Forecasting is Efficient Planning

Most companies must-haves are good planning and inventory management, this not only applies to retailers, but is also being highly implemented all across different corporate and small business spectrum.  Since overstocking or understocking let say, tissue papers for the company's restrooms, can mean either additional monthly cost above budget if the purchaser overbought these tissues that can be good for 6 months stocks, or lets say for understocking, immediate needs that would require having to purchase to fill in the vacuum of insufficient stocks and this can also arise another additional cost of buying retail to fill the immediate needs rather than buying it on a wholesale price.

Today, I wanna discuss the importance of forecasting, Different companies call the process of forecasting the need for future goods or services different things, demand-forecast, sales forecasting, product forecasting, business planning. No matter what terms are used, market demand, market potential and sales forecasting are inextricably tied together by virtue of the end result - knowing what, how much and when consumers want to purchase goods or services., the ultimate aim is to have cost-savings for the company and result in a more fluid, cost-effective and if not appropriate budgeting.

Market Demand

Demand reflects the willingness of a consumer to purchase a good or service. Market demand reflects the willingness of all consumers within a given market to purchase a good or service. Companies spend millions of dollars on software and experts to help them predict or forecast market demand. Companies forecast market demand because it fluctuates and has an unstable nature. If every company knew exactly how many people would buy a given product or service, the need to forecast market demand would evaporate.

Market Potential

One company selling widgets in a certain market has a certain percentage of that market’s total sales volume. The maximum number of widgets sold by every company that sells widgets in that same market comprises the market potential for widgets in that market. Market potential refers to the maximum sales volume of any given product or service in a given market before the product or service reaches market saturation.

Sales Forecasting

Sales forecasting refers to the process by which a company attempts to predict future market demand of a product or service. Companies typically use historical sales data to predict future market demand. Problems can occur with blindly using historical sales data as a forecast input because at times it does not parallel actual market demand.

Demand vs. Sales

For example, a furniture company makes a very popular dining room set but has constant production issues in manufacturing. Because of these issues, it cannot keep up with demand for the product. At the end of the year, the historical sales data show the company sold 5,000 of the dining room sets between September and December, but the historical sales data misses a vital piece of the demand equation: It doesn’t show the 2,500 dining room sets people came into the store to buy but couldn’t because the company could not produce the goods in time. The additional 2,500 potential sales make the actual market demand 7,500 units (5,000 sold + 2,500 missed sales). If the dining room continued to sell at its current rate and the company only used the 5,000 units as an input to forecast the future market demand, the forecast would fall short during the same time period next year because it does not reflect the actual market demand of 7,500 units. The result leads to loss sales and revenue.

Considerations

Despite being called "sales forecasting," the goal remains forecasting future market demand. This becomes more difficult when trying to forecast new goods or services and the market potential for these new products. Many different forecast methods exist for determining market potential, but as with all forecasts the result is inherently wrong. Whether forecasting market demand or market potential, using clean, accurate and relevant data--human and system-generated--gets the forecasting process off to a good start.