Forecasting accuracy is an important issue for effective decision making in the areas of strategic planning, production planning, inventory management and other areas. In particular, this aspect is most relevant for items that have demand patterns with important levels of intermittency and lumpiness. This work describes the efforts of a Mexican company to look for opportunities to improve the level of forecasting accuracy through the application of demand aggregation to all the items of the company´s catalogue. The level of demand aggregation considered is a period equivalent to the review plus de response time periods of the periodic review management system used by the firm. Initial results are obtained from a pilot study carried out in all the stores of the Tijuana plaza of the company. The resulting forecasting mean squared error (MSE) was decreased significantly in the range of 32 to 56%. The firm estimates a reduction in the order of 17.7 to 33.9% in safety stock requirements will be possible due to the improvement in forecasting accuracy.
|Title of host publication||Proceedings of the International Conference on Industrial Engineering and Operations Management|
|Number of pages||8|
|Publication status||Published - 26 Jul 2018|
|Name||Proceedings of the International Conference on Industrial Engineering and Operations Management|
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
Villarreal, B., delia Villarreal, Mariana Herrera, & Quintanilla, E. (2018). Applying Demand Aggregation to Improve Forecasting Accuracy. In Proceedings of the International Conference on Industrial Engineering and Operations Management (JUL ed., Vol. 2018, pp. 1521-1528). (Proceedings of the International Conference on Industrial Engineering and Operations Management). IEOM Society.