A Tale of Two QuotesPosted: June 30, 2014
“I don’t like using words like ecology to explain in shorthand a rich and useful organizational concept for business. For one, these soft edged metaphors turn off a lot of hard edged business people who occupy a large portion of the organizational power structures, especially in operations and manufacturing.. For another, nature has the patience and resilience to absorb a lot of failed or marginal experiments that would terminate a business enterprise…. Simply referencing the metaphorical links and then postulating a new business paradigm doesn’t appear successful in communicating with most people who have operational concerns.” Rick Dove, Response Ability: The Language, Structure, and Culture of the Agile Enterprise. John Wiley and Sons, Inc., 2001, p 134.
A Harvard business school alumnus responding to the intra-Harvard debate between Jill Lepore, an historian, and Clay Christensen, a business school professor, about theories of disruptive technologies is quoted as saying “We don’t learn laws of business. We learned stories.” John McDermott, Career Advice from Marina Keegan, Financial Times (US), June 26, 2014.
Rich Dove’s book is about agile manufacturing but also much more. In the next blog in this series I shall introduce a few of Rick’s concepts and discuss whether they can throw more light onto how innovation ecosystems may become agile; an ability to adapt rapidly to changes and shocks.
Meanwhile, let’s (1) gently dissect these two quotes, and (2) suggest what practical results the complex adaptive systems theory of innovation ecosystems predicts which will be of value to the most skeptical operations person. We only have space to begin here, and will continue next time.
In the above “.. throw more light onto..” is itself a metaphor; we are not literally going to use a flashlight. Francis Thompson (1859-1907) in his poem Contemplation uses the metaphor which nudges us into a sense of contemplation.
“This morning so I, fled in the shower,
The earth reclining in a lull of power”
Much has been written by philosophers about how the hearer decides to seek a nonliteral meaning in a metaphor, makes us attend to some likeness between two things, conveying an idea to open different frames of mind beyond the more straightjacketed analogy (A is like B, freshness after a rain shower is like the earth resting).
Thus, we are saying that a metaphor can help express a theory, but first we should be sure that we have some common ground as to what is a theory. Thomas Kuhn, a philosopher of science, set out criteria (although not necessarily precise ones) to help chose a theory or chose from competing theories. He stated that a theory should be:
1. Accurate, in that it empirically adequate with experimentation and observation.
2. Consistent, namely internally consistent, but also externally consistent with other theories.
3. Broad Scope, with consequences extending beyond the phenomena it was initially designed to explain.
4. Simple, using the principle that the simplest explanation is usually the better one.
5. Fruitful, in that any theory should predict new phenomena or new relationships among phenomena.
Others might add one more requirement, that of “falsifiability” or proving a theory to be wrong by making an observation or conceiving an argument which proves a theory statement to be false.
Or, put more succinctly, a theory must explain and predict. Without prediction a theory is worthless. I suggest we should hold stories and other narrative forms to Kuhn’s five-test scrutiny. Narratives have become a popular (as the Harvard graduate stated), and effective, metaphorical explanation of events – for example, in complex adaptive systems, where a mathematical description is not possible. Can narrative predict as well as explain? Let’s begin to investigate by applying Kuhn’s tests to complex adaptive systems concepts introduced in recent blogs in this series. For example:
Emergence is an outcome of self-organization in the form of a new level of order in the system that comes into being as novel structures and patterns which maintain themselves over some period of time. Innovation springs from emergence. Emergence may create a new entity with qualities that are not reflected in the interactions of each agent within the system. Emergent organizations are typically very robust and able to survive and self-repair substantial damage or perturbations.
Kuhn’s tests 1 through 3 are easily satisfied, whereas #4 might be more problematic – depending on how we define ‘simple.” Complex adaptive systems theory has been especially fruitful (test 5) as we described in April’s blog Games of chance? Cause and effect in innovation ecosystems Part 2 http://innovationrainforest.com/2014/04/21/games-of-chance-cause-and-effect-in-innovation-ecosystems-part-2/ which reported the work of Sharon Zivkovik on social entrepreneurship. Prof. Zivkovik reports on how complex adaptive systems theory predicts, under certain conditions ” interactions between independent agents produce system-level order as agents interact and learn from each other, change their behavior, and adapt and evolve to increase their robustness. Empirical research has shown large complex systems such as communities require enabling conditions to be created in order to maintain the coordination required for emergence self-organization and adaptive capability.”
In T2VC’s recent innovation ecosystems work with Medellín, Colombia, similar behavioral changes and adaptations occurred by adjusting certain conditions (this case example will appear in a future blog).
Another concept is:
If new emergent order is creating value it will stabilize or legitimize itself, finding parameters that best increase its overall sustainability in the ecosystem. Stability results by slowing the non-linear process that led to the amplification of emergence in the first place.
We don’t have space this month to go into detail, but discussions of empirical studies on networks scattered among several previous blogs, such as the stabilizing effects of weak links, could be shown to meet all five requirements.
I hope readers of this blog series will now at least be beginning to understand that Rainforest innovation ecosystems are complex adaptive systems, and that the Rainforest metaphor expands our thinking. Philosophers have postulated that “even a quite definite speaker intention does not finally determine the meaning of a metaphor’ and that “the interpretation of the light the metaphor sheds on its subject may outrun anything the speaker is thought explicitly to have in mind.” An Irenic Idea about Metaphor, Philosophy, Vol.88, No.343, p 25. In the Rainforest case the metaphor in fact preceded the more detailed analysis of the complex adaptive systems model. The metaphor worked.
Next time, more on agile innovation ecosystems and more tests of theory and predictions.