The article Metrics: R&D Should Settle for Second Best in CEB Views points out that it generally not worth putting in a lot of investment in developing new R&D metrics. However, as we have seen, there is plenty of research out there that suggests what you measure will drive behavior of your R&D teams – so please keep that in mind.
The article points out that most R&D departments use very simple metrics:
These simplistic measurements might not necessarily be because simple metrics are the most effective, they might be because measuring the right thing is difficult to do. For example, not one of the top metrics above addresses performance or maturity of R&D projects underway and how they compare with the expectations. Even though this is hard to do, it might have a huge benefit to overall R&D management.
Overall, the four takes aways have two useful ones:
- Use qualitative metrics to evaluate early-stage investments: Very important because it is hard (if not impossible) to value benefits of early-stage technologies – especially when they might impact many different product lines or would require other technologies to mature before they can be of use.
- Use business outcome targets to classify project types: I take this to mean that it is important to categorize the R&D pipeline and then measure them based on the category they fall into (some what related to the bullet above).
- Supplement business outcome metrics for accurate performance assessments: Idea being revenues/profits should not be all that drive decisions…
- Use metrics to motivate not intimidate: Easy to say, hard to do…