An established internal framework is a backbone to a successful sales organization. This includes an organized onboarding process, consistent coaching, and ongoing training. However, the importance of sales forecasting is not to be overlooked.
What is forecasting exactly? Sales forecasting is a way to estimate the expected revenue within a certain period of time.
Sales forecasting is an imperative piece of the process because it impacts the sales team directly and the entire company. While it’s the sales leaders and reps who actually own the forecast system, the rest of the organization uses the data to make long-term, company-wide decisions.
Kevin Knieriem, the CRO at the revenue operations platform Clari, says,
“The forecasting process is so much more than just calling a number. It represents the entire operating rhythm of the whole company.”
Multiple departments use sales forecast information to make business decisions, set goals, and determine budgets.
Due to its importance, a sales team must have a forecasting structure in place. In this article, we’ll discuss the different types of sales forecasting methods and the benefits and challenges that come with forecasting future revenue.
Benefits of Sales Forecasting
Forecasting is a great resource for your team’s future success and growth. Research has shown that sales teams are over 7% more likely to hit their revenue and sales quotas with accurate sales forecasts. Here are a few more benefits to incorporating a sales forecast method:
Increase in growth and revenue
A thorough and accurate forecasting system can lead to greater win rates and higher revenue. CSO Insights — a research division of Miller Heiman Group — found that organizations with a structured forecasting process increased their win rates by 25%, compared to companies that did not have one in place, per their 2018 Sales Operations Optimization Study.
Furthermore, research by the Aberdeen Group found that companies with accurate sales forecasts saw a 13.4% increase in their year-over-year growth compared to companies with inaccurate estimates.
Multiple departments use their visibility into forecasting information to regulate budgets and manage risk, as well as assist with future business planning. These decisions influence an entire organization, so the benefit of forecasting sales properly can shape the company’s growth over time.
Proactive sales strategy
For the sales team, in particular, sales forecasting can assist with setting quotas and goals and ensuring reps remain proactive throughout the selling process. With an accurate forecast, a sales team can create a set of expectations that includes anticipated revenue and growth insight. It also encourages better territory planning and more informed management decision-making overall.
Precise forecasting assists with strategic planning, implementation, and improvement. The key is to find a sales forecasting method that works for your team while maintaining the highest level of accuracy possible within your sales process.
Sales Forecasting Methods
Every sales team prefers their own method when estimating their numbers. There are many different ways to forecast sales, but here are some of the most common sales forecasting methods explained:
Length of the sales cycle
This method relies on the age of the sales opportunity. It’s based on the length of your particular sales cycle. By using this information, this method determines how likely a deal is to close based on how far along it is in the sales cycle.
- Example: Let’s say your sales cycle lasts four months and a sales rep has been working on a prospect for two months. You would then forecast that this account has a 50% chance of closing.
- Important Note: In order for this method to be accurate, customer information has to be promptly entered into a CRM. The pipeline and the real-time account status need to match — otherwise, the entire method will be unreliable.
This method involves assigning a probability to each opportunity stage within the sales cycle. The pipeline is typically broken down into sections — initial outreach, qualified, demo, etc. Then a percentage is assigned to each stage to calculate the probability of a deal.
- Example: Let’s say your opportunity stages are broken down as follows:
- Initial Outreach/Incoming: 5%
- Qualified: 10%
- Demo: 25%Proposal: 50%
- Negotiation/Final Talks: 75%
- Close: 100%
Using this breakdown, let’s say there is a $5,000 deal at the Qualified stage, which means there is a 10% chance it will close. This would mean the opportunity forecast amount would be $500.
- Important Note: Unlike the sales cycle length option, the opportunity stages method does not incorporate the amount of time spent on an account. So while an opportunity may be listed at 50%, if it’s been at that stage for longer than your typical sales cycle dictates, then that forecast may be imprecise.
The pipeline sales forecasting method is considered one of the most accurate methods available from a data standpoint. It involves analysing all opportunities within the pipeline against multiple factors and uses that information to deliver a forecast.These factors are typically unique to your company but can include the previously mentioned deal stage breakdown and sales cycle length, as well as the individual rep’s average win rate.
- Example: Your sales rep has a high win rate with deals that are worth between $2,000 and $4,000 within the 90-day sales cycle. In that case, all of the current open opportunities in the rep’s pipeline that fit those parameters would be forecasted with a high chance of closing.
- Important Note: This method requires a sophisticated algorithm that pulls information from multiple locations. So, you will need to have a centralized and integrated CRM system.
Utilizing historical data is a helpful recommendation for building many parts of the sales process. But it can be particularly helpful when it comes to forecasting revenue. This method is fairly straightforward. It takes past performance data and then estimates sales and growth for the next revenue period.
- Example: Based on historical data, you know that your team’s monthly recurring revenue (MRR) is $100,000. In addition, you also know the sales revenue has grown 10% each month over the past 12 months.
Using that information, you would assume the MRR would remain the same and factor in the 10% growth rate. This gives you an estimated forecast amount of $110,000 for the next month.
- Important Note: This method can be tricky since it doesn’t incorporate additional circumstances, like external factors or internal changes. It also assumes that the buyer demand for your particular product will remain consistent each month.
The intuitive method relies on the sales rep’s perspective and intuition about their pipeline. The rep reports the likelihood and timing of when their deal will close, as well the total worth of the sale. Some teams like this sales forecasting method since the rep knows the client best. So, their intuition is usually based on specific client communication and insight.
- Example: A sales rep reviews their pipeline for the upcoming month and makes stage and deal determinations for each of their accounts. Using this information, they will estimate that they will close x number of deals for x amount. That becomes the forecasted number for the month.
- Important Note: As you can probably imagine, this method is incredibly hard to quantify since it relies heavily on the sales rep’s subjectivity. It’s also difficult to replicate since each individual thinks differently. However, this may be a helpful method for new businesses or ones that lack a large amount of historical data.
This method is highly analytical and data-driven, which means it’s one of the most reliable options in terms of accuracy. This more advanced method uses many of the factors mentioned above — like cycle length, probability percentages, individual performances, and historical data — and exports a forecast based on that information.It’s similar to the pipeline method. However, it's a bit more complex since it also involves utilizing predictive and customer intelligence data.
- Example: You have two sales reps working on two separate accounts. Rep #1 is in the Demo stage of a potential $5,000 deal with a new customer. This rep is also historically one of your best closers. Rep #2 is in the Negotiation stage of a $8,000 deal with a repeat customer. This rep has a lower win rate percentage comparability.
The algorithm would take into account the stage of each opportunity, the sales cycle length, the deal worth, the rep’s individual win rates, and the historical performance of new versus repeat customers. Using all of these variables, the system would deliver an estimated forecast for each opportunity. This will give you a total sales forecast for both reps.
- Important Note: This option also requires a sophisticated system that can calculate multiple variables across different platforms. Precise, prompt and centralised data entry is a necessity for this method to be successful.
Challenges of Sales Forecasting
While forecasting future revenue is an imperative part of the sales process, it’s also important to understand some of the challenges that can come along with it. Here are just a few to be aware of when forecasting sales:
Total and consistent accuracy
A common thread throughout each sales forecasting method is the need for consistency — whether it’s with timely data entry or clear judgements on account statuses. This consistency increases the accuracy of the data — an important aspect considering the fact that 79% of sales organizations miss their sales forecast by more than 10 percent. Your data collection tools also need to be efficient and capable of exporting forecasts in a reliable way.
A major challenge with sales forecasting methods is that many of them are based on some form of subjectivity. Some reps may be overly optimistic with their account outlook while others may be underestimating their sales out of caution. Both scenarios can result in inaccurate data, so it’s important to encourage determinations based on as much quantitative and objective information as possible.
Uncertain industry environment
As many of us learned in 2020, external and uncontrollable factors can have a profound impact on our businesses and their futures. Everything from economic influences — like large fluctuations in the stock market, for example — as well as shifts in global trends can drastically change demand. As a result, it can impair our ability to correctly forecast future business.
Time and money
While it’s important to spend time ensuring accuracy within the deal stages or pouring over historical data to recognize future trends, it can also be a time and resource commitment.
Forecasting needs to be consistent, which means sales managers and reps have to spend quality time frequently mapping and estimating their accounts. The good news is there are many forecasting tools and software on the market that can help streamline the process.
Forecasting sales can be executed in a multitude of ways — the important part is determining which method works for your team and your organisation. Forecasting is also an effective tool for sales growth and proactivity.
Revenue growth coach, consultant, and author Scott Edinger says,
“Forecasting can become a strategic endeavour with a positive impact on results versus an inspection exercise that produces an educated guess.”
Accurate sales forecasting influences not only the sales organisation but also the entire business as a whole. Investing your resources into creating a scalable and consistent forecasting plan is essential to the overall success of your company.