Great Moments in Tacit Knowledge, High-Energy Physics Division

From Alan Krisch’s 2010 account of research involving the (still-unresolved) anomalous behavior of tranversely polarized colliding protons:
After all this hardware was installed, an even larger problem was tuning the AGS. In 1988, when we accelerated polarized protons to 22 GeV, we needed 7 weeks of exclusive use of the AGS; this was difficult and expensive. Once a week, Nicholas Samios, Brookhaven’s Director, would visit the AGS Control Room to politely ask how long the tuning would
continue and to note that it was costing $1 Million a week. Moreover, it was soon clear that, except for Larry Ratner (then at Brookhaven) and me, no one could tune through these 45 resonances; thus, for some weeks, Larry and I worked 12-hourshifts 7-days each week. After 5 weeks Larry collapsed. While I was younger than Larry, I thought it unwise to try to work 24-hour shifts every day. Thus, I asked our Postdoc, Thomas Roser, who until then had worked mostly on polarized targets and scattering experiments, if he wanted to learn accelerator physics in a hands-on way for 12 hours every day. Apparently, he learned well, and now leads Brookhaven’s Collider-Accelerator Division.
Score a data point for the individualist view of organizational capability.

Genetically Engineered Human Capital?

NPR reports that geneticists have crossed a line that has been considered taboo: They changed human DNA in a way that can be passed down to future generations. The researchers at Oregon Health & Science University say they took the step to try to prevent women from giving birth to babies with genetic diseases.

Applied to such health issues, over a long haul, it could make richer nations genetically predisposed to better health. Stronger health, in turn, may create economic opportunities that might not otherwise exist. One can imagine that this could widen existing gaps between emerging economies where such technologies are less likely to be applied. Of course, it may also exacerbate such gaps within wealthy nations where income inequality is already a hot-button issue.

This assumes all that the technology is not applied to more controversial traits like enhancing intelligence (which we can’t even measure very well much less identify a gene that would have such an effect).

You can listen to the story by clicking here.


Diving into Human Capital Pools

An article in the current edition of the Economist describes Alfred Marshall’s original observation of geographic clusters of activities. They describe four main logics for clustering:

 First, some may depend on natural resources, such as a coalfield or a harbour. Second, a concentration of firms creates a pool of specialised labour that benefits both workers and employers: the former are likely to find jobs and the latter are likely to find staff. Third, subsidiary trades spring up to supply specialised inputs. Fourth, ideas spill over from one firm to the next, as Marshall observed.

However, there are also costs to being in a cluster such as higher rent or transportation costs associated with distances to customers or suppliers. The burst of communications and computing power should make it easier since natural resources are less important and  workers can live farther away from their offices.

It hasn’t worked this way. Pools of human capital continue to drive clustering as people prefer to work near where they live. Very small distances can make a big difference. The article goes on to describe clusters within clusters in the Bay area for specialized knowledge.


Motivation Trumps IQ. What now?

An article recently posted in Slate reviews research showing that a significant portion of the variation in IQ tests is attributable to motivation rather than ability. In one striking study researchers measured the children’s IQ and split them into High, Average, and Low groups. They reran the test offering the low group an M&M for every correct answer. As a result of this simple incentive, the low group’s score went from 79 to 97 – on par with the average group.

Ok, so incentives work. Perhaps not a big surprise on many levels.

On the other hand, there is a large OB/HRM literature invested in the conclusion that performance increases are associated with hiring employees with a higher IQ. The assumption there is that IQ measures ability as opposed to motivation.

This raises a critical question for strategy scholars. Is motivation an immutable attribute of human capital Read the rest of this entry »


Strategic Human Capital Paradoxes…

For a PDW, I was asked to develop a short list of paradoxes linked to the strategic human capital (spoiler alert for those of you planning to be at the session at 8am on Friday). I’m sure some of them would not surprise you in the least. Others might spur some discussion though. Here is the short list:

  • Rent from human capital may not show up in profitability
  • “Who” is a firm?
  • Firm-specificity isn’t as important as we might think
  • HR Departments may not matter much
  • High performance work systems don’t tell us much about such advantages

Rent. The first point is what you would expect from me so let me dismiss it quickly. Obviously, if rent is linked to human capital, some portion of it is likely to be captured by people. Nuff said.

Who is a firm? A sharp distinction is made between hiring on the spot market and an internal labor market. Rightly so. However, one might think that once labor is “internal” such people are part of the firm. Read the rest of this entry »


Marginalism and the Higher Ed Paradox

By now, you may be getting sick of reading articles and blog posts about the crisis in higher education. This post is different. It proposes an explanation of why students have been willing to pay more and more for undergraduate and professional degrees at the same time that these degrees are becoming both less scarce and more dumbed down. And that explanation rests on a simple and plausible economic hypothesis.

Read the rest of this entry »


How do you grow a capability?

The “dynamic capabilities” literature, I think, is a bit of a mess: lots of jargon, conflicting arguments (and levels of analysis) and little agreement even on a basic definition.  I don’t really like to get involved in definitional debates, though I think the idea of a capability, the ability to do/accomplish something (whether individual or collective), is fundamental for strategy scholars.

Last weekend I was involved in a “microfoundations of strategy” panel (with Jay Barney and Kathy Eisenhardt).  One of the questions that I raised, and find quite intriguing, is the question of how we might “grow” a capability.  The intuition for “growing” something, as a form of explanation, comes from simulation and agent-based modeling.   For example, Epstein has argued, “if you didn’t grow it, you didn’t explain it” (here’s the reference).   I like that intuition.  As I work with colleagues in engineering and computer science, this “growth” mentality seems to implicitly be there.  Things are not taken for granted, but explained by “growing” them.  Capabilities aren’t just the result of “history” or “experience” (a common explanation in strategy), but rather that history and experience needs to be unpacked and understood more specifically.  What were the choices that led to this history?  Who are the central actors?  What are the incentives and forms of governance?  Etc.

So, if we were to “grow” a capability, I think there are some very basic ingredients.  First, I think understanding the nature, capability and choices of the individuals involved is important.  Second, the nature of the interactions and aggregation matters.  The interaction of  individuals and actors can lead to emergent, non-linear and collective outcomes.  Third, I think the structural and design-related choices (e.g., markets versus hierarchy) and factors are important in the emergence (or not) of capabilities. Those are a few of the “ingredients.”

I’m not sure that the “how do you grow a capability”-intuition is helpful in all situations.  However, I do find that there is a tendency to use short-hand code words (routines, history, experience), and the growth notion requires us to open up these black boxes and to more carefully investigate the constituent parts, mechanisms and interactions that lead to the development or “growth” of capability.


Jeremy Lin and Moneyball: The Problem of Identifying Talent

After watching Jeremy Lin (Knicks) score 38 points against the Lakers tonight, I’m now on the Lin bandwagon.  I don’t really even follow basketball that closely, but this seems like an intriguing story.

How on earth did someone like this go unnoticed?   Seriously.  He happened to get an opportunity to show his stuff as Carmelo Anthony and Amare Stoudemire are injured – and boy has he delivered.

Here’s a kid who didn’t get recruited for college ball, despite a tremendous record in high school.  He was a superstar at Harvard but went undrafted by the NBA after graduating from Harvard (in economics) in 2010.  He played a few games for Golden State and Houston, but was cut by both.  He has played D-league basketball this year, until a few weeks ago.  As of last week, he did not have a contract.

But come on: is basketball truly this inefficient at identifying and sorting talent?  The comparisons and transfer of ability across “levels” (high school-college-professional) of course is tricky, though you would think that with time there would be increased sophistication.

Now, four games of course doesn’t make anyone a star.  But even if Lin proves to “just” be a solid bencher, it seems that talent scouts clearly undervalued Lin (who lived in his brother’s apartment until recently).  How much latent talent is out there?  (I think that at the quarterback position in professional football – there are significant problems in identifying talent, but that’s another story.)

There are of course also some very interesting player-context/team-fit, interaction-type issues here, and I’m not sure that this really gets carefully factored beyond just individual contribution (thus not recognizing emergent positive, or negative, player*player effects).  It’ll be interesting to see what happens, for example, when Carmelo Anthony is added back into the mix.

Well, it’ll be interesting to see how all this plays out.  There is in fact a sabermetrics-type, stats-heavy, Moneyball-like thing in basketball as well – called ABPRmetrics.  I would be curious to know whether there are ways to statistically identify Lin-type undervaluation and potential, and whether phenoms like this lead to better metrics for identifying talent.

UPDATE: Here’s ONE analyst/statistician who saw Lin’s potential in 2010.


Actually, small companies are better at innovation than large companies

Grant McCracken summarizes an Economist post that argues that big companies are better at innovation than small ones (well, he discusses both sides).

But theory says that small companies are actually the winners.

Economists have long wrestled with this, the “diseconomies,” problem: why do smaller organizations outperform large ones?  (Todd Zenger’s 1992 Management Sci piece summarizes this work nicely.)  Schumpeter indeed went both ways on this (Dick Langlois discusses the “two Schumpeters”-thesis a bit here).  But yes, large organizations seemingly have the resources, complementary assets, access to talent etc to outperform small organizations.  But small organizations still outperform large ones.

Large organizations have lots of problems (I’ll spare the references, for now).  They

  • mis-specify incentives,
  • suffer from problems of social loafing (free-rider problem),
  • engage in unnecessary  intervention, etc.

And, if large organizations had such an advantage, why not take this argument to the extreme and simply organize everything under one large firm?  That, of course, was one of Coase’s central questions.  Obviously the organization-market boundary matters and there are costs associated with hierarchy.

Sure – there are lots of contingencies, caveats and exceptions [insert example from Apple or 3M].  And, definitions matter [what exactly is "small" versus "large"].  But on the whole, the theory says small companies win in the innovation game.


Model thinking and game theory: more free online classes

Via StrategyProfs reader Andrew Boysen’s Twitter feed (@boysenandrew) — some upcoming, very cool, free online classes: Model Thinking by Scott Page (University of Michigan) and Game Theory by Matt Jackson and Yoav Shoham (Stanford).

Love this trend of free online classes, I’m auditing that mega Artificial Intelligence class just to see how a class with 100,000+ registered students might actually work (I’m guessing a small fraction actually do the work – but still fascinating).

Here’s the pitch for that class by Scott. Sounds fantastic.


Who are the top one percent?

Interesting podcast at Econtalk on wealth, income distribution etc – “Kaplan on inequality and the top 1%.”   Much of the Roberts and Kaplan discussion focuses on this paper (pdf) – “Wall Street and Main Street: What Contributes to the Rise in the Highest Incomes.”

Paul Krugman makes a different argument – “Oligarchy, American Style.”

This is obviously a heated debate – as illustrated by Freek’s post (also see the comments).


Steve Jobs – the man was fallible

Steve Jobs at the WWDC 07

Image via Wikipedia

As a student, at Reed College, Steve Jobs came to believe that if he ate only fruits he would eliminate all mucus and not need to shower anymore. It didn’t work. He didn’t smell good. When he got a job at Atari, given his odor, he was swiftly moved into the night shift, where he would be less disruptive to the nostrils of his fellow colleagues.

The job at Atari exposed him to the earliest generation of video games. It also exposed him to the world business and what it meant build up and run a company. Some years later, with Steve Wozniak, he founded Apple in Silicon Valley (of course in a garage) and quite quickly, although just in his late twenties, grew to be a management phenomenon, featuring in the legendary business book by Tom Peters and Bob Waterman “In Search of Excellence”.

But, in fact, shortly after the book became a bestseller, by the mid 1980s, Apple was in trouble. Although their computers were far ahead of their time in terms of usability – mostly thanks to the Graphical User Interface (based on an idea he had cunningly copied from Xerox) – they were just bloody expensive. Too expensive for most people. For example, the so-called Lisa retailed for no less than $10,000 (and that is 1982 dollars!). John Sculley – CEO – recalled “We were so insular, that we could not manufacture a product to sell for under $3,000.” Steve Jobs was fantastically able to assemble and motivate a team op people that managed to invent a truly revolutionary product, but he also was unable to turn it into profit. Read the rest of this entry »


Moneyball and Strategy

The book Moneyball seemed to be all the talk at some academic strategy and orgs conferences around 2004-2005.  It annoyed me: why all the buzz about some practitioner book about baseball? Please.

Some time later I was the faculty advisor for a small MBA readings group and one of the books we decided to read was Moneyball.  I quickly discovered that the book indeed is a good introduction and case study of some central issues in strategy: human capital, appropriation and competitive advantage.  Billy Beane and Paul DePodesta’s strategy was brilliant.  As the students read the book, they immediately understood the power of a more scientific approach to managing human capital (e.g., selection) and the power of differentiation.  It seems, though I’m no baseball fan (it’s hockey or soccer for me, since I grew up in Finland), that the game of baseball has changed as a result.  (Though, of course sabermetrics had been around for quite some time).

I have also now seen the movie.  I quite liked it.  And the movie stayed relatively true to the book.  I may use the movie in future classes, as some sort of extra assignment.

There are certainly some more academic-y strategy issues to discuss related to Moneyball – but perhaps I’ll highlight those in a later post.  As Google Scholar shows, Moneyball seems to have influenced research in various disciplines (psychology, decision-making, human resources, economics).

Here are some academic blogs that have recently reviewed Moneyball, the movie:


The Genius versus Social Construction of Steve Jobs

For me Steve’s post raises the age-old question of whether the “greats” are geniuses or simply products of their time.  As the wiki entry for “great man theory” highlights, this question has been around for some time (for Thomas Carlyle history was the “biography of great men,” while both Tolstoy and Herbert Spencer cited social complexity and ridiculed Carlyle).

There are many reincarnations of this debate.  One of the more interesting ones focuses on the great ones of music, the likes of Mozart, Beethoven and Haydn.  Sociologist Tia DeNora wrote a provocative book that said the greats were (essentially accidental) products of their context (see her book Beethoven and the ‘construction’ of genius).  Others, like Rutgers Peter Kivvy, argue for the genius itself (see his book, the possessor and the possessed about Mozart).

This is a quite relevant debate in strategy, essentially, individual versus collective effects/heterogeneity.  There’s a decomposition, variance-components type question here, similar to the firm versus industry debate.  Of course, you can imagine that variance exists both at the individual and collective levels.  But I think this is a question that continues to be worth tackling.  (I’ve published some research related to this but I’ll spare the reader, for now.)

There’s a deeper discussion here about the social construction of hero-ness as well but I’ll leave that for another time.

What is problematic to me is the hand-waving that I see about how invention is, oh, all about context, social complexity, history, etc.  That type of explanation is simply shorthand and an admission that we have no clue what actually happened.  Don’t just say that it is complex.  Rather, explain the complexity.  Reminds me of this Jewkes et al quote from their 1969 book The Sources of Invention:

it is the practice of some writers to present a fuzzy picture of invention as a “social process”; to suggest that, if one inventor had not done what he did when he did, someone else would have done it. . . . this attitude—that nothing can be understood unless all is understood, that by piling one unresolved enigma upon another some all-comprehending solution is made the more likely—involves the error of “seeing depth in mere darkness”, as Sir Isaiah Berlin once put it (26–27).

More on this later.


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