How does your innovation performance compare to your competitors’?
It’s just human nature to be curious about how your performance compares with that of your competitors. But when it comes to innovation performance, this instinctive desire for benchmarking is also a valuable tool for innovation leaders. It can help leaders monitor the adequacy of their performance, communicate about ambition and achievement, and target performance improvement efforts.
Companies invest in innovation because it’s essential to them maintaining or enhancing their competitive position. That means relative innovation performance matters as much as absolute performance does. Benchmarking can be used to determine whether your relative performance is in line with your innovation strategy and objectives. Note that means you’re not using benchmarking to determine whether your performance is at the same level as your competitors. Your strategy should help you establish the relative level of performance you are targeting. For example, a longer average speed to market may make sense if you’ve decided to invest heavily in developing an emerging technology. A higher proportion invested in “core” makes sense if you’re following up on a recent breakthrough.
Benchmarking is also a valuable tool when communicating about innovation performance. Demonstrating the value you’re creating for the organization will typically carry more weight (especially when reporting “up” the organization) if you’re able to compare your performance against an objective industry benchmark. For example, reporting a vitality index1 metric of 30% is a lot more meaningful if you also report that the sector average is just 15%. Industry benchmarks of innovation performance can also provide succinct, compelling context for communicating targets “down” the organization.
Benchmarking of innovation performance doesn’t just have to be external. It can also be useful to compare performance within the organization. In fact, if external benchmarking helps you determine whether or not you need to improve innovation performance, then internal benchmarking is critical for determining where to improve innovation performance. It can, for example, help you determine which divisions or business units are most in need of improvement. Or which aspects of your innovation process to focus on.
Data availability makes benchmarking innovation performance a challenge
Unfortunately, meaningful benchmarking of innovation performance is challenging due to a lack of publicly available data.
There are very few innovation metrics that publicly traded firms share externally—particularly when it comes to output and outcome indicators. GAAP (& IFRS) require firms to report on research and development expenditure. This is at least a partial measure of inputs to the innovation process, even if its definition may be too narrow to cover all innovation related expenditure. See here for publicly available data on R&D expenditure collated by Commodore.
Patent data is generally available, but is a crude output activity indicator, at best. We place little value on patent activity data for benchmarking innovation performance for two main reasons:
- Not all innovations are patented (e.g. many are kept as trade secrets)
- The existence of a patent tells you virtually nothing about its value to a firm
Only the coarsest outcome indicators—revenue and earnings—have to be public reported by firms. And that also means relative performance indicators are rare—beyond those attempting to relate R&D expenditure to revenue2. McKinsey analysts thought they’d solved this problem when they proposed two conversion indicators: (1) new product sales per dollar of R&D expenditure and (2) gross margin per dollar of new product sales. Unfortunately, a critical component of these metrics, revenue from new product sales, is not nearly as available as the authors implied (although we note that these are still interesting metrics to look at internally). In fact, a quick analysis of earnings transcripts and SEC-filings from 2018 found just 40 examples of companies citing results for this metric (or something close to it)—see below to download this data. That compares with the ~2,000 US-listed firms that reported R&D expenditure in filings to the SEC for 2018.
Occasionally survey-based studies that benchmark innovation performance are conducted. For example, Stage Gate® International has previously published two benchmarking surveys of new product development metrics (in 2003 and in 2011). Unfortunately, such studies tend to be one-off or infrequent and give just a snapshot of performance at a point in time. This means they appeal to our curiosity, but rarely provide insight that is both actionable and timely.
Finally, niche services benchmarking innovation performance existing in some sectors. Clarivate and KMR Group are two examples in the pharmaceutical sector (where regulatory processes and investor pressure tend to mean there is more data available).
Develop a robust internal benchmarking program and “scrape together” what you can externally
So, what should you do to benchmark innovation performance? First up, we recommend ensuring you have a robust and systematic system of benchmarking internal innovation performance—to enable comparison of performance both across the organization and over time. Secondly, we suggest it’s worth at least taking a quick look at what data you can gather externally—it might be limited, but even that is better than nothing. The resources below are a good starting point.
Product Vitality Index Data
A spreadsheet with product vitality index data from around 30 companies who have publicly disclosed this information in recent years.
R&D Expenditure Data
R&D expenditure data—for all companies who report quarterly R&D expenditure in SEC filings.
1 – Percentage of revenue from new product sales.
2 – This has generally been a fruitless exercise. However, we recently came across an interesting article that appears to have had some success with an estimate of firms’ “ability” to convert R&D expenditure into sales growth. Mathematically: they performed a firm-level regression of the log of sales growth on the log of the lagged R&D expenditure to sales ratio, for five different lags (1 to 5 years); and averaged the five regression coefficients.