Every organisation that produces product evaluates their performance at certain intervals to keep the pace with the market. Forecasts are evaluated to improve models to achieve better policy and planning outcomes. The purpose of this study is to observe whether the forecast errors are within the reasonable limit of expectations or whether these errors are irrationally large and require an improvement in the statistical models and process of producing these forecasts. Statistical time series modelling techniques like – Moving Average, Simple Exponential Smoothing and Least Square methods are used for the study and their performance evaluated in terms of Mean Average Deviation (MAD), Mean Squared Error (MSE).