Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE credits
Background: Management control systems (MCS) are used to control organizations and make employees behave and act in the desirable way. Performance measurement (PM) systems one type of MCS and are used to communicate company strategies throughout the organization, motivate the employees to work towards company goals, and measure the outcome. PM systems can be a powerful tool, but if used in the wrong way they can have adverse effects.
Aim: This thesis focused on the use of PM systems for management control purposes in research and development (R&D) organisations with the question: How can performance measurement systems be utilized in R&D organizations?
Method: The thesis is based on a literature study, complemented by a case study (metric analysis, survey and deep interviews) at a R&D department. The department was investigated at two time points, in between which the PM system was re-designed. In the metric analysis, the performance targets of the PM system were categorized into quantitative-objective, quantitative-subjective and qualitative-subjective targets.
Results: The results from the case study were in line with findings from the literature. At study point 2, when the PM system had been re-designed, the employees felt more involved in shaping and influencing the goals. Also the follow-up of the goals was experienced as more implemented at study point two. The types of measured targets had shifted from quantitative to qualitative, including soft values such as team spirit, at study point 2. However, the members did not feel that the goals motivated them at any time point. .
Conclusion: In the literature review it was evident from the number of publications that there is a great interest in measuring R&D performance, and that PM systems are an important tool to R&D managers. Just as the company in this case study, each organization needs to analyze its own needs and adopt the PM system thereafter. Moreover, no system should be seen as static, instead it should be continuously evaluated and adjusted to make sure it measures what it is intended to measure and that it does not cause adverse effects on the organization.
2015. , 63 p.