It’s been said that “experience” is a wonderful thing. It allows you to recognize your mistakes when you make them again. Metrics can be like that, especially when applied to innovation. Informative, but not so helpful. That’s because innovation metrics often suffer from Why, When and What problems.
The “Why” problem: One of the most popular innovation metrics is the vitality index… % of total sales derived from new products (usually introduced in the last 3 or 5 years). This is a worthwhile metric, but it doesn’t tell you why your % is going up or down, does it? Sure, you can explore which new products contributed to the metric, but what’s the underlying reason you had more or fewer of these products? Such metrics can become more of a spectator sport than a participant sport.
A race team that counts wins—instead of pit crew times and engine torque—stops winning.
The “When” problem: Your home heating has a “feedback loop” in it. You turn up your thermostat, and when the temperature rises to the set point, your furnace quickly shuts off. Imagine if it took 8 hours before your thermostat got the message your house had warmed up. Many innovation metrics have very long feedback loops. If you experiment with new ways to understand customer needs in the front end—and all your metrics occur after product launch—your feedback loop could be measured in years.
The “What” problem: It’s not enough to measure your innovation results; you also must measure your innovation capabilities. Most companies measure the former, but few understand if they are truly getting better at understanding customers’ deepest needs, assessing competitive alternatives, creating data-driven value propositions, etc. A race team that counts wins—instead of pit crew times and engine torque—stops winning.
You need both ultimate and intermediate innovation metrics. Ultimate metrics—such as the vitality index mentioned earlier—are important tools because they let a company measure whether it is winning over time. But we’re going to focus on intermediate metrics in this newsletter, because intermediate metrics are…
Have you ever pulled out a tape measure and simply started measuring things around your home? Of course not. Every time you measure something you have a purpose. The purpose for the metrics we’re exploring in this newsletter is profitable, sustainable, organic growth. Specifically, we’ll look at innovation metrics to measure success in the front end of innovation… which in turn leads to profitable, sustainable, organic growth.
We’ll divide these intermediate metrics into two groups: Results metrics and Capabilities metrics. At AIM, we’re invested in helping clients learn new skills while working as teams on real projects… so we refer to these metrics as “New Product Success” metrics and “Learning Success” metrics. The former tells us if a new product project will succeed; the latter if employees are building needed skills so that future new product projects will succeed.
At the end of this article, you can request a PowerPoint presentation that describes 12 intermediate innovation metrics. Some of these are specific to the New Product Blueprinting process, but I think you’ll see they can be easily adapted to other approaches. Rather than focus on each of the 12 metrics here, let’s build a “metrics taxonomy” or classification system. First, consider two types of “New Product Success” metrics.
You have two options: 1) Ask for pricing decisions. 2) Understand customers’ pricing decision making.
If your intermediate innovation metrics say you’ve got a bunch of teams doing the right work on the right projects, you’re probably headed for good growth over the next few years. But how can your company become a growth juggernaut over the long haul? How can you change its DNA, its very growth culture? You need to embed new behavior, and this is where “Learning Success” metrics help.
Never rely on Brownian motion for change management.
I am amazed by executives that expect employees to deliver better results (e.g. sustainable growth) without investing in company-wide tools and skills to achieve those results. Either nothing changes, or employees run off changing things in separate directions. Never rely on Brownian motion for change management. It’s much better to be intentional about what new behavior is needed, and then use two types of “Learning Success” metrics to monitor progress.
Ultimately, we are each responsible for what we choose to learn.
Some of these “Learning Success” metrics can be subjective. But please don’t underestimate their importance. These metrics don’t just change your projects: They change your company.