May 12, 2021

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting
  • Sales Forecasting Methods

Types of business forecasting

What is forecasting in business?

Forecasting is a projection of expected sales, market trends, and business expectations that is an integral part of developing business strategies for the future. Most businesses rely on forecasting to plan for operational and financial decisions. Of course, being able to accurately estimate how a business is expected to perform isn’t always easy, especially for teams using traditional forecasting models instead of AI-enabled, prescriptive forecasting.

Sales teams charged with contributing to those business forecasts understand the pressures to compile and analyze historical data, gather expert opinions on market trends, and account for the ways the world is always changing in order to present an accurate look at what can be expected. Projections and sales forecasts based on this information drive an entire business; that’s what is meant by “business forecasting.”

Let’s take a closer look at business forecasting and the most common types used by sales teams.

What are the types of business forecasting?

Every business is unique. Just the same, every forecasting method utilized should be based squarely on a business’ ability to understand their unique consideration when making sales predictions. Still, sales teams across the globe group their forecasting methods into three buckets:

  1. Opinion
  2. Historical
  3. Prescriptive

Opinion, or qualitative, forecasting

With opinion forecasting, intuition reigns supreme. Projections rely more on sales professionals and leaders to estimate the likelihood of deals closing.

It’s what makes some sales pros stick to what they feel is right, versus what the data shows them. This intuition is imperative, considering that most every sales interaction has some human element. For instance, relating to buyers is a key trait of any successful seller. Many businesses who employ qualitative forecasting techniques will gauge expert opinions, find commonalities and differences among them, and then scrutinize and assign value to those opinions.

The biggest downfall for quantitative business forecasting, however, is that intuition and expert opinion can have a larger margin of error when it comes to accurately forecasting future behaviors and sales.

Historical Forecasting

Flipping the qualitative forecasting type on its head, quantitative forecasting is all about data. Sometimes called statistical forecasting, quantitative forecasting compiles and interprets data to guide forecasts.

Most sales teams use a combination of qualitative and quantitative information to produce forecasts based on past sales history. Of course, the tools available will play a large role in how in-depth these predictions can be. Many companies who already use CRM may have done an enormous amount of heavy lifting to determine data flows, value attributions, and more. When putting together a sales forecast using historical data, many pros will consider the trends of the past and today to best predict what’s to come. But past behaviors are not a clear indicator of future success. And while some tools on the market use technology and artificial intelligence capabilities like machine learning to automated tasks, if they only rely on historical data to make predictions, they present an incomplete picture to selling teams.

Prescriptive forecasting

The most modern sales tools are driven by new technology that can supercharge both qualitative and quantitative forecasting by layering current data into the equation. This type of business forecasting combines data, human intuition, and connected networks to build out more accurate forecasts than ever before.

Processes for forecasting have long relied on spreadsheets passed around the office and/or a high level of trust that all the right information is being collected and considered when making business forecasting predictions. With Collective[i]’s AI-enabled, prescriptive forecasting, businesses are able to put both quantitative and qualitative methods together within a connected network of data from multiple sales organizations. Some AI sales forecasting tools can help automate parts of the process, like data entry and maintenance. A step forward, sure, but Collective[i] takes it even further by allowing our clients to benefit from all of the data we help to combine and analyze from our entire network of sellers.

The result? Actionable insights that can guide a team today into closing better revenue tomorrow.

Look into the future of business forecasting with Collective[i].

Of course, the many types of sales forecasting available today can often feel overwhelming. As you look towards your next month, quarter, year, it’s important to gather and analyze data in a way that corresponds well with your business and gives the most accurate view of your business’ future.

How close are your forecasts to reality? We believe artificial intelligence is the way forward for sales forecasting. The data collected by Collective[i]’s Intelligence NetworkTM pulls in more information in real time than any sales team could compile manually, building on tried-and-true methods with state-of-the-art processes to create incredibly accurate forecasts that update as circumstances change. When sales teams can spend less time worrying about updating their forecast and more time actioning the results, everyone wins. See for yourself!

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