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Data evaluation and process improvement in the P2P process through process mining

Challenge

  • Heterogeneous IT landscape, e. g. use of AMETRAS and SAP for the P2P process
  • Different execution of the purchasing process across companies
  • Limited transparency about demand sources, suppliers, complex contracts with impact on operating costs
  • Lack of process conformity, multitude of process sequences and non-transparent costs

Service

  • Connection to Celonis for mapping the as-is purchasing process flows
  • Development of the P2P to-be process and identification of trade-specific key figures, e. g. delivery reliability (price, quantity, time), document type by order volume
  • Provision of needs-based analyses in Celonis e. g. for the evaluation of order processes, suppliers, deviation of the order confirmation checks, manual changes
  • Illumination of process chains with regard to standardization and automation
  • Identification of error sources and creation of a catalog of measures for mitigation, e. g. to increase the rate of on-time deliveries

Key data

  • Duration: 6 months
  • Scope of brief: 100 FTE
  • Sector: furniture dealer
  • Company size: 8.000 employees

Results

  • Scalable on-demand visualization of business processes and process variants
  • Rapid identification of major sources of errors and critical deviations from the to-be process
  • Provision of analysis conformance check for continuous monitoring and to increase process compliance
  • Uncovering of optimization potentials, such as paid goods that have not been delivered, double payments, last minute order cancellations, delivery and time displacement of goods delivery
  • Productivity increase and further development of employees through success control
  • Establishment of management reporting for regular communication

Summary

  • Creation of transparency in the purchasing process across all companies
  • Development of PPIs and KPIs to manage purchasing and ensure compliance requirements are met
  • Increasing the automation rate and operational efficiency by using the Action Engine

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