Rear View Research

I came across an interesting blog post by Jeff Henning. He provides an account of a talk at the University of Georgia by Stan Sthanuathan, VP of marketing strategy for Coca-Cola. Sthanuathan points out that a lot of industry research is “rear view”–mining data to figure out what has happened, create “report cards” and analyze mistakes. Sthanuathan calls for a change in mindset. That works–but how is a mind supposed to just change? How’s group think supposed to change? Not to mention the bozonet.

Here’s the key point–Sthanuathan differentiates between responding to change and shaping change. Remember, this is from the perspective of an industry leader. The distinction is insightful. “Large companies have a responsibility to shape the change, not just respond to change…. They must shift from quantifying the expected to listening for the unexpected.”

Bewilderment–be-wild-er-ment— dreaming, experimenting where the outcome is not known, exploring the unknown–these are looking through the windshield rather than the rear view mirror. It would appear a lot of university research also may suffer from this rear view problem, that it is there to demonstrate a known (or claimed) point in dispute rather than to explore. It may be, even, that the way university funding is set up, with “peer-reviewed” grant proposals, one has to propose research that sounds plausible, doesn’t disturb the consensus view of what’s important, and has to use approaches that “peers” approve–that is, “best practices.” To otherwise is a sign of incompetence, poorly conceived projects, and foolishness–if not for science then for career.

I’m thinking about Michael Crichton’s talk at Caltech on consensus in science. Consensus is one of the attributes of the status quo, which is my point of reference for thinking about innovation, as innovation is a vector of change in the status quo. The obvious thing about this is that the status quo also seeks to manage its change. There is a roadmap, there are projections, there is evolution of products and markets and standards and efficiencies and value chains, and all these things are matters of interest for the status quo. One characteristic of all this change management is that those leading the status quo rarely propose to give up their leadership in any contemplated change. One doesn’t plan at Coca-Cola to reposition the company as a secondary player. The folks at Kodak really wanted to remain leaders, and so followed their brand, based on world leadership in thin film chemistry, into digital goods and services, where the company was nothing, abandoned their thin film work just as it was becoming hugely important in glass coatings for mobile handsets and solar panels, and as a result are on pretty shaky ground. But they really wanted to stay leaders and so could not reposition as a growing company with new markets other than selling cameras.

This is the dilemma for anyone anchored in the status quo. It is the dilemma of blue-ribbon panels and inventories of best practices, it is the problem of confirmation bias and flattery of those in power, it is the determination to maintain, if not expand, a dominant position, even if, down the road, that means disaster.

Same holds in the smallish world of university technology transfer. There’s a dominant world view, the linear model and its variations, and that’s held by organizations like AUTM, which puts out training materials and holds courses and lobbies the government for policy. It fosters a consensus view of innovation that’s remarkably conservative, ideological, and rationalized into a smooth line about compulsory ownership, professional marketing, and public benefit. Confirmation bias abounds. Defensiveness abounds.

When the Kauffman Foundation proposed in the Harvard Business Review a “breakthrough idea” to open up university innovation management to specialist agents, AUTM went wild with objections, publishing a stammeringly ideological retort in Business Week, writing letters to the Department of Commerce seeking to stifle any public debate on changes to the Bayh-Dole Act, and more importantly, to prevent any changes to the operating model for technology transfer that AUTM has advocated for nearly 30 years–advocated so long that it has gone from one approach among many to something that is not only believed but is championed as the best, if not only, approach. The burden for anyone else is to show that there is any reason to change.

With the Stanford v. Roche case, we find the Supreme Court telling AUTM that it has no friggin’ clue what it is talking about. No one seems to understand–especially among AUTMites–that the whole consensus model what shot down by the Supreme Court. Bayh-Dole not a vesting statue. No requirement in federal policy that universities own inventions. No mandate or special privilege that they own. Drat.

The whole 30 years of idea to repeating to belief to driving out the error of others with a best-practices ideology down the drain. But of course AUTM is still standing, still fixated on its ideology, and now AUTM organizations are working to replace their failed claims regarding federal policy with institutional policies that serve the same ideology of central control, licensing for money, and aspirations of public benefit measured in income to universities–even if the universities rarely ever report in any detail how they spend their bitter-won money. The point is that a consensus is a tough thing to change, and all the more so from the outside.

Stan at Coca-Cola then has this problem.  On the one hand, he would like to redirect research from studying past data to pushing transformation, but on the other hand, to push transformation means that one has to launch out where one isn’t necessarily in one’s areas of strength.   It’s almost like an appeal from the status quo for help–“I’m caught in the status quo, and it obscures what it disdains, and it proposes what is increasingly boring and ineffective, and I sense, somehow, that we’re becoming vulnerable to big forces that will take us down, Kodak style, if we simply assume the course of greatest continued dominance.”

Henning provides a list of things industry can do to get past this problem of the tyranny of the consensus.  It’s worth reading the whole list.  The themes that come out, though, are an interest in idiographic approaches over nomothetic ones–dreaming, embracing risk, questioning the conventional wisdom–pushing out into the unknown.  These aren’t about responding to change or even shaping change–these are fundamental acts of epiphany.  Epiphany work does not come from merely thinking–there are active elements at work in composition, in exploration, in associative memory, in building the capability to recognize patterns as previously unrecognized.

How does one find the weak signal, the rare event, the odd combination, the long nose of innovation, the chance, the spark, the epiphany.  One cannot propose an approvable line of proper, orderly action to get there.   One does not assemble a blue ribbon panel of ex CEOs and venture investors and university presidents to inform everyone of the latest restatement of how the status quo has decided to change.   How does such stuff come into the world?  It is almost as if it could be as easily said by a child in a moment of insight.   We had some 12 year olds visiting the Ganter 3d printing lab.  We had a toy train engine and some track printing out in the Stratasys.   As they look in at the build chamber, one turns to the other and says, “This is the future of toys.”   It’s stuck with me.  Seems he has a point.  I wonder how it would go over at Mattel.

The challenge, then, for university research is that it risks being boringly consensus-derived and driven.  Yes, there are reports of new findings.  But as a recent issue of Science and a story it the Wall Street Journal make clear, a whole lot of those findings are simply wrong.  This is not progress of science, or even the conditions of scientific debate–just slop science, because the pressure to publish is, apparently, so great in the status quo that any good sounding slop will do.  Maybe instead of publication listing and citation counts, academics could be evaluated on how long their articles persist before being cited at all, and how long until they are withdrawn or shown to be in error.

The consensus view in technology transfer is that it’s all about “commercialization” under the cover of the “public benefit” (which means, in terms of priorities, making money for university-owners through licensing for commercial sale or sucker investors, and since universities are assumed to be acting in the public interest, there it is).   But what if the university role that matters is as a steward, helping individuals dream and wander and epiph?  Then all the emphasis on inventions and patents and licensing and big commercialization deals is sort of wasted.  And all the compulsory systems, accumulation of patents and holding out to make someone pay is rather selfish and isolating and trollish.  And all that dreaming and wandering and epiphing is just so much fluffy nonsense to practical money makers sitting on a wad of patents.

What if the key thing is that an invention in research is highly productive when it emerges outside any institutional claim to ownership?  Perhaps it’s the thing that the research should be transferred *before* there are substantive inventions, and if there are substantive inventions (meaning, things are running a bit late), then special care has to be taken to ensure that the status quo doesn’t come sweeping in and extract the patent rights from the research before everything can be moved outside the institution.  Rather than rushing in and demanding to own, and demanding to get there earlier and earlier–to the point of just having a present assignment before anything ever is done–one might expect then for a university to focus on moving research out, and showing people how to do this, preferably before there are inventions, and if there are inventions, carefully to keep everything as together as possible for external use.

I know, this isn’t how it’s done.  There are no training programs on this approach available. (I’m happy to develop one if anyone is interested).  There is no “standard practice” by which a university seeks to be a rain maker rather than a rights piggy.  There isn’t any way even to test out this approach, because university policies are uniformly drafted to authorize the linear model and properly distribute the plunder in pre-defined ways, so that refusing to participate in the plundering is seen as unethical behavior–conflicts of interest, disrespect of authority, selfishness, imprudence–clearly against the “public interest” (it has to be, since the university and its tech transfer operation are already defined as being in the public interest).

The consensus is built on the idea that people know a whole bunch and agree on it and the call is for them to all work together to get everyone on board with this knowing, and to shape how the knowing will change over time, so the experts stay the experts, the leaders stay the leaders, and what’s important is what keeps the leaders leading and experts perting.   It’s really useful to have status quo activities.  We are creatures of habit, we rely on routine and order, and there are things that benefit from having someone know what they are doing.

What we are concerned with here, however, is that little part of the status quo that has to do with innovation.  Will innovation be so domesticated that it is merely the watchword of how the status quo decides to change?  Or can it be something more like the high plains drifter, who comes into town to shake things up in the status quo?  For that little part, it’s not at all clear that we need more order, ownership, process, or institutional thumbs in the pie.  There are times that perhaps we do.  So keep some of it around.  But there are lots of times where institutional control has nothing to offer innovation, collaboration, advancement of science, research productivity, economic development, cluster formation, national competitiveness, or pursuit of happiness.

Things started with the idea that individuals collaborating with industry could establish patent positions that would motivate industry adoption of new technology, with proceeds going to support more research conducted with a similar ethos, we have progressed to the idea that the research has to be at the originating school, can be for anything that folks want, that this is such a good idea that it should be applied to all research, and all use of facilities regardless of whether its research or instruction or just noodling, and now we have folks arranging this already pretty transformed and rationalized idea into an end-to-end process of ownership, accumulation, marketing, and money.

Let me tell you:  if there were consistently money at the output end, and that money came distinctively because of the marketing, then there would be no problem with the ownership piece.   But the consensus is working the ownership piece precisely because the outputs just aren’t there–not money, not practical application, not public benefits.  Just a hoard of patents and some iffy metrics about money-making without any attention to how that money has been made–sale of product in the marketplace, or sucker investors in yet another university puppy-mill company?

I’ll suggest that it may be that a metric for universities is how many cool things do their personnel create that get transferred for use before the institution brings its IP policy down like Gallagher’s mallet.   That might be the best test of whether the university’s research programs are rear view (and therefore highly competitive for more federal funding) or transformative (because outside the scope of the status quo, high plains drifter style).   It might be, folks need to propose dreaming, wandering, and epiphing more often, but what pragmatic government would ever approve that?  How could a major center be funded that wasn’t tied to the consensus view of compelling reasons to exist, agreed-upon objects for study, using the best practices available?  What university IP policy could leave well enough alone?  How could tech transfer officers not want to own everything they could, early and often?  It would be a fun policy to write, that backs folks off and lets emerging signals emerge.




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