Forecasts are notorious for guesswork and being difficult to predict accurately. 

Forecasting seems to require nailing just the right fine-tuned mix of adjustments to better predict the revenue you’ll bring in. But do you have tools, software and processes to help make that easier? Do you incorporate historical facts and engagement patterns from your buyers, or base forecasts solely on sales rep updates?

Stellar revenue operations is at the core of successful enterprise selling teams.

They make the tech stack work for sales reps. They put processes and resources in place for sales enablement and create the reports that give marketing, sales and success leaders the scoop on what’s working and what’s not.  Top notch revenue operations teams everywhere are analyzing and asking:

• Does this work?
• If not, why?
• How can I fix this?
• How can it be improved?

Ultimately, revenue ops gives sales leaders the information they need to forecast.They are the backbone behind the systems and processes in place—responsible for the tools that help your reps and managers validate their pipelines. 

Unfortunately, revenue ops leaders and sales leaders alike continue to find a common pitfall after working tirelessly to optimize the processes, systems and tracking of revenue generation efforts: we are still suffering from “garbage in, garbage out” in our forecasts.

Garbage in, Garbage out. 

Many technology solutions and predictive tools—usually aimed at quick wins—are aimed at helping to improve forecasting results.  While they do help streamline process, the reality is that most of these tools lack the critical insights into deals—the underpinnings of any forecast—necessary for fundamental forecast improvements. After all, most of these tools rely on your data. When is the last time you met an ops colleague who said “our deal data is clean, up-to-date and comprehensive”?   

Opportunities, pipelines, and forecasts in CRMs are far too often filled with inaccurate, incomplete and one-sided views of the deals. Changing this reality can only happen through alignment of Sales leadership and Revenue Ops.  

So, can technology fix your forecasts?

New approaches to CRM technology can play a significant role in driving change. However, without understanding your buyers engagement and your buyers perspective, technology will continue to fall short.  Simply measuring IF there’s been activity—without understanding the nature of it in relation to how your buyers buy—just isn’t enough.  You need to understand the buyers point of view. Well what if you could bring buyers’ perspective to your pipeline reviews? Think about how much that would improve forecasts. Technology with an underlying model that includes the buyers journey, and confirmation of buyer engagement using signals from actual interactions can provide visibility into the involvement of buying groups… essentially, you (and your technology) need to capture an understanding of your buyers and how they buy if you want to increase sales predictability.

When buyer-awareness falls short, we’re still relying heavily on instinct and guesswork.

A few examples of typical forecast adjustments:

• Sales Rep A is always optimistic, so you create a rule or process for adjusting her forecast
• Sales Rep B typically meets their quotas but is a sandbagger, so you adjust their forecast upwards accordingly
• Sales Rep C doesn’t know enough about what is happening in his deals, so you cautiously adjust the forecast downwards

You get the point. This handicapping is the art of forecasting—based on the people, patterns and deals we know, we can adjust the projected outcomes and try to predict what will close. This process is critical. It’s core to being a sales manager. But, the stark reality is that more than half of forecast deals don’t close. CSO Insights Sales Performance Optimization Study found that the average win rate of forecast deals was 45.8%.

If your algorithms and technologies help you hone in on the amount that’s closing, but you’re still wrong about half your deals, are you really optimizing for revenue? Are the systems really working if you’re still forecasting deals that don’t win more than half of the time? If what’s getting more predictable is that we’re better at predicting we’ll be wrong, isn’t it time to think about how to get it right?

How can you improve forecasting? 

You can potentially move the needle closer to an accurate dollar amount, but uncovering what’s really not working—gaps in buyer awareness, sales process and deal strategy—in a meaningful way can get you much further, much faster. It’s not about fixing the forecast, it’s about understanding and fixing underlying issues that are rampant in opportunity management.

You can start working with revenue ops to help collect the right data—incorporated into strategic processes—and get to work on giving sales managers and reps the insights they need to build accurate pipelines that fuel better forecasting.

Learn how to rethink opportunity management as a strategic process that supports, tracks and manages the execution of a sales process in pursuit of closing a sale.