Shipulski On Design

Evaluation of innovation efforts is a hot topic. Sometimes it seems evaluating innovation is more important than innovation itself.

Metrics, indicators, best practices, success stories – everyone is looking for the magical baseline data to compare to in order to define shortcomings and close them. But it’s largely a waste of time, because with innovation, it’s different every time. Look back two years – today’s technology is different, the market is different, and the people are different. If you look back and evaluate what went on and then use that learning to extrapolate what will happen in the future, well, that’s like driving a Formula One car around the track while looking in the rear view mirror. You will crash and you will get hurt because, by definition, with innovation, what you did in the past no longer applies, even to you.

Here’s a rule – when you look backward to steer your innovation work, you crash.

When you compare yourself to someone else’s innovation rearward looking innovation metrics, it’s worse. Their market was different than yours is, their company culture was different than yours is, their company mission and values were different. Their situation no longer applies to them and it’s less applicable to you, yet that’s what you’re doing when you compare yourself to a rearview mirror look at a best practice company. Crazy.

We’re fascinated with innovation metrics that are easy to measure, but we shouldn’t be. Anything that’s easy to measure cannot capture the nuance of innovation. For example, the number of innovation projects you ran over the last two years is meaningless. What’s meaningful is the incremental profit generated by the novel deliverables of the work and your level of happiness with the incremental profit. Number of issued patents is also meaningless. What’s meaningful is the incremental profit created by the novel goodness of the patented technology and your level of happiness with it. Number of people that worked on innovation projects or the money spent – meaningless. Meaningful – incremental profit generated by the novel elements of the work divided by the people (or cost) that created the novel elements and your level of happiness with it.

Things are a bit better with forward looking metrics – or leading indicators – but not much. Again, our fascination with things that are easy to measure kicks us in the shins. Number of patent applications, number of people working on projects, number of fully staffed technology projects, monthly spend on R&D – all of these are easily measured but are poor predictors innovation results. What if the patented technology is not valued by the customer? What if the people working on projects are working on projects that result in products that don’t sell? What if the fully staffed projects create new technologies for new markets that never come to be? What if your monthly spend is spent on projects that miss the mark?

To me, the only meaningful leading indicator for innovation is a deep understanding of your active technology projects. What must the technology do so the new market will buy it? How do you know that? Can you quantify that goodness in a quantifiable way? Will you know when that goodness has been achieved? In what region will the product be sold? What is the cost target, profit margin and the new customers’ ability to pay? What are the results of the small experiments where the team tested the non-functional prototypes and their price points in the new market? What does the curve look like for price point versus sales volume? What is your level of happiness with all this?

We have an unhealthy fascination with innovation metrics that are easy to measure. Instead of a sea of metrics that are easy to measure, we need nuanced leading indicators that are meaningful. And I cannot give you a list of meaningful leading indicators, because each company has a unique list which is defined by its growth objectives, company culture and values, business models, and competition. And I cannot give you threshold limits for any of them because only you can define that. The leading indicators and their threshold values are context-specific – only you can choose them and only you can judge what levels make you happy.  Innovation is difficult because it demands judgment, and no metrics or leading indicators can take judgment out of the equation.

Creativity creates things that are novel and useful while innovation creates things that are novel, useful and successful. Dig into the details of your active technology projects and understand them from a customer-market perspective, because success comes only when customers buy your new products.

Image credit – coloneljohnbritt

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