How to Conduct a Sales Forecast

The question of how to predict sales is a common one asked by new business owners. These business owners are consistently upbeat about the prospects for their fledgling enterprise. The specifics, however, are where most people lose confidence in their ability to accurately forecast future sales and earnings.

Predicting the future is a daunting task. The bright side is that none of us can predict the future, and we can’t possibly know more about your new company than you do. Don’t bother with a company if you have precognitive abilities; use your money more wisely on the stock market instead. It will save you time and help you amass more wealth.

Experts recommend taking a few deep breaths and calming down. The resources at your disposal are comparable to those of other forecasters. Let’s jump in and start working it out.

Essential Elements of Reliable Sales Predictions

The most crucial factor in producing an accurate sales prediction is having access to high-quality data. That’s why it’s so important to get your hands on reliable information. Due to a lack of internal sales data, new businesses may have to settle with industry norms or even informed assumptions when trying to predict revenue. However, larger, more established businesses can utilize their past performance data to predict how they will do in the future. Here are the steps you need to take before even considering a sales forecast:

Keep track of your sales procedure

You won’t be able to accurately anticipate the success of any individual offer unless you have a well-documented sales process outlining the actions and procedures required to get a successful close.

Establish targets or quotas for sales

You can’t tell if your forecast is good or bad without a target to compare it to. Therefore, the sales team as a whole needs unique quotas for each member. Click here to learn more about how to establish sales quotas.

Improve sales

The third step is to establish a baseline or the existing average of key performance indicators.

The following fundamental sales metrics can greatly facilitate planning and forecasting if they are easily measured.

• The length of time it takes for a customer to show interest.
• The time required to finalize a transaction
• The typical cost of a transaction
• The time required to complete the customer onboarding process
• A measure of how often customers come back to do business with you again
• Rates of success at various points in the sales cycle

You need to establish a standard for how long and effectively your sales cycle typically runs.

Be familiar with the state of your sales funnel

Check that your customer relationship management system is up to date and that you have a thorough grasp of the opportunities currently in your pipeline. Forecasting is more challenging but still achievable without a customer relationship management system.

Models for Predicting Future Sales

Sales projections can be made using a number of different approaches. Combining the results of many methods of sales forecasting is common practice for many firms. Thus, they will be prepared for both the best and worst possible outcomes. Typical approaches to predicting future sales are:

Putting stock in the advice of salespeople

The most common question asked by sales managers to their employees is the closing time and price of the deal.  You could try to make a sales prediction in this way, but it’s not a good idea. There is no dependable mechanism to make a constant forecast using this approach, and sales representatives frequently exaggerate their projections. Even though it is clearly inaccurate, many companies still use this strategy to predict their sales.

Using past records

To predict future success, this strategy relies on analyzing prior results achieved under analogous conditions. Let’s take an example of a sales forecast here; say that you brought in X amount of new business during this same time period last year and that your annual growth rate is Y%.

If so, you should expect to bring in around X * 1.Y amount this month. This approach is slightly more precise, but it doesn’t take into account things like the amount of sales agents you have or how well your competitors are doing, both of which could have changed over the course of a year.

Utilizing the deal-making process

With this form of forecasting, you give each step in the sales process a certain chance of success. The potential earnings are then estimated by multiplying the chance of success by the size of a potential gain at any particular period.

This sales forecast example is even more accurate, and its widespread use is due to its ease of use. But there is a flaw: it doesn’t take into account how old the chance is. Are the odds of closing the two chances that have scheduled a sales demo, one three weeks old and the other three months old, exactly the same?

Predicting the sales cycle

Therefore, a different approach to forecasting is to evaluate the health of the pipeline based on the age of the sales opportunity rather than the probability of its success. This metric evaluates the amount of time a deal has been in the pipeline relative to the average time it takes to close a contract.

If your products and sales cycles vary based on whether you’re following up on a referral or a lead from prospecting, you’ll need to account for these factors separately when estimating the likelihood that a deal will close. This strategy requires precise information.

The CRM must be properly utilized to understand what kind of lead it is and how long it has been in the system. Your sales team may have to manually enter a lot of information if you don’t have a customer relationship management system in place that can conveniently keep track of everything.

Predicting the pipeline

Though this technique yields better results, it remains sensitive to data quality. Each opportunity in your pipeline is evaluated according to a variety of criteria, such as its age, transaction type, and pipeline stage. Given the complexity of the process, it is highly unlikely to succeed without specially developed pipeline analysis tools.

Custom forecasting with lead scoring and numerous variables

All of these factors are used in tandem to make predictions using this strategy. It’s somewhat analogous to pipeline forecasting, though it’s far more involved and intricate. Creating such projections typically necessitates the installation of an analytics solution or the creation of sophisticated CRM reports.

Because of the importance of having high-quality data to work with, you must have faith in the information entered by your salespeople. This approach to sales forecasting can be very precise if you have the necessary resources at your disposal. An opportunity’s age, its place in the sales cycle, the qualities of the prospect that increase the likelihood of a sale, and other factors can all be considered.

Common Blunders in Forecasting

In this climate, accurate forecasting takes center stage as pressure mounts on sales teams to meet targets. Salespeople are under increasing pressure to meet escalating expectations as the market becomes more volatile and competitive. Sales activity, and thus the health of the organization, can be tracked most easily through projections.

It’s unfortunate that businesses repeatedly fail to learn from their past forecasting errors. Several typical pitfalls while sales modeling are listed below.

• A lack of visibility into contract status is a major limitation of sales data. Existing forecast systems have the drawback of relying significantly on sellers to supply precise information about the status of individual prospects, which can be misleading at times. Sellers are under a lot of pressure, so it’s not unexpected that the information they present is generally more optimistic than the reality.
• Manual procedures that take too much time will eat into sales opportunities. Estimates show that managers spend an average of 1.5 hours per week on forecasting, while sales reps devote 2.5 hours per week. Spending time on these tedious tasks is counterproductive because more time could be made available for making actual sales.
• Accuracy often suffers in the haste to commit to financial commitments. When sellers are pressed for upbeat statistics, they often exaggerate the number of sales that will actually close. Not surprisingly, most sales teams underperform by more than 10% compared to their projections. But despite salespeople’s best efforts, 54% of predicted deals ultimately fail to materialize.

Sales Forecasting Success Factors

Strong organizational coordination, automation, trustworthy data, and an analytics-based process are all crucial to improving the accuracy of your sales forecasting plans and the efficiency of the forecast approach. In a perfect world, sales projections would:

• Collaborative. Leaders need to aggregate data from many different sales positions, departments, and geographic areas. Here, input from frontline sales personnel can be invaluable, as they often have access to insights about the industry that management just doesn’t.
• Data-driven. Subjectivity, which is frequently more retroactive than prospective, can be mitigated through the use of predictive analytics. It will be easier and faster to reach a consensus and use similar data definitions and baselines.
• Created instantly. Sales managers may make better decisions more rapidly by investing in the ability to course-correct or forecast in real-time. By doing so, they can easily adjust the forecast in response to changes in demand or the market.
• Multiperspective information gathered from a single source. The forecast is a single source of truth that may be used to gauge the success of individual sales reps, geographic areas, and the entire company, as well as to coordinate the efforts of many departments.
• Enhanced with age. Make better predictions in the future using the information gained from a streamlined sales forecasting process, with the expectation that you will achieve your accuracy targets more often.

Companies with stronger forecasting methods and tools outperform their competitors because they have a better grasp on the factors that affect their business and may influence the results of a certain sales cycle before it ends.

Constraints in Making Accurate Sales Predictions

Sometimes it’s tough to predict sales with any reliability. The following are some of the most important aspects of accurate sales forecasting:

Credibility and Skepticism

Using spreadsheets for sales forecasting can lead to inaccuracies, which in turn produce less reliable forecasts for the company. Accuracy problems may be made worse by:

• Underutilization of customer relationship management software and tardy data entry by staff members.
• Inconsistencies in data collection or salespeople failing to enter all relevant information
• Participants in the company’s decision-making process who use varying approaches to formulate their projections
• Not enough communication between the product, sales, and finance departments. Inadequate communication can be exacerbated when sales estimates are created in silos.

Subjectivity

Despite the fact that a great sales forecast depends to some extent on the forecaster making excellent decisions about how to use the data, most businesses rely too heavily on expert opinion and not enough on reliable predictive analytics.

For instance, businesses that use mathematical pipeline weightings may overlook the intricacies that are the true drivers of accuracy, such as staffing levels, price choices, and route-to-market priorities.

Usability

A sales forecast loses much of its value if it is not generated in a way that is helpful to stakeholders across the organization. Good forecasting should yield information that is useful and accessible to more than one group.

Inefficiency

When there are flaws in the way sales projections are calculated, it can be a monumental challenge. Disputes can arise, for instance, if a forecast has many owners or if the process of producing a forecast is not clearly stated with a standard set of guidelines. In a similar vein, if the forecast’s inputs aren’t reconciled before the forecast is produced, the forecast itself may be subject to several modifications, which might undermine trust if versions are rolled out and then amended.

What Affects Sales Prediction Factors

• The state of the economy affects the success or failure of every company and market. When the economy is healthy, people are more likely to invest and make purchases, but during a recession, people are more likely to cut back.
• Policy shifts, such as the adoption of new laws or regulations, can be beneficial or detrimental to your company. So, it’s crucial to factor these in when making projections about the next period’s sales.
• Shifts in the Market Duplicate goods are produced by a variety of companies across all markets. Your sales projections should account for external factors that could affect the market share of your industry, such as the introduction of new technologies, changes in design, promotional efforts from competitors, and the entry of new enterprises.
• Sales projections are sensitive to variations in your product. These modifications could involve releasing a brand-new feature in response to high demand, retiring an unused function, or fixing issues. These modifications to the product can help salespeople close more deals and reduce the length of the sales cycle.

Tools and software for sales forecasting

This is by no means a full list, but it does include many of the most useful sales forecasting tools that can help you get closer to making accurate predictions.

• Customer relationship management (CRM) software is a specific sales tool that helps your sales representatives close transactions by storing and recording information important to closing sales. Lead tracking, statistics for your sales funnel, call scripts, and a log of how new customers heard about you can all be viewed and used to better plan out your follow-up with leads and current clients. Many factors, including company size and kind, should be taken into account when selecting a customer relationship management system.
• You’ll need a lead scoring system that ranks prospects based on their engagement with your website or other criteria you set.
• Predicting more complicated metrics, including gross margins, typically requires data related to accounting software; fortunately, most of these programs offer connections that make data transmission easy.
• Simple spreadsheets like Excel or Google Sheets are typically used for sales forecasting, but it’s important to keep in mind all external and internal factors that could impact the reliability of your numbers.