Agile DMAIC cycle: incorporating process mining and support decision

Abstract

Purpose

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

Design/methodology/approach

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

Findings

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Practical implications

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

Originality/value

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

Citation

Prado, R.R.D., Boareto, P.A., Chaves, J. and Santos, E.A.P. (2024), "Agile DMAIC cycle: incorporating process mining and support decision", International Journal of Lean Six Sigma, Vol. 15 No. 3, pp. 614-641. https://doi.org/10.1108/IJLSS-04-2022-0092