The document discusses metrics for measuring research and development (R&D) and innovation. It begins by listing the top 5 traditional metrics as spending, headcount, percentage of sales from new products, patents, and new products released. However, it notes that metrics need to shift focus more to processes, engagement, and outcomes. Leading indicators that predict outcomes are favored over lagging outputs. Comments discuss measuring innovation enablers, experimentation, impact over time, and qualitative alongside quantitative metrics. Change in metrics over time and impact on capabilities are important.

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Using Metrics for R&D and Innovation

2. What should we measure?
How should we do it?

4. Common understanding on input, process
and output
Top 5 metrics (Goldsense Group, 2013):
1. R&D spending
2. R&D headcount
Both are input metrics, the next three are output
metrics

5. “Headcount is a key metric for R&D. In
operations, the unit of production capacity is
generally “a piece of equipment assisted by
people.” In R&D, however, the unit of production
capacity is generally “people assisted by a piece
of equipment.” An R&D organization’s capacity is
best measured by its people. Appropriately,
these are the top two metrics.”
Bradford Goldsense
Is spending, headcount really that important?
The power of the ecosystems can change this.

6. Common understanding on input, process
and output
Top 5 metrics (Goldsense Group, 2013):
3. % of current sales due to new
products/services launched in x years
4. Patent production
5. New products released
Too little focus on process metrics?

7. Common understanding on input, process
and output
Much focus on leading versus lagging indicators

8. Lagging indicators: Historic, can’t be changed
(patents granted, expenses, new revenue)
Input, output is fairly easy to identify. Processes
are more difficult, but could be more rewarding.
Leading indicators: Predictive, can be changed
(patents filed, development time spent, # of
ideas and ongoing projects)
Jimm Feldborg, Director Global Projects

9. Leading indicators let you know what to expect.
Have two leading indicators for each one
lagging. (Doug Wick)

11. Number of innovation-related rewards and recognitions
Numbers from various feedback mechanisms, showing employee
acceptance and understanding of the initiative
Results from the innovation self assessment capability maturity
framework (survey measuring five levels of maturity related to innovation
behavior)
Percentage of our budget dedicated to innovation, research, and
exploration of emerging technologies
Shareholder value created from innovation activities. (Shareholder Value
= IT Efficiencies + Business Value provided to the IT customers)
# of ideas generated in specific innovation harvesting campaigns
# of ideas harvested from campaigns, turned into implementable projects
# of Intel patent submissions
#Number of white papers published

12. 1) Focus on engagement, training and
participation of individuals. Get critical mass
2) Shift / add focus on innovation pipeline (active
projects by stage, flow of projects, development,
launch and kill)
3) Shift / add focus on end goals (ROI,
successful products/services, revenue/savings
from new launches, optimized processes)
Hundreds of potential metrics, but not more than
8-10
Jeff Murphy, former Executive Director

13. What should we measure?
How should we do it?
Why you should NOT pay too much
attention to this?

15. Faster pace, shrinking window of
opportunity, less time for cash cows
Driven by global megatrends: faster, more
open, more transparent and more connected
The future of innovation is open and holistic
(go beyond technology and products =
business models and services)

16. A new paradigm for innovation changes the
perspectives and approaches for metrics
on research and innovation

19. What are good metrics for or good ways to
quantify foundational activities / enablers (i.e.
databases or knowledge system or
proprietary devices that accelerate the
development of products for a customer)?
Today, we measure usage, users, # of projects it
was used in.
Klaus Gassenmeier, Givaudan
Experimentation is key due to many unknowns

20. Ask yourself at management team level: What are our
company objectives and how do we best measure
them?
If you change your company's objectives or
measurements later, that's fine. In fact, I would argue
that if you're producing charts that nobody is reading or
acting on, you're probably measuring the wrong stuff.
And if you're not meeting as a team to discuss these
metrics and have a regular debate about how you're
doing and what needs to change, then I can assure you
that you'll never reach your destination. You'll have no
idea when you're off course.
Mark Suster, GRP Partners

21. Using the metrics for R&D is a critical subject.
Importantly from the point of view on how the
project is doing - "no-go" - "pivot or not pivot" etc.
Additionally, as we use these metrics, how is the
best way in the evaluation of employees during
performance appraisal or bonus purposes?
Jim French, Panasonic
Reward behaviors as well as outcomes; what
metrics can be applied to “smartfailing”?

22. How to track the R&D impact during a multi-year
time cycle? How to quantify the impact of an
R&D activity when the output takes a different
form than the original idea but was influenced by
it? Both qualitative and quantitative metrics seem
to be needed and more importantly assessing
R&D based on an indicator of change that R&D
brings to the company that needs to innovate
continuously could be an idea.
Jean-Claude Junqua, Panasonic
Change is key - don’t get stuck with fixed
metrics; measure impact on overall innovation
capabilities in each project?

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A recent comment on 15inno.com
KPI = Kill Potential Innovation