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    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, 209, 2018 DOI: 10.1016/j.ijpe.2018.06.016

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Incorporating macroeconomic leading indicators in tactical capacity planning

Research output: Contribution to journalJournal articlepeer-review

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Incorporating macroeconomic leading indicators in tactical capacity planning. / Sagaert, Yves R.; Kourentzes, Nikolaos; De Vuyst, Stijn; Aghezzaf, El-Houssaine; Desmet, Bram.

In: International Journal of Production Economics, Vol. 209, 01.03.2019, p. 12-19.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Sagaert, YR, Kourentzes, N, De Vuyst, S, Aghezzaf, E-H & Desmet, B 2019, 'Incorporating macroeconomic leading indicators in tactical capacity planning', International Journal of Production Economics, vol. 209, pp. 12-19. https://doi.org/10.1016/j.ijpe.2018.06.016

APA

Sagaert, Y. R., Kourentzes, N., De Vuyst, S., Aghezzaf, E-H., & Desmet, B. (2019). Incorporating macroeconomic leading indicators in tactical capacity planning. International Journal of Production Economics, 209, 12-19. https://doi.org/10.1016/j.ijpe.2018.06.016

Vancouver

Sagaert YR, Kourentzes N, De Vuyst S, Aghezzaf E-H, Desmet B. Incorporating macroeconomic leading indicators in tactical capacity planning. International Journal of Production Economics. 2019 Mar 1;209:12-19. https://doi.org/10.1016/j.ijpe.2018.06.016

Author

Sagaert, Yves R. ; Kourentzes, Nikolaos ; De Vuyst, Stijn ; Aghezzaf, El-Houssaine ; Desmet, Bram. / Incorporating macroeconomic leading indicators in tactical capacity planning. In: International Journal of Production Economics. 2019 ; Vol. 209. pp. 12-19.

Bibtex

@article{683303a90a4347548e51fb484eeef043,
title = "Incorporating macroeconomic leading indicators in tactical capacity planning",
abstract = "Tactical capacity planning relies on future estimates of demand for the mid- to long-term. On these forecast horizons there is increased uncertainty that the analysts face. To this purpose, we incorporate macroeconomic variables into microeconomic demand forecasting. Forecast accuracy metrics, which are typically used to assess improvements in predictions, are proxies of the real decision associated costs. However, measuring the direct impact on decisions is preferable. In this paper, we examine the capacity planning decision at plant level of a manufacturer. Through an inventory simulation setup, we evaluate the gains of incorporating external macroeconomic information in the forecasts, directly, in terms of achieving target service levels and inventory performance. Furthermore, we provide an approach to indicate capacity alerts, which can serve as input for global capacity pooling decisions. Our work has two main contributions. First, we demonstrate the added value of leading indicator information in forecasting models, when evaluated directly on capacity planning. Second, we provide additional evidence that traditional metrics of forecast accuracy exhibit weak connection with the real decision costs, in particular for capacity planning. We propose a more realistic assessment of the forecast quality by evaluating both the first and second moment of the forecast distribution. We discuss implications for practice, in particular given the typical over-reliance on forecast accuracy metrics for choosing the appropriate forecasting model. ",
keywords = "Forecasting, Leading indicators, Inventory, Capacity planning",
author = "Sagaert, {Yves R.} and Nikolaos Kourentzes and {De Vuyst}, Stijn and El-Houssaine Aghezzaf and Bram Desmet",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, 209, 2018 DOI: 10.1016/j.ijpe.2018.06.016",
year = "2019",
month = mar,
day = "1",
doi = "10.1016/j.ijpe.2018.06.016",
language = "English",
volume = "209",
pages = "12--19",
journal = "International Journal of Production Economics",
issn = "0925-5273",
publisher = "Elsevier Science B.V.",

}

RIS

TY - JOUR

T1 - Incorporating macroeconomic leading indicators in tactical capacity planning

AU - Sagaert, Yves R.

AU - Kourentzes, Nikolaos

AU - De Vuyst, Stijn

AU - Aghezzaf, El-Houssaine

AU - Desmet, Bram

N1 - This is the author’s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, 209, 2018 DOI: 10.1016/j.ijpe.2018.06.016

PY - 2019/3/1

Y1 - 2019/3/1

N2 - Tactical capacity planning relies on future estimates of demand for the mid- to long-term. On these forecast horizons there is increased uncertainty that the analysts face. To this purpose, we incorporate macroeconomic variables into microeconomic demand forecasting. Forecast accuracy metrics, which are typically used to assess improvements in predictions, are proxies of the real decision associated costs. However, measuring the direct impact on decisions is preferable. In this paper, we examine the capacity planning decision at plant level of a manufacturer. Through an inventory simulation setup, we evaluate the gains of incorporating external macroeconomic information in the forecasts, directly, in terms of achieving target service levels and inventory performance. Furthermore, we provide an approach to indicate capacity alerts, which can serve as input for global capacity pooling decisions. Our work has two main contributions. First, we demonstrate the added value of leading indicator information in forecasting models, when evaluated directly on capacity planning. Second, we provide additional evidence that traditional metrics of forecast accuracy exhibit weak connection with the real decision costs, in particular for capacity planning. We propose a more realistic assessment of the forecast quality by evaluating both the first and second moment of the forecast distribution. We discuss implications for practice, in particular given the typical over-reliance on forecast accuracy metrics for choosing the appropriate forecasting model.

AB - Tactical capacity planning relies on future estimates of demand for the mid- to long-term. On these forecast horizons there is increased uncertainty that the analysts face. To this purpose, we incorporate macroeconomic variables into microeconomic demand forecasting. Forecast accuracy metrics, which are typically used to assess improvements in predictions, are proxies of the real decision associated costs. However, measuring the direct impact on decisions is preferable. In this paper, we examine the capacity planning decision at plant level of a manufacturer. Through an inventory simulation setup, we evaluate the gains of incorporating external macroeconomic information in the forecasts, directly, in terms of achieving target service levels and inventory performance. Furthermore, we provide an approach to indicate capacity alerts, which can serve as input for global capacity pooling decisions. Our work has two main contributions. First, we demonstrate the added value of leading indicator information in forecasting models, when evaluated directly on capacity planning. Second, we provide additional evidence that traditional metrics of forecast accuracy exhibit weak connection with the real decision costs, in particular for capacity planning. We propose a more realistic assessment of the forecast quality by evaluating both the first and second moment of the forecast distribution. We discuss implications for practice, in particular given the typical over-reliance on forecast accuracy metrics for choosing the appropriate forecasting model.

KW - Forecasting

KW - Leading indicators

KW - Inventory

KW - Capacity planning

U2 - 10.1016/j.ijpe.2018.06.016

DO - 10.1016/j.ijpe.2018.06.016

M3 - Journal article

VL - 209

SP - 12

EP - 19

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

ER -