Even the organizations that claim to have long term goal of delivering sustainable innovate product seem worry about whether continued spending in research and development (R&D) worthy of investment. One alternative thought for many corporate leaders have been to acquire startups and fill the void for innovation to stay competitive in today’s rapidly changing competitive environment. However, you cannot simply buy your way in. There are three reasons, organization should refrain from trying buy their way in to stay competitive. First, there is not enough innovative startups that can fill the void for a technology or product gap. Secondly, most startups appear more innovative than they are, because their initial investment typically come from outside. For example, Bill gate did not invent DOS – he bought it from Seattle Computer Company for USD$5000. Similarly, Steve Job hired employees from Xerox PARC to develop a graphical user interface after seeing one at Xerox. These stories are norm rather than exception. Statistics shows organization that done well tend to have higher R&D investment than those lacks it. For example, Amazon invested roughly 9.4% (roughly USD$22Billions) of its total revenue of USD$232.88Billions in R&D investment during 2018. The organization spent USD$16.1Billon in R&D in 2016 while it’s revenue was USD$136Billion. Amazon attained nearly USD$97B revenue growth since 2016 which directly correlates to increase investment in R&D. Same goes for Google, Intel, Microsoft, Samsung and so on. Long-term viability of these organization solely depends on their continued investment in R&D. There is really no alternative to R&D investment.
Acquiring your way to make organization innovative is not best course of action. Luckily for big companies, investing in R&D is a good strategy. Higher R&D yield results in higher profits as evident from Amazon, Google, Intel and other organizations. One reason organization often question the outcome of their R&D investment as measuring R&D performance remain dubious art and many managers are continued to be disappointed trying to develop KPI to measure R&D performance.
In this article a series of metrics are presented that collectively known as Integrated Metrics that can be used to measure both present and future R&D Performance.
Integrated Metrics
In many organizations, program level KPI is used to measure R&D performance as such measure fails to consider subjective aspects of R&D investment and focuses mainly on objective aspects of R&D investment. Integrated metrics (Werner & Souder, 1997) are thus important to consider both subjective and objective elements to measure R&D performance. It takes into context current and future performance and metrics are presented in a series of calculations as follows:
- Effectiveness Index (EI) = Present value of revenue generated from products introduced in the last 5 years (Pr) / Present value of last 5 years cumulative R & D costs (Pc).
- Timeless Index (TI) = Number of projects completed on time during some representative period (Pn) / Number of projects started in that period (Ps).
- Future Potential Index (FI) = Present value of expected future revenues from technologies currently under development (Pf) / Present value of all costs to develop these technologies (Pt).
- Pra = Peer rating audit of unfilled future needs that will inhibit the achievement of future greatness, expressed on a scale from 0 to 100%.
- Overall assessment of the value of R&D (Oa) = EI + [(FI x TI) x Pra].
- Ahmed & Zairi (2000) have reported practical examples on integrated metrics following how HP (Hewlett-Packard) measure it’s product development performance:
- Staffing level effectiveness (Se) = [(Staff initially forecast as needed for a project) / (Staff actually needed by project)] x 100%.
This measure monitors how close the projections for the staff needed on a project matched the actual staffing required by the project (Ahmed and Zairi 2000).
- Stability of the design (Sd) = [(Number of design changes in a project) / (Total cost of project)] x 100%.
This measure tracks the number of design changes made. As large projects might need more changes simply because they are larger, this metric, by dividing against the cost of the project, adjusts for the size of the project (Ojanen & Vuola, 2003).
Additionally, Ahmed & Zairi (2000) presented innovation effectiveness metrics as practiced in HP:
- Innovation Effectiveness (IE) = [(Number of projects finishing development)/ (Number of projects started development)] x 100%.
McKinsey’s R&D Productivity Metric
Hannon, Smits & Weig (2015), employees at McKinsey & Company also attempted to quantify R&D performance and benefit through a formula which was later published in McKinsey Quarterly. The formula, according to the authors, may not have solved the issue of quantification with respect to R&D productivity; however, it could be used as a tool for organizations to obtain a transparent overview of their R&D department. The formula has been designated, in the article, mainly as a tool for conducting projects with a commercial product as the end result (Larsen & Lindquist, 2016). Still, the formula could be used to measure productivity for other types of projects as well.
McKinsey’s R&D Productivity formula consists of three parts: total gross contribution, achieved product maturity and consumed R&D costs.
- R&D Productivity = [(Total Gross Contribution) x (Achieved Product Maturity)]/Consumer R&D Cost.
Total gross contribution is defined as projects economic value to its beneficiaries, although difficult to quantify, historical data can be used to determine projects productivity in retrospect. The achieved maturity refers to how close a project or a product is to be finalized and ready for commercial use. The last part of the formula, consumed R&D costs, refers to the costs associated with a project.
This formula can be used to measure the relative R&D productivity as well as specific R&D productivity, that enables organizations to track the performance of individual projects in order to investigate which project teams are performing well.
Conclusion
While quantifying R&D investment and measuring results can be difficult, Integrated metrics provides some possible measure that enables an organization to better judge the performance of their R&D investment. Both Integrated Metrics and Mckinsey’s R&D Productivity metrics are useful tool to gain insights to into the productivity and success of R&D organizations. However, there are many dimension for which a organization specific metric development is beneficial, for example, basic research vs product development and customer retention vs market leadership etc.
Reference
- Ahmed, P.K. and Zairi, M., 2000. Innovation: A Performance Measurement Perspective. In: Tidd, J. (ed.) From Knowledge Management to Strategic Competence: Measuring Technological, Market and Organizational Innovation. Series on Technology Management – Volume 3. Singapore, Imperial College Press.
- Hannon, E., Smits, S. & Weig, F., 2015. Brightening the black box. McKinsey Quarterly.
- Larsen, A. & Lindquist, P., 2016 . A performance measurement framework for R&D activities: Increasing transparency of R&D value contribution. Master of Science Thesis. KTH Industrial Engineering and Management, Industrial Management, SE-100 44 STOCKHOLM.
- Ojanen, V. & Vuola, V. 2003. Categorizing the Measures and Evaluation Methods of R&D Performance – A State-of-the-art Review on R&D Performance Analysis. Telecom Business Research Center Lappeenranta, Working Papers 16. Available online at http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.109.3330&rep=rep1&type=pdf
- Werner, M. B. & Souder, E.W., 1997. Measuring R&D Performance—State of the Art. Research-Technology Management, 40:2, 34-42.
