Cognitive approach to innovation
A while ago, I wrote an article on Push and Pull innovation (http://bit.ly/3pUhkaE). It received plenty of attention and in this article, I want to explore one of the central premises of innovation, problem solving.
Whether it is push innovation or pull innovation, it involves one important factor, matching a problem and solution. In push innovation, organizations seek problems that their solution can solve. On the other hand, with pull innovation, they seek solutions to the problems.
Writing on the cognitive process of human problem solving, Wang and Chiew (2008), identify 8 different approaches to problem solving
Direct facts – finding a direct solution path based on known solutions.
Heuristic – adopting rule of thumb or the most possible solutions.
Analogy – reducing a new problem to an existing or similar one for which solutions have already been known.
Hill climbing – making any move that approaches closer to the problem goal step by step.
Algorithmic deduction – applying a known and well-defined solution for a problem.
Exhaustive search – using a systematic search for all possible solutions.
Divide-and-conquer – solving a whole problem via decomposing it into a set of subproblems.
Analysis and synthesis – reducing a given problem to a known category and then finding particular solutions
Some of these methods are regularly applied in operational problem solving. However, problem solving for innovation is quite different.
Most operational problem solving is incident based, the trigger for problem solving may be an unacceptable event, an operation failure, quality failure, safety failure or the need for improvement. Problem solving for innovation on the other hand tends to explore the unknown, needs and requirements that are not clearly articulated, requirement for new knowledge, uncertain cause and effect and so on. Problem solving in such cases generally involved multiple iterations and experiments, continuous learning from these experiments and discovery of new knowledge.
Recently, I had an epiphany, learning about cognitive and meta cognitive learning principles from my wife, a math teacher, who applies cognitive problem-solving principles to teach middle and high school children. She introduced me to Polya’s seminal work on problem solving techniques, a book he wrote way back in 1945, How to Solve it (Polya, 1945).
I believe innovation experts can learn a lot from what Polya taught teachers to ask students questions. He taught 4 basic principles. I have added a number of elements to the original questions of Polya here though.
Understand the problem
This is obvious and yet rarely do organizations (including consultants) do a good job of identifying. Polya recommends asking the following questions
Do you understand every word used in the problem statement?
What do you need to find? What is the unknown?
What are the conditions? Is there sufficient information about them? Do you know the “killers”?
Can you restate the problem in your own words? Can you draw a picture of the solution?
Devise a plan
There are multiple ways of solving every problem and it becomes imperative to explore. There are multiple strategies one could adopt to devise a plan
Find the connection between the data and insights you have available and the unknown. Are there related or auxiliary problems that exists if the connection isn’t visible?
Take an anthropological approach, go and engage the end user. What job does the user want to get done? Find out if you have seen the same problem or a slightly similar problem before
Look if a similar problem has been solved by another industry? Can you use that method or philosophy?
Can you restate the problem in a very different way? Can the user job be done in a significantly different way?
While you are looking atthis problem, is there some related problem or challenge that you can solve? Can you solve part of the problem?
Develop hypothesis regarding the problem and test them. How important is it for the customers to solve the problem? Will they buy your solution?
Develop a customer discovery process. Who are the valid customers? Can you identify subsets of customers? Can you prioritize?
Carrying out the plan
Executing the plan effectively is something many struggle. Innovation execution requires careful consideration of not just solution development, but also the business model impact. Consider the following
Have multiple teams work on multiple concepts simultaneously. Integrate the concepts from different teams to come up with newer concepts. Learn from each team
Adopt fixed, fast cycles and iterate multiple times. Shorter the cycles the better it is. Never wait till perfect solutions are developed, you will probably never develop a perfect solution in a single iteration
Carry out multiple experiments with real customers. Take feedback and refine solution multiple times.
Look back at the process
Every innovation and problem-solving exercise is an opportunity to generate knowledge and insights. Examine the solution and the process
What are the learnings? How has it been documented and disseminated within the organizations?
What IP can you generate? What spin offs can be executed?
Can some of the failed experiments solve other problems?
What can you learn from all the hypothesis that you tested?
I hope this process is useful. For further discussion do reach out to me at: firstname.lastname@example.org or WhatsApp me: 9791033967
Krishnan is a leading innovation consultant and focuses on helping people and organizations innovate and build capabilities for innovation. He brings over 25 years of experience in the industry and consulting.
Wang, Y., & Chiew, V., On the cognitive process of human problem solving, Cognitive Systems Research (2008)