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On the accuracy of judgmental interventions on forecasting support systems

Research output: Working paper

Published

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On the accuracy of judgmental interventions on forecasting support systems. / Nikolopoulos, K; Lawrence, M; Goodwin, P et al.
Lancaster University: The Department of Management Science, 2005. (Management Science Working Paper Series).

Research output: Working paper

Harvard

Nikolopoulos, K, Lawrence, M, Goodwin, P & Fildes, RA 2005 'On the accuracy of judgmental interventions on forecasting support systems' Management Science Working Paper Series, The Department of Management Science, Lancaster University.

APA

Nikolopoulos, K., Lawrence, M., Goodwin, P., & Fildes, R. A. (2005). On the accuracy of judgmental interventions on forecasting support systems. (Management Science Working Paper Series). The Department of Management Science.

Vancouver

Nikolopoulos K, Lawrence M, Goodwin P, Fildes RA. On the accuracy of judgmental interventions on forecasting support systems. Lancaster University: The Department of Management Science. 2005. (Management Science Working Paper Series).

Author

Nikolopoulos, K ; Lawrence, M ; Goodwin, P et al. / On the accuracy of judgmental interventions on forecasting support systems. Lancaster University : The Department of Management Science, 2005. (Management Science Working Paper Series).

Bibtex

@techreport{900cda0f52be4d739844258ed36038eb,
title = "On the accuracy of judgmental interventions on forecasting support systems",
abstract = "Forecasting at the Stock Keeping Unit (SKU) disaggregate level in order to support operations management has proved a very difficult task. The levels of accuracy achieved have major consequences for companies at all levels in the supply chain; errors at each stage are amplified resulting in poor service and overly high inventory levels. In most companies, the size and complexity of the forecasting task necessitates the use of Forecasting Support Systems (FSS). The present study examines monthly demand data and forecasts for 44 fast moving, A-class, durable SKUs, collected from a major U.K. supplier. The company relies upon a FSS to produce baseline forecasts per SKU for each period. Final forecasts are produced at a later stage through the superimposition of judgments based on marketing intelligence gathered by the company forecasters. The benefits of the intervention are evaluated by comparing the actual sales both to system and final forecasts. The findings support the case that adjustments do improve accuracy, particularly under the condition that the adjustment is conservative, in the right direction, but does not overshoot. The question is how best to meet these conditions.",
keywords = "Forecasting Support Systems, Judgmental Interventions, Supply Chain",
author = "K Nikolopoulos and M Lawrence and P Goodwin and Fildes, {R A}",
year = "2005",
language = "English",
series = "Management Science Working Paper Series",
publisher = "The Department of Management Science",
type = "WorkingPaper",
institution = "The Department of Management Science",

}

RIS

TY - UNPB

T1 - On the accuracy of judgmental interventions on forecasting support systems

AU - Nikolopoulos, K

AU - Lawrence, M

AU - Goodwin, P

AU - Fildes, R A

PY - 2005

Y1 - 2005

N2 - Forecasting at the Stock Keeping Unit (SKU) disaggregate level in order to support operations management has proved a very difficult task. The levels of accuracy achieved have major consequences for companies at all levels in the supply chain; errors at each stage are amplified resulting in poor service and overly high inventory levels. In most companies, the size and complexity of the forecasting task necessitates the use of Forecasting Support Systems (FSS). The present study examines monthly demand data and forecasts for 44 fast moving, A-class, durable SKUs, collected from a major U.K. supplier. The company relies upon a FSS to produce baseline forecasts per SKU for each period. Final forecasts are produced at a later stage through the superimposition of judgments based on marketing intelligence gathered by the company forecasters. The benefits of the intervention are evaluated by comparing the actual sales both to system and final forecasts. The findings support the case that adjustments do improve accuracy, particularly under the condition that the adjustment is conservative, in the right direction, but does not overshoot. The question is how best to meet these conditions.

AB - Forecasting at the Stock Keeping Unit (SKU) disaggregate level in order to support operations management has proved a very difficult task. The levels of accuracy achieved have major consequences for companies at all levels in the supply chain; errors at each stage are amplified resulting in poor service and overly high inventory levels. In most companies, the size and complexity of the forecasting task necessitates the use of Forecasting Support Systems (FSS). The present study examines monthly demand data and forecasts for 44 fast moving, A-class, durable SKUs, collected from a major U.K. supplier. The company relies upon a FSS to produce baseline forecasts per SKU for each period. Final forecasts are produced at a later stage through the superimposition of judgments based on marketing intelligence gathered by the company forecasters. The benefits of the intervention are evaluated by comparing the actual sales both to system and final forecasts. The findings support the case that adjustments do improve accuracy, particularly under the condition that the adjustment is conservative, in the right direction, but does not overshoot. The question is how best to meet these conditions.

KW - Forecasting Support Systems

KW - Judgmental Interventions

KW - Supply Chain

M3 - Working paper

T3 - Management Science Working Paper Series

BT - On the accuracy of judgmental interventions on forecasting support systems

PB - The Department of Management Science

CY - Lancaster University

ER -