Automated store ordering has been offered as a potential solution to many store level problems: Automation could improve availability, decrease inventories, and reduce the time and labor required for ordering. However, despite the potential advantages, it seems that the majority of retailers have only just started to implement automated ordering systems at store level. Furthermore, very little published information can be found on store level processes, not to mention automated store ordering. Therefore, well-documented research on how and if conventional inventory management practices can be applied at store level operations should be extremely engrossing both from academic and business viewpoints. This master’s thesis examines how automated store ordering could more efficiently be utilized to improve store operations and performance. The problem is approached first from the theoretical viewpoint: In the literature review, the retail supply chain and store level processes and performance are examined. Furthermore, inventory management and forecasting practices as well as their application in retailing are reviewed.
The empirical work in the thesis consists of a part where survey material form the study “Logistics processes of European grocery retailers” is analyzed, and a case as well as a simulation study. The survey material provides information on how common ASO systems are and what kind of systems actually have been implemented; The case study offers the opportunity to explore the implementation of an ASO system in practice; And the simulations enable developing and testing ways in which the performance of ASO systems can be enhanced. Both the theoretical and empirical parts of the thesis present practical conclusions and results. The most important findings of the thesis are the following: – Many companies have just started to implement automated store ordering systems.
The systems in use are typically fairly simple, and they are most often used for managing the normal material flow. Exception situations as well as more challenging product groups are still usually handled manually. – The performance of basic automated store ordering systems can be enhanced by taking into consideration special characteristics of store environment. In case of normal material flow, robust methods are needed to tackle weekday demand and varying replenishment intervals. This can be accomplished by applying material requirements planning logic in order determination. – For efficiently managing promotions with automated store ordering systems, it is important to improve flexibility and react to initial promotion demand.
Key words: Automated store ordering, retail logistics, inventory management, retail store processes
Special word of thanks to the people who have contributed to the completion of this thesis. First, I would like to thank my instructor, and friend, Johanna Småros for her support, feedback and guidance. Without her deadlines, and understanding, this thesis would not exist. My appreciation goes to Professor Kari Tanskanen for his supervision and guidance, and to all the members of the Logistics Research Group for a wonderful and inspiring working environment. I would also like to thank the people in the case company, especially Aleksi. And most of all, I would like to thank those closest to me. My wonderful friends at Helsinki University of Technology have been a great cause of happiness and comfort during the last five years, and especially this spring. Finally, I am deeply grateful to my family: What allows me to risk getting shattered is the knowledge that you will be there to pick up the pieces.
University/College: University of Chicago
Type of paper: Thesis/Dissertation Chapter
Date: 1 October 2016
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