Disruptive Vs Incremental Innovation

In a recent debate going on at Economist http://www.economist.com/debate/days/view/667
the topic is

which is better - Incremental Innovation - The Japanese Model
OR Disruptive Innovation - The "Western" Model

I posted my views as

Dear Sir,
The natural way a system changes is by evolution based on adapting to the change. However, it is clear the best way to adapt to change in the changing environment is to be the creator of change that one desires. As M.K. Gandhi said, "you being the change that you want to see in the world" - according to me there is no other better definition of Innovation than this. Best model for innovation is neither Japanese nor Western (read American). Here is the model - 1. define the key functions that the system need to deliver 2. define the IDEAL system delivering that function(s) - no cost, no resources and least complex structure and no harm to environment yet the key functions are delivered 3. start looking at options of making the ideal system - since it is ideal system it will not be achievable - look at the various ways to achieve as close to ideal system as possible 4. explore all paths in a set based manner - where you pursue sets of alternatives simultaneously as for example Toyota does 5. continue by Elimination of the weakest - not choose the survival of the fittest 6. Some paths will reach to the ideal system much sooner.

So in my opinion - this is the model Create an Ideal system (which may be disruptive) - but achieve it through multiple explorations simultaneously as you do not know which path connects with which future.

The above combines two very potent methods - one is the Russian TRIZ (theory of inventive problem solving) and other from lean product development called Set Based Concurrent Engineering. We call these along with systems thinking as Lean Inventive Systems Thinking (LIST)

It is integrative - achieve disruption through simultaneous evolution

Evolution and Emergence of NEW

1904 Hugo De Vries


"Natural Selection may explain "The Survival of the Fittest", but it can not explain the ARRIVAL of the Fittest"

A Great Mystery of EVOLUTION - Emergence of Novelty!

Does Strategy Matters?

Is this the death of strategy? Does strategy matter?

We always are in evolutionary mode - organizations, businesses and all of us evolve - in our life period, in multiple generations - does it really matter -

What is your organization's Strategy - right now! It is very difficult to answer this

Most of us will say - well - My organizations strategy so far is Blah Blah blah - but what is my strategy now - well - I don't know!

Multiple Random Starting Points - Can they help Faster solutions

Genetic Algorithms are part of evolutionary computing that help in solving problems using genetics as a methophor. The GAs have been part of heuristic optimization techniques which includes simulated annealing, tabu search, Ant Colony Optimization etc.
The GA work on simultaneous search for optimal solution in a search space through the metaphor of mutations, reproductions, genetic inversions, cross-over etc. The solution variables are pre-defined and their ranges are also pre-defined which creates the boundaries of the search space. The solution variables are organized as bit-strings that are akin to chromosomes.
At the start of the search - a set of random bit-strings are created (it has to be random) as starting points in a play of evolutionary population simulation. Just like population reproduce, mutate, etc, the solutions population is run through multiple rounds of reproduction etc simulations called generations. Each generation chooses the fittest solutions to create further offsprings. The fitness function acts as the environment where many solutions gets killed in each generation but fittest solutions are propagated to the next geneartion. If one chooses the right fitness function and have proper genetic operators, it is likely that population converges rapidly to the global optimal solution rather than getting stuck in the local optimas.
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READER MAY SAY - OK WHATS MY POINT!
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Well, Ideation/ problem solving is exactly like this. Can we use the GA metaphor to create multiple starting points (may be random) to converge to solutions through a series of generations - there may be many questions - for example what is the fitness function? How will one represent the idea bit string and how will anyone know the variables upfront?

If we start thinking using TRIZ Inventive Prinicples and TRIZ Trends and combine them with other inventive principles (Vedic Mathematics) and then use the GA engine search for Ideas, I think we have something here!

Lean Product Development, Theory of Evolution

The above picture from my paper at last year's TRIZCON explain's the Lean Product Development - the way evolution should be looked at as "Elimination of the weakest" rather than "Survival of the Fittest".

As we start looking at evolution as elimination of the weakest, may be the competition to be the so called best may slow down and world may actually be less stressful, well, may be!