Process management based on SAP technologies
DOI:
https://doi.org/10.46299/j.isjea.20260502.02Keywords:
SAP S/4HANA, process management, BPMN, SAP Activate, process mining, SAP Signavio, SAP BTP, workflow, KPIAbstract
The paper is devoted to the management of business processes of an enterprise based on SAP technologies (SAP S/4HANA, SAP Business Technology Platform, SAP Signavio) in the context of digital transformation and improving the manageability of operational activities. The relevance of the topic is due to the growing demands for transparency, auditability, and speed of process adaptation in conditions of unstable demand, supply disruptions, and increased compliance. The aim of the research is to justify a practice-oriented approach to modeling, standardization, monitoring, and continuous improvement of processes in the SAP landscape based on a combination of BPMN modeling, controlled implementation using the SAP Activate methodology, process mining, and workflow automation. A closed-loop methodology of “model — implementation — measurement of facts — optimization” is proposed, in which (1) a process benchmark and a catalog of control points are formed, (2) the minimum sufficient set of events for the execution log L is determined, (3) process discovery and conformance checking are performed to identify deviations, their frequency, and contribution to key KPIs, (4) analytics results are transformed into manageable changes: rules, approval routes, automated checks, and SLA controls. The scientific novelty lies in the formalization of a reproducible protocol for evaluating deviations and prioritizing them according to business value (delays, rework, risks of non-compliance), as well as in the practical combination of process mining with the change circuit in SAP. The practical result of the work is a structured experiment plan for the “Procure-to-Pay” process with a description of the stages of data preparation, KPI/SLA construction, and “before/after” effect assessment; illustrative examples of cycle time, cost, and deviation level metrics are provided, which can be directly used as a template for implementation on real enterprise data.References
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