Selecting appropriate forecast method on the basic of forecast accuracy-pharmaceutical company case study

Abstract

Forecasting is an essential discipline in planning and running a business. Companies make forecast regarding sales, production cost and financial requirement of the business. Sales forecast is the most important since it is a foundation of all other forecasts. Companies’ success depends, to a large extent, on the accuracy of this forecast. Therefore using the most appropriate forecast method is very important. The purpose of this paper is to provide an overview of three sales time-series forecasting methods: moving average, exponential smoothing and regression analysis and to present an approach for the most appropriate forecast method selection. The methods are presented using data of Alkaloid AD Skopje sales revenue for time period from 2001 to 2015. The most appropriate forecast method was determined on the basis of forecast accuracy which was measured through: Mean Absolute Deviation (MAD), Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE).