Focusing business process lead time improvements using influence analysis

Teemu Lehto; Markku Hinkka; Jaakko Hollmén

Focusing business process lead time improvements using influence analysis

Teemu Lehto, Markku Hinkka, Jaakko Hollmén

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

97 Downloads (Pure)

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
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
Publisher	Rheinisch-Westfaelische Technische Hochschule Aachen
Volume	2016
ISSN (Electronic)	1613-0073

Conference

Conference	International Symposium on Data-Driven Process Discovery and Analysis
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

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Lehto, T., Hinkka, M., & Hollmén, J. (2017). Focusing business process lead time improvements using influence analysis. In P. Ceravolo, M. Van Keulen, & K. Stoffel (Eds.), Data-driven Process Discovery and Analysis: Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017 (pp. 54-67). (CEUR Workshop Proceedings ; Vol. 2016). CEUR. http://ceur-ws.org/Vol-2016/

Lehto, Teemu ; Hinkka, Markku ; Hollmén, Jaakko. / Focusing business process lead time improvements using influence analysis. Data-driven Process Discovery and Analysis: Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017. editor / Paolo Ceravolo ; Maurice Van Keulen ; Kilian Stoffel. CEUR, 2017. pp. 54-67 (CEUR Workshop Proceedings ).

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title = "Focusing business process lead time improvements using influence analysis",

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{\textquoteright}s service desk process we demonstrate the effect of using either continuous or binary approach combined with possible weighting.",

keywords = "Contribution, Data mining, Influence analysis, Lead times, Process analysis, Process improvement, Process mining, Root cause analysis, Working capital",

author = "Teemu Lehto and Markku Hinkka and Jaakko Hollm{\'e}n",

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publisher = "CEUR",

pages = "54--67",

editor = "Paolo Ceravolo and {Van Keulen}, Maurice and Kilian Stoffel",

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Lehto, T, Hinkka, M & Hollmén, J 2017, Focusing business process lead time improvements using influence analysis. in P Ceravolo, M Van Keulen & K Stoffel (eds), Data-driven Process Discovery and Analysis: Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017. CEUR Workshop Proceedings , vol. 2016, CEUR, pp. 54-67, International Symposium on Data-Driven Process Discovery and Analysis, Neuchatel, Switzerland, 06/12/2017. <http://ceur-ws.org/Vol-2016/>

Focusing business process lead time improvements using influence analysis. / Lehto, Teemu; Hinkka, Markku; Hollmén, Jaakko.

Data-driven Process Discovery and Analysis: Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017. ed. / Paolo Ceravolo; Maurice Van Keulen; Kilian Stoffel. CEUR, 2017. p. 54-67 (CEUR Workshop Proceedings ; Vol. 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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AB - 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.

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Lehto T, Hinkka M, Hollmén J. Focusing business process lead time improvements using influence analysis. In Ceravolo P, Van Keulen M, Stoffel K, editors, Data-driven Process Discovery and Analysis: Proceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017), Neuchatel, Switzerland, December 6-8, 2017. CEUR. 2017. p. 54-67. (CEUR Workshop Proceedings ).