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Guest Talk: Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Chris­tian Fleig, M.Sc. 

Date/Time: 30.05.2018, 12:00 

Loca­tion: D2.2.094 

Abstract 

Process stan­dar­di­za­tion allows to opti­mize ERP systems and is a necessary step prior to ERP imple­men­ta­tion projects. Tradi­tional approa­ches to trans­for­ming and stan­dar­di­zing busi­ness processes are based on manu­ally created "de-jure" process models, which are distorted, error-­prone, simplistic, and devia­ting from process reality. This rese­arch project employs a design science approach to develop a process minin­g-enabled deci­sion support system (DSS) which combines bottom-up process mining models with manu­ally added top-down infor­ma­tion to recom­mend a suitable stan­dard process speci­fi­ca­tion.

For deci­si­on-­ma­king, attri­bu­te-ex­tended process models are compared against a repo­si­tory of best-prac­tice stan­dard process models using an attri­bu­te-­based process simi­la­rity matching algo­rithm. Thus, the DSS aims to reduce the overall costs of process stan­dar­di­za­tion, to opti­mize the degree of fit between the orga­niza­tion and the imple­mented stan­dard processes, and to mini­mize the degree of orga­niza­t­ional change required in ERP imple­men­ta­tion projects.

The rese­arch project is conducted in the context of a large-­s­cale stan­dar­di­za­tion project of an indus­trial corpo­ra­tion and includes an ERP imple­men­ta­tion of the SAP S/4 HANA Busi­ness Suite.

The current project status comprises a working proto­type instan­tia­tion in the open-­source process analy­tics plat­form Apro­more. The proto­type is based on a real-­life event log for the Purcha­se-­to-Pay and Order-­to-­Cash processes from three SAP R/3 ERP systems and asso­ciated process infor­ma­tion from process respon­si­bles.

Bio 

Chris­tian Fleig is as Project Manager and PhD Student in an IT service provider of a German indus­trial company and pursues a docto­rate at Karls­ruhe Insti­tute of Tech­no­logy (KIT) with the focus on Busi­ness Process Manage­ment. In his rese­arch, he devotes himself to the ques­tion of how Process Mining can effec­tively be used for Deci­si­on-­Ma­king in the trans­for­ma­tion of busi­ness processes. He studied busi­ness admi­nis­tra­tion at the univer­si­ties of Mann­heim, Manchester and Frank­furt with various internships in industry.



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