Six Sigma in Urban Logistics Management—A Case Study

Abstract

A city as a system that constitutes one of the most important areas of human activities. The significant role to fulfill their expectations pay the goods transport and deliveries. These issues are the subject of urban logistics. In broad terms, urban logistics may be construed as a number of processes focused on freight flows, which are completed in cities, including deliveries, supply, goods transfer, services, etc. Due to the different urban logistics stakeholders’ expectations, these systems generate many challenges for managers, especially in the context of city users’ needs and their quality of life. Today, there is a lack of broadened approach and methodology to support them from the processes’ efficiency perspective. To fulfill this gap, the purpose of this paper is to apply the Six Sigma method as a support in last mile delivery management. Six Sigma method plays important role in production systems processes management. However, it could be useful in much wider perspective, including transport and logistics processes. The Authors emphasize that the Six Sigma method could be efficient approach in the last mile delivery processes’ analysis in the context of their efficiency. It helps positioning the customer satisfaction level and quantify the delivery processes defects, related to the undelivered goods. Following that it could improve significantly the last mile delivery processes efficiency. The concept is illustrated by a sample evaluation of one of the urban logistics processes: completion of deliveries. To this end, urban logistics processes were defined. In particular, the delivery completion process was mapped, and the process client was defined along with their expectations. The defects that occurred in the process were identified and analyzed. A DPMO (Defect per Million Opportunities) indicator was established for three randomly selected months. In addition, a root cause analysis of errors was performed. The sigma level for the studied process ranged from 2.61 to 2.89. The factor that had the greatest impact on the number of defects defined as failed deliveries was customer’s absence. The obtained results indicate that the delivery process should be examined in more detail.