sales forecasting

In the early days, even the best sales forecasts were more art than science. Most sales organizations just didn’t have the resources to collect the level of customer data they needed to create statistically rigorous revenue predictions.

Instead, sales forecasts relied on intuitive predictions (i.e., gut feelings) and historical revenue trends. Unsurprisingly, these forecasts soon earned reputations as being about as useful to a company’s long-term strategic planning as a tarot card reading.

Many companies still rely on this kind of subjective approach to sales forecasting. Rather than being based on hard data about purchasing trends, these reports are built around incomplete pipeline data, outdated spreadsheets, and the optimistic self-reporting of sales reps. And again,  these reports unsurprisingly tend to be highly inaccurate, and they often contribute to bad strategic planning and lost revenues.

Sales forecasts don’t have to be this way. If you want to generate reliable forecasts for your company, the best place to start is by collecting high-quality customer and sales data. To complete this first step, you need a customer relationship management (CRM) solution that uses modern technology to track sales. With the right tools in place, any business can create reliable, data-driven sales forecasts.

Why Sales Forecasting Matters

Even in relatively small organizations, sales is a fast-paced and hectic job. By necessity, the most successful sales reps are always trying to move deals further down the pipeline, hunting for new prospects, and trudging through contracts and paperwork. As a result, even the sharpest salespeople can fail to recognize major sales trends because they’re so completely focused on making their next big sales.

At the same time, sales is responsible for generating much of the company’s most valuable data. It’s not just a matter of extrapolating next month’s sales numbers by using the data from the last quarter.

Data-driven sales data can provide:

These insights can be used to inform major strategic decisions—from hiring new staff members to product launch dates.

Sales forecasts also act as a kind of early warning system. If sales suddenly drop off after a long period of growth, there’s usually a reason. Maybe a competitor is playing hardball by offering major discounts. Or a change in the economy is hitting your industry in an unexpected way. These trends are often visible in sales reports long before the business feels their full impact.

If the company can notice a negative trend early enough, it might just be able to avoid a full-blown catastrophe.

Essential Elements of a Sales Forecast

Every organization has unique needs from their sales forecasts. Even the most comprehensive list couldn’t hope to fully cover every possible consideration. That said, the best sales forecasting tools all share a handful of common traits. In this section, we’re going to look at four essential building blocks of an effective data-driven sales forecast…

  1. Standardized Definitions & Processes

For any report to be useful to an entire organization, everyone needs to be on the same page about the information it’s trying to communicate. There’s a lot of industry-specific jargon in the business world, particularly in sales and marketing.

At a minimum, the report should clearly define each stage of the sales pipeline. It should also explicitly state the requirements for moving a prospect from one stage to the next. The goal here is to avoid any ambiguity (both intentional and unintentional) about the quantity and quality of future sales.

  1. Historical Data & Context

Any sales forecast is only as accurate as its data of origin. While simple trends (e.g., seasonal sales increases and declines) only require basic inputs, more sophisticated insights require a more comprehensive data set.

In general, the more historical data you have to pull from, the more accurate your forecast results will be. It’s also important to remember that all data isn’t directly comparable, particularly if that data comes from multiple sources. For example, this lack of comparability often occurs after a company implements a new CRM, since these systems often use different methods to generate similar datasets.

  1. Key Metrics & Performance Indicators

Each stage of the sales process includes an opportunity to collect data about prospects, eventual customers, and sales-rep performances. While this bread-and-butter data is what most people think of when they talk about sales forecasts, it’s also just scratching the surface of what this technology can do.

With the right analysis tools, these key metrics can be manipulated to provide new insights. It can be broken apart to examine your organization’s sales performance at a truly granular level.

  1. Sales & Pipeline Reviews

The purpose of a sales report isn’t simply to document sales trends. It’s a communication tool that provides an essential resource and helps an organization’s leadership make good strategic decisions, discover obscure buying trends, and anticipate future market conditions.

Sales managers can use these reports to gain better visibility into the sales process and a deeper understanding of the health of the sales pipeline. With the right reporting technology (which is typically provided within the CRM), these sales forecasts can also be visually intuitive and easy for anyone in the organization to follow.

Conclusion

Data-driven forecasting is an essential business tool for any sales organization.

Forecasting reports confirm that everyone is working toward the same goals, provide shared challenges that keep everyone motivated, highlight new opportunities, place a spotlight on long-overlooked problems, and take the guesswork out of planning. So they make it that much easier to improve future results—from closed deals to new revenue.

Learn more about the ways Faye can help your company create outstanding data-driven sales forecasts via CRM technology. Set up a free consultation today.