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Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge

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  • Petropoulos, Fotios
  • Goodwin, Paul
  • Fildes, Robert

Abstract

There are several biases and inefficiencies that are commonly associated with the judgmental extrapolation of time series, even when the forecasters have technical knowledge about forecasting. This study examines the effectiveness of using a rolling training approach, based on feedback, to improve the accuracy of forecasts elicited from people with such knowledge. In an experiment, forecasters were asked to make multiple judgmental extrapolations for a set of time series from different time origins. For each series in turn, the participants were either unaided or provided with feedback. In the latter case, the true outcomes and performance feedback were provided following the submission of each set of forecasts. The objective was to provide a training scheme that would enable forecasters to understand the underlying pattern of the data better by learning from their forecast errors directly. An analysis of the results indicated that this rolling training approach is an effective method for enhancing the judgmental extrapolations elicited from people with technical knowledge, especially when bias feedback is provided. As such, it could be a valuable element in the design of software systems that are intended to support expert knowledge elicitation (EKE) in forecasting.

Suggested Citation

  • Petropoulos, Fotios & Goodwin, Paul & Fildes, Robert, 2017. "Using a rolling training approach to improve judgmental extrapolations elicited from forecasters with technical knowledge," International Journal of Forecasting, Elsevier, vol. 33(1), pages 314-324.
    • Handle: RePEc:eee:intfor:v:33:y:2017:i:1:p:314-324
    DOI: 10.1016/j.ijforecast.2015.12.006
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    1. Mirko Kremer & Brent Moritz & Enno Siemsen, 2011. "Demand Forecasting Behavior: System Neglect and Change Detection," Management Science, INFORMS, vol. 57(10), pages 1827-1843, October.
    2. Willemain, Thomas R., 1989. "Graphical adjustment of statistical forecasts," International Journal of Forecasting, Elsevier, vol. 5(2), pages 179-185.
    3. Goodwin, Paul & Wright, George, 1993. "Improving judgmental time series forecasting: A review of the guidance provided by research," International Journal of Forecasting, Elsevier, vol. 9(2), pages 147-161, August.
    4. Eggleton, Irc, 1982. "Intuitive Time-Series Extrapolation," Journal of Accounting Research, Wiley Blackwell, vol. 20(1), pages 68-102.
    5. Lawrence, Michael & Makridakis, Spyros, 1989. "Factors affecting judgmental forecasts and confidence intervals," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(2), pages 172-187, April.
    6. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
    7. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
    8. Onkal, Dilek & Muradoglu, Gulnur, 1995. "Effects of feedback on probabilistic forecasts of stock prices," International Journal of Forecasting, Elsevier, vol. 11(2), pages 307-319, June.
    9. Bolger, Fergus & Onkal-Atay, Dilek, 2004. "The effects of feedback on judgmental interval predictions," International Journal of Forecasting, Elsevier, vol. 20(1), pages 29-39.
    10. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
    11. Willy Aspinall, 2010. "A route to more tractable expert advice," Nature, Nature, vol. 463(7279), pages 294-295, January.
    12. Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
    13. Harvey, Nigel, 1995. "Why Are Judgments Less Consistent in Less Predictable Task Situations?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(3), pages 247-263, September.
    14. Remus, William & O'Conner, Marcus & Griggs, Kenneth, 1996. "Does Feedback Improve the Accuracy of Recurrent Judgmental Forecasts?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 66(1), pages 22-30, April.
    15. Sanders, Nada R. & Ritzman, Larry P., 1992. "Journal of behavioral decision making: "The need for contextual and technical knowledge in judgmental forecasting", 5 (1992) 39-52," International Journal of Forecasting, Elsevier, vol. 8(4), pages 651-652, December.
    16. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    17. Robert Fildes & Paul Goodwin, 2007. "Against Your Better Judgment? How Organizations Can Improve Their Use of Management Judgment in Forecasting," Interfaces, INFORMS, vol. 37(6), pages 570-576, December.
    18. Sanders, N. R., 1997. "The impact of task properties feedback on time series judgmental forecasting tasks," Omega, Elsevier, vol. 25(2), pages 135-144, April.
    19. Reimers, Stian & Harvey, Nigel, 2011. "Sensitivity to autocorrelation in judgmental time series forecasting," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1196-1214, October.
    20. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
    21. Lawrence, Michael & O'Connor, Marcus, 1992. "Exploring judgemental forecasting," International Journal of Forecasting, Elsevier, vol. 8(1), pages 15-26, June.
    22. Willemain, Thomas R., 1991. "The effect of graphical adjustment on forecast accuracy," International Journal of Forecasting, Elsevier, vol. 7(2), pages 151-154, August.
    23. Goodwin, P & Wright, G, 1994. "Heuristics, biases and improvement strategies in judgmental time series forecasting," Omega, Elsevier, vol. 22(6), pages 553-568, November.
    24. Andreassen, Paul B., 1988. "Explaining the price-volume relationship: The difference between price changes and changing prices," Organizational Behavior and Human Decision Processes, Elsevier, vol. 41(3), pages 371-389, June.
    25. Fischer, Ilan & Harvey, Nigel, 1999. "Combining forecasts: What information do judges need to outperform the simple average?," International Journal of Forecasting, Elsevier, vol. 15(3), pages 227-246, July.
    26. O'Connor, Marcus & Remus, William & Griggs, Ken, 1993. "Judgemental forecasting in times of change," International Journal of Forecasting, Elsevier, vol. 9(2), pages 163-172, August.
    27. Franses,Philip Hans, 2014. "Expert Adjustments of Model Forecasts," Cambridge Books, Cambridge University Press, number 9781107081598, September.
    28. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    29. Makridakis, Spyros & Hogarth, Robin M. & Gaba, Anil, 2009. "Forecasting and uncertainty in the economic and business world," International Journal of Forecasting, Elsevier, vol. 25(4), pages 794-812, October.
    30. Sanders, Nada R. & Graman, Gregory A., 2009. "Quantifying costs of forecast errors: A case study of the warehouse environment," Omega, Elsevier, vol. 37(1), pages 116-125, February.
    31. Lurie, Nicholas H. & Swaminathan, Jayashankar M., 2009. "Is timely information always better? The effect of feedback frequency on decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 108(2), pages 315-329, March.
    32. Lawrence, Michael J. & Edmundson, Robert H. & O'Connor, Marcus J., 1985. "An examination of the accuracy of judgmental extrapolation of time series," International Journal of Forecasting, Elsevier, vol. 1(1), pages 25-35.
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    Cited by:

    1. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
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      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    3. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    4. Sroginis, Anna & Fildes, Robert & Kourentzes, Nikolaos, 2023. "Use of contextual and model-based information in adjusting promotional forecasts," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1177-1191.
    5. Makridakis, Spyros & Hyndman, Rob J. & Petropoulos, Fotios, 2020. "Forecasting in social settings: The state of the art," International Journal of Forecasting, Elsevier, vol. 36(1), pages 15-28.
    6. Andrey Davydenko & Paul Goodwin, 2021. "Assessing Point Forecast Bias Across Multiple Time Series: Measures and Visual Tools," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(5), pages 1-46, September.

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