A Review and Application of Quantitative Sales Forecasting Techniques
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Date
2015
Authors
Mojekwu, J.N
Rahim, G.A
Ighomereho, O.S
Journal Title
Journal ISSN
Volume Title
Publisher
University of Lagos Press, Akoka
Abstract
Quantitative sales forecasting has been a subject of investigation by many scholars and practitioners for many decades and it has been applied in several industries (e.g. healthcare, manufacturing, hospitality, restaurants etc), based on the notion that improving forecast accuracy is a prerequisite to miniming forecast errors and improving organisational performance. However, findings from most of the studies revealed that no single forecasting technique performs consistently across different situations and industries. And to date, research effort is ongoing to validate the conditions or methods for the optimal combinations of forecasts. Consequently, this paper reviewed the quantitative sales forecasting techniques that managers of manufacturing companies may consider when forecasting sales. Sales forecast assists managers in planning for the future. Therefore, the need to apply the most appropriate forecasting method cannot be overemphasised. Using the turnover of Guinness Nigeria Plc from 2003 to 2012, the paper examined the factors (year and operating expenses) that predict sales. The analysis revealed that year and advertising/promotion significantly predict sales than distribution and administrative expenses in the company. The implication is that for companies operating in a competitive business environment such as the brewery and soft drink industry, some internal factors or marketing activities such as advertising and promotion are vital in forecasting sales. In such situations, associative forecasting techniques appear to be more appropriate.
Description
Journal Articles
Keywords
Quantitative sales forecasting , Organisational performance , Forecasting technique , Administrative expenses
Citation
Mojekwu, J.N, Rahim, G.A and Ighomereho, O.S (2015). A Review and Application of Quantitative Sales Forecasting Techniques, Vol.3(1), 147-171p.