There is not much written in this article that hasn’t been written about numerous times before, but it does provide a concise summary of many of the issues large companies face and some of the reasons they are not good at disruptive innovation.
After describing the problem, and then posing the intriguing question “What if there was a way to test and optimise our assumed problem and solution before investing in subsequent development?” one expects the revelation of, or at least a proposal for, something new and different. But what the author describes, low cost experimentation using iterative testing and learning, has also been extensively written about and is being widely adopted throughout the business world.
A more interesting answer to the question the author puts forth would be something like the new tool “Predictive Testing of Opportunities (PTO)” that is based on the Growth Science predictive analytics platform that uses AI and big data to accurately predict the success or failure of new opportunities early in the front-end.
There is, however, one intriguing statement buried in the article:
More and more people in the corporate innovation space are wisening (sic) up to the fact that design thinking, while incredibly powerful when it comes to testing for problem solution fit, is simply not and never will be enough when it comes to testing for business models and product market fit.
The current frenzy about design thinking often overlooks where it fits into the panoply of methods, tools, behaviors, processes and mindsets required to do innovation in today’s world. A deeper and more thought out exploration of this question would have been welcome.