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

Abstract

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 (e.g. a-miner), a process model is created based on data from central information systems (e.g. enterprise resource systems) allowing a systematical analyzation of causalities. Furthermore, PM can help to identify the relevant metrics for the RPA selection in a data-driven way, in order to support the selection process decisively. In the current state of research, most paper focuses on quantifiable key figures for evaluating RPA capabilities. Qualitative criteria for RPA use are rarely considered. This paper focuses on a qualitative criteria-based and quantitative indicator-based evaluation system for the use of RPA in administrative order processing The approach is validated in process mining software using a data set related to administrative order processing.