University of Twente Student Theses


Inventory Management optimization through a Demand Forecasting improvement

Rouwers, J.A.M. (2022) Inventory Management optimization through a Demand Forecasting improvement.

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Abstract:Verosol produces high quality indoor blinds and offers these to the international market. Verosol did not meet its customer delivery performance target over the past years. It was observed that the basis of an inventory control policy is currently missing; i.e. an optimized statistical demand forecasting method and the forecasting performance logging. We investigated how the integration of a statistical forecasting method could contribute to an improved inventory control policy and evaluated the impact of this solution on the current situation by means of comparing the advised minimum safety stock (SS) levels to the minimum inventory levels currently established. The included SKUs have been classified using the ABC- and a Demand Pattern (DP)-method and its demand has been forecasted by using the Simple Exponential Smoothing (SES), Holt, Winters and Croston methods accordingly. Based on the research findings, it can be concluded that the relatively simple forecasting methods, such as SES and Croston, outperform the current forecasting methodology and also outperform the more sophisticated methods such as Holt and Winters. In addition, it can be concluded that the documentation of the demand data, used as input for the forecasting, should be adjusted in the light of demand forecasting and inventory control.
Item Type:Essay (Master)
Verosol, Eibergen, Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:58 process technology, 85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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