Focusing business process lead time improvements using influence analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

Research units

  • QPR Software Plc

Abstract

Shortening lead times in a business process is important for meetings service level agreements, decreasing inventories and working capital, keeping customers satisfied and in short: staying in business. Process mining methods make it possible to generate a large amount of transaction event data and case attributes that are useful for analysing lead times. However, finding root causes for long lead times is not so straightforward with current process mining methods. In this paper we extend our prevously presented influence analysis methodology by providing alternative treatment for continuous target variables like lead times and making it possible to give weights for each process case. We extend our contribution measure by presenting the definitions for binary/continuous as well as weighted/non-weighted needs. Using a publicly available real-life case study from Rabobank’s service desk process we demonstrate the effect of using either continuous or binary approach combined with possible weighting.

Details

Original languageEnglish
Title of host publicationData-driven Process Discovery and Analysis
Subtitle of host publicationProceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017
EditorsPaolo Ceravolo, Maurice Van Keulen, Kilian Stoffel
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventInternational Symposium on Data-Driven Process Discovery and Analysis - Neuchatel, Switzerland
Duration: 6 Dec 20178 Dec 2017
Conference number: 7

Publication series

NameCEUR Workshop Proceedings
PublisherRheinisch-Westfaelische Technische Hochschule Aachen
Volume2016
ISSN (Electronic)1613-0073

Conference

ConferenceInternational Symposium on Data-Driven Process Discovery and Analysis
Abbreviated titleSIMPDA
CountrySwitzerland
CityNeuchatel
Period06/12/201708/12/2017

    Research areas

  • Contribution, Data mining, Influence analysis, Lead times, Process analysis, Process improvement, Process mining, Root cause analysis, Working capital

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