Home > Research > Publications & Outputs > Forecasting with Judgment

Research

Links

Text available via DOI:

View graph of relations

Forecasting with Judgment

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Published

Standard

Forecasting with Judgment. / Goodwin, Paul; Fildes, Robert.
The Palgrave Handbook of Operations Research. ed. / Said Sahli; John Boylan. Cham: Palgrave Macmillan, 2022. p. 541-572.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Harvard

Goodwin, P & Fildes, R 2022, Forecasting with Judgment. in S Sahli & J Boylan (eds), The Palgrave Handbook of Operations Research. Palgrave Macmillan, Cham, pp. 541-572. https://doi.org/10.1007/978-3-030-96935-6_16

APA

Goodwin, P., & Fildes, R. (2022). Forecasting with Judgment. In S. Sahli, & J. Boylan (Eds.), The Palgrave Handbook of Operations Research (pp. 541-572). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-96935-6_16

Vancouver

Goodwin P, Fildes R. Forecasting with Judgment. In Sahli S, Boylan J, editors, The Palgrave Handbook of Operations Research. Cham: Palgrave Macmillan. 2022. p. 541-572 doi: 10.1007/978-3-030-96935-6_16

Author

Goodwin, Paul ; Fildes, Robert. / Forecasting with Judgment. The Palgrave Handbook of Operations Research. editor / Said Sahli ; John Boylan. Cham : Palgrave Macmillan, 2022. pp. 541-572

Bibtex

@inbook{2c37205070bf4e9a8d7d5db0cabe0136,
title = "Forecasting with Judgment",
abstract = "This chapter explores the roles that human judgment plays in forecasting in organisations. It focuses on the latest research findings to examine why, despite advances in predictive analytics, the rise of machine learning and the availability of Big Data, forecasts still often rely heavily on judgment. We identify the circumstances where judgment brings benefits to forecasts, as well as the dangers that motivational and cognitive biases bring, leading to inaccurate forecasts. Strategies for improving judgment in forecasting are then evaluated. These include providing feedback, restricting interventions, decomposition, correcting forecasts to remove biases, manipulating the time available to produce forecasts, structuring group forecasting processes and integrating judgment with statistical methods. We conclude that, despite advances in predictive analytics, judgment is likely to continue to have a major role in forecasting. There is therefore a need to develop more advanced software systems that provide enhanced support for judgmental inputs to forecasting processes.",
author = "Paul Goodwin and Robert Fildes",
year = "2022",
month = jul,
day = "8",
doi = "10.1007/978-3-030-96935-6_16",
language = "English",
isbn = "9783030969349",
pages = "541--572",
editor = "Said Sahli and John Boylan",
booktitle = "The Palgrave Handbook of Operations Research",
publisher = "Palgrave Macmillan",

}

RIS

TY - CHAP

T1 - Forecasting with Judgment

AU - Goodwin, Paul

AU - Fildes, Robert

PY - 2022/7/8

Y1 - 2022/7/8

N2 - This chapter explores the roles that human judgment plays in forecasting in organisations. It focuses on the latest research findings to examine why, despite advances in predictive analytics, the rise of machine learning and the availability of Big Data, forecasts still often rely heavily on judgment. We identify the circumstances where judgment brings benefits to forecasts, as well as the dangers that motivational and cognitive biases bring, leading to inaccurate forecasts. Strategies for improving judgment in forecasting are then evaluated. These include providing feedback, restricting interventions, decomposition, correcting forecasts to remove biases, manipulating the time available to produce forecasts, structuring group forecasting processes and integrating judgment with statistical methods. We conclude that, despite advances in predictive analytics, judgment is likely to continue to have a major role in forecasting. There is therefore a need to develop more advanced software systems that provide enhanced support for judgmental inputs to forecasting processes.

AB - This chapter explores the roles that human judgment plays in forecasting in organisations. It focuses on the latest research findings to examine why, despite advances in predictive analytics, the rise of machine learning and the availability of Big Data, forecasts still often rely heavily on judgment. We identify the circumstances where judgment brings benefits to forecasts, as well as the dangers that motivational and cognitive biases bring, leading to inaccurate forecasts. Strategies for improving judgment in forecasting are then evaluated. These include providing feedback, restricting interventions, decomposition, correcting forecasts to remove biases, manipulating the time available to produce forecasts, structuring group forecasting processes and integrating judgment with statistical methods. We conclude that, despite advances in predictive analytics, judgment is likely to continue to have a major role in forecasting. There is therefore a need to develop more advanced software systems that provide enhanced support for judgmental inputs to forecasting processes.

U2 - 10.1007/978-3-030-96935-6_16

DO - 10.1007/978-3-030-96935-6_16

M3 - Chapter

SN - 9783030969349

SP - 541

EP - 572

BT - The Palgrave Handbook of Operations Research

A2 - Sahli, Said

A2 - Boylan, John

PB - Palgrave Macmillan

CY - Cham

ER -