Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/1750
Title: Sales prediction for a pharmaceutical distribution company: a data mining based approach | Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining
Authors: Ribeiro, Augusto
Seruca, Isabel
Durão, Natércia
Keywords: medicines
stock unavailability
data mining
time series
sales prediction
Issue Date: 2016
Publisher: AISTI | ULPG
Citation: • Ribeiro A, Seruca I and Durão N (2016) Sales prediction for a pharmaceutical distribution company: a data mining based approach | [Previsão de vendas numa empresa de distribuição farmacêutica: uma aproximação baseada em data mining], Á. Rocha, L. P. Reis, M. P. Cota, O. S. Suárez & R. Gonçalves (eds.), Atas da 11ª Conferência Ibérica de Sistemas e Tecnologias de Informação (CISTI'2016), Gran Canaria, Espanha, 15-18 Junho 2016, pp 532-538, AISTI | ULPG.
Abstract: For pharmaceutical distribution companies it is essential to obtain good estimates of medicine needs, due to the short shelf life of many medicines and the need to control stock levels, so as to avoid excessive inventory costs while guaranteeing customer demand satisfaction, and thus decreasing the possibility of loss of customers due to stock outages. In this paper we explore the use of the time series data mining technique for the sales prediction of individual products of a pharmaceutical distribution company in Portugal. Through data mining techniques, the historical data of product sales are analyzed to detect patterns and make predictions based on the experience contained in the data. The results obtained with the technique as well as with the proposed method suggest that the performed modelling may be considered appropriate for the short term product sales prediction.
URI: http://hdl.handle.net/11328/1750
Appears in Collections:REMIT - Comunicações a Congressos Internacionais / Papers in International Meetings

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