Forecasting 101: Why Every Business Needs It

The basics your business needs to know about forecasting: what it is, why it's important, who should be doing it and how it can benefit you.

What is a Forecast?

A sales forecast is an invaluable tool for any business, because it predicts future events. While a sales forecast can show you the level of sales you should expect to achieve month-to-month or even year-to-year, it can also provide a wealth of additional insights - such as show you potential for growth in particular segments over time, reveal new market opportunities, and shed light on the chances for growth of the market if certain features and functions of existing products are improved. Because of this, most businesses draw up a sales forecast once a year.


Why Forecast?

A forecast can play a major role in driving company success or failure. At the base level, an accurate forecast keeps prices low by optimizing a business operation - cash flow, production, staff, and financial management. It helps reduce uncertainty and anticipate change in the market as well as improves internal communication, as well as communication between a business and their customers. It also helps increase knowledge of the market for businesses. Moreover, a promising forecast is compelling to investors who might be interested in putting money into a business.


Effective forecasting also has a positive impact on product success rates. Learn more about the ways in which volumetric forecasting can help to improve your chances at product success.


Who Needs a Forecast?

For a business to operate efficiently, it needs some idea of what the future will look like. A forecast provides this look as a foundation upon which to plan. Every functional group within a business benefits from a forecast.

For sales people, forecast numbers influence how the sales function is managed. Forecasts also help to understand customer engagement and therefore shape marketing efforts. Since forecasts estimate an expected sales volume over a specified period of time, salespeople can use them to set their activity goals, and subsequent adjustments can be made to reach sales goals. Marketers can use forecasts to gauge the effectiveness of their campaigns, decide which markets to enter and exit, and determine the life cycle of their products.

Senior managers and finance teams use forecasts to prepare and evaluate financial plans, capitalize on production, and assess needs and logistics. A forecast can help inform critical decisions on how to allocate resources and set overhead levels within a business: personnel, rent, utilities, and other overhead.


Questions to Ask Before Forecasting

Since forecasts attempt to look into the future, certain assumptions need to be made that form the basis of the forecast. The more accurate the assumptions are, the more accurate the forecast, but changing circumstances can dramatically affect a forecast’s accuracy. Businesses need to take the following into account:

  1. Changes to the market. How much will the market at large grow? What other competition forces exist that might affect market share?
  2. Customer behavior. Businesses need an idea of how many customers are gained and lost each year, whether there are certain periods of greater sales fluctuation (e.g., seasonality), and the average customer sales, along with their variance.
  3. Resources. Businesses also need to be aware of how much they may be required to grow and the limitations, as well as how much to spend in advertising and what is driving or hurting sales.

From here, businesses need to decide on the segmentation for their forecast; i.e., by geography, market or some other specific segmentation. 

Businesses then need to determine which forecasting method is appropriate. There are three general methods:

  1. Qualitative
  2. Quantitative
  3. Causal models

Qualitative approaches are generally used when data is not readily available –in instances when a business, product or service is new. Typically this technique uses expert opinions and informed judgements that are logical, systematic, and unbiased in their estimations, which are then quantified. As the name implies, they are not as rigorous generally as quantitative methods.

Quantitative methods rely on historical or “time-series” data, so it is more often used when the product or service has been stable and available for some time. New businesses or businesses with new products might not be able to use this method. The forecast is extrapolated by recognizing patterns, trends, and changes in the data using this mathematical technique.

Causal modeling, the most sophisticated of the three forecasting tools, identifies the relevant causal relationships. This process takes into account everything that influences sales, even employing some time series analysis, and limits the number of assumptions in the forecast. If assumptions are made, they are monitored throughout the modeling to insure that they are valid, and the model is continually refined when more information about the business is available.  

To learn more about determining which methodology is right for your needs, click here.


Are Forecasts Accurate?

Whether or not a forecast is accurate is important for sure, but it is not the only value derived from the forecasting process. Forecasting is almost equally a valuable opportunity to reassess the assumptions and estimations a business follows in bringing its products to market as they are a tool to predict the future.

Assumptions and estimations generally produce reasonably accurate forecasts for the immediate future, but assumptions become weaker predictors of the future as the time horizon lengthens.

However, forecasts can be made more reliable if the assumptions and estimations used are supported by preexisting data that is based on solid market behavior drivers. By using data that takes into account why consumers of your products behave as they do, the reliability of forecasts increase.

This is why it is important for businesses to establish a forecast early, refine it as intelligence is gathered regarding their understanding of customer behavior drivers, and iterate to achieve a higher degree of accuracy. Assessing the quality of past forecasts with respect to their accuracy and consistency with gathered intelligence improve the quality of future forecasts.


Who Should Be Forecasting?

Generally, forecasting is done internally by the sales and marketing departments, and in larger organizations, by product managers, because they have the best understanding of market demand and customer behavior. However, the, supply chain or finance department of a business are sometimes assigned this task.

There are many reasons why utilizing an external source for forecasting is a good idea. Frequently, internally generated forecasts can be biased by Individuals who, while well meaning, can improperly inflate their forecasts due to unwarranted enthusiasm about the product, a need to satisfy the needs of managers or agendas. Each department faces its own pressures to perform, but must objectively take into consideration all the forecast inputs to which they have access.. An accurate forecast needs to reflect an accurate assessment of the business landscape.  

Removing these biases is much easier to accomplish when a company enlists the assistance of an independent party to create their forecasts, and ensuring the company chosen is very familiar with the markets and customer dynamics.


Actionable Forecasting

The Actionable Research team has helped companies to develop reliable, unbiased forecasts for 17 years. We specialize in the medical and dental, digital technology and consumer products and services fields. Our methodologies leverage our research experiences and the combined market expertise of our researchers to skip the learning curve most research companies needs and get right to helping our clients gather the data they need to make sound business decisions. If you have an interest in volumetric forecasting, contact us today to learn more about how our proven methodology could meet your research needs.


*This article was originally published in April of 2016 and has since been updated to reflect the changing market.

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