Optimization of logistic services of DIESL

Abstract

3PL services market in India is a high growth industry and is fast becoming a necessity for the different domestic and multi-national organizations who desire to outsource their warehousing and logistics functions to these specialized players in order to achieve cost efficiencies and focus on their own core competencies. Drive India Enterprise solutions limited (DIESL) is a major Indian 3PL logistics company which is a Tata subsidiary and is involved in a gamut of 3PL services. It has a wide range of 3PL services for diverse customers spread across different industry sectors ranging across automobile, IT hardware, FMCG, consumer durables, e-commerce, telecom, etc. DIESL is in the business of providing a plethora of end-to-end logistics services like warehousing, distribution and last mile fulfilment, freight forwarding, customs clearance services, trading services, kitting and packaging, warehouse management services, reverse logistics, and other value-added services like case management and e-commerce, etc. The objective of our project was to identify the bottlenecks in its logistics process and to suggest solutions for optimization of its cost and other logistics parameters. In course of our study we had identified several challenges faced by DIESL’s logistics among which absence of product segregation among different line of businesses (LoB), non-optimized vehicle mix and lower transport capacity utilization, inadequate route planning, low presence in the field of inbound logistics are a few. As part of our analysis we have come up with a basis for segregation of the different business types of DIESL into a matrix and have defined the levels of different parameters that should be standardized for each product class. Based on this segregation matrix, we have developed a theoretical Linear Programing (LP) model for minimization of the operation costs associated with logistics through optimization of different factors like determination of optimized vehicle mix in terms of number and truck type, consignment load factors of the trucks and the utilization of truck capacity levels. During the term of the project, validation of the model was not possible since the necessary data could not be provided to us by DIESL within the time frame of the project. But by using appropriate real-time operating data from DIESL, the optimum levels of the different working parameters could be estimated as well as the models could be validated for the different product segregations. The obtained results could then be used to calculate cost saving as compared to the present operational processes and used to benchmark and quantify the different process KPIs. We have also made a qualitative comparative analysis between the existing last mile delivery techniques of milk run with hub-and-spoke model as was suggested by the DIESL executives. After analysis of the two techniques for the different product segregations, we have been able to come up with justifications regarding the appropriate last mile delivery technique and have based our recommendations on that. Since the models could not be validated under real-time operational data from DIESL which was unavailable from the company within the time frame of the project, it could be a useful future exercise to test the validity of the models and verify the cost optimizations provided from them in practical operational scenarios. As part of the project work, we aim to study and understand the processes involved in the 3PL company Drive India enterprise solutions Limited (DIESL) and identify and analyse the issues involved with its operations. Our objective is to identify the different bottlenecks and challenges associated with the logistics process of DIESL and to explore options for providing solutions to the same.