What is a Sales Forecast?
Sales forecasting or sales forecasting is the process of estimating future revenue by predicting the number of products or services that a sales unit (which can be an individual salesperson, sales team, or company) will be sold in the following week, month, quarter, or year.
Simply put, a sales forecast is a projected measure of how the market will respond to a company’s entry into the market.
Why is Sales Forecast Important?
Forecast is about the future. It’s hard to overstate how important it is for companies to produce accurate sales forecasts.
Private companies gain confidence in their business when leaders can trust forecasts. For public companies, accurate forecasts provide credibility in the marketplace.
Finance, for example, relies on forecasts to develop budgets for capacity and recruitment plans. Production uses sales forecasts to plan its cycle. Forecasts assist sales operations with territory and quota planning, supply chains with material purchasing and production capacity, and sales strategies with channel and partner strategies. These are just a few examples.
Unfortunately, in many companies, this process remains disconnected, which can result in a loss of business. If information from sales forecasts is not shared, for example, product marketing may create demand plans that are not in line with sales quotas or sales attainment levels.
This leaves the company with too much inventory, or too little inventory, or inaccurate sales targets — all mistakes that hurt the bottom line in your business. Committing to quality and regular sales forecasts can help avoid those costly mistakes.
What are the benefits of having an accurate sales forecast?
- An accurate sales forecasting process provides many benefits. This includes:
- Better decision making about the future
- Reduction of sales channels and risk forecast
- Alignment of sales quotas and revenue expectations
- Reduction of time spent planning area coverage and setting quotas
- Benchmarks that can be used to assess future trends
- Ability to focus the sales team on high-return, high-profit sales channel opportunities, resulting in better win rates
How to Accurately Forecast Sales
To create an accurate sales forecast, follow these five steps:
1. Assess historical trends
Check sales from the previous year. Break the numbers down by price, product, representation, sales period, and other relevant variables.
Turn them into “sales rate”, which is the projected number of sales per sales period. This forms the basis of your sales forecast.
2. Merge changes
This is where estimates get interesting. Once you have a basic sales level running, you’ll want to tweak it according to the number of changes you see coming. As an example:
Did you change the price of a product? Are there competitors who might force you to change your pricing plan?
How many new customers do you anticipate landing this year? How much did you land the previous year? Have you hired a new representative, gained measurable brand exposure, or increased the likelihood of acquiring a new customer?
Will you be running a new promotion this year? What was the ROI on the previous promotion, and how do you expect it to compare with the new promotion?
Did you open a new channel? New location? New territory?
Are you introducing a new product? Changing your product range? How long did it take for the previous product to gain traction in the market? Would you expect a new product to act similarly?
3. Anticipating market trends
Now is the time to project all the market events you have tracked. Are you or your competitors going public? Are you anticipating an acquisition? Will there be laws that change how your product is received?
4. Monitor competitors
You’ve likely already done this, but consider competing products and campaigns, especially the major players in the field. Also check to see if new competitors might enter your market.
5. Include a business plan
Add it to all your business strategic plans. Are you in growth mode? What are the hiring projections for this year? Is there a new market you are targeting or a new marketing campaign? How does all this affect the forecast?
Once you’ve calculated all of these things, build them into your estimates. You want everything to be detailed, so that you can understand the estimate in as much detail as possible.
Different stakeholders in the company will likely want to understand different aspects of the forecast, so you should be able to zoom in or out as far as needed.
In general, there are two types of sales forecasts: bottom-up forecasts and top-down forecasts.
Bottom-up forecasting begins by projecting the number of units the company will sell, then multiplying that number by the average cost per unit. You can also build the number of locations, number of sales reps, number of online interactions, and other metrics.
The idea behind bottom-up sales forecasting is to start with the smallest component of the forecast, and build from there.
The advantage of bottom-up forecasting is that if a variable changes (such as cost per item, or number of representatives), the forecast is easy to change. It also provides quite detailed information. The top-down sales forecast starts with the size of the total market, then estimates what percentage of the market the business can capture.
If the market size is $500 million, for example, a company can estimate that they can win 10 percent of that market, making their sales forecast $50 million for the year. When creating sales forecasts, it is important to use both of these methods.
Start with a top-down method, then use a bottom-up approach to see if your first estimate is feasible. Or do both separately and see how well they fit together. To produce the most accurate estimates, companies must perform both types of estimates, and then adjust them to produce the same amount.
The Key to Success in Forecasting Sales
Improving the accuracy of your sales forecasts and the efficiency of the forecasting process depends on many factors, including strong organizational coordination, automation, reliable data, and analytics-based methodologies. Ideally, the sales forecast should:
Leaders must combine input from a variety of sales roles, business units, and regions. Frontline sales teams can be very useful here, providing an overview of the market you’ve never considered before.
Based on data
Predictive analytics can reduce the impact of subjectivity, which is often more backwards than forwards. Using common data definitions and baselines promotes alignment and saves time.
Produced in real time
Investing in real-time capabilities for correcting or re-estimating allows sales leaders to gain insight quickly so they can make more informed decisions. This allows them to quickly and accurately update forecasts based on demand or market changes.
Single source, with multiple views
Generating forecasts as a single data source gives you good visibility into your company’s reputation, region and performance, and helps align business functions across the organization.
Better from time to time
Use the data provided by the improved sales forecasting process to create more refined future forecasts with increasing accuracy over time against a set of accuracy goals.
Companies with better forecasting processes and tools perform better than their peers because they better understand the drivers of their business and have the ability to shape the results of the sales period before the period closes.
What are the Key Challenges in a Sales Forecast?
It can be difficult to consistently produce accurate sales forecasts. Some keys to success in sales forecasting:
Accuracy and Distrust
When companies use spreadsheets for sales forecasts, they can run into accuracy issues, which in turn make forecasts less reliable. This accuracy issue can be exacerbated by:
- Poor implementation of CRM across the company, and employees don’t enter data in a timely manner
- Inconsistent data across teams or salespeople don’t include complete data.
- Stakeholders across the company use different methodologies to generate their estimates
- Inadequate collaboration across product, sales, and finance teams. This lack of collaboration can be enhanced when companies create sales forecasts manually or using spreadsheets.
While generating quality sales forecasts relies heavily on forecasters making sound decisions about how to use data, in general, companies rely more on judgment and less on credible predictive analytics than they should.
Companies that forecast with simple arithmetic pipe weighting, for example, may miss the nuances of the true drivers of accuracy, which might be number of employees, pricing decisions, or route-to-market emphasis points.
When a sales forecast is not created in a way that makes it useful to stakeholders across the company, it becomes much less effective than it should be. A good estimate should produce data that is relevant to many teams, and understandable to them.
Sales forecasts can be very difficult to create when inefficiencies are incorporated into the forecasting process. For example, if an estimate has multiple owners, or the forecasting process is not clearly defined by a standard set of rules, there may be disagreements about how the forecast will be produced.
Similarly, if input into the forecast is not reconciled before the forecast is produced, the forecast itself may undergo multiple revisions, which can reduce confidence in the forecast if a version is released and later revised.
To perform company-wide forecasts, companies need different elements of each business function.
The following functions can contribute to sales forecasts:
- Sales: Provides a bottom-up view, using data from CRM and PRM, building judgments from sales leaders. Sales can manage this process through the Sales Operations function, using the right tools, and reporting
- Finance: Provide macroeconomic guidance and work with product teams.
- Marketing: Provides macro market guidance, especially in industries such as telecommunications, retail and CPG. Marketing can also provide the financial team with market data.
- Supply Chain: Provides input on inventory and production.
- IT: Assist with sales forecasting by providing platform, data, integration, and technical support.