Empirical analysis of factors contributing to deviations from routing guidelines in order picking: a case study

Abstract

Order picking remains a time-sensitive operation in warehousing, with pickers following predetermined routes. Previous research identified potential drivers for deviations from these routes through qualitative studies or descriptive data analysis. We take a novel approach by applying a statistical analysis on two years of data (i.e., 2 448 000 picks). Our mixed-effects logistic regression model shows that factors such as workload, picks completed, congestion and aisle layout may significantly affect the likelihood of route deviations. Such deviations could significantly reduce route efficiency. These insights highlight the need to integrate real-world dynamics into routing models, aiming to enhance overall efficiency in warehouse operations.