Procedimento para implantar um modelo de previsão de demanda com incorporação de julgamento de especialistas
A procedure to implement a judgmental adjustment of the statistical forecasts model
Staudt, Francielly Hedler; Gonçalves, Mirian Buss; Rodriguez, Carlos Manuel Taboada
http://dx.doi.org/10.1590/0103-6513.054612
Production, vol.26, n2, p.459-475, 2016
Resumo
As informações do mercado, quando interpretadas pelo especialista e incorporadas na previsão quantitativa de forma adequada, aumentam a acuracidade da previsão final. Entretanto, o julgamento humano pode inserir vieses na previsão e uma forma de evitá-los é estruturar a incorporação do julgamento. Este artigo apresenta um procedimento estruturado para que as empresas possam implantar um sistema de previsão de demanda considerando a incorporação de julgamento à saída de previsões estatísticas. A utilização do procedimento em uma pequena empresa demonstra a aplicação do método. Na análise dos resultados verificou-se que os ajustes por julgamento reduziram os erros das previsões quantitativas em média em 5%. Além disso, o melhor desempenho dos ajustes ocorreu para o produto com maior variabilidade na série histórica de dados e os maiores ajustes trouxeram os melhores resultados.
Palavras-chave
Integração de previsões. Ajuste por julgamento. Previsão de demanda
Abstract
When marketing information is well interpreted and incorporated into a quantitative forecast by an expert, forecast accuracy may be enhanced. However, human judgment might introduce biases into the forecast. One way to avoid these biases is to use structured adjustment approaches. This article presents a procedure to help companies implement a demand forecasting system with a judgmental adjustment of statistical forecasts. The use of this procedure in a small company shows its implementation. The results demonstrated that judgmental adjustments improved quantitative forecast accuracy by an average of 5%. The results also showed that the product with the greatest variability in a time series had the best adjustment performance and that the best outcomes came from the larger adjustments.
Keywords
Judgmental forecasting. Forecast adjustment. Demand forecasting.
References
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Ansuj, P. A., Camargo, M. E., & Petry, D. G. (1994). Redes neurais: uma aplicação na previsão de vendas. Produção, 4, 58-63. http://dx.doi.org/10.1590/S0103-65131994000300007
Arkes, H. R. (2001). Overconfidence in judgmental forecasting. In J. S. Armstrong. Principles of forecasting: a handbook for researches and practitioners (pp. 495-516). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_22
Armstrong, J. S. (2001). Principles of forecasting: a handbook for researches and practitioners. Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3
Armstrong, J. S., & Collopy, F. (1998). Integration of statistical methods and judgment for time series forecasting: principles from empirical research. In G. Wright & P. Goodwin (Eds.), Forecasting with judgment (pp. 269-293). Chichester: John Wiley & Sons. PMid:9921536.
Clemen, R. T. (1989). Combining forecasts: a review and annotated bibliography. International Journal of Forecasting, 5, 559-583. http://dx.doi.org/10.1016/0169-2070(89)90012-5
De Gooijer, J. G., & Hyndman, R. J. (2006). 25 years of time series forecasting. International Journal of Forecasting, 22(3), 443-473. http://dx.doi.org/10.1016/j.ijforecast.2006.01.001
Eroglu, C., & Croxton, K. L. (2010). Biases in judgmental adjustments of statistical forecasts: the role of individual differences. International Journal of Forecasting, 26(1), 116-133. http://dx.doi.org/10.1016/j.ijforecast.2009.02.005
Fildes, R., & Goodwin, P. (2007). Against your better judgment? How organizations can improve their use of management judgment in forecasting. Interfaces, 37(6), 570-576. http://dx.doi.org/10.1287/inte.1070.0309
Fildes, R., Lawrence, M., & Goodwin, P. (2006). The design features of forecasting support systems and their effectiveness. Decision Support Systems, 42(1), 351-361. http://dx.doi.org/10.1016/j.dss.2005.01.003
Fildes, R., Goodwin, P., Lawrence, M., & Nikolopoulos, K. (2009). Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, 25(1), 3-23. http://dx.doi.org/10.1016/j.ijforecast.2008.11.010
Gönül, S., Önkal, D., & Goodwin, P. (2009). Expectations, use and judgmental adjustment of external financial and economic forecasts: an empirical investigation. Journal of Forecasting, 28(1), 19-37. http://dx.doi.org/10.1002/for.1082
Goodwin, P. (2000). Improving the voluntary integration of statistical forecasts and judgement. International Journal of Forecasting, 16(1), 85-99. http://dx.doi.org/10.1016/S0169-2070(99)00026-6
Goodwin, P. (2002). Integrating management judgment and statistical methods to improve short-term forecasts. Omega International Journal of Management Science, 30(2), 127-135. http://dx.doi.org/10.1016/S0305-0483(01)00062-7
Goodwin, P., Fildes, R., Lawrence, M., & Stephens, G. (2011). Restrictiveness and guidance in support systems. Omega, 39(3), 242-253. http://dx.doi.org/10.1016/j.omega.2010.07.001
Harvey, N., & Bolger, F. (1996). Graphs versus tables: effects of data presentation format on judgmental forecasting. International Journal of Forecasting, 12(1), 119-137. http://dx.doi.org/10.1016/0169-2070(95)00634-6
Herzog, S. M., & Hertwig, R. (2009). The Wisdom of many in one mind: improving individual judgments with Dialectical Bootstrapping. Psychological Science, 20(2), 231-237. PMid:19170937. http://dx.doi.org/10.1111/j.1467-9280.2009.02271.x
Julianelli, L. (2007). Problemas de julgamento e tomada de decisão no atendimento da demanda. Rio de Janeiro: Coppead. Recuperado em 20 de março de 2012, de www.coppead.ufrj.br
Lawrence, M., Goodwin, P., O’Connor, M., & Önkal, D. (2006). Judgmental forecasting: a review of progress over the last 25 years. International Journal of Forecasting, 22(3), 493-518. http://dx.doi.org/10.1016/j.ijforecast.2006.03.007
Leitner, J., & Leopold-Wildburger, U. (2011). Experiments on forecasting behavior with several sources of information: a review of the literature. European Journal of Operational Research, 213(3), 459-469. http://dx.doi.org/10.1016/j.ejor.2011.01.006
Lemos, F. O. (2006). Metodologia para seleção de métodos de previsão de demanda (Dissertação de mestrado). Universidade Federal do Rio Grande do Sul, Porto Alegre.
Lim, J. S., & O’Connor, M. (1996). Judgmental forecasting with time series and causal information. International Journal of Forecasting, 12(1), 139-153. http://dx.doi.org/10.1016/0169-2070(95)00635-4
Makridakis, S., Wheelwright, S., & Hyndman, R. (1998). Forecasting: methods and applications. New York: John Wiley & Sons.
Marmier, F., Gonzales-Blanch, M., & Cheikhrouhou, N. (2009). A new structured adjustment approach for demand forecasting. In International Conference on Computers & Industrial Engineering, Lausanne, Switzerland.
Montgomery, D. C., & Runger, G. C. (2003). Applied statistics and probability for engineers. Phoenix: John Wiley & Sons.
Pellegrini, F. R., & Fogliatto, F. S. (2001). Passos para implantação de sistemas de previsão de demanda: técnicas e estudo de caso. Produção, 11(1), 43-64. Samohyl, R. W. (2006). Measuring the efficiency of an informal forecasting process. Foresight: The International Journal of Applied Forecasting, (3), 16-21.
Samohyl, R. W., Souza, G. P., & Miranda, R. G. (2007). Métodos simplificados de previsão empresarial. Rio de Janeiro: Ciência Moderna. (Apostila).
Sanders, N. R., & Ritzman, L. P. (2001). Judgmental adjustment of statistical forecasting. In J. S. Armstrong, Principles of forecasting: a handbook for researches and practitioners (pp. 405-416). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_18
Souza, G. P. (2008). Método para estruturar a integração de previsões utilizando a técnica Delphi. (Tese de doutorado). Universidade Federal de Santa Catarina, Florianópolis.
Staudt, F. H. (2011). Estudo de métodos de previsão de demanda com incorporação de julgamentos. (Dissertação de mestrado). Universidade Federal de Santa Catarina, Florianópolis.
Syntetos, A. A., Nikolopoulos, K., Boylan, J. E., Fildes, R., & Goodwin, P. (2009). The effects of integrating management judgement into intermittent demand forecasts. International Journal Production Economics, 118(1), 72-81. http://dx.doi.org/10.1016/j.ijpe.2008.08.011
Vondouris, C., Owusu, G., Dorne, R., & Lesaint, D. (2008). Service chain management: technology innovation for the service business. Berlin: Springer. http://dx.doi.org/10.1007/978-3-540-75504-3
Wanke, P., & Julianelli, L. (2006). Previsão de vendas: processos organizacionais e métodos quantitativos e qualitativos. (Coleção Coppead de Administração). São Paulo: Atlas.
Webby, R., & O’Connor, M. (1996). Judgemental and statistical time series forecasting: a review of the literature. International Journal of Forecasting, 12(1), 91-118. http://dx.doi.org/10.1016/0169-2070(95)00644-3
Webby, R., & O’Connor, M. (2001). Judgmental time-series forecasting using domain knowledge. In J. S. Armstrong, Principles of forecasting: a handbook for researches and practitioners (pp. 389-404). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_17
Webby, R., Connor, M. O., & Edmundson, B. (2005). Forecasting support systems for the incorporation of event information: an empirical investigation. International Journal of Forecasting, 21(3), 411-423. http://dx.doi.org/10.1016/j.ijforecast.2004.10.005
Werner, L. (2004). Um modelo composto para realizar previsão de demanda através da integração da combinação de previsões e do ajuste baseado na opinião (Tese de doutorado). Universidade Federal do Rio Grande do Sul, Porto Alegre.
Werner, L., & Ribeiro, J. L. D. (2006). Modelo composto para prever demanda através da integração de previsões. Produção, 16(3), 493-509. http://dx.doi.org/10.1590/S0103-65132006000300011
Wild, T. (1997). Best practice in inventory management. New York: John Wiley & Sons.
Ansuj, P. A., Camargo, M. E., & Petry, D. G. (1994). Redes neurais: uma aplicação na previsão de vendas. Produção, 4, 58-63. http://dx.doi.org/10.1590/S0103-65131994000300007
Arkes, H. R. (2001). Overconfidence in judgmental forecasting. In J. S. Armstrong. Principles of forecasting: a handbook for researches and practitioners (pp. 495-516). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_22
Armstrong, J. S. (2001). Principles of forecasting: a handbook for researches and practitioners. Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3
Armstrong, J. S., & Collopy, F. (1998). Integration of statistical methods and judgment for time series forecasting: principles from empirical research. In G. Wright & P. Goodwin (Eds.), Forecasting with judgment (pp. 269-293). Chichester: John Wiley & Sons. PMid:9921536.
Clemen, R. T. (1989). Combining forecasts: a review and annotated bibliography. International Journal of Forecasting, 5, 559-583. http://dx.doi.org/10.1016/0169-2070(89)90012-5
De Gooijer, J. G., & Hyndman, R. J. (2006). 25 years of time series forecasting. International Journal of Forecasting, 22(3), 443-473. http://dx.doi.org/10.1016/j.ijforecast.2006.01.001
Eroglu, C., & Croxton, K. L. (2010). Biases in judgmental adjustments of statistical forecasts: the role of individual differences. International Journal of Forecasting, 26(1), 116-133. http://dx.doi.org/10.1016/j.ijforecast.2009.02.005
Fildes, R., & Goodwin, P. (2007). Against your better judgment? How organizations can improve their use of management judgment in forecasting. Interfaces, 37(6), 570-576. http://dx.doi.org/10.1287/inte.1070.0309
Fildes, R., Lawrence, M., & Goodwin, P. (2006). The design features of forecasting support systems and their effectiveness. Decision Support Systems, 42(1), 351-361. http://dx.doi.org/10.1016/j.dss.2005.01.003
Fildes, R., Goodwin, P., Lawrence, M., & Nikolopoulos, K. (2009). Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning. International Journal of Forecasting, 25(1), 3-23. http://dx.doi.org/10.1016/j.ijforecast.2008.11.010
Gönül, S., Önkal, D., & Goodwin, P. (2009). Expectations, use and judgmental adjustment of external financial and economic forecasts: an empirical investigation. Journal of Forecasting, 28(1), 19-37. http://dx.doi.org/10.1002/for.1082
Goodwin, P. (2000). Improving the voluntary integration of statistical forecasts and judgement. International Journal of Forecasting, 16(1), 85-99. http://dx.doi.org/10.1016/S0169-2070(99)00026-6
Goodwin, P. (2002). Integrating management judgment and statistical methods to improve short-term forecasts. Omega International Journal of Management Science, 30(2), 127-135. http://dx.doi.org/10.1016/S0305-0483(01)00062-7
Goodwin, P., Fildes, R., Lawrence, M., & Stephens, G. (2011). Restrictiveness and guidance in support systems. Omega, 39(3), 242-253. http://dx.doi.org/10.1016/j.omega.2010.07.001
Harvey, N., & Bolger, F. (1996). Graphs versus tables: effects of data presentation format on judgmental forecasting. International Journal of Forecasting, 12(1), 119-137. http://dx.doi.org/10.1016/0169-2070(95)00634-6
Herzog, S. M., & Hertwig, R. (2009). The Wisdom of many in one mind: improving individual judgments with Dialectical Bootstrapping. Psychological Science, 20(2), 231-237. PMid:19170937. http://dx.doi.org/10.1111/j.1467-9280.2009.02271.x
Julianelli, L. (2007). Problemas de julgamento e tomada de decisão no atendimento da demanda. Rio de Janeiro: Coppead. Recuperado em 20 de março de 2012, de www.coppead.ufrj.br
Lawrence, M., Goodwin, P., O’Connor, M., & Önkal, D. (2006). Judgmental forecasting: a review of progress over the last 25 years. International Journal of Forecasting, 22(3), 493-518. http://dx.doi.org/10.1016/j.ijforecast.2006.03.007
Leitner, J., & Leopold-Wildburger, U. (2011). Experiments on forecasting behavior with several sources of information: a review of the literature. European Journal of Operational Research, 213(3), 459-469. http://dx.doi.org/10.1016/j.ejor.2011.01.006
Lemos, F. O. (2006). Metodologia para seleção de métodos de previsão de demanda (Dissertação de mestrado). Universidade Federal do Rio Grande do Sul, Porto Alegre.
Lim, J. S., & O’Connor, M. (1996). Judgmental forecasting with time series and causal information. International Journal of Forecasting, 12(1), 139-153. http://dx.doi.org/10.1016/0169-2070(95)00635-4
Makridakis, S., Wheelwright, S., & Hyndman, R. (1998). Forecasting: methods and applications. New York: John Wiley & Sons.
Marmier, F., Gonzales-Blanch, M., & Cheikhrouhou, N. (2009). A new structured adjustment approach for demand forecasting. In International Conference on Computers & Industrial Engineering, Lausanne, Switzerland.
Montgomery, D. C., & Runger, G. C. (2003). Applied statistics and probability for engineers. Phoenix: John Wiley & Sons.
Pellegrini, F. R., & Fogliatto, F. S. (2001). Passos para implantação de sistemas de previsão de demanda: técnicas e estudo de caso. Produção, 11(1), 43-64. Samohyl, R. W. (2006). Measuring the efficiency of an informal forecasting process. Foresight: The International Journal of Applied Forecasting, (3), 16-21.
Samohyl, R. W., Souza, G. P., & Miranda, R. G. (2007). Métodos simplificados de previsão empresarial. Rio de Janeiro: Ciência Moderna. (Apostila).
Sanders, N. R., & Ritzman, L. P. (2001). Judgmental adjustment of statistical forecasting. In J. S. Armstrong, Principles of forecasting: a handbook for researches and practitioners (pp. 405-416). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_18
Souza, G. P. (2008). Método para estruturar a integração de previsões utilizando a técnica Delphi. (Tese de doutorado). Universidade Federal de Santa Catarina, Florianópolis.
Staudt, F. H. (2011). Estudo de métodos de previsão de demanda com incorporação de julgamentos. (Dissertação de mestrado). Universidade Federal de Santa Catarina, Florianópolis.
Syntetos, A. A., Nikolopoulos, K., Boylan, J. E., Fildes, R., & Goodwin, P. (2009). The effects of integrating management judgement into intermittent demand forecasts. International Journal Production Economics, 118(1), 72-81. http://dx.doi.org/10.1016/j.ijpe.2008.08.011
Vondouris, C., Owusu, G., Dorne, R., & Lesaint, D. (2008). Service chain management: technology innovation for the service business. Berlin: Springer. http://dx.doi.org/10.1007/978-3-540-75504-3
Wanke, P., & Julianelli, L. (2006). Previsão de vendas: processos organizacionais e métodos quantitativos e qualitativos. (Coleção Coppead de Administração). São Paulo: Atlas.
Webby, R., & O’Connor, M. (1996). Judgemental and statistical time series forecasting: a review of the literature. International Journal of Forecasting, 12(1), 91-118. http://dx.doi.org/10.1016/0169-2070(95)00644-3
Webby, R., & O’Connor, M. (2001). Judgmental time-series forecasting using domain knowledge. In J. S. Armstrong, Principles of forecasting: a handbook for researches and practitioners (pp. 389-404). Dordrecht: Kluwer Academic Publishers. http://dx.doi.org/10.1007/978-0-306-47630-3_17
Webby, R., Connor, M. O., & Edmundson, B. (2005). Forecasting support systems for the incorporation of event information: an empirical investigation. International Journal of Forecasting, 21(3), 411-423. http://dx.doi.org/10.1016/j.ijforecast.2004.10.005
Werner, L. (2004). Um modelo composto para realizar previsão de demanda através da integração da combinação de previsões e do ajuste baseado na opinião (Tese de doutorado). Universidade Federal do Rio Grande do Sul, Porto Alegre.
Werner, L., & Ribeiro, J. L. D. (2006). Modelo composto para prever demanda através da integração de previsões. Produção, 16(3), 493-509. http://dx.doi.org/10.1590/S0103-65132006000300011
Wild, T. (1997). Best practice in inventory management. New York: John Wiley & Sons.
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