The South African Post Office supply chain design and route optimisation

Abstract

The South African Post Office (SAPO) has experienced a major decline in revenues over the past five years, with a recoded net loss of R1.37 billion for the 2015 financial year. The major contributor to these losses was due to the SAPO’s inability to conform to the requirements of the ever-changing logistics industry. The parcel industry of the SAPO is regarded as the highest contributor to revenues, amounting to R3.58 billion during the 2015 financial year. The SAPO has however, experienced a major decline in revenue due to their inadequate ability to achieve the required customer service levels, resulting in 1641 recorded complaints over the past 12 months. A lack of trust and reliability between the SAPO and their customers is due to the SAPO’s poor delivery services, which ultimately leads to customers changing to alternative options for courier purposes. The entire supply chain of the SAPO is responsible for the poor levels of customer service and an improvement to all the processes of the supply chain is necessary in order for the SAPO to once again record a profit. The most significant constraint that has been identified in the supply chain is through the transportation process and in particular, the routing of vehicles. The transportation costs of the SAPO amounted to R747 million for the 2015 financial year, thus the ability to reduce these expenses would have a major impact on the profitability of the SAPO. In this document, various route optimisation tools and techniques were evaluated and assessed for the transportation of parcels from retail outlets, to mail centres across South Africa. The Emalahleni mail centre was used as the pilot location to solve a sequential insertion heuristic that generated near-optimal transportation routes for the SAPO. The model was validated using various different assessments, which include increasing the number of vehicles used, changing the capacity and demand of vehicles, as well as analyzing the effect of the computational time on the model. The generated solution reduced the distance travelled by the SAPO in the Emalahleni region by 315.65km per day, which amounted to a total cost saving of R1 220 200.80 per annum. This document provides a complete literature review, the background of the problem, the project aim, the problem investigation, the project approach, data analysis, the solution design using a sequential insertion heuristic, validation and verification of the model and finally, the implementation plan and future work of the project.