthcare providers.

The essential tradeoff is economic opportunity versus cost of living.  The Cost of Living Indices for each region’s major cities are shown below.  The average index nationally is set to 100.  A major contributor to high or low values is the cost of housing.

  • Northeast: New, York (Manhattan, 217; Brooklyn, 182; Queens, 159), Hoboken (183), Washington (140), Boston (133), and Philadelphia (127)
  • West Coast: San Francisco (164), San Jose (156), Orange, County (146), Los Angeles (136), San Diego (132), and Seattle (121)
  • Midwest: Chicago (117), Minneapolis (110), Denver (103), Salt Lake City (101), Kansas City (98), Cincinnati (94), Pittsburgh (92), and St. Louis (90)
  • Sun Belt: Miami (106), Phoenix (101), Raleigh (98), Atlanta (96), Charlotte (93), Houston (92), and Dallas (92).

Clearly, the large Sun Belt cities offer jobs and low costs of living, with a major contributor being significantly lower costs of housing.  The Northeast and West Coast have lots of job opportunities but are very expensive places to live.  The Midwest is closer to the Sun Belt in costs, but not in terms of job opportunities.

Pundits’ Performance

There is a wealth of self-proclaimed pundits providing pronouncements on sports, politics, the economy, and so on.  There seem to be unlimited numbers of Democrat and Republican strategists.  Some are wizened pros that have been through many campaigns, some successful and some less so.  Many are quite young.  Despite having seemingly no credentials, they are happy to make sweeping pronouncements about global warming, same-sex marriage, and tea party turmoil.

Editorial writers for major newspapers seem to be better informed and balanced, and are usually quite transparent about their liberal or conservative leanings.  They are usually clear about their opinions versus observations based on data.  My experience has been that print journalists are much more thought provoking that television or radio journalists.  Writing takes much more discipline than speaking.  Of course, reading also takes more discipline than listening.  Sound bites are much more likely to be misleading.

Sports pundits are rather different.  Many are former professional athletes or coaches.  So, they have reasonable credentials.  Their prognostications are readily evaluated by the outcomes of the sport they follow.  The successes of their predictions are tabulated and reported.  They tend to do a bit better than just flipping coins, but are seldom highly successful.  Nevertheless, fans seem to enjoy their banter and tune in regularly.

How are pundits judged?  Expecting their predictions to be correct is a tough yardstick.  We can assess whether or not sports pundits’ predictions are accurate.  However, it is difficult to evaluate the statement by the 28-year-old Republican strategist that global warming is a hoax and same-sex marriage will lead to the end of civilization.  It is equally difficult to judge the equally young Democratic strategist pronouncement that income inequality will likely lead to a revolt of the downtrodden.

It may be that people like pundits whose pronouncements agree with their positions and whose choices of positions and articulations are entertaining.  People are not looking for enlightenment.  They want to feel comfortable in their preconceived opinions and entertained in the process.  It is not about fact-finding journalism.  It is about intellectual comfort food with a few laughs thrown in for entertainment.

The Economics of Retirement

My last post addressed my frustration with a 60% taxation rate that left me wondering if my role was mainly to provide resources to be redistributed to other, undoubtedly needy, people who do not pay taxes.  The 40% that I get to spend barely covers my financial commitments.  So, how do I ever get ahead of the game and retire when I am 75 or 80 years old?

Many people are asking this question.  The number of highly educated older seniors delaying retirement has soared, resulting in an income tax windfall for the government that has helped fund the early retirement of less educated people caught by the Great Recession and unable to find employment.  Despite the recent recovery, such seniors continue to delay retirement.  What choices do they have?

One scenario is to simply die with their boots on, provide various life insurance proceeds, and accept the tax folks scarfing up their portion of the proceeds.  Another scenario is to make sure they end up poor.  Give away everything.  Leave themselves wards of the state.  Do their best to assure the state pays for hip, knee, kidney, and heart transplants.  Could be pretty expensive.

I can imagine this becoming a sport for baby boomers.  How much can you cost the system?  What percent of lifetime taxes paid can you recoup via medical expenses paid?  If you can exceed 100%, you get a free heart transplant or an evening with an aging Hollywood star.  If you identify a mechanism that others can use, you get an additional double hip replacement and an annual evening with aging Hollywood stars.

Of course, all of these whimsical ideas are avoiding the central issue.  We need the capable folks to provide the resources for the 50%+ of people who cannot be net contributors.   There is obviously a point at which the capable people will balk.  However, such people have demonstrated abilities to game the system in ways that minimize the number of capable earners who walk away from continued earning.  They find loopholes, which once closed, lead them to find new loopholes.

Underlying this dilemma are three compensating phenomena – people who are really capable, motivated to work very hard, and sufficiently insightful to identify opportunities for innovation – see Malcolm Gladwell’s Outliers.  These types of people change the world. Everyone else, in effect, lives off the consequences of these phenomena.

Well, it is not at all that simple.  If the masses of workers do not have the income needed to consume, markets will not have the scale to enable cars, airplanes, and smart phones.  Henry Ford identified this need a century ago when he doubled wages to $5 per day, although his primary motivation was to reduce the substantial employee turnover he was experiencing.

We need masses of people who are willing and able to consume.  Carnegie, Ford, Morgan, Rockefeller, and Vanderbilt depended on this.  Bezos, Brin, Gates, Jobs, Page, and Zuckerberg more recently have depended on people to consume.  Thus, income redistribution via taxes is essential to the economic growth of the country.  Our consumption-driven economy totally depends on people consuming – buying more and more stuff.  This, in turn, depends on people having incomes sufficient to enable the needed consumption.

What does this mean for the economics of retirement?  The success of my attempt to recoup my retirement investments lost to the real estate bubble has been diminished by the unexpected heavy taxation on my “homestretch” income.  In fact, I have to use retirement assets to pay the increased taxes, so the nest egg is decreasing rather than increasing.

In other countries, there is a substantial value added tax on consumption that provides a large percentage of the government’s income.  This tax on consumption is often called regressive, as it is indifferent to the income of the consumer.  The benefit to someone close to retirement is that you can choose to not consume, e.g., not buy a new car or engage in expensive travel.

Yet, this does not address the dilemma.  Income redistribution is essential to a civil society. Without redistribution, the impoverished inevitably revolt at the ballot box or in the streets. However, there is another solution — full employment and well-paying jobs. This may sound utopian, but it is not. See my earlier post “Five Million Jobs.”

Income Taxes

Over the past three years, my tax rate has increased to over 60% of my income.  This includes Federal and State Income Taxes, Social Security Taxes, Workmen’s Compensation, Medicare Tax, Sales Tax, and Property Taxes.  This tax rate, combined with the costs of living in an area where I earn a high enough income to pay over 60% taxes, has given me some pause.  The amount remaining after taxes, and high rents, provides for Ramen noodles and an occasional beer.

This post reviews various “theories” of taxation, starting in the late 19th century.  All of these theories recognize the difficulty of high rates of taxation decreasing the motivation of high earners to continue earning.  For example, at a 100% tax rate, the government could redistribute all income to meet its obligations.  In fact, incomes would no longer be individual citizens’ incomes; it all would be the government’s income.

Government could then provide citizens their daily Ramen allocation – probably no beer though.  People would work their 10-12 hour days, eagerly looking forward to their Ramen, and a bit of rest before the next day.  People could even work seven days per week.  Why not?  Such a scheme would provide the resources needed to redistribute income to the 50%+ low-income Americans who pay no income taxes.

I could see many of the “powers at be” being quite excited about this model.  The most capable people would be indentured to support the least capable.  This is not a new idea.  Many people have thought about this possibility over the past 100+ years.

Edgeworth (1897) discusses what he terms the pure theory of taxation. Written before the 1913 establishment of U.S. federal income tax, he focuses on taxes on the consumption of goods and commodities.  Invoking the principle of equal sacrifice, he assesses impacts of taxes on each stakeholder.  Equal sacrifice is defined as each taxpayer losing the same utility to the tax collector – in other words, the goal is equality of perceived pain for each taxpayer.

Ramsey (1927) continues this line of reasoning.  He is concerned with the following:  Given a bundle of goods and commodities, how to design the differing tax rates on each type of item to minimize loss of utility of those taxed.   He mathematically shows that “the taxes should be such as to diminish the production of all commodities in the proportion” (p. 54).  The key point here is that taxes on goods and commodities will diminish consumption of them.

Mirrlees (1971) explores the theory of optimal income taxation.  He presents a mathematically rigorous approach to determining optimal progressive income taxes such that taxes impose equal utility losses on everyone.  Individuals have a utility function for consumption (x) and time worked (y). An individual of ability n is paid ny for his or her work.  The government imposes an income tax percentage of c(ny) on this income.  The overall result is that a c(ny) function that is linear in rate progression is near optimal, unless “the supply of highly skilled labor is inelastic.”

Mirrlees suggests, however, that greater equality could be achieved by taxing people by ability to earn income, perhaps proportional to IQ, rather than actual income.  He argues that this would be “an effective method for offsetting the unmerited favors that some of us receive from our genes and family advantages.”  The difficulty that Mirrlees is trying to overcome with this idea is that high tax rates are likely to discourage high ability people from maximizing their earnings, thereby undercutting the tax revenues that were expected from them.  Taxing by IQ, in theory at least, implies that people would have to pay taxes on what they could earn even if they chose not to earn these amounts.  It is, of course, very difficult to imagine this ever being implemented – but is it?

More recently, Feldstein (1982) and Summers (1981) address the impacts of tax rates and inflation on investments. Feldstein argues that, “Inflation creates fictitious income for the government to tax” (p. 154).  Taxes are paid on inflated returns while investors only gain real returns.  In this way, a positive real return can become a net loss once taxes are deducted.

Summers (1981) discusses trends in business investments versus those made to satisfy regulations, e.g., pollution control.  The investment rate in the 1975-1979 period was 3%, the lowest in three decades.   Total taxes (on corporate profits, dividends, and capital returns) declined from 71.5% in 1953 to 52.7% in 1979. Inflation soared, “In a tax-less world, firms invest as long as each dollar spent purchasing capital raises the market value of the firm by more than one dollar” (p. 77).  However, as Feldstein notes, high inflation rates undermine this possibility.

Much more recently, Mankiw, Weinzierl, and Yagan (2009) discuss optimal taxation in theory and practice. They argue that, “The social planner has to make sure the tax system provides sufficient incentive for high-ability taxpayers to keep producing at the high levels that correspond to their ability, even though the social planner would like to target this group with higher taxes.”  They report a range of lessons from their review: 1) optimal marginal tax rate schedules depend on the distribution of ability, 2) the optimal extent of redistribution rises with wage inequality and 3) optimal taxes should depend on personal characteristics as well as income.

Thomas Piketty has focused on income inequality and capital taxation (Piketty & Saez, 2012; Piketty, 2014), with his 2014 book receiving an enormous amount of attention.  They focus on “socially-optimal capital taxation,” on both savings and bequests, to deal with the problem of a “large concentration of inherited capital ownership.”  They assert that, “Inequality permanently arises from two dimensions: differences in labor income due to differences in ability, and differences in inheritance due to differences in parental tastes for bequests and parental resources.”

They show that the “socially optimal” tax rate on inheritances, TB, can range from 40-60% to 70-80% when bequests are highly likely.  Increasing TB allows decreasing the tax rate for labor, TL.  For a 20% bequest probability, TB = 73% and TL = 22%.  Their model also includes a tax rate for capital gains, TK.  They consider how people shift income from monies subject to TL versus TK.  They find that the optimal TK increases with uncertainty about future returns due to TB.  They also consider a consumption tax, TC.  This tax can enable TL < 0, which implies a labor subsidy for low-income people.

Of course, whatever schemes are proposed for TB, TL, TK and TC, high ability people will figure out how to take advantage of these schemes, effectively thwarting income redistribution.  People with high incomes and/or wealth, will have the resources to hire high ability people to figure this out for them.  Thus, any scheme is subject to “gaming” and adaptation will inevitably be necessary.

So, is my frustration with my 60% tax rate justified?  I clearly am doing my part to help with income inequality.  Further, I am still working; so the tax rate has not reached the extent to which I have given up trying.  Of course, I am keenly aware of my financial commitments.  The 40% that I still get to spend covers many things.  There is a point, however, where living in a high cost of living area to earn a highly taxed income is no longer worth it.

I have a vague sense that the taxation system understands this, if only implicitly.  The intention is to squeeze as much revenue as possible from highly capable earners to just before they are no longer willing or capable.   Upon retirement, the taxation system will drain taxable resources from former earners via one mechanism or another, e.g., required Medicare charges linked to income.  It almost seems that the system will, if possible, create penniless citizens just as they draw their last breadths in nursing homes, having no assets and supported by Medicaid.

There are various mechanisms to fend off this future.  Trusts can be formed and foundations can play a role.  However, perhaps with the exceptions of the super rich, the system is designed to suck resources from capable people who earned them and redistribute these resources to people who need them.  Interestingly, this redistribution leads to a subset of these under-resourced people becoming enormously successful and then being subject to the same dynamic.

The redistribution of resources keeps society from rebelling.  High ability folks – creative and crafty – understand how to prosper.  The social and political system knows how to balance idea generation, venture formation and allocation of resources, while also redistributing income to support those who, for one reason or another, cannot compete.  Those losing income, like me, gripe and complain but, as the long history discussed above illustrates, redistribution is a necessity of modern society.  The mechanisms and magnitudes are debatable, but the phenomenon is not.


Edgeworth, F.Y. (1897). The pure theory of taxation. The Economic Journal, 7 (25), 46-70.

Feldstein, M. (1982). Inflation, capital taxation and monetary policy. In R.E. Hall, Ed., Inflation: Causes and Effects (pp. 153-168). Chicago: University of Chicago Press.

Mankiw, N. G., Weinzierl, M., & Yagan, D. (2009). Optimal taxation in theory and practice. Journal of Economic Perspectives, 23 (4), 147-74.

Mirrlees, J.A. (1971). An exploration of the theory of optimal income taxation. The Review of Economic Studies, 38 (2), 175-208.

Piketty, T. (2014). Capital in the Twenty-First Century. Cambridge, MA: Belknap Press.

Piketty, T., & Saez, E. (2012). A Theory of Optimal Capital Taxation. Cambridge, MA: National Bureau of Economic Research, Working Paper 17989.

Ramsey, F.P. (1927). A contribution to the theory of taxation. The Economic Journal, 37 (145), 47-61.

Summers, L.H. (1981). Taxation and corporate investment: A q-theory approach. Brookings Papers on Economic Activity, 1, 67-140.

Reflections on New York City

I am on the homestretch of being in New York City for three years, actually in the bleachers of Hoboken watching the game played by this remarkable city.  For over 400 years, it has been an innovation ecosystem embracing change, creativity, and diversity.  The only colony without a religious or political agenda, New York City was, and still is, focused on commercial success.  Your religion and politics did not matter – and still do not matter.  Abilities to attain power and make money mattered – and they still do.

One element of the City’s success has been constant change in the gene pool of its citizens.  The endless stream of immigrants was at first dominated by the Dutch, then the English, and in the 19th century by the Irish, then Germans, and then Italians, followed by Eastern European Jews, and more recently in the 20th century by Blacks, Hispanics and Asians.  The resulting diversity is truly astounding.  A walk on the City’s streets displays every skin color imaginable.  The idea of race becomes completely lacking in meaning.


As impressed, perhaps awed, as I am of New York City, there are drawbacks.  The city is quite dirty, noisy and, in general, rather untidy.  People are always in a rush.  Watching people trying to get out of the city on a Friday afternoon is like viewing panicked lemmings with horns, not extensions of the skull, but technological noise-making devices.  I cannot help but speculate on the potential benefits of banning personal vehicles in Manhattan.

The city is also amazingly expensive.  Everyday staples are reasonable, but everything to do with real estate is overwhelming.  Purchasing or renting a place to live is off the charts.  Property taxes make mortgages look modest in terms of monthly payments.  Income taxes are not for the faint hearted.  It costs a lot to run this complex city and it often feels that you are the main source of municipal income.

I was recently part of a dinner discussion of the costs of living in the City.  One person who had recently moved to Manhattan mentioned that she had looked at a building where the monthly condo fee was $50,000.  Everyone gasped.  She said that you could endure this expense by just thinking in terms of buying the management services company a BMW every month.  Few of the people around the dinner table felt that this characterization made the idea more palatable.


Politics in greater New York City, including northeastern New Jersey and southwestern Connecticut, have always been complex and messy.  Centuries of massive immigration have created a wide range of political camps and mechanisms for achieving desired ends.  A good example is provided by the ways that Tammany Hall looked after the interests of Irish immigrants.  Of course, the Tammany leaders also made sure that they personally benefitted from these political shenanigans.

The constant flood of immigrants into the City seeking economic opportunity results in modest population growth despite the steady flow of people out of the City to the suburbs and elsewhere, for example, the Sun Belt.  Most immigrants start at the bottom of the economic ladder.  Once they make it up a few rungs, and have a couple of children, many move to the suburbs or elsewhere in search of larger and less expensive housing, better schools and more opportunities for their children and, in general, the American Dream.

Many still have economic ties to the City and commute from the suburbs to Manhattan each day.  1.6 million commuters each day double the daytime population of the island.  Nevertheless, the suburbanites’ political issues morph from urban issues of fair housing, rent control, and so on to property taxes, school concerns, and especially transportation infrastructure to lessen the pains of their daily commutes.  The overall result across greater New York City is fragmentation of political interests in terms of who gets what benefits and who pays for them.


I was born on the island part of Rhode Island, rather than the Providence Plantations part.  From Fort Butts, a high earthworks from the Revolutionary War, we could see the Sakonnet River to the East and Narragansett Bay to the West and North.  There were two bridges to and from the island on the north end, and a ferry at the south end in Newport.  Water and boats were pervasive on the island.

My relationship with water is deeply seated and hence my affinity for the Hudson, East, and Harlem Rivers, as well as Long Island Sound.  My great-great grandfather’s Fall River Line steamboats provided overnight service from Fall River to Newport, then into the Atlantic, and through the Sound to the East River, and then to the Hudson to dock at Piers 18 and 19.  I can see where these piers were from my office window at Stevens Institute of Technology, five stories above the western shore of the Hudson.

A couple of boat tours of the City, as well as many walking excursions, have easily displayed the ways in which water has been and is integral to the fabric of the City.  Getting over or under one or more rivers is a daily task for millions.  Countless business ventures took advantage of and sometimes abused these rivers.  The ebb and flow of the Hudson in particular affects river traffic to the head of the tide in Troy, 140 miles to the north.  The power and beauty of the water are transcendent.


New York City used to be the largest port in the US – a position gained with the opening of the Erie Canal in 1825.  Now it needs to join with New Jersey to be in second place behind Los Angeles/Long Beach.  The shipping container was the culprit.  The container eventually decreased the cost of shipping by 90%+ per pound, but Manhattan had no place to stage containers, much to New Jersey’s benefit.  Employment of longshoremen was decimated in the City and elsewhere.  Manufacturing jobs in the City plummeted.  If you can move things so cheaply, why assemble them in a high cost place like the City?

The dramatic loss of manufacturing jobs, in parallel with energy crises, cheap labor in the South, increased global competition, and decreased defense budgets, created great economic stress for the City in the 1960s and 1970s.  Over 10% of the population left.  The City’s service sector eventually led the rebound — finance, law, public relations, advertising, publishing, and entertainment.  Dramatic increases of immigrants from Puerto Rico, Dominican Republic, and Asia replaced the out migration to the suburbs and Sun Belt.


Weather is a challenging aspect of New York City.  I grew up in the northeast – Boston and Rhode Island – so I felt prepared for the weather in New York City.  I was wrong.  The wind down the Hudson is unforgiving.  Silk long underwear is a necessity.  Without a car, iced sidewalks and intersections result in very slow walking.  Falls are anathema to people my age and it requires significant effort to be careful.

Summer is also a challenge.  One would think that winter represents “dues paid” for a pleasant summer.  However, June and especially July are as unbearable as summer in the south, enough so that I need to bring changes of clothes to the office so that I can shed sweat-drenched clothes from the walk to the office.  Mercifully, by mid August, one can sense Fall coming and changes of clothing are no longer necessary.

The weather also makes traveling more complicated, more so for airline travel then the trains.  Winter snowstorms and ice can completely bog down airports.  Summer thunderstorms, not to mention hurricanes and nor-easters, also wreck havoc.  Delays at airports get longer and longer, and people get increasingly frustrated and angry.  Enormous amounts of time are wasted.


Diversity and creativity are the hallmarks of the City.  This can be seen in many ways.  Certainly the architecture of the City displays the richness of ideas for urban form and function.  The number corporations headquartered in greater New York City, as well as the number of professional sports franchises, are also indicators.  The best measure, however, is the breadth and depth of creative contributions by people.

The industrial tycoons such as John Jacob Astor, J.P. Morgan, John D. Rockefeller, and Cornelius Vanderbilt are well known.  Beyond these captains of industry, the City has benefitted from many creative contributors in cosmetics (Elizabeth Arden, Helena Rubenstein and C.J. Walker), fashion (Hattie Carnegie and Ralph Lauren), entertainment (Samuel Rothafel and Florenz Ziegfeld), performance (Leonard Bernstein and Duke Ellington), publishing (Bennett Cerf and Horace Liveright), and media (William Paley and David Sarnoff).  These are just a few members of an enormous cast of creative and influential people who have woven the fabric of New York City.

Why New York City, rather than Boston or Chicago, for instance?  Urban economist Edward Glaeser provides the answer. “The tendency of people to attract more people is the central idea of urban economics, and nowhere is that idea more obvious than in America’s largest city.  New York’s remarkable survival is a result of its dominance in the fields of finance, business services, and corporate management. Finally, and most spectacularly, for almost 200 years, the success of New York owes a great deal to the city’s role as a place where the latest news can be picked up quickly.”

New and Improved Frequent Flyer Programs

The airlines have long recognized the inherent liabilities of their frequent flyer programs.  There is – or was – an enormous legacy of free flights waiting to be redeemed by frequent travelers who planned to take their families on vacations or use their nest egg of points for retirement travel.  The airlines, however, are working diligently to undermine the value of these nest eggs and avoid having to pay off on their promises.

Their plans have three components.  First, constantly increase the number of points needed for free flights from 25,000 to 50,000 to 100,000 or more.  Second, make the flights available for free flights overwhelming onerous.  For example, the free flight from Atlanta to Boston stops in Dallas-Fort Worth, Salt Lake City, and Detroit on the way to Boston, turning a 2-3 hour flight into 16 hours.

Third, charge for redemption of points.  If you use points for Atlanta to Boston, it costs $1,000 to redeem the needed points.  Or, you can buy a ticket for $400-500.  Thus, the frequent flyer points are not just worthless.  They have negative value.  The millions of miles flown on the major airlines are now a liability for passengers, at least if they do not understand the airlines’ games.

Our investigators interviewed several airline executives to more fully understand their strategies and how they are creatively avoiding the legacy of frequent flyer programs.  All of these executives spoke anonymously, fearing retribution from their employers. Their stories are eerily similar, despite their being no evidence of conspiracy.

They spoke to us because they are also frustrated.  One said, “We used to be loved by business flyers.  They said things like, ‘I already feel at home when I relax in my seat on the homeward leg of my trip.’  Now, they ridicule us and clearly hate us.  But it seems that is where the business is headed.”

Another executive told us, “It is important to understand that, despite slick marketing programs and promotions, airlines have absolutely no interest in the welfare or satisfaction of passengers.  All the nice words are just a front.  The intent is to squeeze as much revenue from passengers as possible while providing as little value as possible.”

Another executive put it differently, “We would really rather just carry freight.  It is difficult to damage and does not complain.  People expect us to care about them.  Why should we?  They are lucky to get from point A to point B so cheaply.  But they also want peanuts, pretzels, drinks, toys for the kids, and space for service animals.  Beyond all that they want airfares as cheap as possible.”

“Why don’t you charge more for your services rather than doing everything possible to fill every seat?” we asked.  They responded, “With the right pricing, we can fill every seat.  In fact, we continually tighten up spacing to allow more seats, all of which we fill with the right prices at the right time.”

“Most people choose airlines based solely on ticket price.  An empty seat generates no revenue.  So we constantly adjust prices to fill seats, while we also increase fees and degrade services.  We are continually surprised with what people will endure for a $199 seat, even though various fees can easily double this price.  It almost becomes a game to see how little value we can provide.”

“But you have turned airline travel into a very negative experience.”  The immediate answer was, “People will put up with high prices and horrible service because they have no choice.  They can complain all they want – we delete their complaints as fast as they submit them.  We don’t care in the least what they think and feel.”

“Won’t this backfire at some point?”  The quick reaction was, “Do the chickens protest the hen coops?   Do the cattle protest the feedlots?  No, they have no choice.  Passengers are just revenue sources and can be treated like chickens or cattle.  We don’t care if they are frustrated and angry.  We don’t care if they seek transportation services elsewhere.”

“What do you care about?”  After a perplexed look, one executive said, “Isn’t it obvious.  Profits, share prices, and executive compensation.  That’s the overarching purpose of an airline.  How could it be anything else?”

Latest Airline Tag Line

New York — In reaction to a flurry of consumer complaints about major airlines’ new “zero fare” model, one airline has unveiled a new marketing pitch, with the following tag line.

“We don’t need you — take the bus!”

Responding to pundits’ criticisms of this being ridiculously “over the top,” an airline spokesperson responded, “We have monopoly positions on many of our routes. We can charge anything we want. We can provide whatever level of service we want. Customers have NO leverage. They have no choice.”

When asked if their intent was to antagonize customers, the response was, “We want to weed out customers who complain. They are just irritants. We have instructed our customer service agents to hang up when customers complain and zero out their frequent flyer accounts.”

“Is that legal?” we asked and the answer was, “We are not concerned with that. Take us to court. Sue us. We can afford years of such suits. Consumers are effectively helpless. They always have been, but now this is an important element of our business strategy.”

“Won’t this eventually backfire?”

“Maybe, although this country has never been interested in investing in serious alternatives. Almost nobody has a functional train alternative. Buses are possible but painfully slow.”

“At some point, won’t the government intervene?”

“We only need 3-5 years. In that time, we will accumulate huge sums of money — we estimate $250 billion — and then we will withdraw from the market, sell the planes, and move on.”

“What will communities do that depend on air transportation?”

“We would be glad to sell them our airplanes, although they will probably need a bit of maintenance and update by then. We actually have planned to sell the planes to developing countries, but I suppose a local deal could be worked out, as long as we are indemnified for all risks.”

“So, you really do not care about your customers and the public in general?”

“Our only goal is to maximize shareholder value in any ways that are legally possible. If you were a major shareholder, you would certainly agree. Our one objective is to turn money into more money — the airline business is just the current means to that end.”

Major Airlines Announce Zero Fares

New York — Major US airlines announced today a new pricing model for air travel. Zero airfares. Free.

The airlines have decided to unbundle all aspects of air travel. Customers will only pay for the services they desire. If they avoid all services, they will fly for free.

The airline CEOs as a group issued a statement with this announcement heralding the coming of free air travel, emphasizing their long commitment to customer service and safety.

Here are some examples of service charges:

Luggage: $100 per piece; no carry-on luggage allowed as overhead luggage bins will be removed, which will allow much more rapid boarding and exiting of the aircraft.

Drinks: Range from $10 for a bottle of water, $20 for a soft drink, $30 for beer, $40 for wine, and $50 for liquor.

Snacks: $10 for each packet of pretzels, peanuts or cookies; snack boxes for $50. A single concierge using pre-stocked vending carts will vend all drinks and snacks.

Sales Period: From the time the boarding door is closed until the plane backs away from the gate, there will be a one-hour period during which items may be purchased from the concierge. There will be no in-flight sales. All flight times will be increased by one hour to accommodate this period and assure passengers on-time arrivals.

Bathrooms: $20 per use, $30 if the bathroom light is activated, no toilet paper or hand towels provided. Bathrooms will be cleaned as often as once per week.

Seats: No assigned seats, no seat numbers, business class eliminated allowing a major increase of seats on each plane. Larger planes will be configured to carry 500 passengers.

Safety: $50 for seat belts, $100 for flotation device under seat, flight attendants are eliminated, replaced by the single concierge noted above who has no safety responsibilities. A single pilot will fly each plane.

Insurance: $100 premium required per person, with the airlines being the beneficiary. Otherwise, passengers must sign “fly at your own risk” waiver of any possible airline responsibility.

Penalties: Passengers’ credit cards will be automatically charged the following penalties: $50 for snoring, $100 for crying baby or barking dog, $200 for each unruly child

Airport lounges are eliminated, as are concourse seating and food services as well as other retail. Passengers are loaded first come first serve via turnstiles similar to subways. No one is provided priority, not handicapped, elderly, or children. Gate agents are eliminated.

The airlines project that these new offerings will result in huge increases in revenues as well as substantial decreases of costs, particularly for airline personnel. With airline liability being eliminated, they expect dramatic decreases of insurance costs. Indeed, any major aircraft accident will result in a windfall due to the aforementioned insurance.

To compensate terminated airline employees, rather than severance pay, each terminated employee will receive 100,000 frequent flyer points in the new program described below.  These awards are valid for six months and can be used any weekday except for holiday weeks. Employees will, of course, be eligible for free travel as outlined above.

Each passenger will be required to provide credit card information prior to each flight. They will be automatically charged for each service and consumable, detected in part via an extensive onboard sensor network. This will enable customers to pay instantly any penalty or service purchase.  The airlines expressed their commitment to providing detailed electronic receipts within 30 days after each flight.

Finally, the airlines frequent flyer programs will be completely revamped. The concept of free tickets for points will be eliminated, reflecting the fact that tickets will now be free.  Further, upgrades will be unavailable with only a single class of service available. Points will now be usable for onboard entertainment.  Four classes of entertainment will be available — Silver, Gold, Platinum, and Diamond — and earned via cumulative onboard expenditures rather than miles flown.  The normal $100 entertainment fee will be discounted by 25%, 50%, 75%, and 100%, respectively, for these four classes of passengers.

The executives commented, “We realize that the lost of first class upgrades and possible free vacations reflects a major change. However, we are confident that the increased quality of our online entertainment will be an enormous hit with our customers.  Our Diamond Members, with 100% entertainment discounts, may even take free flights just for the opportunity to compete, for free, in our online games. We expect to be seen as a major entertainment venue.”

Industry pundits reacted to this announcement with skepticism.  One suggested that frequent flyers would game the system and judiciously avoid any fees.  Another suggested that people would form teams to take flights in mass to assure airlines lose money.  One airline spokesperson said, “Our abilities to instantaneously change fees and implement new fees will be akin to pari-mutuel   betting.  For each flight, we will know how much we need to charge passengers’ credit cards to be profitable.  We will adjust fees accordingly once the concierge period is over.”  When asked about the possibility of passengers paying far more than they expect, she responded, “Flying has always been risky.”

Five Million Jobs

A few years ago, I co-chaired the National Academies Healthy America Initiative.  The members of this committee came from both the Institute of Medicine and the National Academy of Engineering.  Our assignment was to wrestle with issues surrounding the effectiveness and costs of healthcare delivery.  However, we wanted to put this in a larger context.  We eventually agreed on an overarching goal of fostering a healthy, educated and productive population that is competitive in the global marketplace.  This essay suggests how to accomplish this goal.

There are roughly 10 million unemployed people in the U.S. right now, down from 15 million a few years ago.  The current unemployment rate is 6.7%.  If we could cut that in half, we would be very close to what is considered full employment in the U.S.  Five million jobs would achieve this goal and, as laid out below, accomplish several other important things in the process.

I propose that we create jobs in three areas.  First, we need to invest in improving and maintaining the nation’s crumbling infrastructures, especially in urban areas.  It is estimated that fixing infrastructures after they crumble, e.g., after the bridge collapses, costs five to ten times more than properly maintaining them.  In the process, we could also add smart sensors and other technologies to both target and decrease maintenance costs.

The U.S. Department of Transportation estimates that each billion dollars spent on infrastructure investments creates 30,000 jobs; 10,000 in construction, 5,000 in manufacturing, and 15,000 “other jobs” due to the other businesses benefitting from the new construction and manufacturing jobs.  (I will use this 2:1 ratio for the other investments as well.)  For reasons that will become clear, we need to create 1,560,000 jobs in this manner, which will cost $52B.  This will save enormous amounts for unplanned maintenance, but that cannot be elaborated here.

There are 117 million people in the U.S. with chronic diseases.  It has been repeatedly shown that regular attention from health coaches and care coordinators can help them to better manage their diseases.  The Agency for Healthcare Research and Quality, a unit of the U.S. Department of Health and Human Services, reports that such programs can lead to reduction of patient visits to specialists by 24%, emergency department visits by 13%, and hospitalizations by 39%.  These savings are far greater than the costs of such programs.

Assume that, on the average, each patient with one or more chronic diseases is provided one hour of attention per month by both a coach and a coordinator. Some, of course, would receive much more attention and others much less.  This would require 702,000 health coaches, 702,000 care coordinators, and total 1,404,000 jobs at a cost of $56.2B per year assuming each job averages $40,000 per year. Using the 2:1 ratio noted above, the total number of jobs created would be 2,808,000.

As indicated, this would save more than it costs due to reduced use of more expensive healthcare services.  Further, these patients would be healthier and more productive.  Thus, the return on this investment would be substantial.

Three million students drop out of high school per year; 45% in 9th grade; 34% in tenth; 23% in eleventh; 16% in twelfth. (The sum of these percentages is greater than 100 because each successive year includes a smaller base of students.)  If they all stayed in school until graduation, we would need an additional 158,000 teachers and 158,000 teaching assistants, totaling 316,000 jobs, at a cost of $14.2B per year assuming each two jobs, teacher plus assistant, average $90,000 per year. Again using the 2:1 ratio discussed earlier, this generates 632,000 jobs.

Note that this assumes each teacher plus assistant focuses on 16 high-risk students.  This 8:1 ratio will enable providing students the attention needed to help them feel more engaged.  It is likely that this will also require that the content of instruction be varied to better target these students’ aspirations.

80% of the people in U.S. jails and prisons are high school dropouts.  The annual costs of incarceration are $80-90 billion.  If we eliminate high school dropouts, we would only need to reduce incarceration costs by 16-18% to beak even on this investment.  It is easy to imagine doing better than that.

Thus, we create 5,000,000 jobs (1,560,000 + 2,808,000 + 632,000) jobs for annual investment of $122.4 billion ($52.0 + $56.2  + $14.2).   This amounts to 4.1% of our annual Federal tax revenues.  If we consider the costs savings of reduced unplanned maintenance, reduced use of expensive health services, and reduced costs of incarceration, these investments should yield a quite impressive return on investment.  They will also yield significant income tax and social security tax revenues.

Beyond the economics of these investments, we get a healthy, educated, and productive population that is competitive in the global marketplace, plus state-of-the-art, well-maintained infrastructures.

Patterns of Change

Invention or ideas lead to innovation and change, often championed by someone other than the originator – think of Carnegie, Morgan, Rockefeller and Vanderbilt.  The change agent builds an empire around the innovation, typically aspiring to monopolize the commercial value of the innovation.  The empire becomes exploitive of customers, employees, and the environment.  Eventually, the world pushes back.

Competitors may provide the counterbalance.  IBM dominated computers until Digital countered with minicomputers and then Apple surprised everyone with microcomputers, after which IBM rebounded for a while before ceding the market to Dell, HP, and Lenovo.  Most recently, microcomputers have given away to portable tablets and other devices.  Networked computer and communications technology has replaced the dominance of big hardware.

The automobile industry provides another compelling example.  Henry Ford transformed the industry with mass production.  Ford dominated until Alfred Sloan changed the game with new models each year and differentiated brands.  Customers wanted more than the lowest priced black vehicle.  By the 1950s and 60s, the Big Three dominated, banishing many smaller brands to oblivion.

This led to decades of poor quality vehicles, with brands becoming decreasingly distinguishable due to sharing of components and platforms to save production costs.  The Big Three seemed to think that consumers would buy whatever these companies decided consumers wanted.  They were right — briefly.  Globalization led to higher quality, reasonably priced vehicles, especially from Japan, resulting in the Toyota Camry and Honda Accord replacing the Ford Galaxie and Chevrolet Impala as the best selling cars in the United States.

Government can also be the counterbalance.  The Progressive Era followed the excess and oppression of the Gilded Age.  The Sherman Antitrust Act (1890), the Federal Reserve Bank (1913), the Securities and Exchange Commission (1934), and the National Labor Relations Board (1935), first championed by Theodore Roosevelt and later by Franklin Roosevelt, reigned in and later broke up the trust empires.  The Dodd–Frank Wall Street Reform and Consumer Protection Act (2010) is perhaps the most recent example of government countering excess.

Nevertheless, the exploitive change agents become enormously wealthy, often famous and are sought after for their opinions far afield from anything related to their expertise.  They, of course, eventually pass away, although their heirs and assets may remain prominent for a couple of generations.  These change agents were usually of great value to society, first for the creative destruction their original innovation fostered, and subsequently for the creative destruction their exploitations motivated.


Fully Understanding

I have been lately digesting an enormous amount of material on biological systems and urban systems.  For both systems, I am interested in their health.  The focus in biology has been on cancer and understanding the signaling mechanisms whose aberrations allow uncontrolled cell growth.  Within cities, I have been exploring urban resilience, including historical narratives in the US for the last four centuries.  Both of these endeavors were motivated by very different opportunities.

Nevertheless, serendipity has intervened as usual and I find myself contrasting the two domains.  The scale of both humans and cities are mind boggling – 50 trillion cells in a human body and 10-20 million people in a city.  Of course, the 50 trillion cells have much less discretion than the 10-20 million residents in a city.  Thus, the two systems may be more comparable in complexity than the difference in the two numbers might lead one to believe.

For example, getting all the cells in a human body to walk in one direction would be much easier than convincing all the inhabitants of a city to walk in the same direction.  The owner of the human body simply has to start walking and all his or her cells follow along.  There is no comparable entity in a city.  On the other hand, getting all the citizens in a city to vote would be much, much easier than getting all the cells in a body to express any intention except birth, growth, and death.

It seems that cells in a human body and citizens in an urban area may not be very good analogies of each other.  However, they both are really difficult to fully understand.  There are too many levels and far too many interactions to be able succinctly describe the essence of either system.  Of course, you could make the same argument about a rabbit or a tree.

This begs a definition of “fully understand.”  It would seem that the definition depends on why one is trying to understand something.  I cannot imagine that anyone really wants to understand everything about a human, a city, a rabbit, or a tree.  Are weight, volume, density, and molecular structure of interest?  How about the current charge of every electron in every atom of every molecule of every substance in a city?

Clearly the notion of understanding is very much intent determined, as are other constructs such as complexity, cognition, and emotion.  We have invented many constructs that are useful such as gravity, energy, and heat.  These are among our ways of labeling regularities in the universe as we experience them.  They help us to predict that things will fall, motion requires something to drive it, and days with higher temperature feel warmer.

But we do not – and cannot – fully understand these phenomena.  Yet, we can employ these constructs and various principles, e.g., conservation and continuity, to engineer useful processes and devices.  Our limited understanding has pragmatic value.  What do we lose by recognizing these limitations?

Much of what we characterize as rigorous research is laced with equations, theorems, and proofs.  However, we can only prove things within the confines of these artificial worlds that we have created.  We can only prove things in our model worlds.  We cannot prove theories in the physical world.  The best we can do is find evidence that supports theories as plausible, as well as be on the lookout for disconfirming evidence.

Optimal solutions in model worlds are, at best, pretty good solutions in the real world.  We have no way of knowing the best answer in the real world.  We make a wealth of assumptions to force reality into a set of equations.  These assumptions are almost never true, but they can be good enough to enable useful outcomes.  The primary value is in these outcomes rather than the equations.

Airlines and Quality of Service

The latest debate on air travel concerns whether a person should recline his or her seat if it inconveniences the long-legged person behind them.  Further, should the person behind be allowed to use the Knee Defender device that blocks a seat from reclining?  There have been thousands of impassioned opinions posted on the overall issue.

The most ingenious suggestion has been that the two passengers involved should stand up in the aisle and fight it out.  No weapons allowed.  Last person standing gets to decide what happens to the seat.  This will result in a lot of injuries, but air travel has its risks.  By the way, the airline would be indemnified from any lawsuits resulting.

Of course, the airline is the source of the problem.  They pack the seats so closely that people are in each other’s way.  They create a substantial amount of stress for an enormous number of people.  It is not just the spacing of the seats.  Everything the airlines do is focused on providing the minimally acceptable quality of service so that profits can be maximized.

I realize that profitable airline has often been an oxymoron.  This has been due to gross inefficiencies and incompetence, both legacies of having been regulated monopolies before 1978.  I know that was 36 years ago, but cultural norms and values only change very slowly – unless some external force compels change.  Here is an idea that might work.

Airlines should be forced to compensate passengers for poor performance.  Each passenger is paid one dollar per minute for delays in departure, taxi, landing, and gate arrival.  If each of these phases were delayed by 15 minutes, each passenger would receive 60 dollars.  For 200 passengers, this would amount to a $12,000 penalty.  Severe delays could easily cost an airline $100,000.

Some would argue that delays are not always the airlines’ fault.  That’s true, but the airlines should be very good at dealing with delays.  With my scheme, I bet they would get better and better.  They would also schedule flights to minimize delays. They would, of course, also price flights to hedge against potential penalties.  To create some balance in pricing, the penalty could be 1% of the ticket price per minute of delay.

This idea could completely change the outlook of passengers.  The pilot announces a one-hour air traffic control hold and the cabin explodes in applause.  Stuck on the tarmac with no arrival gate open?  More applause.  People would see their tickets as potential lottery winners.  They are betting that the airline will screw up, while the airline is betting they won’t.

What if an airline could not cope with this underlying uncertainty, could not perform, and failed as a business?  That would be creative destruction at work.  Poor performers would be weeded out, as they should be.  New airlines would emerge and absorb many of the employees whose jobs disappeared with the poorly performing airline.

How does this solve the reclining seat problem?  Much time is lost when loading and unloading the aircraft.  Two things would make it easier – more space per passenger in general and more control of luggage.  Checked luggage should be free and carry on luggage, other than an item that fits below the seat, should be something like $100 per roll-aboard.  But people do not like waiting at baggage claim.  They will if they are paid a dollar per minute of delay beyond 15 minutes after offloading of the aircraft.

Overall, we need an incentive scheme that highly motivates airlines to dramatically improve quality of service, while also providing passengers some respite when service degrades.

Plucking Geese

Over the past two years, I have become a frequent train traveler between New York and mostly Washington, but also Albany and Boston.  The Acela is more expensive than flying but much more convenient and usually on time.

The other Amtrak trains provide much poorer service. Delays are frequent; an hour or more is not unusual. Multiple gate changes can happen, resulting in huge swathes of people flooding from one gate to another and then another. Agents often seen uninformed and confused.

Why is there such disparate service when the same organization provides both services?  A strong possibility is that the Acela gets priority because it provides much better revenue and profits.  I have several times experienced the Northeast Regional being sidetracked to let the Acela pass.

Of course, I could always fly. The captains of private industry should know how to provide high quality service compared to the semi-public sector passenger train business. But, they do not!

In fact, this segment of the private sector could not be much worse. We should hear almost daily of airline CEO firings.  But, we do not. Their Boards of Directors seem content with their companies being hated. Clearly, the commercial aviation industry has completely lost its luster.

To be fair, however, first-rate airlines still exist, for example, Cathy Pacific and Singapore Airlines. There are also excellent automobile companies such as BMW, Honda, Mercedes, and Toyota.  The US still has leading high tech companies like Apple, Intel, and Texas Instruments, although global competitors are snapping at their heels.

How have US airlines and automotive companies become mediocre?  The primary answer is leadership. When these companies were still high performers, they persistently hired CEOs to be stewards of the status quo. They needed to “hit the numbers” in any way possible.

Consequently, truly strategic thinking about customers and innovation were limited to litanies of buzz words.  These companies increasingly antagonized and confused customers. No one any longer believes US airlines marketing slogans. As one airline executive told me, “We keep pulling feathers until just before the goose honks.”

We lost Mercury, Oldsmobile, Plymouth, and Pontiac as the Big Three cut costs and quality, rendering these brands effectively de-badged.  The wonder is that these companies’ leaders did not think customers would notice. They must have imagined that they would be just like the airlines’ geese.

Stewards of the status quo cannot imagine being anywhere except at the top of the heap. A key competency is ease of being deluded. If this is combined with a strong dose of arrogance, a top firm is well on its way to creative destruction, having cooked its own goose.

Complexity Overload

How many user names and passwords do you have? Do you need passwords with exactly six or eight or ten characters including as least one numeric character and one non-alphabetic or non-numeric character? How often are you required to change them for security reasons?   Do you have a list, tucked away physically or electronically that helps you manage this information?  In general, how do you keep track of all the essentials of connectivity?

Many of these user names and passwords enable access to websites for your bank accounts, investment accounts, airlines, various utilities, seemingly endless retailers, and countless news sites.  For the most part, transactions on these websites are easy and successful.  However, when something goes wrong, e.g., a credit card or an address is not acceptable, it can take enormous effort to straighten things out.

The problem, of course, is that there is no knowledgeable human to ask for help.  Some sites provide a phone number to call for help; some of the helpers are actually knowledgeable.  Many sites, however, provide limited or no access to help.  The objective of the enterprises associated with these sites is, I assume, to minimize labor costs.  Further, they expect to regularly lose irritated customers and see this as just part of business.

This ever-growing connectivity infrastructure provides us with a vast number of choices of ways to spend (or possibly invest) our money and consume seemingly endless goodies and entertainment.  Beyond these benefits, what are the costs of this wild west of opportunities?  Certainly there are occasional frustrations as noted above.  There is also sporadic electronic fraud that might affect one of your credit cards or retail accounts, e.g., the recent Target fiasco.

More pervasively, how do you feel about unknown entities that know every online transaction and cellular call you make?  How about their knowing every email you send, every movie you watch and every download you make?  How about their knowing your every keystroke?  Of course, we willingly give up all this information in exchange for the things we seek.  By searching, downloading, etc., we “opt in” to divulging the basic transactions of most of our lives.

If you reflect on all of the above, the complexity of everyday life has increased substantially.  The number of things you need to know and relationships you need to manage has burgeoned.  The probability, albeit extremely small, that all your assets could suddenly disappear is very real.  When you call about your suddenly zeroed accounts, you will hear, “Chose 7 if your account balances are now zero.”  Once you choose 7, you will hear, “Our customer support center for this service is open on Tuesdays between 7:00 and 8:00AM, IST (India Standard Time).”

How Great Companies Transform — Then Fizzle

From many years in Atlanta, I have known many UPS executives, including CEO Mike Eskew who led the transformation of UPS from a package delivery company to a global supply chain services company.  I use a case study of this transformation in my classes and workshops on enterprise transformation.  It is one of my favorite success stories.

Well, at least I thought it was until recent experiences trying to ship several boxes via  These recent negative experiences, detailed below, led me to the local UPS store a few times for explanations of various practices.  In the process, I discovered that the UPS franchised stores have a very arms-length relationship with the corporation that owns all the brown trucks.  Put simply, they use UPS as their shipper – as a vendor of services – but cannot help you with anything about UPS.  I might as well have asked my UPS-related questions at McDonalds or Baskin-Robbins.

I had hoped to ship several boxes by using to print labels, schedule a pickup, and pay in advance.  I created an account on, but found that this was not really a UPS account; it was only access to the website.  So, I needed to set up another personal account, but it would not allow this because my address is on a university campus.  When I tried a different address, it would not accept it because it was not the address associated with my credit card.

So, I called customer service.  The representative told me that I could schedule a pickup and then do all the paperwork with the driver, including printing out the shipping labels.  She could not help with the address and credit card problem at all.  When the driver arrived the next day, he would not take the boxes because I had not completed the online transaction and printed the labels.  In fact, he never prints labels.

I eventually got the boxes shipped three days later by manually lugging the five large boxes to the UPS store.  This experience caused me to explore other people’s experiences with UPS.  I found an enormous wealth of complaints, far too many to detail here.  Interestingly, one of the most common complaints is that there is no mechanism to complain, other than via your state’s consumer protection agency.  UPS clearly does not want to know about unhappy customers.  Thus, they can avoid learning and adapting to customers’ desires and expectations.

This is not the UPS that I knew ten years ago.  Of course, their Atlanta neighbor, Delta Air Lines, is also not the company I used to know, in their case twenty years ago.  In both cases, excellent service has been severely compromised in the pursuit of efficiency.  The fact that many customers now despise them is not of concern.  You have to conform to their rules and accept whatever level of service they provide, or you have to choose among all the other companies with the same philosophies of service.

Are there implications of such changes, or is the demise of service quality simply a fact of life?  My limited data on UPS and extensive data on Delta suggest that customers are very much looking for alternatives.  I have heard many premium Delta customers say, “I used to be a huge Delta fan; now I wish they would go bankrupt and out of business.  I really hate Delta Air Lines.”  Similarly, my limited UPS data says the love is gone.  Many customers are looking forward to the creative destruction of these companies by innovative new concepts and technologies.

What Might Happen

Various pundits in sundry domains attempt to predict what will happen.   In domains such as climate change, urban systems, and national politics, which are laced with human and social phenomena, such predictions are folly.  There are far too many possible ways in which individuals and social groups can behave in response to evolving events, whether they be physical (e.g., environmental threats), economic (e.g., new financial bubbles), or social (e.g., changed attitudes towards social issues).

Pundits may try to hedge their predictions by making them contingent on particular assumptions such as “if humans continue to consume resources as they currently do,” or “if economic growth follows the historical average.”  These types of assumptions certainly narrow the range of uncertainties if the assumptions are warranted.  However, we are left to wonder about the probabilities of the assumptions being true over the time periods of interest.

I have lately become attracted to a new line of reasoning that focuses on what might happen.  This perspective allows us to consider a variety of things that might happen and the conditions under which they might happen.  Some of the things that might happen will be appealing; others will not be at all appealing.  Such differentiation by level of appeal can prompt an exploration of the differing conditions leading to likely outcomes.  This enables a discussion of how we can foster the conditions that seemingly lead to more appealing outcomes.

This approach suggests that problem solving and planning should not focus on predicting a particular future.  It should instead be a discussion and exploration of alternative futures, how these futures might emerge, and how today’s choices might influence the possibilities of these futures.  If we find that X almost always leads to appealing futures, and Y almost always results in unappealing futures, we should try to facilitate X and avoid Y.

This approach has enormous implications for planning and control of enterprises, organizations, and even careers.  Instead of having specific targets, which drive actions and determine controls, attention should be focused on a portfolio of possible scenarios, leading indicators of emergence, and lagging indicators of performance.  Instead of focusing on how well targets are being hit, e.g., 10% revenue increase and 20% profit increase, the key questions should be, “What is happening?  What might happen next?”

Consequently, strategies and plans are needed for each current and nascent scenario.  This requires careful consideration of situation assessment, strategic planning, and the efficiency and effectiveness of execution.  Traditional metrics, such as revenues and profits are the consequences of accurate assessments, effective strategies and plans, and efficient execution of plans.  However, one should first make sure that the right things are being pursued.

How can we project what might happen?  There are data sets and analytic tools that can help, but they seldom enable clairvoyance.  I have found that the keys are understanding, sustaining, and enhancing the organization’s relationship network with key current stakeholders and prospective stakeholders, including competitors, customers, suppliers, and employees, as well as thought leaders in the realms of economics, politics, and technology.  Their concerns and insights, as well as their reactions to your ideas, can be invaluable.

Encounters with stakeholders can happen in a variety of ways – meetings, telephone calls, emails, etc.  The key is to capture knowledge from each encounter, planned or otherwise.  Many questions are of interest.  What would customers like next?  What are competitors thinking of doing next?  What technologies are maturing to the point of realistic deployment?  What effects are healthcare reforms likely to have?  What aspects of climate change are undoubtedly real and likely to have impacts sooner rather than later?

Answers to these questions should be captured, compared, and contrasted.  Opportunities and challenges should be gleaned from this information and lead to further questions for subsequent encounters.  Insights should be curated with links to information sources.  This accumulating wealth of information will, over time, enable understanding what might happen.

Converging Experiences

Recently, I went to Kara Schlichting’s lecture, “From Dumps to Glory: City Planning, Coastal Reclamation, and the Rebirth of Flushing Meadow for the 1939-1940 New York World’s Fair.”  The next morning, I read Russ Buettner’s article in the New York Times, “They Kept a Lower East Side Lot Vacant for Decades.”  That afternoon, I went to the Lower East Side Tenement Museum and, in particular, watched their 20-30 minute movie on the evolution of the Lower East Side from 1840 on.

So, in 24 hours, I experienced the complexity of how cities evolve – three times.  It seems like a chaotic mess of conflicting interests, struggles for power, and strong personalities.  In the midst of all this, there are thousands or millions of people and families trying to make ends meet, get their children educated, and occasionally have some fun.  A few people make a lot of money and everybody tries to do a bit better tomorrow.

It strikes me that cities do not get engineered.  Road networks, sewer systems, and subways are engineered.  Infrastructure and buildings are engineered.  However, the cultural fabric of cities is not engineered.  It emerges from the hustle and bustle of people seeking to make money, get a job, earn a promotion, educate their kids, play a game of cards, and enjoy a ball game.  We cannot predict where all that will lead, what serendipity will prompt.

How can we research this?  I think we need to focus on insights rather than predictions.  It is reasonable to assume that the actors are rational, although they will not necessarily conform to classical economics.  I think we can assume that they will take advantage of and adapt to the environment.  However, all the rationality and adaptability of enormous numbers of independent actors will lead to an abundance of possible paths and outcomes.  Our understanding will be limited to how particular paths and outcomes might emerge.

The best approach to gaining this understanding will, in my opinion, result from studies of virtual urban worlds.  Simulated immersive representations of Hoboken, NJ and Red Hook, NY, for example, will enable exploring how “humans in the loop” as well as synthetic avatars respond to emergency warnings, actual weather, power outages, terrorist events, and perhaps even economic opportunities due to redevelopment.  We will learn about how people “game” the system and, in the process, learn what innovations to encourage and what behaviors to inhibit.

We cannot approach cities in the same ways we address airplanes, factories, and power plants.  Cities are laced with too many complex behavioral and social phenomena.  Yet we can systematically explore the ways in which cities might respond to opportunities, incentives, and inhibitions, and identify the conditions more likely to lead to one response rather than another.  Then we can think about how we might engender the conditions leading to more appealing responses.  Our methodology should focus on how to get a city to design itself in ways that improve the quality of life for everyone.

Transformation as a Wicked Problem

In 1973, Horst Rittel and Melvin Webber published “Dilemmas in a General Theory of Planning” in the journal Policy Science (volume 4, pp. 155-169).  In this article, they characterized “wicked problems” as follows:

  • —  There is no definitive formulation of a wicked problem
  • —  Wicked problems have no stopping rule – there is always a better solution
  • —  Solutions to wicked problems are not true or false, but good or bad
  • —  There is no immediate nor ultimate test of a solution to a wicked problem
  • —  Wicked problem are not amenable to trial and error solutions
  • —  There is no innumerable (or an exhaustively describable) set of potential solutions and permissible operations
  • —  Every wicked problem is essentially unique
  • —  Every wicked problem can be considered a symptom of another problem
  • —  Discrepancies in representations can be explained in numerous ways – the choice of explanation determines the nature of problem’s resolution
  • —  Problem solvers are liable for the consequences of the actions their solutions generate.

It can be useful to look at enterprise transformation as a wicked problem.   Rather than exhaustively discussing every characteristic in the above list, let’s just focus on three – no stopping rule, no trial and error, and liability for consequences.

Transformation is never done.  There may be ebbs and flows of change, but the need for change is persistent.  The nature and level of value desired by markets and other constituencies continually evolve, sometimes very slowly, but other times quite quickly as, for example, technology breakthroughs such as electric lighting are suddenly available.  The key insight here is that you need to get good at changing rather than thinking that change is something you finish.

Transformation is not amenable to nibbling.  You cannot experiment with a wide range of ways of changing and then adopt the winner.  Empirical confirmation that a new value proposition works is certainly valuable.  However, such evidence is only meaningful and useful if you have clear intentions and plans for how to accomplish changes.  Otherwise, all you have is ideas.

Transformation is real.  Good outcomes are sought but bad outcomes are possible, with the enterprise leadership liable for the outcomes.  You can lower the risk by adopting changes that others have perfected, for example, back office and supply chain efficiencies.  But, this just keeps you in the game and will not win the market returns of being the innovator rather than the follower.

Another very important consideration is not in the above list.  You need to balance creativity and continuity.  Creative new value propositions drive market innovations – and creative destruction.  New approaches to value are likely to need new competencies and capacities, while obsoleting older ones.  Organizations usually have limited capacities to absorb such changes.  Yesterdays’ machinists may not be easily transformed into tomorrows’ computer programmers.  People highly skilled at a particular set of tasks cannot quickly become highly skilled at a very different set of tasks.

Thus, a central driver of transformation is that once you become really good at something, there is a significant risk that what you are really good at will eventually no longer be valued.  What you were really good at it – perhaps the best – was likely of great value to the economy and society.  But new innovations will eventually creatively destroy that value proposition.

How long should you cling to hard-won competencies and capacities?  When is it time to shift attention and resources to new value propositions?  There is no “starting rule.”  We can add this to the list of characteristics of wicked problems.  It is not at all clear how you decide that now the wicked problem really has to be addressed.  You can always wait until tomorrow.  Eventually time and resources are no longer available and change is impossible.   This dilemma is certainly wicked.

Levels of Change

Fundamental change is pervasive across every level of life.  In this post, I compare four levels and time scales of change including evolution (millions of years), history (thousands of years), industry (centuries), and technology (decades).  This comparison leads to a few overall observations about transformation and a few insights into how people think about fundamental change.

Central concepts in evolution are species, populations, and extinctions.  Example species, in order of appearance, include plants, insects, reptiles, mammals, and birds. Relatively recent are primates, which include Homo sapiens (humans), all within the mammal species.  The populations of species tend to grow unless predators weed them out.  More significant are mass extinctions, which are defined by more than 50% of all species being eliminated.

There have been five mass extinctions, the last one of which eliminated the dinosaurs.  Some scientists argue that we are on the verge of a sixth mass extinction.  Fortunately, the time scale on which mass extinctions happen is such that we need not worry about this right now.  Nevertheless, this possibility doubtlessly represents transformative fundamental change.

Central concepts in history include civilizations, empires, revolutions and conquests.  Notable civilizations and empires include Egypt, Mesopotamia, China, Maya, Greece, and Rome.  All of these empires ended, often due to internal strife (revolutions) or external sources (conquests).  In some cases civilization ended.  It appears that the typical life of a civilization is one thousand years or so.  This does not mean that all the people disappear, but standards of living usually plummet.

Core ideas for industry include needs, markets, and creative destruction.  Markets emerge to meet human needs for food, housing, energy, transportation, finance, etc.  Industries change due to increased efficiencies (e.g., agriculture), technology replacement (e.g., horse-drawn streetcars), and consolidation (e.g., airplane manufacturing).  The winners of the competition perfect their offerings, which greatly benefits customers, until their offerings (e.g., buggy whips) are no longer needed.  Then industries face creative destruction, in part due to new technologies.

Key notions in technology are invention, innovation, and obsolescence.  Over millennia, humankind has invented tools, wheels, propellers, crossbows, and gunpowder; waterwheels, steam engines, and gears; aqueducts, drainage, sails, and rudders; steamboats, railroads, automobiles, and airplanes; and electricity, telephones, computers, and Internet.  These inventions, often rather slowly, became market innovations as technologies and infrastructures matured.  As they were perfected, these offerings tended to become commodities or, in many cases, obsolete.  In the process, most companies and, sometimes, whole industries were creatively destroyed by new market innovations and value propositions.

Reflection on these four levels of transformation prompts a notional life cycle of change operating on all four levels:

  1. New epochs eventually lead to consolidation and refinement or perfection
  2. Assumptions on which perfection is based are eventually no longer tenable
  3. New entities emerge to exploit new assumptions, but are bit players at first
  4. Existing entities attempt to adapt, even transform, but almost always fail
  5. New epochs emerge — go to step 1

If transformation inevitably fails, at least eventually, why try?  First of all, you cannot know a new epoch is emerging until after it happens.  There are economic and social benefits to sustaining the current epoch.  For example, capital assets cannot be quickly redeployed, unless via liquidation.  Further, the stewards of the current epoch will inevitably attempt to survive.  Overall, it seems reasonable to observe that, despite their inevitability, extinctions, revolutions, conquests, destruction and obsolescence are only addressed when their time has come.  We strive to hold them off even though we know they are inevitable because such is the only rational and productive strategy.

What to Keep

Enterprise transformation involves redesigning or creating new work processes that enable remediating anticipated or experienced value deficiencies.  This implies that some aspects of the enterprise have to be discarded.  Why not discard everything?  That is certainly as option, but it is called liquidation rather than transformation.

A central question is what do you keep and how does it need to change?  To avoid answering with a stream of abstractions, let’s consider a specific example.  Higher education has replaced healthcare as the poster child for runaway costs.  It is useful to look at this from the perspective of a single enterprise in higher education attempting to transform itself.

What should they keep?  Typical mission statements involve some combination of education, research, and service.  Students, their families, and employers value education as a means to a good standard of living, employees who excel at their jobs and, in general, productive, informed, and involved citizens.  Every educational institution wants to meet this need.  The question is how best to do this.  Is it classrooms and lectures, or online courses, or something different?

This is the point where strategic thinking often falters.  Most universities have made enormous investments in faculties and facilities for delivering education in traditional manners.  There is an increasing trend of “outsourcing” delivery to adjunct faculty rather than more-expensive tenure track faculty.  This saves money but does not fundamentally change the process.

The value of research is much more ambiguous than education.  At one level, research helps the faculty to be on the cutting edge, thereby enhancing the education mission.  At the other extreme, the research enterprise becomes an end in itself.  The goal is typically ever-increasing sponsored research budgets, which results in many faculty members teaching little or perhaps not at all.

If successful, the research enterprise can help the university’s ranking by increasing funding and PhD graduates per faculty member and, over time, the number of faculty members elected to prestigious academies.  It can reasonably be argued that increasing rankings will lead to increasing numbers of applicants for admissions, which will enable increasing entrance requirements and lead to better quality students.

This all seems to make sense, except for the costs of doing it.  The costs of creating winning proposals are enormous.  This is due to the 5-10% success rate at the prestigious National Science Foundation (NSF) and National Institutes of Health (NIH).  Faculty members are provided release (non-teaching) time to devote to proposal preparation and submission.  Every tenth time or so, they succeed.

Once the grant or contract is won, the university is reimbursed for its direct costs plus indirect costs, typically estimated to be 50-70% of direct costs.  These “overhead” monies pay for administrative costs (provosts, deans, libraries, etc.) that are spread uniformly across all sponsored projects.  Administrators argue that the overhead funds received do not really cover all the relevant costs.  Sponsors argue that many of the costs in the overhead pool are not relevant to conducting research.  The final overhead rate is a matter of negotiation.

The research enterprise has to be subsidized because it loses money on both the front end and back end of the process.  This is inherent to the market being addressed – NSF and NIH.  Other research sponsors such as the Department of Defense (DOD) and the National Aeronautics and Space Administration (NASA) have different award decision processes and typically higher success rates.

Industrial funding (as contracts, grants, or gifts) is such that proposals are discussed and refined along the way.  One quickly learns that the idea is a loser or is able to refine the idea until funding is assured.  The upfront costs per success are much lower.  The downstream overhead costs are still an issue, but are open to negotiation.  If a university were to strip out all the costs of working with the government, industrial overhead costs would be lower. In fact, they are typically higher because universities can get away with this.

One strategy for fixing the economics of research would be to minimize or avoid NSF and NIH proposals.  This would run into another very large obstacle.  Funding from NSF and NIH is viewed as more valuable because of their peer review process.  To get funded, one needs more than a good idea.  One has to convince anonymous peers in one’s discipline that the proposed research fits into the discipline and will advance the discipline.

Thus, NSF or NIH funding vets the faculty member as fitting in, as being valued by peers.  This lessens the burden on administrators and faculty committees in evaluating faculty members.  In effect, they have outsourced evaluation. This places great emphasis on the source of funding and peer approval rather than the outcomes of the research such as articles published, patent filings, and artistic exhibitions.

If evaluation was limited to outcomes, then the problems of money-losing research operations could be overcome in a variety of ways.  High probability funding sources would be much more important than low probability, and typically very slow, funding sources.  The marketplace of ideas, rather than solicitation announcements and peer review panels, would become the focus.  Researchers would spend much more time on producing outcomes.

The third element of a university’s mission is service, sometimes called outreach.  Support of professional societies and involvement on advisory committees are good examples.  Unfortunately, academia is highly subject to mission creep.  They find more and more services they could provide and invest resources to provide them.  The result is that the numbers of academic staff has long been growing at twice the rate of the numbers of academic faculty.  All the new vice presidents need staff assistants and growth continues.

Among the many areas that could be discussed, entertainment deserves the closest attention.  The biggest elements of many universities’ entertainment enterprise are men’s football and basketball.   They earn billions of dollars of revenue, pay millions to coaches and athletic directors, and graduate few of their “student athletes.”  These athletes rightfully should be employees of the entertainment business.

It is not a question of the merits of this entertainment business in itself.  It is a question of whether academic institutions should be in this business and subsidizing it, as the vast majority has to do.  Some argue that alumni like this entertainment and this generates increased donations to the university.  My experience is that a significant portion of these donations goes to the sports side of the university rather than academics.

One solution would be to set up the entertainment business independent of the university.  Alternatively, it could be outsourced like food services are done at most universities, and the bookstores at many universities.  The football and basketball entertainment business could be outsourced to the National Football League (NFL) and National Basketball Association (NBA), respectively.  The NFL and NBA could then pay athletes minor league salaries as done in baseball.

Considering what to keep when transforming an academic enterprise, the following conclusions seem warranted:

  • Keep the education line of business, but consider a much broader range of approaches to delivery; be cautious when investing in physical classrooms
  • Keep the research line of business, but get the economics right to generate both knowledge and money; be skeptical of low probability opportunities
  • Keep the service line of business that relates directly to the education and research businesses; spinoff or outsource all the rest

Success in adopting this strategy will depend on several other things:

  • Move to activity based cost accounting and minimize non-attributable overhead costs; aspire to achieve a near-zero overhead rate
  • Price services based on costs directly attributable to these services; include profit margins that are competitive in relevant markets
  • Retain money-losing services only to the extent that they are vital to one of more lines of business; if there are many of these, you have not faced reality
  • Outsource everything that someone else can perform better and/or cheaper; become expert at selecting and managing vendors and partners

There is one final, critical need.  Define, measure, and reward performance in all aspects of the business.  This can be problematic in academia.  Universities have great difficulty penalizing poor performance and even greater difficulty rewarding good performance.  Thus, poor performers hang around – for years, even careers – and good performers get frustrated and leave.  Fix this as soon as possible.

Execute, Execute, Execute

The lack of committed visionary leadership will doom any transformation aspirations.  However, will the presence of such leadership assure success?  The simple answer is, “No!”

Great aspirations and ideas need compelling plans to succeed.  Further, these plans have to be successfully executed to realize these aspirations.  Quite often, plan fall prey to inabilities to execute.  Consider the following examples:

  • Marketing and sales functions fail to leverage natural competitive advantages, focused instead on business as usual and trying to promote fading ideas and dying brands.
  • Sales and proposal functions fail to pay attention to idiosyncrasies of new market opportunities, resulting in non-compliant proposals and lost business opportunities.
  • Financial management functions fail to pay attention to the new cost structures of emerging market opportunities, for example “peanut buttering” overhead costs across opportunities where these costs are unwarranted.
  • IT and web support functions fail to maintain and update capabilities, resulting on stodgy and out of date capabilities, or perhaps capabilities that simply do not function at all.

What is going on in such organizations?  There are several possibilities.  Perhaps strategists and planners have not translated their high-level plans to specific action plans for these functions.  Thus, these functions are unaware of needs for any different behaviors.

Another possibility is the “as is” business simply consumes all capabilities. There is little, if anything, left to devote to the “to be” business.  Keeping the status quo functioning is all consuming, even when the status quo is on a downward spiral.  There is no energy left to nurture change.

Yet another explanation is that the staff members in these functions simply “do what they do.”  Regardless of any newly articulated strategies and plans, people put in their time until the end of the day and then go home.  The next day, they do the same things again.  No one holds them accountable for anything, other than showing up.

At worst, people resent being held accountable.  They are used to placidly positive annual reviews and modest raises, both of which prompt considerable grumbling.  They are used to being liked and fitting in.  They are used to much of the workday being devoted to discussions of children, schools, and sports.

To assure execution of plans from top to bottom of the organization, senior leadership has to convince everyone that change is for real.  A sense of urgency has to be created.  This may require large-scale replacement of the “no accounts” with new people eager to pursue change.  Key functions might be outsourced to high performing providers.  Poorly performing divisions might be sold or liquidated.  The key is to get everybody paying attention to execution, and either executing or leaving.

Three Strikes and You Are Out

The poor performance of the US healthcare system can primarily be attributed to three things.  First, the “fee for service” payment model incentivizes providers to provide as many services as possible to maximize reimbursements from insurers, either private or public.  Second, the lack of integration of archival and operational information systems undermines the delivery of effective and inefficient services.

I as well as many others have argued that a systems approach to redesigning the system of healthcare delivery would address these issues and transform the system to provide high quality, affordable healthcare for everyone.  There appears to be widespread agreement in this.  Why then is this so slow to happen?  This leads to the third source of poor performance – the orientation of senior leadership of many healthcare providers.

Three examples illustrate this well.  In talking with the CEO and CQO (chief quality officer) of a major provider in the southeastern US, with whom we had been working regularly, they commented that the best characterization of their delivery system was “chaos.”  We proposed an approach to mapping and improving their delivery processes.  The cost would be modest as the proposed team was composed of engineering faculty and graduate students.

The CEO balked at the price.  I argued that this would quickly save him much more than the cost of the effort.  He agreed with this assertion but, as a former CFO, indicated that he was not willing to spend a single dollar on process improvement.  He suggested that we try to find a grant that would pay for this effort.  He clearly saw his role as steward of the status quo.

We worked to create an alliance with a major provider in the northeastern US.  Meetings and briefings with the CMO (chief medical officer) and his leadership team led to a planned set of initiatives.  A process mapping and improvement initiative was agreed upon at modest cost; much less than the instance cited above as we had refined our methods and tools for such an initiative.

Meetings with the department heads associated with this effort led to great enthusiasm, but no progress.  Everyone was far too busy to provide access to the information needed to proceed.  I suggested that they were not really committed to the project.  They apologized profusely and reaffirmed their commitment — but still did not supply the promised information.  These leaders were also far too busy stewarding the status quo.

We reached agreement with a major, internationally renown, provider to study human-centered, computer-based systems to support patients, their families, and clinicians in delivery of out-patient services.  Funds for this research effort would be provided by an external source.  Our initial proposal, with the provider, was not submitted because they could not achieve agreement across various stakeholders by the deadline.  We decided to delay submission until the then next round, six months later.

The detailed proposal was developed and ready for submission.  A final briefing was scheduled to review the completed proposal three days before the due date.  At that point, one of the affected groups complained that they had not been given adequate time to digest and react to the proposal, despite the fact that time with them had been repeatedly requested during proposal development.  They were concerned that the proposed effort was much more ambitious than their ongoing effort in this area.

They were also concerned that they were losing control of efforts to improve out-patient services.  It was observed that their progress was both modest and slow, due to the demands of their status quo responsibilities.  Further, the proposed effort would bring in outside resources and significant external recognition. Nevertheless, the provider leadership involved did not want to antagonize this group.  They withdrew from the partnership and the completed proposal was not submitted three days later as planned.

What can be learned from these three experiences?  First, the status quo is all consuming.  The current way of doing things demands almost all attention and resources.  One executive, in a different organization, said, “Bill, you don’t understand.  I am far too busy underperforming to have the time to get good at this.”  Of course, this is not just the case for healthcare.  It is also true for education and government, for example.

Some organizations, however, escape this conundrum.  The key ingredient is senior leadership who have a vision of the “to be” organization as well as a clear sense of the path from the “as is” to the “to be.”  They communicate this vision and stay closely involved with its pursuit.  They are not afraid to ruffle feathers in the process.  Such leaders would never be characterized as stewards of the status quo.  As a result, their organizations tend to be innovators rather than reluctant followers.  Much more of this is needed in healthcare.

So, three strikes and we are out, at least for this inning.  If we look at the differences between our successes and failures in pursing change via systems approaches, what have we learned that will help us with our next times at bat?  First and foremost, regardless of the technical merits of an idea and the expertise and skills of the team, the full commitment of senior leadership is crucial.  We know from extensive studies of a wide range of industries that middle management will not spontaneously transform an enterprise.  Second, senior leadership has to explicitly commit to helping overcome pushback from the forces of the status quo.  Initially at least, visionary leadership is not the frosting on the cake – it is the cake!

Back Online

This blog has been on hold for 18 months as I have transitioned from Atlanta to Hoboken, the sixth borough of New York City.  I retired from Georgia Institute of Technology and am now on the faculty of Stevens Institute of Technology.  I am still immersed in enterprise transformation, focused on healthcare delivery, higher education and, in my new context, urban resilience.

The change of context has been amazing, the primary reason this blog has been on hold.  Greater New York City is a very large highly diversified economy with over 20 million people.  Atlanta is large as well (6 million people), but the economy revolves around being the Southeast’s supply chain and logistics hub, as well as real estate development.  New York City rivals Silicon Valley in terms of technology-oriented venture capital, while Atlanta is well outside the top ten cities for technology investments.

So, it has taken me awhile to get my feet fully on the ground in New York City and its surrounds.  Opportunities abound and corporate headquarters dot the landscape.  Mastering the train, subway, and bus system has been an important task.  One benefit has been a dramatic reduction in plane trips.  The pleasure of hopping on the train to Washington at the last minute was, at first at least, immeasurable.  Changing reservations just minutes before leaving, with no penalties, continues to be a pleasure.

Another difference has been the food.  As a vegetarian, the more ethnic restaurants the better, particularly Italian as well as Asian.  Pizza in New York is a different experience than Atlanta.  Bakeries are much more pervasive.  Pubs of every make and model are on most corners, although their appetites for college football are quite limited.  However, with two professional baseball, basketball and football teams, as well as three hockey teams and a soccer team, pubs are crowded with fans during game times.

I am a bit of a history buff and I have broadened my view of the Northeast beyond Boston (my roots) to include greater New York City.  The technological innovations here from the 18th, 19th and 20th centuries are most impressive, making Silicon Valley a “Johnny come lately” in the late 1930s and the Route 128 “Massachusetts Miracle” a very recent arrival in the early 1950s.  Stanford and MIT enjoy the applause for their association with these upstarts.  New York is much less interested in applause.   Power and money seem to be the dominant goals.

My plan is to continue Rouse on Transformation in the spirit with which it started in 2009.  The geographical footprint will be larger and the range of examples broader, e.g., including urban resilience.  However, the goal is the same – understanding fundamental change of complex organizational systems.

The Transformation Debate

Who is more American?  Is it the Kenyan or the Mormon?  Who created or destroyed more jobs?  Is it the community organizer or the private equity economizer? The candidates are focused on attacking personalities and circumstances rather than reality.

But, what really happened to blue collar jobs?  This answer is straightforward. Our blue-collar laborers became too expensive due to union agreements and healthcare costs while other countries’ laborers were less expensive and better educated.  They are more likely to have the knowledge and skills needed for hi-tech manufacturing.

It is not really just about wages, however. Germany has higher wages than the U.S.  Germany also has much higher social costs than the U.S.  Yet, their manufacturing sector is thriving — the envy of Europe.  This is due to the fact that they systematically and substantially invest in technical training for those not headed to the university.

Why would Germany make such investments?  My conclusion is that they see a healthy, educated and productive workforce as a “public good.” In other words, all Germans are better off if every German is healthy, educated and productive. This was once part of the belief system of America, but such beliefs have faded. Healthcare and education are now “private goods.”

In other words, if one wants healthcare and education, one should pay for it just like you pay for cell phones, televisions, and automobiles. No one else benefits from your being healthy and educated. If you are unhealthy and uneducated, that is your problem.  It is your problem as well if you cannot find a job and cannot afford to take care of your children.

But is that really the case?  Are unhealthy, uneducated and unemployed people of no cost to society?  Use of hospital emergency rooms for non-urgent care by uninsured people costs the average American well over $1,000 per year.  Costs of unemployment benefits add over $1,000 to the average American tax bill. Add the two items together and we are coming close to 10% of the average American’s after-tax income.

Bottom line — we are spending more per capita on compensating for uneducated, unhealthy and unemployed people than we are saving for our future.  It is very expensive — for all of us — to have large numbers of unhealthy, uneducated and unemployed people wandering around, trying to find something to eat. We need to reinvent the concept of public goods and invest prudently in health and education in ways that will yield enormous returns for all of us.

It’s Really Tough

You are leading a very successful enterprise in airplanes, automobiles, mobile devices, healthcare — or perhaps higher education. The business model that got you to where you are — successful, profitable — seems to be faltering.  The growth of revenue is diminishing while costs are escalating.  The costs of infrastructure — physical, financial and human — are inexorably growing. Customers seem to be sticking with you, but they are not happy. Cynical jokes are pervasive.

What should you do?  How about sticking to the knitting?  Just keep doing what you have always done, perhaps a little bit better and a lot cheaper. If you need to sell airline seats as cheaply as possible, charge people for everything else — baggage, food, entertainment, bathrooms, and seat belts. If revenue comes from students in seats, put hundreds of students in each classroom.  Let the students sit in the aisles unless the fire marshal protests.

Perhaps you should lead the enterprise towards a new business model. Rethink the whole transportation or education experience. But, this requires a lot of courage because most if not all of the key stakeholders are clinging to the status quo.  Embracing change means creating enemies — people whose rice bowls are threatened by change.  Leading change requires strong self-confidence and abilities to absorb enormous criticism. You will be challenging many people’s comfort zones.

What about your comfort zone?  Do you need everyone to be happy?  Do you need everyone to like you?  What if your vision of an alternative future is wrong?  What if the faltering status quo is as good as it gets?  The key question is whether you are willing and able to lead in times of change.  It’s really tough because you cannot be sure of what will happen and whether you will succeed. However, you can be sure that your willingness and abilities are exactly why they gave you the job in the first place.

One Journey to Engineering Systems

The organizers of the 3rd International Symposium on Engineering Systems asked me to provide a brief story of my journey to engineering systems — how I came to be at this Symposium on this June evening in Delft.   The idea is to stimulate your thinking and perhaps motivate you to share your stories during dinner this evening.

I have always been a planner, so the story of how I came to be at this meeting begins in 1961. I was 14 years old when I bought my first car.  My intention was to teach myself to drive, but it turned out that I was also to teach myself some engineering.  The object in Picture 1 prompted the need for this.

1952 Plymouth Carburetor

Picture 1. Carburetor

This picture shows the carburetor of the car I bought — the 1952 Plymouth in Picture 2.  This is the same model and colors of the car I bought.  However, for $35 the car did not exactly look like this one.  In fact, as I repaired body dents and rust, red primer slowly replaced much of the blue and white.

Being too young to get a driver’s permit, I decided to learn by driving through the fields in this small, island town of Portsmouth, Rhode Island — the smallest state in the United States.  Picture 3 shows my training track, which was captured during an aerial survey of the town prior to building a new road.  The track started out very bumpy but over time the Plymouth smoothed it out.

1952 Plymouth Cranbrook No. 1

Picture 2. 1952 Plymouth

Driving endlessly on this track, I became very good at left-hand turns, and right-hand turns, in second gear but could never get going fast enough to get into third gear.  I also could make it to the center of town, with its 3-4 stores, without going on a public road. This meant driving through fields normally populated by cows or potatoes. Again, it was very bumpy.  The carburetor did not like this. It failed often.  Pieces bent or disappeared.

Driver Training 1962

Picture 3. Training Track

I got to know the carburetor very well.  I constantly had to figure out how to get it functioning again.  I did not have the money to buy replacement parts.  I resolved this quandary with my Erector Set, shown in Picture 4. I used the linkages and sliders from this set to restore the carburetor’s function, although not quite in the way originally intended. The result was a Rube Goldberg version of a carburetor.

Erector Set

Picture 4. Erector Set

The Erector Set could not compensate for my lack of knowledge that cars had oil filters. Eventually the Plymouth’s engine succumbed to a lack of oil — plenty in the reservoir but little making it to the engine.  Next came a 1949 Chevrolet, again for $35.  This car’s specialty was leaks. During heavy rains, the floor wells in the front seat would fill up.  I learned that water would always have its way.

Each subsequent car provided its own lessons.  There were many lessons. We managed to successfully implant a Ford V-8 in a Jeep.  However, a Renault’s frame could not support a Thunderbird V-8, providing a lesson in mechanics of materials.  We also learned that people were happy to get rid of old cars in their backyards and we could try all sorts of things, while selling parts salvaged from these cars.

By the time I was 20, I landed a job as an assistant engineer at Raytheon, a large defense contractor in Portsmouth.  I was involved with the AN/BQS-13 sonar system, which looked much like Picture 5.  During my two years at Raytheon, before heading to graduate school at MIT, I worked in mechanical, electrical, and systems engineering. It was a wonderful immersive experience.

My ultimate task was to figure out how many spare parts to bring on a submarine, given the different reliability and maintainability characteristics of the subsystems, assemblies and components and, of course, the limited space for spare parts.  I also was able to participate in some of the discussions of the human operators of these systems in terms of the information and interface needed to support their tasks.

Sonar Room

Picture 5. Sonar Room

Picture 6 shows my current involvement.  In some ways, the hospital operating room is like the sonar control room. However, there are critical distinctions.  The information systems and the incentive systems in healthcare are much more poorly aligned with human behavior and performance requirements.  Inadequate information and poorly aligned incentives are issues that must be addressed in a broader context than depicted by Picture 6.

Operating Room

Picture 6. Operating Room

This observation reflects a life-long penchant to question external constraints — to wonder why “givens” are given. The “best” solution to a problem is almost always only best within a given set of assumptions. These assumptions often reflect constraints that, when viewed broadly, can be seen as totally arbitrary.  In this way, problem solutions are often limited by problem definitions.  I am always energized by the question of what is the real problem.

So, what have I learned?  Three lessons seem like a good number.  First, no matter at what level you address a complex system, there is always a broader context that impacts the system.  Simply externalizing the context is not a good idea; this assumption will plague you later by hindering successful operation and maintenance of the system.  For example, better design of hospital operating rooms will not, in itself, remediate the information and incentives problems of healthcare delivery.

Second, complex systems cannot be addressed successfully by a single, traditional discipline.  Appropriate consideration of interactions at different levels of abstraction and aggregation require a mix of knowledge and skills. Consequently, one professor and one PhD student cannot single-handedly address complexity successfully. Interdisciplinary approaches are needed to transform complex systems.

Third, the engineering of complex systems requires a professional community that embraces the first two lessons. For me, the Council of Engineering Systems Universities and the International Symposium on Engineering Systems is that community.  I am indeed fortunate that the 1952 Plymouth carburetor headed me in this direction five decades ago. I expect CESUN and the Symposium to be central to transforming complex systems for many years to come.

Technology-Driven Change

Change tends to be very difficult, but it does happen.  Technology is one of the key drivers of change.  Technologies enable new possibilities, such as typing this post on my iPad early Sunday morning, sipping coffee and listening to the rain. The iPad means that I can be productive any time, any place. This capability has become very popular and Apple’s share price has soared.

Why does this constitute change?  The immediate impact is that my laptop seldom leaves my office at the university. I have not had a home computer for several years. I am questioning whether I really need a smart phone any longer since Wi-Fi is becoming ubiquitous. I read many books and 90% of them I download to the iPad.  I read newspapers this way as well.

So, one device has eliminated my previous inclinations to buy a home computer, a smart phone, most books, and all newspapers.  I imagine the companies who sell these things are quite aware of such changes of buying habits. Employees, or former employees, of these companies are also, I am sure, very aware of these changes. Decreasing demand for products and services means that fewer people are employed to provide these products and services.

This pattern has repeated throughout history, ranging from steamboats to railroads to electricity to automobiles to airplanes and computers. It often takes quite some time for patterns to play out. The transistor was invented and refined in the late 1940s. More than six decades later, the iPad is having the impacts noted above. Of course, there were many steps along the way, and many other technologies were needed in addition to semiconductors.

One cannot help but wonder what is next. Many think that technologies associated with the life sciences and health will be the next drivers of change. Personalized medicine is the current Holy Grail. It is imagined that this will replace mass produced medicine.  Treatments and drugs will be tailored to each individual’s genetic makeup. This means much smaller markets for each type of treatment and drug. This threatens pharmaceutical companies’ penchant for blockbuster, high volume offerings.

Changes on a personal level are likely to be much more profound. Once you are aware of your genetic predispositions, what range of interventions do you entertain?  What increased probability of a health problem will justify intervening?  How will you or your employer or the government pay for these interventions? How will your employer or the government limit the allowable interventions? There are many possible answers to these questions; most of them portend substantial changes to how we live.

Report From the Front

Over the past two semesters, I have been helping Georgia Tech undergraduate teams to contribute to transforming healthcare delivery.  Their senior “capstone” projects have focused on patient in-flow (Emergency Department), in-patient operations (Operating Rooms) and patient out-flow (Discharge and Bed Turnover).  Three eight-person teams addressed each of these areas of hospital operations.

The problems these students faced were excessive waiting time in the Emergency Department, low utilization of Operating Rooms, and delayed Discharge and Bed Turnover.  All three of these problems resulted in inefficient use of capacities, decreased revenues, and excess staffing costs. The students’ solutions focused on improving use of capacities to increase revenues and decrease costs, resulting in net gains in the millions.

In all three instances, the hospitals had many ideas for how to improve operations. However, they did not understand the economic implications of the alternatives. The students used their engineering models; sleuthed down the data they needed; and projected the benefits and costs of alternative courses of action. They presented their results and implications in clearly actionable recommendations.

Perhaps not surprisingly, these projects depended on each other. Most significantly, increased use of the Operating Room capacity depends on improved Discharge and Bed Turnover. Otherwise, where do you put the increased number of patients emerging from surgery? In this way, inefficiencies in one functional area can impose inefficiencies in another area.

These three projects show how highly motivated, well-intended healthcare professionals can promote inefficient solutions due to having to operate within the significant constraints imposed by the rest of the organization.  We have the methods and tools to overcome these limitations. We just need the courage to approach healthcare delivery problems systemically.

Why Transformation Is So Difficult

It is fairly common for the perceived benefits of current market offerings to fade and new value propositions to displace older offerings.  As noted in earlier posts, Schumpeter called this process “creative destruction.”  Steel ships replaced iron ships, which replaced wooden ships.  Microprocessors subsumed transistors, which replaced vacuum tubes. Change happens and creative destruction causes obsolete offerings to be replaced by new innovations.

This process of fundamental change sounds much smoother than it actually is.  The stewards of the “as is” enterprise — in other words, the stewards of the status quo — usually do their best to thwart the emergence of the “to be” enterprise.  In fact, they are likely to do their utmost to undermine the very thought that a new paradigm may emerge and be successful.

Last week, I spent a night in Bethlehem, Pennsylvania.  The carcass of the Bethlehem Steel Plant dominates the town.  This sprawling facility has been deserted for three decades.  This was once the “as is” enterprise.  There were thousands of people who did their utmost to steward this “as is” enterprise.  I expect that they simply did not believe that a different future was emerging.

This is not at all surprising.  The builders of wooden ships were not intrigued by the capitally intensive emergence of iron and steel ships.  The vendors of oil and gas lamps were not very enthusiastic about the possibility of electric lights.  The owners, managers, and employees at the Bethlehem Steel Plant were not big fans of high-efficiency continuous casting, not to mention low-wage foreign steel production.

Transformation is, to a great extent, very difficult because an enormous number of people are depending on change not happening. They expect the jobs at the steel plant or automobile plant to continue forever, generation after generation. A few members of each generation break out, perhaps becoming engineers after one generation, and lawyers or doctors after two.  However, the ranks of those seeking the factory jobs grow much faster than of those seeking to leave.

Of course, this phenomenon is not limited to factory work.  Teachers and doctors, for instance, argue against new processes and technologies that they perceive will undermine the value of the knowledge and skills they have long invested in gaining and refining. Thus, online education is impugned for not embodying the human skills of the physically present teacher.  Yet, the current generation of young people has mastered Internet-based interactions with people in far-flung other locations.  The trend in this arena is clear.

Transformation would be much easier if everyone were more adaptable in the sense that they would willingly gain new knowledge and skills whenever necessary.  Factory works would quickly become computer programmers.  Teachers would give up lecturing and rapidly refine facilitation skills for guiding students in online education.  Everyone would happily discard skills that are becoming obsolete and eagerly gain newly valuable skills.

Beyond the problem of motivating everyone to act in this manner, there is a more fundamental limit to this idea.  It takes a long time to become really good at something.  As Malcolm Gladwell popularized in Outliers, research has shown that it takes around 10,000 hours to become an expert.  This is five years if done full-time, perhaps ten years if work involves other activities than just focusing on gaining the targeted expertise.

So, it takes the factory worker 5-10 years to become a skilled computer programmer and the teacher 5-10 years to become an expert “guide on the side” rather than a “sage on the stage”.  I may be overestimating the time required, since the teacher, for example, would not be starting with no facilitation skills.  However, the point is that there is a limit to how fast people can adapt, even if they are willing.

A counter argument is that people do not need to be experts to be productive. But, would you want the flight management software on the plane you are flying in to have been programmed by a less than expert programmer?  Would you want to undergo surgery with a surgeon that just a few years ago was in a completely unrelated profession?  Clearly, high levels of expertise and the resulting high levels of performance are often very important.

Dynamic, innovative economies lead to high levels of creative destruction.  This results in needs for frequent and significant transformation of enterprises.  Often people do not want to make the changes transformation requires.  They may be unwilling, but more fundamentally, they are unlikely to be able to change fast enough to maintain their positions — and incomes — in the transformed enterprise. That is one of the basic reasons why transformation is so difficult.

Worst Practices

I have recently been involved with an enterprise that has somehow managed to embrace just about the worst transformation practices possible.  It all started with the vocabulary the leaders chose to employ.  They managed to paint a transformation picture that they apparently had no intention of pursuing.  While they portrayed fundamental change, their actions totally represented those of stewards of the status quo.

They did not “walk the talk” in several ways.  While cutting production staff and freezing salaries, they relentlessly increased the size and payroll of the management staff.  This included changing elements of the leadership team without communicating to those reporting to these leaders.  New bosses just showed up and took over.  It did not seem to matter to the senior leadership that the subordinates involved were totally confused.

They also rolled out policy changes that fundamentally affected people without informing them.  For example, they moved accounts and responsibilities without announcing the policy changes, leaving managers unable to find accounts and manage them.  The resulting confusion among program managers was apparently of no concern to senior leadership.  It did not matter that financial management was now impossible — the issue was power and control, not performance.

It would seem that only the most wooden-headed leadership would expect that these practices could succeed.  Middle management has had endless debates over whether senior leaders are inept or simply do not care.  No one seems to know what the leaders have been thinking.  However, most employees feel that the leadership was simply assuming that employees are lucky to be employed and should put up with anything.  The stewards of the status quo could not imagine that people would do anything other than what they were supposed to do, even when what they supposed to do was never communicated.

I asked several senior mid-level executives how they felt about events of the past year or two.  One of them put it best, “It is like being pecked to death by ducks.”  All sorts of irritating little changes happen, things that might have been acceptable if communicated and discussed. However, these changes – most small but some big – were simply implemented without explanation.  With supervisors unable to explain the source or intent of these changes, staff morale is steadily slipping..

So, what happens next?  Does this organization spiral to oblivion?  The problem is that such incompetency can be embraced for an amazingly long time.  Bloated work processes that provide little value can be sustained and expanded with little scrutiny. Investments can be made in competencies that are no longer needed, or were never needed.  The realization of irrelevance comes much too late.  The leadership is completely at odds with the future, which they consciously ignore seeing.  The message, strategy, and plan are totally at odds with reality.  The severance packages may be much too generous, but the sooner such leaders are gone, the sooner the wonders of creative destruction can commence.