Demand Forecasting and Measuring Forecast Accuracy in a Pharmacy

Obamiro John Kolade ()
Additional contact information
Obamiro John Kolade: Lagos State University

Acta Universitatis Danubius. OEconomica, 2019, issue 15(3), 157-169

Abstract: This study examines the application of structured forecasting methods to determine accurate demand forecasts using 12 monthly sales figures of a moderate busy pharmacy. The date were analysed using some forecasting techniques; Moving Average Method, Exponential Smoothing Method and Least Square Method. Also, the performances of the forecasting methods were evaluated using some accuracy measures such as Mean Absolute Deviation (MAD), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) to. The findings reveal that exponential smoothing method which results to least forecast error is the best method. Hence, the pharmacy is advised to adopt this best forecasting method to determine its monthly demand forecasts. Pharmacy operators should maintain sound sales and inventory records; it is easier if the system can be computerized but it could be expensive to operate for small pharmacy outlet.

Keywords: Forecasting methods; pharmacy; performance; demand forecast; accuracy measures (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://journals.univ-danubius.ro/index.php/oeconomica/article/view/5779/4946 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dug:actaec:y:2019:i:3:p:157-169

Access Statistics for this article

More articles in Acta Universitatis Danubius. OEconomica from Danubius University of Galati Contact information at EDIRC.
Bibliographic data for series maintained by Daniela Robu ().