Performance measurement (PM) needs objective empirical data with causal relevance in order to steer and control financial performance generation. In business practice, there is often a lack of such objective data. A surrogate might be collected subjectively based on data generated by questioning corporate experts. Such an involvement of subjects can rapidly lead to an immense extent of data that (partially) imply incomplete information. To handle this imperfection of data, the Grey systems theory (GST) and especially its element, the Grey relation analysis (GRA), seem to be methodologies able to improve informational bases for PM purposes. Therefore, GRA is able to reveal those performance indicators that considerably influence the corporate financial performance, the key performance indicators. GRA is able to supply valid results with only four data points of a time series. Hence, the GST provides an improvement of the PM framework in situations of incomplete information, which is demonstrated in the following.
Part of the book: Operations Research
As implied by the performance management (PM) concept, modern corporate management has to focus on cause-and-effect relationships underlying a firm´s financial performance generation. To determine the causes of financially desirable effects, subject-bound experiences and knowledge of employees, called tacit knowledge, should be realised. For this, knowledge management (KM) offers various elicitation techniques to reveal corporate-specific success factors (SFs) of financial performance generation from the corporate experts´ implicit knowledge. The identified factors have to be organised within a network of cause-and-effect relationships. In this framework, PM can apply the instrument of mapping to structure the individually revealed knowledge, to aggregate and visualise it for the entire company. For a valid representation of the causal relationships, the subjective bias arising within the mentioned process has to be minimised. In the literature, a variety of mapping methods can be found that differ in their approaches and their level of significance. As such a method, causal mapping will be presented in this paper. For providing intersubjectivity, the decision-making trail and evaluation laboratory (DEMATEL) as a multi-criteria approach will be debated in the context of mapping as a research field.
Part of the book: Knowledge Management Strategies and Applications