Understanding Entropy Generation during the Execution of Business Process Instantiations: An Illustration from Cost Accounting

The instantiation and execution of business processes typically generates an enormous set of data, including financial- and accounting-related information, based on different aggregation levels. As a result, it can be very complex to draw conclusions from this data, such as which steps in a business process are causing delays or, in an accounting context, which tasks are causing high costs. In this paper, we relate this complexity generated through business process execution to the concept of entropy, as defined in thermodynamics. More specifically, we show how information aggregation seems to be at the core of this phenomenon. We discuss six types of information aggregation dimensions which tend to increase entropy (and hence, complexity) in a cost accounting context. As entropy is generally controlled by adding structure to the considered system, we propose a set of preliminary guidelines to control this entropy based on insights from the Normalized Systems (NS) theory rationale.