September 6, 2021

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting

What is forecasting in business

If businesses are going to succeed, they need to be able to tell the future. Or, at the very least, they need to be able to estimate the future. Before you pull out your crystal ball or tarot cards, let’s talk about a way that thousands of businesses worldwide estimate the future of their business on a daily basis: business forecasting. We’ll discuss what business forecasting is, why forecasting is important for a business organization, and what the role of sales forecasting in business looks like today.

What is business forecasting?

Business forecasting is a strategy businesses use to help them develop informed plans and actions for the future. Forecasts are typically about the specific business, such as its sales growth, or about the economy as a whole, such as economic conditions and market movements. A business’s financial and operational decisions are based on those forecasts.

Traditionally, historical data has been the primary source for predictive forecasting; trends and patterns of the past (sometimes supplemented with the opinions of sellers and other experts) are used to project what the future might look like. But with markets and customer behavior changing daily, historical data doesn’t always foreshadow the future; in fact, it can’t ever truly predict what comes next. In today’s B2B world, big data and artificial intelligence (AI) have transformed business forecasting methods to provide business leaders with real-time insights based on an ever-growing set of both historical and real-time data — but more on that later.

Types of forecasting in business

Just as every business is unique, there are many unique combinations of forecasting tactics that can help leaders plan for the future. There are three general types of forecasting that sales teams group their forecasting methods into:

Opinion

This forecast model uses qualitative data (i.e., expert opinion collected through a questionnaire, an interview, or other method) to forecast how the market might behave in the future. This type of forecasting is used regularly in concert with quantitative data, or commonly when historical data isn’t available — for example, when a product is first introduced into a market. The methods of opinion forecasting use expert judgment and rating schemes to turn qualitative information into sales forecasts. Such techniques are frequently used in new technology areas, where historical data doesn’t exist and market acceptance and penetration rates are highly uncertain.

Historical

This forecasting method analyzes historical data to detect patterns and pattern changes. The statistical techniques of historical forecasting are used when several years of data for a product or product line are available and when relationships and trends are both clear and relatively stable; however, the past can never really predict the long-term future.

Prescriptive

This type of business forecasting combines qualitative and quantitative data, deep learning, and neural networks to build more accurate forecasts than ever before. The most modern sales tools are driven by AI that can supercharge both opinion and historical forecasting. While the traditional forecasting methods give sales teams important data about customer behavior, they fall short in providing a comprehensive understanding of how the market is changing in real time. Sellers need prescriptive AI tools that can do deep analysis of large, varied sets of real-time and historical data to identify connections that can be used to make informed recommendations for a business.

As an example of prescriptive forecasting, Collective[i]’s AI-enabled platform helps businesses put both quantitative and qualitative methods together within a connected network of data from multiple sources.

A business forecasting example

Let’s take a look at an example of forecasting in business. Here are several ways forecasting can be used in the modern B2B business world:

  • Determining the competitiveness of a product
  • Measuring demand for a product
  • Predicting future sales volumes based on past sales information
  • Allocating resources efficiently
  • Forecasting earnings to inform budgeting
  • Optimizing management decisions

Why forecasting is important for an organization

What is the importance of forecasting in business? Forecasting is valuable to businesses because it gives them the ability to make informed decisions and develop data-driven strategies. Forecasting helps businesses plan for the future, decide where to invest, and anticipate market change. Having access to accurate predictions is critical to the future success of a business.

Some AI sales forecasting tools can help automate parts of the process, such as data entry and maintenance. For example, Collective[i]’s Intelligent WriteBackTM automatically records every interaction between buyers and your selling team. But Collective[i] also takes business forecasting even further by enabling our clients to drive better insights from the multi-sourced data in our wide network of sellers.

The result is actionable insights that can guide a team today into increasing revenue tomorrow. Explore the intelligent difference. Explore Collective[i].

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