PL EN


Journal
2013 | 1(39) | 61-70
Article title

Demand forecasting in an enterprise – the forecasted variable selection problem

Content
Title variants
Languages of publication
EN
Abstracts
EN
Forecasting process efficiency depends – to a large extent – on the correct determination of the forecasted variable. Therefore, companies should use for sales forecasting, the variables that reflect actual consumer demand. However in practice, since demand is usually not directly observable, many operational measures of demand are used. In the manufacturing and retail enterprises, the most often used variables are historical orders, shipments, and billed sales volumes. The purpose of this paper is to characterise the effects of using as the predicted variable, different operational measures of consumer demand. Theoretical discussion is illustrated by an attempt to estimate errors in demand forecasts for Avon Cosmetics’ products that are related to changes in data used for forecasting.
Journal
Year
Issue
Pages
61-70
Physical description
Dates
published
2013
Contributors
  • Uniwersytet Ekonomiczny we Wrocławiu
  • Uniwersytet Ekonomiczny we Wrocławiu
References
  • Chase C. (2009), Demand-Driven Forecasting. A Structured Approach to Forecasting, John Wiley & Sons, Hoboken.
  • Chockalingam C. (2009), True demand: How to define and measure demand for forecasting, Demand Planning Newsletter, Demand Planning LLC.
  • Dittmann P., Szabela-Pasierbińska E., Dittmann I., Szpulak A. (2011), Prognozowanie w zarządzaniu sprzedażą i finansami przedsiębiorstwa, Oficyna Wolters Kluwer Business, Warszawa.
  • Dittmann P. (2003), Prognozowanie w przedsiębiorstwie, Oficyna Ekonomiczna, Kraków.
  • Gilliland M. (2003), Fundamental issues in business forecasting, Journal of Business Forecasting Methods & Systems 22: 7–14.
  • Gilliland M. (2010), The Business Forecasting Deal: Exposing Myths, Eliminating Bad Practices, Providing Practical Solutions, John Wiley & Sons, Hoboken.
  • Jain C.L. (2003), Forecasting errors in the consumers products industry, Journal of Business Forecasting 2: 2–4.
  • Jain C.L. (2011), Forecast errors: How much have we improved? Journal of Business Forecasting 2: 27–30.
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-80a235f5-31e9-4533-8336-8d7468eabee5
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