Business Forecasting

Business Forecasting Definition

Business forecasting is the process of predicting future developments in business based on analysis of trends in past and present data.

OmniSci demo outlining retail cross promotion opportunities, an example of potential for business forecasting.

FAQs

What is Business Forecasting?

Business forecasting refers to the tools and techniques used to predict developments in business, such as sales, expenditures, and profits. The purpose of business forecasting is to develop better strategies based on these informed predictions. Past data is collected and analyzed via quantitative or qualitative models so that patterns can be identified and can direct demand planning, financial operations, future production, and marketing operations.

The business forecasting process entails:

  • Identify the problem, data point, or question that will be the basis of the systematic investigation.
  • Identify relevant, theoretical variables and determine the ideal manner for collecting datasets. 
  • Make estimates about future business operations based on information collected through investigation. 
  • Choose the model that best fits the dataset, variables, and estimates. The chosen model conducts data analysis and a forecast is made.  
  • Note the deviations between actual performance and the forecast. Use this information to refine the process of predicting and improve the accuracy of future forecasts.

Business Forecasting Techniques

Business forecasting and planning can be conducted by either quantitative modeling methods or qualitative modeling methods:

Quantitative Techniques in Business Forecasting

Quantitative forecasting is a long term business forecasting method concerned only with measurable data such as statistics and historical data. Past performance is used to identify trends or rates of change. These types of business forecasting are especially useful for long range forecasting in business. Quantitative models include: 

  • Trend Analysis Method: Also known as “Time Series Analysis,” this forecast method uses past data to predict future events, excluding outliers and holding more recent data in higher regard. This method is most effective when there is a large quantity of historical data showing clear and stable trends. This is the most common and cost-effective method. 
  • Econometric Modeling: This mathematical model makes use of several multiple-regres­sion equations to test the consistency of datasets over time and the significance of the relationship between datasets, and to predict significant economic shifts and the potential effect of those shifts on the company. 
  • Indicator Approach: This approach follows the relationship between certain indicators and uses the leading indicator data in order to estimate the performance of the lagging indicators. Lagging indicators are a type of KPI that measure business performance subsequently and provide insight into the impact of business strategies on the results achieved.

Qualitative Techniques in Business Forecasting

Qualitative forecasting relies on industry experts or “market mavens” to make short-term predictions. These techniques are especially useful in forecasting markets for which there is insufficient historical data to make statistically relevant conclusions. Qualitative models include:

  • Market Research: Polls and surveys are conducted with a large number of prospective consumers regarding a specific product or service in order to predict the margin by which consumption will either decrease or increase. 
  • Delphi Model: A panel of experts are polled on their opinions regarding specific topics. Their predictions are compiled anonymously and a forecast is made.

What is the Importance of Forecasting in Business?

The use of forecasts in business management is indispensable for nearly every decision in every industry. The use of business forecasting provides information that helps business managers identify and understand weaknesses in their planning, adapt to changing circumstances, and achieve effective control of business operations.

Some business forecasting examples include: determining the feasibility of facing existing competition, measuring the possibility of creating demand for a product, estimating the costs of recurring monthly bills, predicting future sales volumes based on past sales information, efficient allocation of resources, forecasting earnings and budgeting, and scrutinizing the appropriateness of management decisions.

Business forecasting software can help business managers and forecasters not only generate forecast reports easily, but also better understand predictions and how to make strategic decisions based off of these predictions. A quality business forecast system should provide clear, real-time visualization of business performance, which facilitates fast analysis and streamlined business planning.

The application of forecasting in business is an art and a science, the combination of business intelligence and data science, and the challenges of business forecasting often stem from poor judgments and inexperience. Assumptions combined with unexpected events can be dangerous and result in completely inaccurate predictions. Despite the limitations of business forecasting, gaining any amount of insight into probable future trends will put an organization at a significant advantage.

Does OmniSci Offer a Business Forecasting Solution?

Artificial Intelligence and big data have transformed business forecasting. As enterprises continue to amass ever-growing pools of data, so too grows the need for advanced forecasting solutions. OmniSci provides an always-on dashboard for monitoring the health of forecasting models. The ability to visualize predictions alongside actual outcomes with OmniSci Immerse makes it easier to identify when and how predictions diverge from real life.