Inventory management in a customer landscape with diverse requirements on flexibility - A case study at Atria Sweden AB

Sammanfattning: Abstract Title Inventory management in a customer landscape with diverse requirements on flexibility - A case study at Atria Sweden AB. Course Degree Project in Production Management – MIOM01. Authors Annika Fredriksson and Andreas Pettersson. Supervisor Johan Marklund. Background and Research Question Atria Sweden AB manufactures meat products towards both the Swedish and Danish markets. As a result of the different products and customer requirements, Atria applies different manufacturing strategies towards the different products. Atria has access to reliable forecasts and regular orders from the Swedish market, making it possible to manufacture these products towards stock. From the Danish market forecasts are currently unreliable and orders are not as frequent when compared to the Swedish market. Therefore, Danish products are manufactured based on customer orders and Atria wants to be flexible enough to satisfy customer demand and achieve targeted service levels. Atria has increased their efforts in information gathering by actively collecting demand data from customers when available to improve their demand forecast. Atria wants to investigate how their processes can be improved to increase overall flexibility to satisfy customer demand. Methodology The study has been conducted using an abductive research approach. Thus, both qualitative and quantitative data was collected to analyze the research question. Quantitative data was collected through the database at Atria, this data was complemented with qualitative data collected through semi-structured interviews. Theoretical Framework This study is based on established scientific literature in the area of inventory management. Conclusion This study has shown that flexibility and service levels can be improved for specific products by implementing an (R, Q) – policy. Additionally, the expected service level can be calculated assuming accurate knowledge of the demand. By calculating the fill rate of the gamma distributed demand, the service levels can be estimated. Keywords Inventory management, fill rate, gamma distribution, MTS, MTO, (R, Q) – policy, food industry, perishable goods, reorder points, process analysis.