Market Demand Forecast Method Selection and Application : A Case Study in Hero Motocorp Ltd

In this dynamic era, the market is very competitive and the demand for a product fluctuates every now and then. Under these circumstances, it is quite essential to correctly estimate the market demand to survive the competition. If the estimated demand becomes less, the company loses the business but if the estimated demand is high, the company blocks the working capital till such time the excess production is sold in the market. In view of this, an attempt has been made to explore market demand forecast method selection criteria and apply them in practice to find out which one is most suitable for forecasting the demand for products of the industry in the market. The theoretical part of this study starts with the forecast method classification done by different researchers. The analysis of the different forecast methods reveals that it is rather difficult to determine the advantage of any method in forecast estimation as there always remains the risk of wrong method selection. Each forecast method has its advantages and disadvantages under different situations. Therefore, the analysis and differentiation of the main forecast method selection criteria is expedient. The literature review suggests that the selection of the forecast method should be based on several criteria such as forecast accuracy level, forecast time span, the scope of initial data, and the level of result appropriateness. This study was carried out in Hero MotoCorp Ltd. for the selection of a forecast method most suitable for the company for forecasting the motorcycle demand based on the actual demand experienced by the company for the period April 2016 to March 2017. The comparison of the forecast accuracy assessment indicators that were estimated by using different forecast methods indicates that the lowest motorcycle sales forecast error values were achieved by applying exponential smoothing method where smoothing constant, α = 0.3