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What is Sales Forecasting? Your Key to Informed Decisions

What is sales forecasting? Well, let's start with a story. On May 24, 2022, the stock price of the social media powerhouse Snapchat cratered by more than 40%. The cause of this calamity? The company made a wrong sales forecast. 

Just one month earlier, Snapchat issued guidance for its quarterly sales. When that sales projection turned out to be too optimistic, the company had to file an 8-K report with the SEC to warn it would miss its own sales forecast, triggering a collapse of its stock price. All it took was one missed target to wipe out over 40%, or $16 billion, of Snapchat's market cap within a few hours. 

The dire consequences of missing sales forecasts aren't limited to public companies. When a private firm misses its sales projection, it loses credibility with investors and partners, making it more difficult to raise funding in the future. Its valuation could get a haircut, and the management could get fired.

Sales forecasting is crucial to any company's business planning and strategy, but we don’t say that to scare you. Rather, we've created this article to offer an overview of the benefits of a good sales forecast, the departments and teams that use them, and the steps you can take to create your own.

What is a Sales Forecast?

Simply put, a sales forecast is a prediction of a company's future revenue. It can include multiple dimensions:

  • Time: Sales forecasts should cover different periods, such as daily, weekly, monthly, quarterly, and yearly.
  • Location: Predict the future sales in each country, region, and city.
  • Sales rep & team: Provide future revenue estimates for each sales rep, which can then be consolidated into forecasts for sales teams and branch offices.
  • Client: By developing a revenue forecast for each client, companies can closely monitor each sale's progress and promptly intervene if it runs into difficulties.
  • Product: A product-based sales forecast offers insights into each product's growth trajectory, informing decisions on investment and resource allocations.

Why is Sales Forecasting Important?

If the intro to this story didn’t make it clear, a sales forecast is an incredibly important tool. It serves as a roadmap for the entire company and leads various functions—from staffing and supply chain management to product development and marketing—to inform their decisions and plan for the future.

Better Sales Quotas

With accurate sales forecasts, a business can set ambitious yet achievable sales quotas. For example, if the quarterly sales forecast for a salesperson is $500,000, you can set a sales goal of $550,000. Establishing such a stretch goal ensures the sales rep has a realistic chance of meeting their quota while making it challenging enough to inspire overachievement.

By developing accurate sales forecasts, you can also prevent the problems of sales reps "sandbagging" their sales projections to improve their odds of beating quotas or overpromising the revenue they can bring in due to unfounded optimism. 

Improved Hiring

With a precise estimation of the future revenue in the coming months, quarters, and years, a business can plan its recruitment accordingly. 

The sales, production, and customer service departments can hire the employees required to generate the projected revenue, produce the expected volume, and serve the predicted number of customers, respectively.

Reduced Employee Burnout and Turnover

According to research by HR analytics software firm Visier, 89% of American employees have experienced workplace burnout, with 27% suffering from burnout “all of the time.” High burnout rates can increase workplace turnover, as 70% of workers would consider leaving their company to reduce burnout.

With an appropriate staffing level guided by an accurate sales forecast, businesses can ensure their workers aren't overwhelmed by impossible workloads, helping to reduce burnout, improve employee satisfaction and reduce turnover.

Organizational Alignment

A sales forecast can serve as a marching order to coordinate an organization's different departments and help them align their efforts. 

Based on an estimated future workload, the HR department can set up training programs to support the new headcounts, the purchasing department can scale up or down the supply chain accordingly, and the finance department can get the funding needed to support the expected business volume.

Enhanced Understanding of the Sales Operation

Developing an accurate sales forecast requires a deep understanding of the sales process and can help a company answer important questions, such as:

  • How long is the average sales cycle?
  • How long does it take for a new sales rep or sales manager to get up to speed?
  • What's the average revenue per sales rep? Per customer?
  • How big is your sales pipeline?
  • What percentage of your total sales come from your top 5 clients?

Timely Sales Interventions To Support Growth

Sales forecasts can help identify issues in the sales pipeline early on and trigger timely interventions to address any problems in the selling process. 

For example, a company may notice a client's revenue projection is lowered 3 months in a row. Upon investigation, that's due to the signing of a deal getting pushed out repeatedly. In response, management can assign more support to help the sales team in charge or offer extra incentives to the client to speed up the deal's completion.

Such early warnings and the resultant interventions can increase a business' sales success rate and boost revenue growth. According to research by the consulting firm Korn Ferry, companies with a formal sales forecasting process increase their win rates of potential deals by 17%.

Improved Resource Allocation

By spotlighting high and low-growth areas, sales forecasting can enable a business to allocate resources more efficiently, leading to better overall business performance.

If your sales forecast predicts certain cities and regions growing faster than average, you can shift headcounts and resources to those locations to capture the expanding opportunities. 

Similarly, if the forecast projects specific product lines to have below-average growth, you may want to scale down their investments to free up resources for other products and initiatives.

More Responsive Strategic Planning

Strategic planning remains a quarterly or annual event in many companies, resulting in outdated strategies unable to keep up with the quickly changing business environment. 

A continuously updated sales forecast can provide an up-to-date outlook of a company's performance and market, enabling organizations to adjust their strategies constantly in response to the latest market changes. 

If the sales forecast predicts a slowdown in revenue due to a deteriorating regulatory environment, you can cut costs immediately to limit the damage. If the forecast expects a speed-up of growth caused by the success of a new business, you can increase investment instantly to maximize sales. There's no need to wait for annual strategic planning before changing business direction. 

Confidence with Board and Investors

As shown by the example of Snapchat at the beginning of this article, missing a sales forecast can be disastrous to a business and its investor relations.

On the other hand, producing accurate sales projections consistently goes a long way in helping a management team build credibility with its board and investors. Investors love reliability, and the best way to show you're reliable is to accurately predict your future revenue and meet your sales target quarter after quarter.

Which Teams Use Sales Forecasts?

In most companies, product, production, and sales teams are primarily responsible for developing sales forecasts. 

Sales teams are in constant contact with customers and thus have the best read on the market conditions and can offer the most accurate estimates of future revenue. Ultimately, sales leaders are responsible for sales forecasting, although sales reps may also play a significant role in the process.

The product and production teams can provide valuable inputs on when new products are ready and how many products can be made within a specific time period to meet customer demands.

Once created, a sales forecast can be used by different teams and functions:

  • Sales: Sales departments use forecasts to determine how many sales reps to hire, fine-tune sales processes, set targets for salespeople, and measure their performance. 
  • Marketing: Guided by sales forecasts, marketing teams can plan their marketing campaigns accordingly to generate the customer interest needed to meet the projected revenue.
  • Production: Production needs to hire enough frontline workers and secure sufficient manufacturing capacity to meet the demands called for by the sales forecast.
  • Supply Chain: Supply chain managers use sales forecasts to coordinate with their suppliers to ensure they can provide the parts and materials required to support the revenue projection.
  • HR: HR plans company-wide recruitment efforts to support sales forecasts. It also ensures sufficient onboarding and training capacity to support all employees.
  • Customer Service: Based on the number of customers projected by the sales forecast, customer service can hire the appropriate number of service reps and expand call centers as needed.
  • Finance: Finance departments use sales forecasts to develop the budgets necessary to produce the projected revenue and ensure sufficient funding is in place.

How to Create a Sales Forecast

Different companies use different methods to forecast sales. While many rely on experience and intuition to predict future revenues informally, adopting a formal, data-driven methodology based on past sales data can result in higher forecasting accuracy.

To create simple sales forecasts, you can use a generic tool such as a spreadsheet. For more complex revenue modeling, specialized sales forecasting software could save you time.

The 4-step sales forecasting method below provides a framework for developing forecast models.

Analyze Past Sales Data

The first step is to collect historical sales data and analyze it to identify revenue growth patterns. 

Uncover and quantify relationships between sales numbers and external factors, such as:

  • Season: Some industries, such as retail and hospitality, exhibit strong seasonality, with peak and off seasons influencing sales heavily.
  • Weather: For some businesses, weather can have an outsized effect on their sales. Examples include airlines and amusement parks.
  • Marketing spend: Higher advertising expenses and more aggressive promotions can boost sales. 
  • Macroeconomic conditions: Your sales may be sensitive to macro variables, such as interest rates, oil prices, inflation, unemployment rates, and GDP growth.
  • Customer satisfaction: Higher customer satisfaction can increase revenue. Find out how customer metrics, such as Net Promoter Score (NPS), affect past sales performance.

Analyze your internal sales process to understand: 

  • Sales funnel: How much time do potential customers spend at each stage of your sales funnel?
  • Win rates: What are the win rates of prospects at each sales funnel stage?
  • Revenue per sales rep: How much revenue does a sales rep generate monthly?

Build Your Sales Forecast Model

Build a model to forecast sales by incorporating the external factors and internal metrics identified above. Common techniques include:

  • Almanac method: Use historical data with appropriate adjustments to predict future sales. For example, your Q4 revenue last year was $5M, and you're averaging 10% sales growth this year. That puts you at $5.5M for Q4. But you've also raised your NPS 20% this year, which historically translated to a 20% revenue increase. Your adjusted Q4 forecast is, therefore, $6.6M.
  • Opportunity stage forecasting: This method forecasts sales based on the stages of potential deals. For example, an opportunity is at the "proposal" stage on your sales funnel. Based on past data, prospects at this stage have a 55% closing probability. Your model then assigns a 55% success odds to this opportunity and calculates future revenue accordingly.
  • Sales cycle forecasting: This method uses the age of potential deals to forecast sales. For example, your average sales cycle is 5 months, and your salesperson has been working on a client for 3 months. Your model then assigns a 60% closing probability to this deal and uses that to forecast revenue.
  • Multivariate regression: Multivariate regression is a statistical technique to unpack the relationships between a dependent variable (your sales) and multiple independent variables (marketing spend, NPS, inflation rate, sales pipeline size, etc.) This method requires technical know-how but can provide more accurate forecasts.
  • Machine learning (ML): You can use your past sales data to train ML models for sales forecasting. Popular ML algorithms, such as XGBoost, LSTM, and Random Forest, are available from open-source software, including scikit-learn

Make Your Calculations

To make sales forecasts, plug your data, such as sales pipeline size, marketing spend, and interest rates, into your model to calculate future revenue.

Your forecast should estimate sales for multiple time frames, including daily, weekly, monthly, quarterly, and annually.

Review and Revise

Sales forecasting is a continuous activity. Track your actual sales against your forecast constantly and fine-tune your model to improve its accuracy.

A Note on Forecast Accuracy

According to research, sales forecasts are typically accurate to within 10%. Customer relationship management (CRM) software can improve forecast accuracy by:

  • Keeping track of each opportunity's age automatically to remove manual errors
  • Defining a standardized sales funnel to record the stage of each prospect, eliminating ambiguity.
  • Integrating with forecasting software to provide up-to-date data and eliminate re-entry errors.

Next Steps

Ready to start your sales forecasting project? Check out our picks for the top 10 sales forecasting software, sales funnel software, and CRM software to choose the best tools for your company. Leave your comment below to let us know what you think.

By Phil Gray

Philip Gray is the COO of Black and White Zebra, a digital publishing and tech company. He hails from rainy Glasgow, Scotland transplanted in not quite as rainy Vancouver, BC, Canada. With 10+ years of experience in leadership and operations in industries that include biotechnology, healthcare, logistics, and SaaS, he applies a considerable broad scope of experience in business that lets him see the big picture. His love for data and all things revenue operations landed him this role as resident big brain for the RevOpsTeam. A business renaissance man with his hands in many departmental pies, he is an advocate of centralized data management, holistic planning, and process automation. An unapologetic buzzword apologist, you can often find him double clicking, drilling down, and unpacking all the things.

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