Research shows widespread, declining innovation performance.
At first glance, the idea that companies are getting worse at innovation seems ridiculous—“innovations” are such a prevalent part of our daily lives. And we are fed a constant stream of information about the “latest” innovations that will change our lives and disrupt our industries—AR/VR, artificial intelligence/machine learning/deep learning, the internet of things, blockchain, additive manufacturing, etc. But there is mounting evidence that innovation performance is declining—costs are increasing and returns are falling.
A study published by the National Bureau of Economic Research in 2017 found that 85% of a large sample of US public companies had seen a decline in research productivity between 1980 and 2010. The average change in research productivity across the whole sample? A 10% annual decline.
Anne Marie Knott, an Olin Business School professor, found that returns to companies’ R&D spending have declined 65% over the past three decades. Knott specializes in the measurement of firms’ innovation performance and is the developer of the research quotient measure of innovation performance.
Studies looking at more recent time periods suggest the trend hasn’t changed. Analysts at Accenture adapted the NBER methodology and found a 27% decline in the return on companies’ innovation spending in the last 5 years. And in a pharmaceutical industry-focused study, Deloitte analysts found that forecast returns on R&D fell to a 9-year low of just 1.9% in 2018. This in an industry with, arguably, some of the strongest drivers to innovate more efficiently (e.g. very high costs of R&D, pressure on drug prices from politicians and manufacturers of generic drugs).
You need to measure your own innovation performance.
The accumulating evidence is difficult to ignore. We believe it raises three urgent questions for innovation leaders:
- Are we getting worse at innovation?
- If so, how do we know what to fix?
- And, are our initiatives to fix these problems successful?
Clearly, being able to accurately and objectively answer the first question is of critical importance. If you don’t know whether your organization is getting better or worse at innovation, you’re essentially flying blind. That’s dangerous when your organization’s medium- to long-term competitiveness depends on your ability to innovate.
Answering the second question (what to fix?) is essential, because it ensures investment in your innovation process is carefully targeted. All too often we see firms who have failed to take a systematic, analytical approach to diagnosing what needs to be improved. Innovation leaders may rely too heavily on judgment (instead of testing judgment with data) and misdiagnose1. Or they essentially skip this question altogether and jump straight to adoption of the latest “solution” sweeping the world of innovation practice—think open innovation, design thinking, agile methods (NOTE: we have nothing against any of these approaches, provided they’re used in the right context and they demonstrably improve performance).
The final question (are our efforts succeeding?) is important because you need to check whether your interventions are working—and, if not, course correct. Often it’s necessary to put in place metrics that can provide an early indication of an intervention’s success. That’s because it can take too long for the impact to flow through to your ultimate measures of innovation performance (the ones you use to answer question 1).
If you can’t answer these questions, your system for measuring innovation performance needs to be improved.
A strong innovation performance measurement system is critical to answering all three of the questions outlined above. Try this simple test: when you’ve finished reading this post, can you immediately answer those three questions for your organization? Check the metric that measures efficiency2 (e.g. return on innovation investment)—is it trending up or down? If it’s trending down, can identify the weak spots in your innovation process, where data supports your judgment? This might require looking at efficiency indicators by division / business unit and by stage of your innovation process. Finally, for those initiatives you’ve introduced to improve innovation: do you have data to confirm they’re having a positive impact on performance?
If you’re unable to answer all of these questions quickly and easily, some aspect of your innovation performance measurement system is inadequate.
What next?
If you’re ready to start improving your organization’s system for measuring innovation performance, check out our post on the topic.
