Dispatches from the Frontier

Red Queens and L-Curves

John Hagel and John Seely Brown have joined Deloitte to create a new research center in Silicon Valley.  Hagel has posted their research agenda here.  Two questions, in particular, are of interest to me:

• How can we escape the Red Queen effect?
• How might we use the "long tail" as a launch pad for "head" strategies?

My colleagues and I are actively involved in organizational experimentation designed to accelerate the pace of product innovation.  More specifically, we are developing a practice of identifying, developing, and validating growth options found in the long tail of inventions in order to facilitate their timely execution by organizations that have built capacity.  Consequently, I look forward to Hagel and JSB's continuing insights.

Hunting Moby Dick

The other day, I took a stab at explaining why group decisions are predictably ambiguous.  Marc Andreessen has taken a more literary approach with his Moby Dick theory of big companies.  Although written from the perspective of a startup, his insights are relevant for those individual inventors who would license their intellectual property to a BigCo:

The most important thing you need to know going into any discussion or interaction with a big company is that you're Captain Ahab, and the big company is Moby Dick...What happen[s] [is] entirely up to Moby Dick. And Captain Ahab would never be able explain to himself or anyone else why Moby Dick would do whatever it was he'd do...The inside of any big company is a very, very complex system consisting of many thousands of people, of whom at least hundreds and probably thousands are executives who think they have some level of decision-making authority...You can count on there being a whole host of impinging forces that will affect the dynamic of decision-making on any issue at a big company...You can't possibly even identify all the factors that will come to bear on a big company's decision, much less try to understand them, much less try to influence them very much at all.

Andreessen's advice seems sound to me:

• Find an expert to do your talking for you.
• Be patient...very patient.
• Don't obsess on a single whale, even if it is the biggest and whitest.
• Don't drive yourself crazy trying to predict or explain a BigCo's behavior.  Your emotional energy is better spent elsewhere.

The Distance Between Hollywood and Cincinnati

In a recent post, Marc Andreessen writes:

I'm endlessly fascinated by the film and television industries in part because the risk and uncertainty they deal with on every project makes my own industry seem sane, rational, and well-ordered.

So from time to time I'll be recommending books on film and television with the idea that if you are interested in technology and startups, you can gain a lot from thinking about how an even more extreme "wild west" business environment works.

Regular readers of this blog will know that I think the data shows that most consumer-oriented business environments have more "wild west" in them than is typically acknowledged.  Hollywood is closer to Cincinnati than one might think; and the distance is diminishing.

Fooled by Randomness in the Movie Business
The Long Tail of Things

Open Innovation and The Trust Paradox

The Red Queen effect (7:13 Flash presentation) makes the business logic of Open Innovation compelling.  However, back in January, I warned that the road to Open Innovation could be slow.  Since then, I'm increasingly confident that relatively few incumbents will be able to take full advantage of Open Innovation.  I suspect that a minority of businesses and their prospective collaborators will have mutually sufficient commitment and ability to withstand the "friction" of what John Hagel and John Seely Brown call productive friction.  Therein lies great risk - and great opportunity.

The relentless increase in industry clockspeed encourages openness to external sources of prospective innovation.  However, by definition, increasing clockspeed reduces product development cycles.  Research by Henry Chesbrough shows that shorter evaluation cycles can increase the perceived risk of externally sourced concepts, thus reducing openness:

[One rational reason for resisting Open Innovation] is the need to manage risk in executing R&D projects, especially when the cycle time to complete a project is accelerating.  When cycle times accelerate a project, there is less time to evaluate and incorporate external technologies into a fast-moving project.  More subtly, when projects are moving fast, project leaders seek to minimize the risk of unexpected outcomes in the project.  Internally sourced technologies pose enough risk to the project meeting its scheduled ship date already.  Externally sourced technologies...may greatly increase the perceived risk to the project.  The expected value of an external technology may be as high - or even higher - than an internal technology.  But the variance around that expected value likely may be much higher as well.

This sentiment is echoed by one of the architects of P&G's Connect and Develop strategy:

Never assume that "ready to go" ideas found outside are truly ready to go.  There will always be development work to do, including risky scale-up.

The relative lack of trust in the work product of external sources of potential innovation is probably one of the key reasons that incumbents typically lean toward a transactional approach to Open Innovation:

• In-licensing of raw ideas offers relatively low cost of acquisition and control over the development process, but time-to-market can be quite long relative to the demands of market-driven product cycles.
• Acquisitions of operating companies has the virtue of reduced levels of uncertainty, but the cost can be quite high.

In their recent article in Harvard Business Review, Satish Nambisan and Mohan Sawhney suggest a third way that offers faster time-to-market at a moderate cost of acquisition: active collaboration with Innovation Capitalists that specialize in what they call market-ready ideas.  They emphasize, however, the importance of building long-term and trusting relationships:

But for companies considering the three approaches and the intermediaries that enable them, perhaps the most important difference - which may not be immediately obvious - is the nature of the interactions with the intermediaries.  Companies seeking innovation at the two ends of the continuum focus primarily on the type of innovation they want to buy, whereas in the middle they need to focus on the intermediary.  That is, because of the nature of the innovation capitalist's offering, large client companies need to build and nurture long-term and trusting relationships with selected IC firms.

Nurturing long-term and trusting relationships sounds swell.  It can be devilishly difficult to do, though.  Consider how trust, in large part, seems to be a function of frequent interaction.  But, the dynamics of trust are not linear.  That is, increasing the frequency of interaction doesn't automatically translate into an increase in trust.  In fact, dynamic simulations by Luis F. Luna-Reyes and his colleagues suggest that an increase in the frequency of interactions will usually lead to an initial decrease in trust:

The highest interaction frequency patterns are the ones that show large fluctuations in the early time periods, then move upwards to high trust levels that remain high.  The low frequency patterns show much smaller initial fluctuations and tend to lower levels of trust at the end point.  Paths with high frequency interactions, interpreted as faster learning, may be more volatile at first, since information that can change perception is flowing in at a higher rate.  But other factors being equal, the more extensive knowledge base generated thereby leads ultimately to higher levels of trust.  On the other hand, higher frequencies of interaction are also associated with more stable levels of trust, suggesting that actor A will tend to be more certain about these subjective probabilities as the frequency of the interaction increases.

Hence, the trust paradox in the context of Open Innovation: trust may be hardest to build when it is needed the most.  The building of trust takes time, requires commitment, and is emotionally demanding.  In other words, the building of requisite trust through productive friction is expensive.  Because it is expensive, one has to make choices in the face of a great deal of uncertainty.  Choose correctly, and you will reap the full benefits of Open Innovation.  However, if you are less lucky in your choices, you stand to lose a great deal.  It is the essence of the strategy paradox.  Most, I suspect, will default to the less risky transactional path.

Marc Andreessen on Entrepreneurs and VC

Marc Andreessen has a new blog.  It's easier to read than mine.  Early posts include:

• Why not to do a start-up
• The truth about venture capitalists - Part I, Part II, and Part III

Check it out.

Homo Economicus is Extinct

In Scientific American, Michael Shermer writes:

Homo economicus is extinct, felled by the new sciences of behavioral economics and neuroeconomics, which have demonstrated that we are remarkably irrational creatures. Thousands of experiments in behavioral economics since Daniel Kahneman and Amos Tversky founded the field with their seminal 1979 paper, “Prospect Theory: An Analysis of Decision under Risk,” have demonstrated that most of us are highly loss averse. Specifically, most people will reject the prospect of a 50–50 probability of gaining or losing money, unless the amount to be gained is at least double the amount to be lost. That is, people feel worse about the pain of a loss than they feel better about the pleasure of a gain. Twice as badly, in fact.

He goes on to describe an experiment that reveals physical, biological evidence that supports this hypothesis.

In my line of work, I can see this asymmetry at work in at least a couple of ways.  First of all, I find that there are relatively few people willing to play the innovation capital game.  It may be because it is a bad game - time will tell.  I suspect, though, that part of the reason is that this particular game involves buying call options in the form of the right to invest in promising inventions.  On most days, we lose money in the hope that we'll make a lot of money every nth day.  As Nassim Taleb noted in Fooled by Randomness:

It requires some strength of character to accept the expectation of bleeding a little, losing pennies on a steady basis even if the strategy is bound to be profitable over longer periods.  I noted that very few option traders can maintain what I call a "long volatility" position, namely a position that will most likely lose a small quantity of money at expiration, but is expected to make money in the long run because of occasional spurts.  I discovered very few people who accepted losing $1 for most expirations and making $10 once in a while, even if the game were fair (i.e., they made the $10 more than 9.1% of the time).

I'm not convinced that "strength of character" is a prerequisite to being an innovation capitalist, but it probably does help to have a mutant brain.

Secondly, most inventors have a grossly inflated notion of the economic potential of their ideas.  My hypothesis is that in order to reduce cognitive dissonance, inventors rationalize their investment of time, money, and emotional energy in a concept that is highly unlikely to see the light of day on a retail store shelf by convincing themselves that the potential reward is much higher than is likely.  The rational approach is to spread the investment across a portfolio of inventions.  But, then again, nobody but economists ever believed that any of us were truly rational.

Big Sky Venture Capital Conference

Gary Bloomer at TechRanch is looking for companies to present at the upcoming Big Sky Venture Capital Conference on August 23rd and 24th:

...registration is now open for venture capitalists, accredited angel investors, and entrepreneurs chosen to present at the Conference.  As long as attendees fall into one of the three categories, there is no cost for registration...Presenting companies should be: high growth, innovative companies (preference will be given to Internet, software, IT, media, communications, energy, life sciences, and medical device companies); seeking seed stage funding through mezzanine stage funding; located in the Northern Rockies Region (OR, CO, WY, WA, ID, UT, MT, AK).

Prospective presenting companies can make an online application here.

Moved to TypePad

I've made the move to TypePad.  The new URL is http://swni.typepad.com/dispatches/.  The change should not effect many, because the RSS feed has been re-directed to the new URL, and subscriptions should be automatically updated.

I published my blog via Radio Userland between August 2002 and June 2007.  Radio was a cool tool with which to learn about blogging.  However, I have been particularly interested in TypePad since Michael Sippey joined SixApart some years ago.  Since that time, I have had the chance to use TypePad for other blogs, and I have been impressed.  In addition, I have grown concerned about the relative lack of development over at Radio Userland.

I think I was able to successfully copy the entire archive of my posts to TypePad.  There are a couple of dozen non-chronological "stories" that I may copy, as well.  In any case, I'll maintain the Radio site as an archive.

Building Adaptive Capacity

Since last September, I've been making a series of posts that describes innovation through the lens of the evolutionary algorithm.  I've struggled to reach some definitive conclusions regarding ways in which companies might build their adaptive capacity.  I suspect that I will continue to struggle.  Nevertheless, my research and experience points toward a consistent set of ideas that offer promising avenues of exploration:

• Uncertainty is the dominant characteristic of the social and, hence, business world.  Consequently, business strategy must necesssarily be contingent.  We should work hard on imagining a full range of possible futures in order to anticipate, reduce the shock of surprise, and accelerate our appropriate response to new information.
  
• In order to increase flexibility, it makes sense to organize our capabilities in a modular fashion.  That is really hard, because it forces us to acknowledge and understand interdependencies (in order to reduce them) and define and manage interfaces between modules (in order to get them to work together).  The upside is that modularity facilitates reconfigurability, which means that we can do new and different things by recombining existing capacities in new ways.
  
• Core and contingent capabilities should be complementary.  Our ability to do something depends capacities accumulated over time.  Consequently, it makes sense to think about how to leverage existing capacities than to default to having to build new capacities from scratch (or acquire others' capacities at a premium).
  
• The future never arrives, so anticipating the future is a dynamic and iterative process.  Furthermore, pacing and industry clockspeed are probably even more important than you think.  The Red Queen is a demanding taskmistress.

Others have written far more eloquently and persuasively on these topics than I'm capable of doing.  So, I've appended this post with a bibliography of some of the books to which I find myself referring on a regular basis.

I began this series of posts by quoting Orgel's Second Rule: Evolution is cleverer than you are.  I continue to be humbled by how the process of innovation is much, much cleverer than me.  That has pointed me toward the following set of personal objectives:

• Innovate, innovate, innovate.  As Paul Oremerod concludes, "It is the best strategy for individual survival, and it is a strategy from which we all, as consumers and citizens, have benefited immensely."
  
• Adopt a strategy of humility.  Prediction is a fool's game; we don't know as much as we think we know.
  
• Aspire to wisdom.  As Jeffrey Pfeffer and Bob Sutton suggest, "Be confident enough to act on the best knowledge you have now, humble enough to doubt what you know, and wise enough to face the hard facts when new - and better - evidence comes along."
  
• Practice your own norms of adaptive behavior.

For further reading, I recommend the following (in no particular order):

The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics
Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets
The Only Sustainable Edge: Why Business Strategy Depends on Productive Friction and Dynamic Specialization
The Strategy Paradox: Why Committing to Success Leads to Failure (and What to Do About It)
Why Most Things Fail: Evolution, Extinction & Economics
20|20 Foresight: Crafting Strategies in an Uncertain World
Adaptive Enterprise: Creating and Leading Sense-and-Respond Organizations
How Breakthroughs Happen: The Surprising Truth About How Companies Innovate
Six Degrees: The Science of a Connected Age
The Modern Firm: Organizational Design for Performance and Growth

Group Decisions are Predictably Ambiguous

The other day, my EIP partners and I had a beer with an experienced member of the corporate development group of a consumer products company.  With typical candor, this person noted:

Show me any idea, and I'll show you at least one fairly senior person in our company who is interested.  It's pretty easy to get someone here interested; it's a lot harder to convert interest into action.

I'm sure many of you who are inventors can relate.  Getting stuck in the "we're interested but not willing to commit right now" do-loop is akin to inventor purgatory.  Consequently, I can imagine many an inventor nodding their heads in agreement at the following line from Men in Black:

A person is smart.  People are dumb, panicky, dangerous animals, and you know it.

How is it that an organization full of smart people (i.e. people who are interested in our great ideas) can be so dumb (i.e. fail to commit to act upon those same ideas)?

Sociologists such as Duncan Watts might say that I'm asking the wrong question, because the question is based upon the fallacy of composition (the whole behaves like the part) or division (the part behaves like the whole).  Specifically, my question assumes a representative agent.  Think about how many times you use phrases like "the market believes" or "the customer thinks" or "the company decided" as if you were talking about an individual.  How many times have you assumed that if you can persuade individuals, in isolation, you can persuade the group?  The assumption that the collection can be described in terms of a representative agent holds up if individuals' behaviors are independent of one another.  However, in business, that's rarely the case. 

Consider the following from Robert Cialdini's book, Influence: The Psychology of Persuasion:

In general, when we are unsure of ourselves, when the situation is unclear or ambiguous, when uncertainty reigns, we are most likely to look to and accept the actions of others as correct.

In other words, when we are uncertain either because we don't have access to sufficient information or we don't have the individual capacity to understand all of the information that is available, we'll turn to our colleagues for guidance.  It should come as no surprise, then, that when faced with the uncertainties inevitably surrounding the decision whether or not to commit substantial resources to a prospective innovation, the beliefs of individuals within the organization would be highly interdependent.

As Watts notes in a recent essay titled "The Collective Dynamics of Belief,"

Under fairly broad conditions...it is possible to show that when individuals make decisions in response to the decisions of other people, the relationship between individual preferences and collective decision breaks down.

and

When individual beliefs are formed interdependently, the collective outcome is fundamentally ambiguous, in the sense that it is not determined in any obvious way by the characteristics of the individuals, considered in isolation of each other.

We experienced this truth quite recently.  The individual members of the management team of a prospective licensee of one of our products seemed quite positively inclined to move forward toward an agreement.  However, in the span of just a week, their collective decision was to pass.  Why the apparent reversal?  I'm not sure that we'll ever know for sure, notwithstanding our respective ability to construct plausible explanations.

So, on the one hand, it is important for inventors to understand that group decisions are fundamentally unpredictable in the strict "if X, then Y" case of linear causality.  A great product concept pitched well to a group of rational decision-makers can fail simply due to the complex dynamics of collective decision-making.  On the other hand, that's not the same thing as saying that anything is possible - weak concepts pitched poorly aren't going to win the approval of a licensee.

As I think about the varied challenges of influencing the probability of adoption, I'll share my thoughts in subsequent posts.  Even if we can't predict the future, we can influence the probability distribution of possible futures.