Executing innovation at scale is a complex task and there’s plenty of advice out there on how supporting structures, whether physical or digital, should be architected, staffed, resourced, implemented, and continuously improved (see the ISO’s recommendations here). The advice is equally abundant when it comes to the steps or actions innovation professionals need to take, or the gates through which they need to pass on their journey from strategy development and consultation with relevant audience groups, to partner management and project execution.
Underpinning this abundance of activities is the perpetual question: Are we executing well enough to the highest standards, with the highest impact while minimizing costs and maximizing returns?
In my experience, adequate monitoring and documenting of the progress and overall “worth” of an innovation activity are some of the most critical yet least understood topics. Here, we offer you some guidance when it comes to measuring your progress with innovation based on the many delightful conversations I had with innovation leaders in 2022 as well as a dedicated Industry Challenge Session at the 9th World Open Innovation Conference in Eindhoven.
I can name at least three reasons why measuring innovation is crucial.
First and foremost, metrics promote behavior. For example, a company might decide to calculate and monitor revenue and profit generated from new products or look at what percentage of new projects are hitting their targets. As a result, teams will be more focused on helping new projects succeed and winding up the underperforming ones promptly.
Second, metrics for innovation can function as a stethoscope or a glucose monitor — to help diagnose an underlying condition or spot a trend. For example, if there are few submissions on an open innovation portal despite numerous visits to the webpage, reviewing the figures regularly can help to identify any bottlenecks.
Third, metrics are valuable to help reflect on and justify the activity’s existence. If a program manages to support the diffusion of a technology, succeeds in attracting promising startups, or produces ROI generating ideas, it’s probably wise to continue. In the absence of good output metrics, justifying the investment becomes hard.
What steps should you take to promote the right behaviors, acquire dynamic insights into your innovation activity, and make any necessary adjustments?
Ignorance might be bliss in some circumstances, but definitely not when it comes to managing your corporate innovation program. The more you know, the more targeted your approach can be.
Your innovation activity (most likely a program) is unique in its makeup. It has its own purpose or goal and its specific target or addressee group(s). It is probably led by a specific function in your organization (often procurement, R&D, marketing, or HR) and is designed to facilitate a unique type of knowledge exchange or flow (insights, ideas, proposals, new contacts etc.).
Finally, there is a very specific set of factors motivating the target group to exchange information with you and a designated legal framework to ensure that what you are transacting stays safe.
Before creating a list of metrics, document these particularities and ask yourself:
Use these questions to have an honest and informed discussion about your goals and the uniqueness of your engagement and to identify some anchor points. Chances are that someone has already tried what you would like to try and has documented the process and results.
Tip: Consider reading case studies or academic articles to uncover anecdotes, inspiration, and statistics regarding the effectiveness of metrics. I’ve included a few in the section that follows.
As you start putting together a list of relevant metrics, let the reference level guide you. Start by thinking about the end goals and how those goals trickle down the organization. Next, look for ways to gauge your progress with those goals at the national/inter-organizational (macro), organizational (mezzo), department/team (micro), and individual (nano) levels. Here are some examples of typical goals and metrics that organizations, consortia, and even countries are looking at:
Level: National/supranational
Sample goal: Strengthening the national or regional innovation/ startup ecosystem.
Possible metrics:
Reading tip: Challenges for the Measurement of Innovation Ecosystems
Level: Interorganizational
Sample goal: Strengthening ecosystem of partners in a given industry
Possible metrics:
Reading tip: Open Innovation Maturity Framework
Level: Organizational
Sample goal: Become the most innovative organization in the country/region/industry
Possible metrics:
Reading tip: The Danish Innovation Index
Level: Team or department
Sample goal: Change culture of the R&D department so that you can become an industry leader
Possible metrics:
Reading tip: The Implementation of Innovation Metrics: A case study
Level: Individual
Sample goal: Promote innovation habits/build confidence in innovation methods
Possible metrics:
Reading tip: Predictors of individual-level innovation at work: A meta-analysis.
Another way to think about metrics is by phase.
In the early setup, you might consider input metrics: number of new internal insights collected, number of innovation activities, number of ideas posted, etc. Next, as the program matures, you might incorporate throughput metrics. Companies look at the speed of testing their hypotheses, speed of new capability acquisition, number or ratio of employees and leaders familiar with innovation or NPD techniques, time to profit, engagement levels, and more.
Finally, in well-established programs, output metrics could provide an indication of how much the innovation is contributing to the business. To this end, we might look at the make-up of the pipeline (how many ideas per horizon), number of implemented ideas, quantifiable change in behavior, number of new partners, ROI, cost savings, etc.).
One of the frequent pitfalls innovation professionals routinely fall into is the complexity trap. Designing a dashboard of metrics for your program can be overwhelming and you might be tempted to keep adding information to it. However, keep in mind that not all that we can measure, we can (actively) manage.
Innovation is fundamentally a human-centric pastime and it’s our task to understand the ways in which those that constitute the innovation engine are “predictably irrational.” Factor this aspect into your approach to measuring a program, a team, or an individual’s performance.
In short, and in addition to reading up on behavioral economics, do your best to keep it simple. Select five to seven key metrics to begin with, describe them, make them visible, and start collecting some data. Consistency here is key, as is the observation that no measurement system is set in stone. Our task is to fundamentally understand the strengths and weaknesses of the innovation activity in scope and to design an adequate intervention to correct the course. Here are some questions to guide you:
Do you use software for your innovation management efforts? Even generic enterprise software can help you monitor your program’s health and understand where it might be failing. When you send out messages to your staff, check the open rate. When you invite people to visit/participate in a new campaign/channel, check the number of visitors or number of inquiries received. When you are launching a call for proposals, understand the demographics of the participants. Built-in metrics are extremely useful and can serve as a starting point.
Additionally, launch a short survey and ask your team: What is the most ridiculous innovation metric you’ve heard of and/or have been asked to report? Why? Open conversations can give you a rare glimpse of where your organization’s mind is at that particular point in time and what experiences have contributed to that mindset.
To keep the conversation going and to establish a safe space to discuss progress try:
Innovation metrics (from which we derive KPIs) are important for a business because they serve many needs. The right measures can help formulate powerful hypotheses, promote innovation-rich interactions and productive behaviors, diagnose and monitor trends, and reflect on the state of the innovation activity or program in a variety of contexts and at various levels.
How can we effectively measure the quality and consequences of our innovation efforts? If there is success, how can we repeat it? If there is (perceived) failure, how can we learn from it? This is all for you to ascertain! Remember: no two activities are alike.
Start by understanding which activity is in scope, your goals, and whether you need to analyze various levels. Remember: not all indicators are equally relevant on the macro, mezzo, micro, and nano levels. Next, put together a simple dashboard and make sure you can consistently record your metrics. Finally, document your journey and be prepared to share!
Metrics can be deceiving and it’s easy to hide behind numbers, especially to prove a point or reinforce a long-standing philosophy. However, when formulated and deployed correctly, metrics can also be revealing because they represent a snapshot of how the collaboration is progressing at a certain point in time. So go ahead and dare to check those vitals. You’ll be surprised by the strength and growth you’ll find, sometimes in the most unexpected places!