The Cost Impact of Sales Prediction Accuracy

49 Pages Posted: 18 Feb 2021

See all articles by Kira Hoffmann

Kira Hoffmann

Copenhagen Business School

Matthias D. Mahlendorf

Frankfurt School of Finance & Management

Kim Pettersson

Copenhagen Business School

Date Written: February 9, 2021

Abstract

Managers’ expectations about future sales are at the core of managerial decision making. While prior literature examines the effects of demand expectations on cost behavior, we disentangle predicted and unpredicted sales changes. We draw on sales expectations from the joint harmonized EU program of business and consumer surveys and introduce the machine learning algorithm eXtreeme Gradient Boosting (xgboost). Consistent with our theory, both, results from subjective expectation data as well as results from the xgboost prediction model suggest that cost increases from unpredicted sales increases are significantly higher than cost increases from predicted sales increases, and costs are substantially more sticky for unpredicted than for predicted sales decreases. Thus, our study is relevant for managers and researchers to better quantify the cost impact of sales prediction accuracy. Moreover, by applying xgboost – a popular algorithm in data sciences – to predict future sales without internal data about the firms, our study also supports stakeholders in updating their beliefs about sales and costs, in particular for medium sized firms with little analyst coverage.

Keywords: cost management, resource adjustment costs, sales prediction, forecasting, machine learning, xgboost

JEL Classification: D24, M41, P22

Suggested Citation

Hoffmann, Kira and Mahlendorf, Matthias D. and Pettersson, Kim, The Cost Impact of Sales Prediction Accuracy (February 9, 2021). Available at SSRN: https://ssrn.com/abstract=3782336 or http://dx.doi.org/10.2139/ssrn.3782336

Kira Hoffmann

Copenhagen Business School

Solbjerg Plads 3
C4
Frederiksberg C, 2000
Denmark
+4538152326 (Phone)

Matthias D. Mahlendorf (Contact Author)

Frankfurt School of Finance & Management ( email )

Adickesallee 34
Frankfurt, DE RLP 60322
Germany

Kim Pettersson

Copenhagen Business School ( email )

Solbjerg Plads 3
Frederiksberg C, DK - 2000
Denmark

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