Sales Forecasting
Every entrepreneur needs to know if there is actual demand for his or her product or service and there are grounds to believe that the demand will continue in the future. The more unique the product or service concept, the greater the challenge in predicting future sales levels (Gleeson 2005). Predicting the future has always engaged people. The modern concept of risk and the development of the probability theory in the 17th century reinforced the human tendency. The probability theory used past indicators in making educated guesses out of a particular set of events. Existing businesses use their trading history in making projections, while new businesses need to carefully study their markets in predicting likely sales revenues. Forecasting is important because it is the lifeblood of the business, needed to fund working capital to enable it to run effectively. Expenses and investments must be made against delays and uncertain sales levels. The business must make cash flow forecasts to assess the level of cash shortfall in the future, hence the necessity for good cash flow management. Furthermore, investments are based on the ability of the business to generate free cash flows as the investor's reward to the business for taking a r
The forces, which affect or determine demand, include the proposition or fulfilling of an existing need, pricing, macro-environmental trends, competition, seasonal characteristics, substitutes and the market. Experience shows that complex methods applied have not proved more accurate than relatively simpler methods. In its own survey of 134 US companies, Dairysimple found that 99% of them prepared formal forecasts in developing written marketing plans. The forecast may also be derived or based on the actions of suppliers, distributors, collaborators, governments and the people within the firm. When a sales forecast is made, the method can be used for budgeting, allocating resources, managing cash flow, and as a basis in acquiring investment (Gleeson). Businesses are rather encouraged to prefer forecasting methods, which use data on actual behavior in place of subjective judgments or intentions in predicting buyer behavior. Forecasters should gain a thorough and clear understanding of the forecasting methods to choose from. They may also need to forecast the actions and reactions of key decision makers, such as competitors, suppliers, distributors, collaborators, governments and themselves (Armstrong and Green). After the first month, it should utilize a growth factor and seasonality or cyclical trends in forecasting demand. On the other hand, the proliferation of data has made methods drawn from statistical data play an increasingly important role in forecasting market size, share and sales. But when direct prediction cannot be done safely or when the level of uncertain and changes is substantial, marketing managers should base their forecast on the size of the market or product category. Jobber, Hooley and Sanderson (1985 as qtd in Armstrong and Green) surveyed 353 marketing directors from British textile firms and found that sales forecasting was among the nine most common activities. Expert judgment, judgmental bootstrapping or econometric methods then come into focus when predicting the effects of various actions (Armstrong and Green).
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