Article
VALUE STREAM MAPPING IN ORDERING PROCESS – A CASE OF RETAIL CHAIN
DOI: 10.7708/ijtte2021.11(4).01
11 / 4 / 488 - 506 Pages
Author(s)
Milan Andrejić - University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade, Serbia -
Abstract
In order to survive in the market, companies must optimally use their resources. Losses are present in all types of companies regardless of the size of the company and the industrial sector. Logistics processes as labor and cost-intensive processes are the potential source of losses. On the other hand, the greatest savings can be achieved in logistics processes. In recent years, more and more companies are realizing mentioned savings. Various tools and techniques are used in the literature for solving problems in this area. One of the most frequently used is Value Stream Mapping (VSM). This is one of the lean methods that serve to visualize activities within a particular process and identify activities that do not add value. This paper investigates how this approach can be applied to improve logistics processes in the supply chain. Applications of VSM in transport, warehousing, order picking, packaging, etc. are analyzed. There is not enough research in the literature on VSM application in the ordering process. In this paper comparative analysis of the manual ordering process and automatic ordering is conducted. A case study refers to the real system - a retail chain in Serbia. The ordering process is very important because does not add value to the product, but must be realized to certain products/services be available to the customer. Results show significant savings in different activities and a total time saving of 92, 31%. Other positive effects are investigated and presented. One of the most important is that store managers can focus on core activities related to sales and communication with employees and consumers. The computer cannot replace the role of man in the communication process with employees and consumers, while a man will never be able to remember and manage a large amount of data at that speed and in the way that the computer can do. The results show great applicability of the proposed methodology which is usable in all companies from different industrial sectors.
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