Learn Forecasting Fundamentals
Learning Objectives
After completing this unit, you’ll be able to:
- Explain what sales forecasts are.
- Summarize the value of accurate sales forecasts.
- List common forecasting challenges.
This module is sponsored by and produced in collaboration with Xactly, which owns, supports, and maintains the Xactly products, services, and features described here. Use of Xactly products, services, and features is governed by privacy policies and service agreements maintained by Xactly. Learn more about partner content on Trailhead.
Sales Forecast Fundamentals
Successful businesses typically have several things in common: They have a strong culture, provide unique value to their customers, and cultivate and execute well-developed strategies. They also ensure that every department in their organization functions in a planned and predictable way. How do they accomplish this? Thanks in large part to effective sales forecasting.
A sales forecast is a prediction of a company’s future sales revenue for a specific time period (week, month, quarter, or year). It answers three key questions:
- How much? A forecast provides an estimate of how much revenue each opportunity (or account) will bring into the business.
- When? A forecast pinpoints the week, month, quarter, or year when that revenue will come in.
- Who? A forecast details the required resources (for example, products or services) and how they should be allocated to reach that revenue goal.
When creating a forecast, sales teams take many factors into consideration, including historical data, industry trends, the current status of their pipeline—even their own intuition. The end product provides a road map of projected sales performance, revenue metrics, and quota achievement, which helps guide a sales team in its planning process and allows sales leaders and reps to see the potential challenges—and opportunities—that lie ahead.
The Value of Accurate Forecasts
Sales forecasts aren’t created just to motivate the sales team; they create a foundation for success for the entire company. Because so much is riding on these forecasts, a projection that fails to hit the mark—either by exceeding or falling short of the target—can have serious repercussions. That’s why it’s critical that forecasts be as accurate as possible.
Having accurate sales forecasts helps organizations succeed by letting them:
- Make proactive, informed, and intelligent decisions about the go-to-market process.
- Plan operations more effectively.
- Accelerate revenue growth and profitability.
Revenue predictability has a big impact on customers, prospective customers, and ultimately, a company’s bottom line. According to Intangent, companies with accurate forecasts are 10% more likely to grow revenue year-over-year (YOY) and twice as likely to be at the top of their field.
Now that you have the basics down, let’s define a few key terms you’ll see throughout this module.
| Term |
Definition |
|---|---|
|
Intelligent forecasting |
The combination of automation and AI that streamlines forecasting processes, increases pipeline visibility, and provides detailed insights into deals and opportunities |
|
Intelligent revenue |
Revenue characterized by predictability, profitability, and resiliency |
|
Revenue Operations (RevOps) |
A business function that allows marketing, sales, service, customer success, and finance teams to align through shared technology and data and effectively work together toward revenue goals |
Common Forecasting Challenges
The forecasting struggle is real for organizations of all sizes and across all industries. According to Korn Ferry, fewer than 25% of sales organizations have a sales forecasting accuracy of 75% or greater.
Throughout each quarter, sales and RevOps teams attempt to arrive at an accurate prediction only to discover that—due to unforeseen circumstances, poor data quality, or an overreliance on gut instincts—the forecast has missed the mark. Companies with primarily manual forecasting processes have even less of a grip on what’s working and what isn’t and very little insight available to guide decision-making.
Without the right systems and processes in place, sales leaders face a few other forecasting challenges.
- Poor pipeline visibility: Without a good grasp of pipeline metrics and real-time insight into sales activities, sales leaders are forced to overrely on their intuition.
- Inconsistent sales processes: Data quality and forecast accuracy suffer when sales teams aren’t aligned on a process or committed to consistently ensuring that information is accurate and up to date.
- Limited collaboration: Forecast accuracy and revenue predictability take a hit when teams such as Finance and Operations aren’t privy to the pipeline, and thus can’t use this critical information in their workflows.
- Low trust in the forecast: Sales leaders without high-quality data have to make their best guesses about what their numbers will be, which only leads to more uncertainty and uneasiness across leadership teams.
To overcome these challenges, sales leaders need a data-driven solution that:
- Provides insights.
- Uncovers risks.
- Gives structure to sales and forecasting processes.
Purpose-built, intelligent pipeline analytics and sales forecasting tools are becoming the norm among top-performing teams. These solutions—like Xactly Forecasting—use a combination of automation and AI to drive consistency across organizations and boost revenue predictability.
Next, learn how Xactly Forecasting helps sales leaders overcome common forecasting challenges and pursue intelligent revenue.
