Process mining and lean six sigma: a novel approach to analyze the supply chain quality of a hospital

Abstract

PurposeThis paper aims to depict the practical execution of the problem-solving structure provided by the define, measure, analyze, improve and control (DMAIC) framework in combination with the analytical power provided by process mining capabilities, to improve the supply chain quality of a health-care provider.Design/methodology/approachPrior to the study, a literature review was conducted to identify existing frameworks combining six sigma with process mining. The authors use a descriptive case study approach to explain how the two methodologies blend across the different phases of DMAIC in a health-care setting.FindingsThis case study describes how analyzing data extracted from core information systems has significant value to improvement initiatives when complemented by traditional quality methods. By intersecting process mining techniques with lean six sigma tools, the researchers found 65% of orders not complying with the target ordering time and 200 redundant purchases with high operational costs.Research limitations/implicationsBy depicting how the two methodologies can be intertwined, this paper complements existing research by presenting it as a viable quality improvement approach.Practical implicationsThis paper provides insights for six sigma and process mining practitioners on the benefits of combining both methodologies within the DMAIC structure. Implementing this blended approach can bring visibility to operations and accelerate process improvement initiatives.Originality/valueThe prime value of this paper lies in the integration of traditional six sigma methods with process mining as a technological approach in a health-care context, going beyond existing research, which, to the best of the knowledge, lacks descriptive case studies.