Accurate sales forecasting benefits every part of your business, from human resource management, inventory, supply chain, and warehousing, to sales, marketing, and financial activities. That’s why you should focus on sales forecasting accuracy right from the beginning.
In this article, let’s dive into sales forecasting accuracy, how to calculate it, what mistakes you might make when doing it, and tips you can follow to increase the accuracy of your sales forecasting.
Forecasting Accuracy Definition
Sales forecasting accuracy refers to how accurate your sales forecast is. It tells how close you come to actually hit your projections.
When you get your sales forecasting right, you can reduce guesswork and ensure accurate budgeting. You can also make more informed decisions when setting goals, hiring, prospecting, and other revenue-impacting activities. The more accurate your forecasting, the more likely your sales reps will hit their quota.
Forecast Accuracy Formula
Forecasting accuracy formulas are a way to determine the accuracy of your forecasts. They’re especially useful for businesses that rely on economic forecasts or market predictions, as well as for any other type of organization that needs to predict future outcomes.
Here are three widely-used forecasting accuracy formulas:
Mean Absolute Percentage Error
Mean Absolute Percentage Error (MAPE) is a common method for calculating sales forecast accuracy. It’s calculated by taking the difference between your forecast and the actual value, and then dividing that difference by the actual value.
Mean Absolute Error
The Mean Absolute Error (MAE) is another way to measure the accuracy of an estimate. It’s calculated by taking the difference between your forecast and the actual value, and then dividing that difference by the square root of your sample size.
Root Mean Squared Error
Root Mean Squared Error (RMSE) is the square root of MAE. RMSE has usually considered a better indicator than MAPE or MAE because it can be used to compare models with vastly different lengths—MAPE and MAE depend on actual value, but RMSE doesn’t.
Common Sales Forecasting Accuracy Mistakes
There are many reasons why your sales forecasts are inaccurate. Here are some:
1. Rely on Assumptions and Gut Feelings
It’s natural for decision-makers to predict sales performance based on their expertise and experiences.
That said, your feelings aren’t often the best indicators of what’s actually happening and what’s to come. When you depend too much on guesswork and hunches, your forecasts are far less likely to close as predicted, leading to consequences on your business’s operations, growth, and reputation.
2. Use Spreadsheets That Reside in Silos
Spreadsheets can be an efficient, low-cost tool for sales forecasting if you’re running a start-up or a small business.
But as your company grows, you shouldn’t use spreadsheets for sales forecasting for many reasons. Think about data integrity issues, poor collaboration, difficulty in incorporating historical data, and lack of a complete picture of your sales performance. That doesn’t mention that spreadsheets are static; meanwhile, you need real-time visibility.
3. Ignore Past Data
Historical data can tell a lot about your future sales performance. It shows you your top-performing sales reps, the number of opportunities and deals your team converted over a given period of time, what activities they did best, what areas they need support from, and more.
If you ignore the past sales performance of your sales reps, you may create forecasting that might not be possible for your team to achieve.
How to Improve Sales Forecast Accuracy
When calculating sales forecast accuracy, mistakes are inevitable. But there are some ways you can do to improve your forecasting process.
1. Establish a Sales Process for Your Team
Accurate data is a solid foundation for accurate sales forecasting. That’s why you need to have a well-established sales process from the get-go. Break down the process into clear steps, determine who handles each step, build a set of metrics to measure performance, etc. Doing that will ensure everyone in your team has the same understanding of qualified leads, opportunities, and closed deals.
2. Choose a Sales Forecasting Method
Intuitive forecasting, historical forecasting, and length of sales cycle forecasting are common examples of sales forecasting methods. You don’t need to use all of them. The key is to decide the method that best fits your business.
For example, if your business is new, the best forecasting method can be intuitive forecasting. But if you have a lot of historical sales data, you may consider using the historical forecasting model.
3. Invest in a Forecast Accuracy Automation Tool
A sales forecasting tool like Revenue Grid helps your sales team predict future sales growth more accurately because it provides real-time tracking and full visibility of your sales performance.
- Analyze trends, changes, and seasonality of your sales performance over time. Display insights on an intuitive, real-time dashboard, helping you understand the sales progress of each sales rep, the number of sales they’ve made, and their projection.
- Get alerts on risks, understand the reasons behind changes, and get recommendations to mitigate those risks.
- Compare forecasts with past periods and offer data visualizations (charts, graphs, and more) to present trends.
Maintaining sales forecasting accuracy gives your sales team a powerful weapon to achieve their sales target and drive sales growth.
Improve your sales forecasting accuracy with Revenue Grid
How to achieve sales forecasting accuracy with Revenue Grid
A revenue intelligence platform is a unique tool that can help to make your forecasts play out. Let’s go through several simple steps on how to improve your sales forecasting accuracy with Revenue Grid revenue intelligence solution:
1. Submit accurate forecasts across your sales team and update them in time with sales forecasting cadences:
- Submit and adjust individual and team forecasts for future periods
- Review your quota, override, and track changes across all forecast categories (Commit, Best Case, Pipeline, Booked revenue)
- Slice and dice any forecast by vertical, product, or time period.
2. See the pipeline growth during the selected period with pipeline evolution reports and adjust your revenue projections when needed
- See the total pipeline value at the beginning and end of a selected period
- Analyze opportunities across Forecast Categories
- Understand the Forecast Category and Opportunity Stage relationship
3. See exactly where you’ll end your quarter with Salesforce-native forecast evolution reports
- Create reports for forecast categories (Commit, Best Case, Pipeline, Booked revenue)
- Perform retrospective analysis per specific sales teams or reps
- Understand what has changed since the previous week’s forecast call with a single click
4. Guide your team at each stage of sales forecasting process with Revenue Signals
- Set up Revenue Signals to remind your team to submit forecasts on time.
- Update forecast figures in one click as soon as the opportunity category changes
- Receive Revenue Signals about important changes in the forecast in real-time
Following these simple steps with a revenue intelligence solution will make your forecasts more accurate.
