Process-oriented evaluation system for the use of robotic process automation

The administrative order processing is confronted with a variety of structural, procedural and organizational changes driven by the increasing demand for shorter delivery times and higher product variances. Thus, business processes become more complex and less transparent having a negative impact on administrative order processing. Studies estimate the waste in indirect areas at around 30 percent. The cause of this waste is, for example, missing information in the process step or interface losses during the transfer to another area of responsibility. This results in queries and coordination efforts that delay the order process. Among other things, robotic process automation (RPA) can be used to reduce waste. This enables the monitoring of administrative processes and the automation of sub-processes (activities). Identifying these automation potentials can be seen as a major challenge in administrative order processing due to the existing complexity. One way to discover automation potential is the use of data-driven tools such as process mining (PM). Using algorithms, a process model can be created on the basis of data from central information systems (e.g. enterprise resource systems), which enables a systematic analysis of causalities. Furthermore, PM can help to identify the relevant indicators for the suitability of the use of RPA in a data-driven way to decisively support the selection process. In the current state of research, most paper applying PM focus on quantifiable indicators for evaluating RPA capabilities. Qualitative criteria for RPA use are rarely considered. This paper proposes on a qualitative criteria-based and quantitative indicator-based evaluation system for the use of RPA in administrative order processing, with the aim of eliminating waste in the sense of Lean Administration. The approach is validated in a PM software using a data set related to administrative order processing.