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Data-Driven Innovation: How to Establish an Effective Metrics Framework

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Read more about author Vinny Kaimal.

Innovation is big business. Whether it is R&D, talent, or physical infrastructure – see the numerous fancy “innovation centers” that are rolled out on a yearly basis – companies pour millions of dollars into their innovation efforts annually. But there is one key difference that separates innovation from every other department in an organization: metrics.

Innovation is the lifeblood of an organization and requires a huge amount of money and time to get right. The problem is that unlike sales, finance, or HR, where data is the “be-all and end-all,” very few innovation departments have any sort of a functional innovation measurement system. It is likely surprising for outsiders to hear, but despite “innovation growth” being bandied about ad infinitum in corporate communications and executive talking points, a vast majority of innovation departments have no meaningful way to measure their success and progress. Instead, they rely on a grab bag of metrics that are borrowed from other departments and not fit for purpose or don’t have any sort of fixed framework to serve as a guidepost for their innovation efforts and decision-making. This is obviously problematic, and not only means that companies are wasting huge sums of money, but that they are almost certainly missing out on potentially paradigm-shifting innovation opportunities on a regular basis.

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But it doesn’t have to be this way.

Measuring innovation effectively is not impossible. In fact, it is very much possible. However, to do this, organizations first need to ring-fence key areas of their innovation infrastructure and gain insight into each in order to build a holistic view of their innovation ops.

With that in mind, here are a few fundamental layers of innovation ops “health” that businesses should be measuring in order to drive sustainable innovation success.

Pipeline Health

Measuring pipeline health is the most basic and mundane area to measure, but it is essential nonetheless. In order to truly find innovation success, companies need to have a firm grasp on exactly what their innovation pipeline looks like. While the metrics around the health of an innovation pipeline are fairly straightforward, many companies fail to even implement these basic KPIs and do not have a good grasp on how many opportunities they have, how long it takes a project to move from one phase to the next, and other factors that would otherwise seem to be no-brainers to keep track of. Therefore, by getting more insight into your innovation pipeline not only will your organization become more informed, but it will also likely move a step ahead of many of its competitors.

Portfolio Health

Once foundational pipeline oversight has been established, companies then need to begin synthesizing these findings and baking in further insights to see how each cog fits into their short-, medium- and long-term innovation goals. Essentially, portfolio health is about measuring how closely your innovation portfolio matches your company’s strategic intent. The most successful innovation departments have a clear sense of not just how each project is fairing, but how it ties into their entire innovation “portfolio.” Sustainable innovation is about more than just one-off projects either making it or falling flat. It is about building an entire ecosystem of projects that feed into one another and allow for simultaneous, widespread perpetual growth. By gaining clear insights into their innovation portfolio, companies can make better decisions when it comes to balancing risk and also build a repository of historic learnings and insights that can aid future innovation projects.

System Health

System health by far is the most amorphous and challenging aspect of an innovation apparatus to measure. Pertaining to the higher-level thinking around an organization’s innovation operations, system health looks into more intangible items such as: 

  • How closely are executives engaging with innovation? Is the governance process working well?
  • What is the quality and fit of the innovation team members to their specific roles?
  • How well are various components working together (upstream vs. downstream, or internal vs. external knowledge networks)?
  • Are the company’s innovation ambitions commensurate with the resources made available?

These are all things that are perhaps tougher to “nail down.” That of course does not mean that they can’t be, but rather that it may require a more novel and flexible approach to get right in comparison to pipeline or portfolio measurement. Despite its apparent nebulousness, maintaining a strong working view of innovation system health is hugely important given how central it is to the strategic vision of a company’s innovation vision.

Conclusion

Innovation measurement may seem intimidating. But given how rapidly the world is changing today, and how business intelligence is becoming more central to performance, organizations simply can no longer afford to not have a data-driven approach to innovation in place. If not, organizations stand to lose a significant amount of ground in the marketplace which they may never get back.

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