“Prediction is very difficult, especially about the future.”― Niels Bohr
In my previous role leading front end innovation in a large company, I routinely gave talks to corporate groups about innovation not only as a practice, but also a theory, a methodology, and a mindset. Being that this company is perennially ranked as one of the most innovative companies in the world, I always felt the need to explain why I was going to talk to them about what they believed they already knew. To kick things off I would show the audience a chart and ask them which of their divisions I was describing. The anonymous chart depicts 5 years’ worth of launched programs. The majority, 61%, were cancelled within a year after launch. Another 11% made it through the first year but were cancelled after that. Only 28% were still alive at the time the chart was made. I’d ask, “Who thinks this is your division I’m talking about?” Between sideways glances several hands would raise. Then I’d reveal the punchline…the “programs” were 5 years of Fall season primetime TV shows from the big networks. There was laughter and an audible sigh of relief in the room because I wasn’t about to single anyone out, but the situation looked and felt familiar to them.
Is it shocking to think of the enormous amounts of money and time that amounted to very little return from these programming investments? Surely TV networks understand their customers. Surely they have no interest in losing money or wasting time. Surely all the people involved in the conception, production and delivery of these shows wanted to work on something successful (I can only imagine that they did). How could it be that within a few years of launching all these new products 73% of them were dead? What happened?
Think about your company. Do you know your innovation success rate? Do you know how long your new product launches survive? Do you know how many of your innovation projects are killed before they get to launch? Do you know why they die? I’ll bet that each killed project has its own unique tale about management that didn’t support it, technology that never delivered, markets that shifted, and the list could go on.
I suspect that there is no accepted commonality between all a company’s innovation failures. There is, however, something they all have in common. They are systems in competition with other systems for resources (internally) or customers and revenue (externally), and systems can be modeled via computer simulation. Through computational modeling to study these complex systems, we may discover more objective and accurate insights. This understanding can be hard to internalize when innovation, even at companies renowned for it, is still imagined as a mixture of one-part solid market understanding, one-part deep customer insight, combined with heavy doses of creativity and intelligence (and perhaps a bit of luck). Thinking of innovation as a system to model can be threatening to some, particularly when the mythology of the brilliant inventor is part of a company’s DNA, but these concepts are not in conflict. The brilliant ideas come from brilliant people, yet the brilliance of the idea does not corollate with business success (I think any of us who have lived through a crushing project cancellation can agree).
So, I leave you with this. Innovation is a practice, a theory, a methodology, a mindset, and also a science. Launching a new product is a many-body problem (to borrow from physics) …a system of interacting entities. Investigating innovation scientifically helps to explain why sometimes the best solution doesn’t win and why we often fail despite everyone’s best efforts. It’s not just luck!