How can an organization be confident that its innovation is creating value, and that its capability to innovate is growing? This question organizes the chapter: the results chain, the three levels of measurement, measuring people and the environment, and the errors that allow indicators to devour the very goals they were meant to serve, before arriving at the concept of maturity.
A government agency added a new indicator to its employees’ individual performance targets: submit at least two innovative ideas a year through the ideas platform. At year’s end, the agency announced in its annual report that the number of ideas submitted had quadrupled. The platform’s evaluation team, however, found that most of the ideas were duplicates or generic, that some had been copied from other agencies’ platforms, and that many had been submitted in the final week of the year. Unable to evaluate such a volume, the team let the ideas pile up unanswered, and the few serious ones among them were lost in the crowd. The following year, employees spoke of the platform as a formality to be completed for the sake of the indicator.
The indicator hit its numerical target and damaged the purpose it was set up to serve: it measured activity and overlooked value, rewarded quantity at the expense of quality, and flooded the system beyond its capacity to respond. In this chapter, we set out how measurement can be designed to support innovation rather than distort it.
After studying this chapter, the reader should be able to:
Innovation is hard to measure for at least three reasons. Its results are delayed: years may pass between an idea and its impact. They are uncertain: most initiatives do not succeed, and the few successes are the fruit of an entire portfolio of initiatives. And they are difficult to attribute: when an organization’s performance improves, it is hard to say how much of the improvement stems from any particular innovation. For these reasons, organizations tend to measure what is easy to measure: the number of ideas, events, participants and amounts spent.
Measurement, however, is not a neutral tool. Hauser and Katz observed that organizations become what they measure: indicators direct people’s attention and effort, and people act in ways that improve the indicator even when this harms the purpose (Hauser & Katz, 1998). Decades earlier, Kerr had drawn attention to what he called “the folly of rewarding A while hoping for B”: organizations often reward one behavior and then wonder why the behavior they wanted is missing (Kerr, 1975). The opening case is a direct example: submitting ideas was rewarded, while innovation was what had been hoped for.
The results chain, known in the evaluation literature as the logic model, helps link what an organization spends to what it achieves (W. K. Kellogg Foundation, 2004). Figure 16.1 shows its links as applied to innovation.
Most innovation reports concentrate on the first two links, because they are the easiest to measure and the most within the organization’s control. Outcomes and impact are what matter, but they take more effort to measure. Chapter 2 presented one version of this gap at the national level: the gap between the Kingdom’s ranking on innovation inputs and its ranking on innovation outputs in the Global Innovation Index. An organization that measures only its inputs and activities may consider itself successful while producing nothing.
Inputs and activities remain necessary for understanding efficiency, but every indicator in the early links needs to be read alongside an indicator in the later ones: the number of ideas on its own says nothing, whereas the share that was implemented and the results it achieved say a great deal.
Innovation management needs measurement at three levels, each with its own questions and indicators, as Table 16.1 shows.
| Level | Question | Suggested indicators |
|---|---|---|
| Initiative | Is the initiative learning enough to deserve to continue? | Number of critical assumptions tested, and which were confirmed or refuted; the cost and duration of each experiment; initiative-specific outcome indicators after implementation |
| Portfolio | Are initiatives flowing, balanced and delivering value collectively? | Distribution of initiatives across types and horizons; average time an initiative spends at each stage; share of decisions made on time; number of initiatives stopped by decision; share reaching implementation; value realized from what was implemented |
| System and capability | Is the organization’s capability for repeated innovation growing? | Creative climate; participation of different units; response time to ideas; share of ideas whose authors received a reasoned response; share of implemented solutions still in use after a year |
Two indicators in this table deserve particular emphasis, because they measure what this book regards as among the most serious breakdowns in the system. The first is the share of decisions made on time, together with the average age of ideas still awaiting a decision; these directly measure the extent of the decision limbo described in Chapter 5. The second is the share of implemented solutions still in use after a year, which distinguishes genuine implementation from the superficial implementation discussed in Chapter 15.
Note that indicators for an initiative in its early stages measure learning; outcome indicators belong to later stages. Asking an initiative in the exploration stage for a financial return is like applying the criteria of the scaling gate at the opportunity gate.
If people are the heart of the innovation system, as this book holds, then measuring them is an integral part of measuring the system. What this means is measuring what people experience in their environment: Do they find recognition, opportunity and support? Counting how many ideas each employee submits, as in the opening case, measures something else entirely.
Well-established research instruments exist for this purpose. Ekvall developed a measure of creative climate covering dimensions such as challenge, freedom, idea support, trust and openness, idea time, risk taking, and conflict as a negative dimension (Ekvall, 1996). Amabile and colleagues developed an instrument for assessing the work environment for creativity, measuring both stimulants and obstacles (Amabile et al., 1996). Such instruments allow an organization to know where it stands and to track the effect of what it does to improve its environment.
The innovator’s experience of the system can also be measured directly, using indicators drawn from the needs set out in Table 7.1:
At the university, the findings of a study on faculty support can be measured by asking students how far their instructors encourage their creative ideas in courses, and how confident they are in their own creative abilities (Alsamani & Alqahtani, 2026). This measures a link in the ecosystem that does not appear in incubator and accelerator reports, even though it touches every student.
Pick ten ideas submitted in your organization six months ago and trace what became of each: Was a decision made on it? When? Did its author learn the reason? This simple measure says more about the innovation system than the number of ideas submitted.
The psychologist Campbell formulated an observation that has come to be known as his law: the more a quantitative indicator is relied upon for social decision-making, the more it is subject to corruption pressures and the more it distorts the processes it was meant to monitor (Campbell, 1979). In the measurement of innovation, this phenomenon appears in recurring forms:
These errors can be limited by using indicators as a balanced, multidimensional set; reading activity indicators alongside outcome indicators; separating learning indicators from individual incentives; and periodically reviewing the indicators themselves by asking: Does this indicator still serve the purpose, or has it become an end in itself? The balanced scorecard offers a closely related idea: performance should not be reduced to a single dimension, and the different dimensions should be read together (Kaplan & Norton, 1992).
An indicator tied to an individual incentive stops measuring reality and starts shaping it. If the aim is for people to put forward good ideas, measure what happens to their ideas after they are submitted.
Many organizations use maturity models to assess their innovation management; these models describe successive levels of capability. Figure 16.2 offers a simplified version of these levels, derived from the logic of this book.
Maturity models have both uses and limits. They are useful in giving an organization a shared language for describing its situation and identifying the next step. Their limit is that they can turn into a ladder climbed for appearances: the organization meets a level’s requirements on paper, much as a certificate of conformity can become a stage for innovation theater. The international guidance on innovation management assessment recommends that assessment serve as a means of understanding the current situation and drawing out what can be improved (ISO, 2019). The most important question in any maturity assessment is not “What level are we at?” but “What is preventing us from innovating repeatedly, and what is the next step to remove it?”
Build a measurement dashboard for your organization’s innovation system with two or three indicators per cell, and no more. Make sure every indicator in the activities column is matched by one in the outcomes column. Then ask of each indicator: How could it be met on paper only? If you find an easy way, rewrite it.
| Level | Inputs and activities | Outputs | Outcomes and impact |
|---|---|---|---|
| Initiative | Cost and duration of experiments | Assumptions tested and those confirmed | Improvement in the problem indicator for beneficiaries |
| Portfolio | Distribution of initiatives across types and units | Share of decisions on time; initiatives stopped by decision | Share implemented; value realized from it |
| System and capability | Courses that include innovation projects | Response time to ideas; student movement between units | Creative climate; students’ confidence in their creative abilities; solutions still in use after a year |