Improving order fulfillment through triple exponential smoothing, ABC and linear programming in an alcoholic beverage delivery company
Abstract
In the current commercial context, the implementation of e-commerce is becoming increasingly prevalent in the Peruvian territory, which gives rise to several challenges in the management of the companies’ supply system. This research focuses on the application of engineering tools, such as ABC classification, triple exponential smoothing and linear programming, in the management of an alcoholic beverage delivery business, in order to increase the order fulfillment rate. The improvement proposal is developed taking into account the constraints faced by retail companies in Peru. Initially, the market demand for beverage orders is forecasted; then, the forecasted products are classified to identify those with higher turnover and revenues; and finally, a model is programmed to minimize the associated costs. As a result, a 95 % order fulfillment rate was achieved and significant cost optimization was reached, which shows the efficiency achieved.
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References
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