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.
Original language | English |
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Title of host publication | Data-driven Process Discovery and Analysis |
Subtitle of host publication | Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017 |
Editors | Paolo Ceravolo, Maurice Van Keulen, Kilian Stoffel |
Publisher | CEUR |
Pages | 54-67 |
Number of pages | 14 |
Publication status | Published - 2017 |
MoE publication type | A4 Article in a conference publication |
Event | International Symposium on Data-Driven Process Discovery and Analysis - Neuchatel, Switzerland Duration: 6 Dec 2017 → 8 Dec 2017 Conference number: 7 |
Publication series
Name | CEUR Workshop Proceedings |
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Publisher | Rheinisch-Westfaelische Technische Hochschule Aachen |
Volume | 2016 |
ISSN (Electronic) | 1613-0073 |
Conference
Conference | International Symposium on Data-Driven Process Discovery and Analysis |
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Abbreviated title | SIMPDA |
Country | Switzerland |
City | Neuchatel |
Period | 06/12/2017 → 08/12/2017 |
Keywords
- Contribution
- Data mining
- Influence analysis
- Lead times
- Process analysis
- Process improvement
- Process mining
- Root cause analysis
- Working capital