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Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter? / Franses, P. H. in Journal of the operational research society (JORS), Vol. 62 N° 3 Special issue (Mars 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 537–543 Titre : Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter? Type de document : texte imprimé Auteurs : Franses, P. H., Auteur ; Legerstee, R., Auteur Année de publication : 2011 Article en page(s) : pp. 537–543 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Model-based  forecasts  Expert  forecasts  Forecast  accuracy  Multi-step-ahead  forecasts Index. décimale : 001.424 Résumé : Experts (managers) may have domain-specific knowledge that is not included in a statistical model and that can improve short-run and long-run forecasts of SKU-level sales data. While one-step-ahead forecasts address the conditional mean of the variable, model-based forecasts for longer horizons have a tendency to convert to the unconditional mean of a time series variable. Analysing a large database concerning pharmaceutical sales forecasts for various products and adjusted by a range of experts, we examine whether the forecast horizon has an impact on what experts do and on how good they are once they adjust model-based forecasts. For this, we use regression-based methods and we obtain five innovative results. First, all horizons experience managerial intervention of forecasts. Second, the horizon that is most relevant to the managers shows greater overweighting of the expert adjustment. Third, for all horizons the expert adjusted forecasts have less accuracy than pure model-based forecasts, with distant horizons having the least deterioration. Fourth, when expert-adjusted forecasts are significantly better, they are best at those distant horizons. Fifth, when expert adjustment is down-weighted, expert forecast accuracy increases. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201087a.html [article] Experts' adjustment to model-based SKU-level forecasts: does the forecast horizon matter? [texte imprimé] / Franses, P. H., Auteur ; Legerstee, R., Auteur . - 2011 . - pp. 537–543. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 3 Special issue (Mars 2011) . - pp. 537–543 Mots-clés : Model-based  forecasts  Expert  forecasts  Forecast  accuracy  Multi-step-ahead  forecasts Index. décimale : 001.424 Résumé : Experts (managers) may have domain-specific knowledge that is not included in a statistical model and that can improve short-run and long-run forecasts of SKU-level sales data. While one-step-ahead forecasts address the conditional mean of the variable, model-based forecasts for longer horizons have a tendency to convert to the unconditional mean of a time series variable. Analysing a large database concerning pharmaceutical sales forecasts for various products and adjusted by a range of experts, we examine whether the forecast horizon has an impact on what experts do and on how good they are once they adjust model-based forecasts. For this, we use regression-based methods and we obtain five innovative results. First, all horizons experience managerial intervention of forecasts. Second, the horizon that is most relevant to the managers shows greater overweighting of the expert adjustment. Third, for all horizons the expert adjusted forecasts have less accuracy than pure model-based forecasts, with distant horizons having the least deterioration. Fourth, when expert-adjusted forecasts are significantly better, they are best at those distant horizons. Fifth, when expert adjustment is down-weighted, expert forecast accuracy increases. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n3/abs/jors201087a.html