I suspect the vast majority of innovation professionals would agree that measuring what you do is important. That may well be a statement of the blindingly obvious, but the debate diverges dramatically when considering what is actually done. Luis Solis of Imaginatik wrote a good post here on Innovation Excellence clearly distinguishing between input and output metrics. I’d like to build on Luis’ article by adding four other considerations to the debate.
First, it’s important to distinguish between LEADING and LAGGING metrics. Lagging metrics are history, they tell you what you’ve already done. For example, the percentage of sales from new products is a lagging indicator; it’s something you can’t change. However looking at the potential value of new products in your pipeline is a leading indicator. It predicts the future and if you’re not meeting your projected targets, you should still have time to do something about it.
In terms of driving performance, leading metrics are much more valuable to managers in charge of innovation. They are the areas that should align with incentives and that should drive portfolio and project management. Lagging metrics are much more relevant to reporting (see below).
Secondly, PROCESS metrics can be very useful, helping you understand your progress towards meeting your goals. For example, how many of your projects are currently planned to meet their targets? By the way, this should never be too close to100%, as it shows you’re not being aggressive enough (another blog post…..). Process metrics enable you to optimize your resources by applying them to the areas in need of the most attention.
Thirdly, REPORTING metrics relate to the information that people further up the organization need to know. For example it’s difficult to get away from reporting the percentage of sales from new products because it can be useful to external analysts. Another example could be metrics based on patent applications and granted patents, as this is often interpreted as a measure of how innovative an organization may be (not by me, by the way).
It’s important to understand why you measure what you do. You should always understand whether it’s input or output; leading or lagging; process; or measured because you need to report it.
That’s where the final point comes in – the FREQUENCY of measurement. Planning, considering and collecting data all take time and effort. If you’re measuring the activity of people in fifteen-minute increments using seventeen metrics and reporting weekly, your organization will be sucking resource away from what really matters – delivering. It also won’t be a fun place to work.
Remember accuracy is more important than precision in this regard. I would recommend a measurement frequency as low as you can get it without losing the real value inherent in metrics, particularly those that help you make decisions.
Measuring things is a crucial activity in innovation, and doing it right can significantly improve your performance, just make sure you get the balance right.
Kevin McFarthing runs the Innovation Fixer consultancy, helping companies to improve the output and efficiency of their innovation, and to implement Open Innovation. He spent 17 years with Reckitt Benckiser in innovation leadership positions, and also has experience in life sciences.