Applicability and accuracy of quantitative forecasting ...

Applicability and accuracy of quantitative forecasting models applied in actual firms

A case study at The Company

Master of Science Thesis in the Management and Economics of Innovation Programme

JOHAN EGNELL LINNEA HANSSON

Department of Technology Management and Economics Division of Innovation Engineering and Management CHALMERS UNIVERSITY OF TECHNOLOGY G?teborg, Sweden, 2013 Report No. E 2013:115

MASTER'S THESIS E 2013:115

Applicability and accuracy of quantitative forecasting models applied in actual firms

A case study at The Company

JOHAN EGNELL LINNEA HANSSON

Tutor, Chalmers: Jan Wickenberg

Department of Technology Management and Economics Division of Innovation Engineering and Management CHALMERS UNIVERSITY OF TECHNOLOGY G?teborg, Sweden 2013

Applicability and accuracy of quantitative forecasting models applied in actual firms Johan Egnell and Linnea Hansson ? Johan Egnell and Linnea Hansson, 2013

Master's Thesis E 2013:115 Department of Technology Management and Economics Division of Innovation Engineering and Management Chalmers University of Technology SE-412 96 G?teborg, Sweden Telephone: + 46 (0)31-772 1000

Chalmers Reproservice G?teborg, Sweden 2013

Abstract

Taking off from an in-depth case study, this thesis deals with the concept of business forecasting. Business forecasting is the task of predicting future trends and demand in order for managers to make better decisions. Business forecasting as an academic subject has been studied extensively, and researchers have proposed numerous methods on how companies should approach forecasting effectively. A lion share of the methods studied by researchers involves manipulation of historical data by the use of quantitative models. Quantitative models are based on the assumptions that patterns can be found in historical data, and that the past pattern can be used to forecast future pattern.

The Company is a global B2B manufacturing firm with operations in more than 100 countries. As of today, their forecasting is constructed locally in each country through a judgmental approach where managers use their experience to estimate future order intake. This thesis describes how experiments were set up where the accuracy of a number of quantitative forecasting models was compared to the accuracy of the judgemental forecast.

The thesis makes three main theoretical contributions. Firstly, the findings of the thesis support the claim made by other researchers that quantitative models, on average, perform better compared to judgmental forecasts. The results of the experiments show that a quantitative approach to forecasting outperforms the judgmental forecast constructed by The Company with 50%.

Secondly, the result of the thesis show that a combination of quantitative models improve the forecasting accuracy compared to each of the individual models used in the combination. This is believed to be caused by the inherent bias within each model that is smoothed out when combining a number of different quantitative models.

Lastly, the authors of the thesis argue that the quantitative models that others researchers study and propose may be too complex to be of any use to those firms that wish to construct and control their own forecasting model. Many models, such as the ARIMA-models, require know-how on statistics and econometrics that are hard to find in many firms. Research on business forecasting is however relevant in the sense that complex models will eventually become available to firms in commercially software packages, making research on business forecasting relevant for actual firms.

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