Measures of success

Abstract

Management of foreign R&D units proves to be a difficult task. This has to do with the observation that, to date, little “hard” data on this topic are available that could guide management in its decisions. For this purpose, evaluations of R&D success would be most important. Only very few studies seek to measure success. Technical success can be measured at the project level as well as the program level. However, this is only a necessary condition for the achievement of economic success. This is difficult to measure because it can be observed only after a substantial time lag and because many departments other than R&D need to collaborate optimally to make this success happen. Thus, while it is difficult to measure the overall economic R&D success of an organization, it appears to be even more difficult to determine the appropriate share by which individual laboratories have contributed to success. Some of the literature puts trust in the ability of experienced managers to solve this problem by asking them to reveal their perceived evaluation of success for individual laboratories. However, the particular division of labor between laboratories and the dispersed customers for whom they work might involve specific biases, depending on whom one prefers to interview. Figure 18 classifies different approaches that one could take. Most frequently, R&D managers from headquarters (Box (4)) have been asked to evaluate the R&D performance of individual laboratories or the success of the overall R&D organization of their company. It is obvious that their answers could be biased in support of their own unit and could downgrade other units that they may view as competitors for scarce internal resources. A few other studies ask managers of foreign R&D units to evaluate its success from their point of view (Box (5)). This could stimulate an opposite bias. No study is known that would contrast evaluations from different viewpoints to check the validity of the responses. This leaves open a wide field for further studies. It is obvious that by comparing responses from interviewees who might be located at different boxes and by finding significant differences, one would immediately become aware of biases and problem areas that need further attention. Similar biases become obvious by comparing the views of R&D managers and scientists in the same laboratories (Compare Boxes (4) and (7) or (5) and (8)). Let us illustrate this point with reference to a strictly national study: in a study of German R&D laboratories, it was found that while managers thought that reducing budget overruns was the second most important issue in securing higher laboratory success, bench engineers in the same laboratories perceived that reducing delays in decision making was the second most important issue in this respect. This can have severe consequences: if such differences in the perception of issues cannot be resolved, many of the management efforts might well be futile. However, the limitations of research perspectives on international R&D cannot be resolved in short time, and, therefore, we issue an early warning to keep this limitation in mind.