Time-driven Activity-based Costing Using Process Data Mining

Abstract

Volatility, uncertainty, complexity and ambiguity are the four aspects that describe today's world in general and the challenges of manufacturing companies in special. Increasing volatility requires fast innovation cycles whereas uncertainty and ambiguity prevent companies from knowing what customers really want. To anticipate eventually upcoming requirements, a vast amount of products and product variants is developed and offered to the market. Due to increasing complexity, the effort, i.e. costs, for product realization rises especially in indirect areas, which cannot be allocated correctly to the causing variants. On the one hand side, this is because of deficits of commonly used cost calculation systems. On the other hand side, it's because of the high effort for introducing and maintaining advanced costing systems, such as Process Cost Calculation or Time-driven Activity-based Costing and, as those are almost interview-based, their low accuracy and timeliness. Digitalization in all areas of manufacturing companies enables the collection of event data, which are already used e.g. by Process Mining. The aim of this paper is to use event data in order to enable a low-effort but increased accurate and timely Time-driven Activity-based Costing by using Process Data Mining. Therefore, the required event data as well as the corresponding data model is presented and it's described how to evaluate the data for Time-driven Activity-based Costing.

Authors 4

1. Michael Riesener Aachen Laboratory of Machine Tools and Production Engineering

   RWTH Aachen University

   Affiliation as printed

   Laboratory of Machine Tools and Production Engineering (WZL), Rwth Aachen University), Aachen, Germany

2. Christian Dölle Aachen Laboratory of Machine Tools and Production Engineering

   RWTH Aachen University

   Affiliation as printed

   Laboratory of Machine Tools and Production Engineering (WZL), Rwth Aachen University), Aachen, Germany

3. Alexander Menges Aachen Laboratory of Machine Tools and Production Engineering

   RWTH Aachen University

   Affiliation as printed

   Laboratory of Machine Tools and Production Engineering (WZL), Rwth Aachen University), Aachen, Germany

4. Günther Schuh Aachen Laboratory of Machine Tools and Production Engineering

   RWTH Aachen University

   Affiliation as printed

   Laboratory of Machine Tools and Production Engineering (WZL), Rwth Aachen University), Aachen, Germany