Data supply for planning and budgeting processes under uncertainty by means of regression analyses

Abstract

Planning and Budgeting (P&B) is an important part of Performance Management (PM). The corresponding processes for medium-sized and large organisations are usually very resource-intensive, time consuming and costly. These issues are mainly caused by uncertainty, which is a big challenge for companies. It is shown that available software and tools do not address this challenge in an appropriate way. Before possible issues and solutions are analysed in detail, an overview of different types of uncertainty is given. Afterwards important steps of the P&B process which suffer from uncertainties are outlined. Quite often it is not really clear which parameters have an impact on the planning object and how strong the planning object is influenced by certain parameters. Additionally, forecasts of the most important parameters which anticipate uncertainties are needed at an early stage of the P&B process. To resolve these issues, the application of different types of regression analyses will be explored. Also, ideas for further processing of fuzzy data in the following P&B steps are given. Furthermore, organisational and cultural prerequisites for the successful application of the outlined approaches will be indicated.