Comprehensive multistage approach for measuring the efficiency of logistics processes in the presence of a mismatch between sales and logistics

Abstract

Frequently, various sectors within the same company often find themselves at odds with one another due to conflicting objectives. For example, the sales and logistics departments frequently fail to synchronize, with sales viewing logistics merely as a cost center. Conversely, sales place demanding delivery tasks on logistics, particularly evident in scenarios involving out-of-stock or non-assortment items. To address this pervasive issue, the primary objective of this paper is to propose a model for assessing the efficiency of logistical processes, distribution centers, and drivers. Hence, it can be asserted that this study, through its proposed model, aims to accomplish several aims: (i) determine the effectiveness of distribution centers (DCs), (ii) analyze how the efficiency of DCs evolves over time, (iii) evaluate the performance of distribution drivers, and (iv) rank proficient drivers for bonus allocation based on their performance. To achieve these objectives, the suggested model relies on the application of the CI-DEA-Malmquist Index-DEA-MEREC-ADAM methodology. Specifically, the model is delineated into three distinct phases. The initial phase entails employing the CI-DEA and Malmquist index methodologies to condense the multitude of parameters considered in the study by utilizing the CI-DEA approach. Additionally, Malmquist analysis is applied to observe the multi factor productivity change in the efficiency of DCs and to identify the most efficient DC across all time periods. Following the identification of the most efficient DC, the subsequent phase focuses on selecting drivers from that center, followed by applying the DEA method to isolate only the most efficient drivers, who are then further evaluated and ranked accordingly. Through the application of these methodologies, it was determined that out of a total of 10 drivers, only four were deemed efficient. In the final phase of the model, these drivers were assessed based on seven criteria for ranking purposes. During this phase, the MEREC method was utilized to ascertain the criteria weights, while the ADAM method was employed for driver ranking. The findings revealed that the second driver ranked the highest and thus should be granted the highest bonus.