That’s the new reality explored in this deep-dive discussion with Greg Lewis, Co-founder and President at revVana, Amy Cook, Co-founder and CMO at Fullcast, and Matthew Volm, CEO of RevOps Co-op and Eventful. Together, they unpack what it really takes to operationalize consumption forecasting—bridging the gap between bookings and revenue, between Sales and Finance, and between strategy and execution.
For an in-depth guide on consumption forecasting, check out this e-book Consumption Forecasting: How to Do it.
The subscription economy is evolving into the consumption economy. Modern SaaS companies—from AWS to Snowflake to OpenAI—don’t charge for seats, they charge for usage. That shift is fundamentally changing how revenue is planned, recognized, and forecasted.
Greg Lewis explains that traditional RevOps forecasting focuses on bookings—when deals are sold. But usage-based revenue unfolds long after the signature, and if you’re not measuring and forecasting it properly, your entire revenue plan starts to drift.
“If your revenue is variable, you have to forecast it, plan it, and target it—just like pipeline.” — Greg Lewis, Co-founder & President, revVana
The challenge: unlike subscription revenue, usage-based consumption isn’t tied neatly to contract start dates. It ebbs and flows based on customer adoption, data processing volume, or even macro events like seasonality. And because Finance still needs predictability, RevOps becomes the critical connective tissue between what Sales commits, what CS delivers, and what Finance books.
Most organizations still rely on spreadsheets as their forecasting engine. Sales leaders export data from Salesforce, apply formulas in Excel, and then email files back to Finance.
The problem?
“Spreadsheets are great for analysis, but terrible for scale. You can’t steer the ship when your visibility lags by three weeks.” — Amy Cook, Fullcast
For more on this topic, check out this whitepaper on Forecasting Complex Revenue Models.
Who owns consumption forecasting—Sales, CS, or Finance? The answer is none of them individually. Sales owns bookings, CS owns usage, and Finance owns recognition. Without RevOps orchestrating these moving parts, data silos grow—and forecast accuracy plummets.
Many companies still treat usage as “pipeline.” They add forecasted consumption into their opportunity amounts. But this inflates bookings, obscures true ARR, and muddies visibility into what’s actually realized.
RevOps needs to separate contracted value (what’s sold) from realized value (what’s consumed), so the organization can manage both acquisition and adoption as discrete metrics.
You should also check out this blog post on Metrics Every RevOps Leader Should Track (Beyond Pipeline).
Forecasting requires clarity: What does a “$1M deal” mean? Is that the committed volume, the expected ramp, or a blend of both? RevOps should create a “consumption dictionary” defining:
By documenting assumptions up front, RevOps prevents Sales from forecasting on “vibes” and gives Finance the structure to model revenue accurately.
A usage-based forecast without time alignment is meaningless. Tie expected ramps to project milestones—deployment dates, go-lives, and customer adoption timelines. If historical usage data is limited, use proxy data like industry benchmarks, customer size, or similar account patterns to model expected ramps.
“Base your forecast on what customers actually do, not what Sales hopes they’ll do.” — Amy Cook
Segmenting consumption forecasts into layers gives clarity and accountability.
Layered forecasting makes it easier to explain variance, identify risk, and focus the team on driving realized revenue, not just pipeline.
For more on identifying Upsell opportunities, check out this blog post on Finding Upsell Opportunities That Drive SaaS Growth.
Don’t let usage data live in a silo. Integrate product telemetry, billing systems, and CRM data so usage actuals automatically flow back into your forecast model. Tools like revVana can automate this, ensuring that actuals update daily instead of quarterly.
That feedback loop enables RevOps to track forecast accuracy in real time—and quickly course-correct when customers under-consume.
Forecasting consumption should be as routine as pipeline reviews.
Usage forecasting is iterative. You’ll never be 100% accurate, but tighter cadence means faster error detection and continuous improvement.
Forecasting consumption is hard enough. Incentivizing it adds another layer of complexity.
Greg recommends a tiered compensation model that balances accountability and control. AEs get credit for committed usage; CS earns accelerators for realized usage beyond baseline. Both functions share a joint “usage expansion” target to align incentives.
“If your comp plan rewards bookings, you’ll get bookings. If it rewards realization, you’ll get revenue.” — Greg Lewis
For more on this topic, check out When Sales Growth Drops, Improve Your Revenue Visibility.
For Finance, usage forecasting isn’t just about predictability—it’s about credibility.
When RevOps can forecast revenue realization with precision, it transforms quarterly guidance from guesswork into confidence. One enterprise client, Greg shared, discovered that only 50% of sold consumption ever realized, exposing a $150M gap between bookings and actual revenue.
By modeling consumption ramps and automating actuals, they cut that variance by 70%—a board-level win.
“RevOps should be the tollgate between Sales and Finance—where truth and accountability meet.” — Greg Lewis
For more on consumption based forecasting in Salesforce, check out How to Forecast Consumption-Based Revenue in Salesforce: Best Practices and Common Pitfalls.
Consumption forecasting is no longer optional. As pricing models evolve, it’s becoming a core competency for high-performing RevOps teams. It blends financial acumen, data analytics, and cross-functional orchestration—everything RevOps was built for.
“If bookings are the promise, consumption is the proof. RevOps is the bridge that keeps the two aligned.” — Amy Cook
Check out our RevOps Co-op Blog for more frameworks and expert insights.
Ready to operationalize your consumption model? Join the RevOps Co-op Community to connect with 18,000+ operators building the next generation of revenue infrastructure.
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