Balancing the Art and Science of Sales Forecasting
Many growth-stage companies struggle to create an accurate forecasting model, citing dirty data or lack of process as the primary barriers. To understand how to implement a sales forecasting model that aligns with your business goals, Mainsail's Meg Heinz hosted a webinar with Rosalyn Santa Elena, Chief Revenue Operations Officer at The Carabiner Group.
While data—the “science”—should always be at the core of this process, Santa Elena believes there is also an “art” to forecasting. In this webinar, several strategies were presented for blending the art and science of forecasting to help hit your revenue targets.
Below are our key takeaways from the webinar. You can also watch the full webinar HERE.
Forecasting helps leaders understand how much revenue the business can expect to earn within a given period. If done well, says Santa Elena, forecasting can also help guide your business decisions by illuminating opportunities to mitigate risk and better allocate resources. Of course, forecasting also helps inform your Board and investors.
Who should own forecasting? According to Santa Elena, this should fall to whomever owns your revenue outcome—typically the CRO or VP of Sales, in conjunction with Rev Ops. In reality, she says, it will be a team effort, with contributions from and visibility to marketing, sales, account managers and customer success.
Forecasting is a team sport
Santa Elena makes the analogy that forecasting is not a baton-passing race, but rather a game of soccer, with the ball being passed between every functional team during the customer journey. With cross-functional visibility into your sales data and forecasting insights, the team can streamline revenue opportunities, build out the sales pipeline, improve the customer journey and reduce customer churn.
How to set a good forecasting foundation
To get buy-in from the team, it’s important to help people understand the benefits of forecasting. Clearly define why you’re forecasting, what the goals are and what the potential benefits will be to the individual and to the company.
Then, set a clear operating cadence for forecasting meetings. Your meeting cadence should align with your sales cycle, and you need to be rigorous about sticking to the schedule, even if you adjust it down the line. Santa Elena recommends weekly 1:1s with sales reps, rolling up to less frequent meetings with directors, leaders, and full teams.
Be rigorous, too, about the topic and objective of each meeting, and host specific meetings per topic (i.e., net new business, retention, renewals). Deal inspection and pipeline should be discussed early and often.
Throughout, ensure that your sales processes align with your methodologies and that you have well-defined metrics to track. Says Santa Elena, “I often think we over-complicate forecasting because we think it needs to have many different factors and information. But it’s not rocket science: you just need clear sales processes that align with your sales methodology and defined metrics.”
Keep it simple
Use data to limit subjectivity
With this foundation in place, Santa Elena outlines ways to lean into the “science” of forecasting. She suggests using centralized systems and automated workflows to make forecasting easier and sustainable.
- Define specific entry and exit criteria for leads within the sales funnel. These should be meaningful and obvious actions that make it clear a lead can move between stages.
- Train your sales team. Document your processes to drive adoption and accountability.
- Reinforce what you’ve trained; make sure everyone uses the same language.
- Update your CRM to align with your process.
- Determine which steps can be automated. This is key to increasing your adoptions and accuracy.
Forecasting is predicting the future
Along the way, deal inspection should be constant. Track meaningful metrics to determine how likely a deal is to close, including:
- Amount and level of engagement
- Meetings and/or calls scheduled
- Meetings held
- Pages viewed and content downloaded from your website
Analyze this information and consider the context of opportunities within your pipeline to better understand your funnel. Many metrics impact your forecasting decisions, but what matters most is striking the balance between metrics that are tied to your business goals and ones that indicate the strength of your forecast.
What’s key, says Santa Elena, is to define your revenue targets that drive your forecasting – expansion, revenue, renewals and retention – measure the leading indicators that provide visibility into attainment, and then rigorously review KPIs such as activity, conversion rates and engagement data.
“It’s important to dig deep, even if the metrics aren’t numbers,” she explains. “What are your conversion rates? Look at when and why deals slip, review linearity and seasonality, and look ahead to the quarter for opportunities to pull in.”
Metrics that matter
How to align processes with rigor and accountability
If analyzing the data is the “science” of forecasting, then addressing the human aspect of running a business is the “art.” How to best align process, rigor and accountability among your employees?
If, argues Santa Elena, you have a process, a CRM, and triggers within your systems to support your process, your departments can move forward concurrently, enabling you to maintain consistency and drive accountability.
“I can’t tell you how many times I’ve seen a deal with a closed date that pushed five or six times,” adds Heinz. “So, how exactly do you get the deal to close?” she asks Santa Elena.
In this scenario, Santa Elena suggests having Rev Ops and managers flag unusual activity or deals that haven’t moved, and ask rigorous questions in 1:1s such as: “What’s changed with this deal? Why is it this month that it is going to close? What’s actually progressed on the deal?”
By digging into data and training your teams to take a hard look at their metrics, you’ll be able to push your business forward.
Process and Rigor
Set a forecast range that allows for upsides
When generating a forecast, it’s common for leaders to define it with one number. In reality, argues Heinz and Santa Elena, your forecast is a range made up of the best- and worst-case scenarios. “It’s really hard to land on an exact number,” says Santa Elena, so she suggests determining a “commit” number, i.e., your best-case scenario, then allowing for variance.
The benefit to this approach is that it uncovers incremental upsides, such as potential add-on sales or identifying customer churn risks early, to ensure you hit your forecasting range.
You should set a reasonable range that’s both attainable and backed by data, which will lead to opportunities that will help you hit your revenue goals.
To define your forecast range, start with a top-down approach, says Santa Elena, “for planning purposes and sanity checks.” Then, take a bottom-up approach by looking at inputs to see what’s happening in deals and at the sales rep level. Identify any discrepancies, such as early customer sell, delayed closes or customer cancellations, in your recurring forecast calls.
According to Santa Elena, the biggest benefit of having a regular forecasting cadence is that you’re consistently holding discussions with the right people to determine who can help with what, mitigate risks and operationalize your processes to ensure deals are closing.
Measure and predict variance in your forecast
How much variance is acceptable in your forecasting? Santa Elena says within the last few weeks of the quarter, you should be close – roughly 99% accuracy – to your goals.
To capture and analyze your data, it’s critical to have the correct the technology and tools in place. Santa Elena says your CRM is your “single source of truth” and the best place to store your data. To drive insights and perform tasks that are actionable, you need to integrate automation and other analytic tools.
Of course, measuring the data is only half of the story. When asked how to best analyze the data and tie it to a forecast range, Santa Elena says it depends on your organization and sales process.
For example, if you have a short sales cycle, you’ll need visibility in the early stages of your sales pipeline. This means you’ll track KPIs early, beginning with first contact, and create marketing events that generate a specific number of leads for conversion so that you can collect historical data to make informed decisions.
Forecasting a shorter sales cycle
As soon as a salesperson is engaged, it should be part of your pipeline, no matter the length of your sales cycles. Why? Because, according to Santa Elena, the first engagement can easily become your next sales opportunity, and it’s easy to miss potential opportunities that will later help achieve your revenue target.
Conversely, it’s just as critical to look ahead to see what opportunities may exist and what deals you can accelerate in your pipeline, adds Heinz. It’s important to look to quarters ahead and pull any data points that will help you make more informed business decisions, and, worst-case, can be a backup opportunity in case a deal falls through.
Look to the future and pull in historic information
Remember: forecasting is iterative. As your organization grows, your business processes will evolve, so standardize your processes and implement accountability.
And, during your in-depth analysis, question what you can improve upon, what you need to change and what metrics are most meaningful to the business strategy. This allows you to further adjust and be confident in your forecast.
Constantly iterate and improve
Forecasting your way to success
Striking a balance between the art and science of forecasting doesn’t need to be complicated. In fact, successful companies use data to limit subjectivity and ensure they are implementing the right processes to drive adoption, measure KPIs and adjust as needed.
The best way to determine your forecasting model is to ensure it’s aligned with your goals. Hitting your revenue targets comes down to the fundamentals: having clear roles and responsibilities, enacting simple and understandable processes, and building systems and guardrails to support those processes.
As you build your pipelines, ensure you are measuring and analyzing the right data over the right time periods. Then, rigorously review your process and iterate your forecasting range, over and over.
Combined, this will make a huge difference in your ability to predict and hit your forecast and revenue targets.
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