Finding the right metrics to track innovation is by no means straightforward. To avoid common mistakes, executives should take a holistic perspective on their company’s innovation process.

For most companies, innovation is a top managerial priority. Many managers look at successful innovators such as Apple Inc. and Google Inc. with envy, wishing their companies could be half as innovative. To boost and benchmark innovation, managers often use quantitative performance indicators.1 Some of these indicators measure innovation as results or outcomes such as sales from new products. Others measure innovation as a process, using metrics such as the number of innovation projects in progress. And some track input measures such as the number of ideas generated, while still others focus on the innovation portfolio, by looking at factors such as the percentage of investments in breakthrough projects versus product line extensions.

Our research on innovation measurement suggests that the key managerial challenge is not identifying metrics — there is no shortage of measures to choose from. Nor should the goal be to find the perfect metric, since that quest is often futile. Rather, the crux of effective innovation measurement is to understand the problem that measurement should solve for the organization and, based on that insight, to design and implement a useful and usable innovation measurement framework appropriate to the organization’s needs.

In this process, identifying the right questions is usually more difficult than finding the appropriate answers. Executives need to understand the innovation challenges the company faces, how innovation is currently measured, and the extent to which current measurement practices help or hinder efforts to achieve the organization’s innovation goals. Only then will managers be able to steer clear of common innovation measurement mistakes.

Some of the most insidious mistakes involve placing too much value on data at the expense of meaning and getting bogged down with too many measures that provide contradictory advice and incentivize employees to do the wrong things. Although companies use performance measurement for almost any activity, measurement of innovation is by no means straightforward.

Managers often get hung up on selecting and implementing the appropriate measures. The goal of this article is to help managers ask the right questions about how to measure innovation and translate their insights into effective innovation measurement practices. We have developed a practical, step-by-step framework that helps managers identify whether their current innovation measurement practices need to change and, if so, how to go about measuring innovation more effectively.

References

1. R. Adams, J. Bessant, and R. Phelps, “Innovation Management Measurement: A Review,” International Journal of Management Reviews 8, no. 1 (March 2006): 21-47; S.D. Anthony, M.W. Johnson, and J.V. Sinfield, “Institutionalizing Innovation,” MIT Sloan Management Review 49, no. 2 (winter 2008): 45-53; European Committee for Standardization, “Innovation Management — Part 1: Innovation Management System,” CEN/TS 16555-1 (Brussels, Belgium: 2013); OECD/Eurostat, “Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data,” 3rd edition (OECD Publishing, 2005); A.R. Shapiro, “Measuring Innovation: Beyond Revenue from New Products,” Research-Technology Management 49, no. 6 (2006): 42-51; and E. Mankin, “Measuring Innovation Performance,” Research-Technology Management 50, no. 6 (2007): 5-7.

2. J. Platt, “Social Traps,” American Psychologist 28, no. 8 (August 1973): 641-651.

3. R.M. Kanter, “Innovation: The Classic Traps,” Harvard Business Review 84, no. 11 (November 2006): 72-83; and L. Välikangas and M. Gibbert, “Boundary-Setting Strategies for Escaping Innovation Traps,” MIT Sloan Management Review 46, no. 3 (spring 2005): 58-65.

4. European Committee for Standardization, “Innovation Management — Part 1”; OECD/Eurostat, “Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data”; Shapiro, “Measuring Innovation”; and Mankin, “Measuring Innovation Performance.”

5. S.K. Markham and H. Lee, “Product Development and Management Association’s 2012 Comparative Performance Assessment Study,” Journal of Product Innovation Management 30, no. 3 (May 2013): 408-429; and R.G. Cooper, S.J. Edgett, and E.J. Kleinschmidt, “Benchmarking Best NPD Practices II,” Research-Technology Management 47, no. 3 (2004): 50-59.

6. G. Barczak, A. Griffin, and K.B. Kahn, “Perspective: Trends and Drivers of Success in NPD Practices: Results of the 2003 PDMA Best Practices Study,” Journal of Product Innovation Management 26, no. 1 (January 2009): 3-23.

7. Cooper, Edgett, and Kleinschmidt, “Benchmarking Best NPD Practices II”; and R.G. Cooper, “What’s Next?: After Stage-Gate,” Research-Technology Management 57, no. 1 (2014): 20-31.

8. N. Nohria and R. Gulati, “Is Slack Good or Bad for Innovation?” The Academy of Management Journal 39, no. 5 (October 1996): 1245-1264.

9. Markham and Lee, “Product Development and Management Association’s 2012 Comparative Performance Assessment Study.”

10. A. Richtnér, P. Åhlström, and K. Goffin, “‘Squeezing R&D’: A Study of Organizational Slack and Knowledge Creation in NPD, Using the SECI Model,” Journal of Product Innovation Management 31, no. 6 (November 2014): 1268-1290.

11. A. De Meyer, C.H. Loch, and M.T. Pich, “Managing Project Uncertainty: From Variation to Chaos,” MIT Sloan Management Review 43, no. 2 (winter 2002): 60-67; D. Reinertsen and L. Shaeffer, “Making R&D Lean,” Research-Technology Management 48, no. 4 (2005): 51-57; N. Modig and P. Åhlström, “This Is Lean: Resolving the Efficiency Paradox” (Halmstad, Sweden: Rheologica Publishing, 2012).

12. A. Papalexandris, G. Ioannou, G. Prastacos, and K.E. Soderquist, “An Integrated Methodology for Putting the Balanced Scorecard into Action,” European Management Journal 23, no. 2 (April 2005): 214-227.

13. Markham and Lee, “Product Development and Management Association’s 2012 Comparative Performance Assessment Study.”