Applying process mining to minimise order waiting time of FitBox. Issue 3 (27th September 2022)

• Record Type: Journal Article
• Authors: Porouhan, Parham
• Is Part Of: International journal of knowledge engineering and data mining. Volume 7:Issue 3/4(2022)
• Page Start: 190
• Page End: 233
• Publication Date: 2022-09-27
• Subjects: process mining -- business intelligence -- process discovery -- bottleneck mining -- handover of work analysis -- process simulation -- fluxicon disco; Knowledge representation (Information theory) -- Periodicals; Data mining -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-2087

Abstract

The main objective of the paper is to investigate the reasons why a lot of complaints (by customers) have been made against the quality of 'food delivery service' in one of the FitBox branches. During the COVID-19 pandemic, it is important for the FitBox customers to receive their (ordered) healthy food in-good-time to help them lose weight and get fit. To achieve the objective of the study, the whole dataset of the notorious branch was initially cleansed and then imported to the fluxicon disco platform, which is a process mining tool. Using several process mining techniques - such as automated process discovery (via frequency and time performance metrics), filtering (via follower, performance, endpoint and attribute metrics), clustering, process map animation/simulation and detailed statistics analytics - enabled us to find out the main reasons why the food delivery work has been piled up and handled improperly. The paper provides groundwork for future research.