R&D Key Performance Indicators

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Interest in the topic of performance measurement in R&D has increased in the last few decades, but the topic is not new at all. Legitimate interest for the “right” KPIs has been shown, in particular, by managers of R&D laboratories. This is especially the case when there is an increased demand for contributions or value of contributions from R&D and a need to make the impact of results more visible to the overall organization. Therefore, the call for transparency is connected to budget allocation procedures, which often results in a search for the “right” KPIs that justify R&D’s existence.

Due to the very broad range of activities covered by the R&D function, a great variety of metrics is to be found. Almost all listings distinguish between qualitative and quantitative metrics. Regarding the categorization perspective, the following taxonomy of performance measurement methods has been suggested by Kerssens-van Drongelen

Taxonomy of performance measurement methods
Subjective, qualitative methods
Semi-objective, qualitative methods
Subjective, semi-quantitative methods:
• Simple: single item/judgmental conversion or averaging of scores for several items into an aggregate metric
• Sophisticated: conversion of scores for several items into an aggregate metric using sophisticated formulae or techniques
Semi-objective, semi-quantitative methods:
• Simple: single item/judgmental conversion or averaging of scores for several items into an aggregate metric
• Sophisticated: conversion of scores for several items into an aggregate metric using sophisticated formulae or techniques
Subjective, quantitative methods:
• Financial
• Non-financial
Semi-objective, quantitative methods:
• Financial
• Non-financial
Objective, quantitative methods:
• Financial
• Non-financial

From the content perspective, many authors cite people-based metrics. These include a focus on skill and training aspects, motivation, moral etc. Furthermore, the intellectual property aspect is often mentioned with metrics such as granted patents, patent application, cost of inventions, counts of patent disclosures, etc.
Publications, papers, books are also present in many listings. Technology transfer to manufacturing or other units and strategic alignment are also often named. Another observation,which is not exactly of the content nature,but more structural,is the fact that many authors try to assign each metric to specific content areas. These areas summarize the metrics and they often represent important areas for the companies evaluated.
For example:

• Value Creation (VC) demonstrating the value of R&D activities to the positioning, profitability and growth of the organization and to the creation of shareholder value;
• Portfolio Assessment (PA) communicating the total R&D program across various dimensions of interest, including time horizon, level of risk, core competency exploitation, and new/old business;
• Asset Value of Technology (AVT) indicating the strength and vitality of the firm’s technology (e.g. proprietary assets, know-how, people, etc.) and foreshadowing the potential of the R&D organization to create future value for the company;
• Integration with Business (IWB) indicating the degree of integration, the commitment of the business to the R&D processes and programs, teamwork, and ability to exploit technology across the organization;
• Practice of R&D Processes to Support Innovation (PRD) indicating the efficiency and effectiveness of R&D processes in producing useful output for the firm. The processes include project management practices, idea generation, communication and other “best practices” in managing R&D.



The connection between individual measures with more general areas is described  by Mertins and Krause and  formulated as an object structure model that is based  on the idea of a goal – measures – process network.

• The first object type is a critical success factor (CSF). The concept of the CSF goes back to Daniel in the early 1960s and Rockart at the end of the 1970s. The concept is based on the assumption that a limited number of individual variables exist that makes a significant contribution to a company’s success. “Critical success factors … are, for any business, the limited number of areas in which results,if they are satisfactory, will ensure successful competitive performance for the organization. They are the few key areas where ‘things must go right’ for the business to flourish. If results in these areas are not adequate, the organization’s efforts for the period will be less than desired. As a result, the critical success factors are areas of activity that should receive constant and careful attention from management.The current status of performance in each area should be continually measured, and that information should be made available. …, critical success factors support the attainment of organizational goals.”
• The second object type in Krause and Mertin’s model is business process.

According to Krause, business processes represent sources of added value and hence of performance. Krause argues that the precise knowledge is the basis for the identification of  CSFs.
• The third type is represented by the performance improvement project. The authors argue that the performance improvement project impacts the efficiency and effectiveness of business processes.
• Performance indicators represent the fourth object type of the model. The justification for including this type into the model is its management support function.

Business processes and performance improvement projects are driven by these goals, and the measured data is consolidated through performance indicators and is usable for the assessment of goal attainment.

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