Innovation is an evolutionary process. Here is John explaining what that means:
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Generic evolutionary processes have three parts – generation of variety, selection, and replication. This maps on to the three steps in the innovation value chain. The Innovation Value Chain also has three steps – idea generation, idea selection and execution, and idea diffusion. The connections between the two models should be fairly apparent!

Innovation as evolution has some interesting implications, including:

• The ideas that spread are often not optimal solutions to problems, they simply happen to be the best solutions currently available. In other words, our innovations just have to be good enough, not perfect.
• Consequently, the idea that we’re not looking for a perfect execution of our new ideas is a strong argument in favour of taking a build, launch, tweak approach to getting our new ideas out there. We’re most likely to get to the best solutions to the problems we are interested in through an iterative process, rather than through pure development.
• This leads to the last point, which is that the evolution of our great ideas is built on collaborative networks. The sooner we can enlist the help of our network (customers, partners, suppliers, etc.), the more likely we are to come up with the best version of our great new idea.

Another important thing to consider is that innovation creates variation. And the more variation we have in the way that our organisations operate, the better our ability to adapt to a changing environment.

Here is a series of interesting quotes from The Power of Positive Deviance: How Unlikely Innovators Solve the World’s Toughest Problemsby Richard Pascale, Jerry Sternin and Monique Sternin:

It is an empirical fact that most of the world’s cities live forever.’ Corporations, on the other hand, live half as long as the average human being. The explanation has to do with the self-organizing and emergent nature of cities as contrasted with companies. True, cities may cycle between decline and ascendance. But the complex interplay between a city’s heterogeneous elements fosters continuing variation and adaptation. Corporations, in the name of efficiency, suppress variation by “getting all the ducks in line.” To optimize productivity, they evolve highly refined and internally consistent operating systems. Payoff results-as long as the music lasts.
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But in the face of nontraditional competitors or major environmental discontinuities, all that streamlining and reengineering limits diversity, suppresses self-organization by those closest to the disruptive change, and curtails a bottom-up emergent response to cope more effectively. We witnessed this at Genentech and Merck. Nothing fails like success. Overadaptive organizations become inflexible. Disruptive change leaves them as helpless as a beached whale.
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The problem is not exclusively technical and requires behavioral or/and social change. • The problem is “intractable”-other solutions haven’t worked. Positive deviants are thought to exist. There is sponsorship and local leadership commitment to address the issue.

This is similar to the idea that Jeffrey Phillips advocates – that efficiency and innovation are two quite different outcomes, and you can’t achieve both at the same time very well.

Efficiency by definition reduces variation. And yet, variation is the one thing that allows us to adapt to uncertain, changing environments.

The Positive Deviance approach is interesting. Here is a description of it:

Positive Deviance is based on the observation that in every community there are certain individuals or groups whose uncommon behaviors and strategies enable them to find better solutions to problems than their peers, while having access to the same resources and facing similar or worse challenges.

The Positive Deviance approach is an asset-based, problem-solving, and community-driven approach that enables the community to discover these successful behaviors and strategies and develop a plan of action to promote their adoption by all concerned.

In other words, instead of ignoring outliers as we usually do, we seek them out. Once we’ve found them, we try to observe how they are able to perform well in highly constrained circumstances. Then we take what we learn and apply it within the wider population.

Innovation drives variation, and variety is the key to successful adaptation and survival.

That seems like a pretty good argument for supporting innovation to me.