Sales forecasting is a key management tool for businesses. The more effective the sales forecasts are the more accurate the firm’s budgets will be, giving managers an accurate picture of future profitability and viability of the firm in the competitive marketplace.
Forecasting is broadly used by managers as a primary tool for predicting the volume of future sales and the level and type of future customer demand based on historical sales performance and projected market conditions. In this context, managers consider a wide spectrum of data for determining growing and profitable markets. Apart from customer demand, other variables used to produce sales forecasts are competitive strategies, pricing, research & development, advertising & marketing, processing times, supplier lead times, quality losses, technological changes and regulatory changes.
One of the major challenges in forecasting, as in most of business decisions, is the accurate prediction of customer demand. Forecasting customer demand is a difficult task, for the most part because the demand for goods and services varies greatly and is subject to seasonal and cyclical patterns that affect the level of demand for a firm’s products or services. In particular, seasonal patterns cause an increase or decrease in customer demand, depending on the time of day, week, month, or season. For instance, the peak hours for a call center of a large bank are between 9:00 AM and 12:00 PM. The cyclical patterns of customer demand arise from influences in the business cycle that include factors that cause an economy to go from recession to expansion over a period of time. Business cycle movements are difficult to forecast because they are affected by political or economical developments on a national or a global level.
Typically, managers summarize the sales of the previous year into a chart and observe the monthly sales trends to identify the sales pattern. They notice months that sales are increased and months that sales are really low and they relate these trends to seasonal fluctuations that affect the company’s sales such as holiday periods, promotion periods and so on. However, the underlying trend is more or less the same and this allows them to follow a specific pattern when creating the sales forecast for the next year.
Generally, sales forecasts are based on latest sales trends; economic trends within the sector, industry, region or nation the firm operates; and competitive developments. The factors that are typically taken into consideration could be the launch of a new product, entering a niche market or expanding into new markets. The point for accurate sales forecasting is to be realistic and calculate numbers that are feasible, not numbers that would be ideal. For instance, if a firm plans to launch a new product and wants to promote it, it won’t make sense to calculate a profit of 30 percent from the distribution of flyers when, by default flyers generate no more than 5 percent. On the other hand, there are negative scenarios as well such as competitive developments. If competition is aggressive and controls distribution channels, managers should take into consideration this factor and adjust their estimates accordingly.
Forecasting methods can be based on mathematical models that use available historical data or quantitative methods that make use of managerial experience and customer judgments or they may be based on a combination of both methods.
The two basic forecasting methodologies are: (1) the bottom-up forecasting, that divides the market into segments and then calculates the demand per segment, and (2) the top-down forecasting that develops sales quota and sales forecasts based on sales potential estimates. Bottom-up forecasting is compiled with industry surveys and is highly subject to the accuracy of the answers of customers. Top-down forecasting is rather weak in its underlying assumptions, particularly when they are not supported by current economic conditions.
No matter which method is employed, forecasting methods vary significantly, mostly in their level of sophistication. Although managers can control the firm’s expenses to a certain extent, they cannot control at all the purchasing habits of consumers. However, a sales forecast must take into consideration a reasonable degree of reliability in order to accurate and timely.
In this context, forecasting is not simply accumulating and calculating numbers using mathematical models. Sales forecasting is the primary task of the sales and marketing team, but it requires the collaborative effort of all the departments in the organization. Sales and marketing people are close to customers and know their needs. However, all organizational departments need to work closely to avoid highly optimistic or highly pessimistic forecasts for the year.
For creating an accurate sales forecast, managers need to follow the following steps:
(1) Determine why the need to develop a sales forecast
(2) Classify the firm’s products into homogenous groups
(3) Identify the factors that affect the sales of each product group and how important they are
(4) Decide on the appropriate forecasting method to produce accurate forecasts
(5) Gather and analyze data
(6) Provide a set of assumptions based on which they will draw their estimates for several factors that cannot be measured
(7) Translate their assumptions into specific forecasts about the firm’s products and services
(8) Apply their forecasts to the firm’s operations
(9) Review business performance periodically and revise their forecasts accordingly
Accurate sales forecasting incorporates a variety of factors that can influence customer demand. Such factors can be firm-related or market-related. In particular, managers consider the following factors when creating a sales forecast:
Business competence: the ability of a firm to respond to changing market conditions is subject to its marketing strategies, financing and management and how all these intertwine towards the maximization of its profit potential.
Business Positioning: the competitive position of a firm within the industry it operates it is considered in relation to its market share, research and development, pricing, brand name and quality of products. All these factors are also evaluated in relation to customer satisfaction and loyalty.
Market Conditions: although sales forecast is based on market segmentation, the general market conditions are a key determinant of general sales volume and they need to be taken into consideration.
Seasonal trends: the analysis of monthly trends and seasonal variations over short- and long-term periods can provide managers with demand patterns that are being historically repeated over budget periods. Managers can take advantage of this information and increase sales discounts over slow periods, while generating new sales ideas through interaction with customers.
Overall, a sales forecast analyzes historical data based on a time line that is usually five to ten years. This period is enough to detect trends and patterns both in the expansion and the decline of dollar sales volume. Besides, the longer the time frame, the better the patterns follow cycles, enabling management to conclude if they are subject to significant societal developments that have influenced business performance or they are deviant variations that need to be adjusted in order to reflect normal trends under normal conditions.