In most SaaS companies, there’s a critical dependency that often goes unexamined: Finance relies heavily on usage data that lives in Engineering’s domain. Whether it’s consumption metrics for usage-based pricing, seat counts for subscription management, or feature adoption data for revenue recognition, the numbers that drive financial reporting and forecasting originate from engineering systems.
When these systems change without proper controls, the consequences ripple through the organization. A seemingly innocuous code deployment might alter how usage is calculated. A database migration could introduce data gaps. A new logging framework might change metric definitions. For Finance, these changes can mean restated revenues, missed forecasts, or compliance issues.
The Hidden Risk in Engineering Changes
Engineering teams move fast—that’s their job. Continuous deployment, agile methodologies, and rapid iteration are the backbone of competitive SaaS development. But when usage data feeds financial processes, speed without controls creates risk.
Consider these common scenarios:
A backend engineer refactors the event tracking system to improve performance, inadvertently changing how “active users” are counted. Finance discovers the discrepancy three weeks later when monthly recurring revenue calculations don’t reconcile.
The data warehouse team updates their ETL pipeline, and a transformation logic change affects how product usage tiers are calculated. Customer invoices go out with incorrect amounts.
An API endpoint that Finance’s billing system depends on gets deprecated without notice, causing a revenue recognition delay at quarter-end.
These aren’t hypothetical situations—they happen regularly in growing SaaS companies that haven’t established proper change management controls.
Building a Control Framework
Effective change management doesn’t mean slowing down Engineering. It means building guardrails that protect data integrity while maintaining development velocity.
Identify Critical Data Assets
Start by mapping which engineering systems and data flows directly impact financial processes. This includes usage tracking systems, billing APIs, customer databases, and analytics pipelines. Work with Finance to understand exactly which metrics they rely on—not just for reporting, but for revenue recognition, forecasting, and compliance.
Create a formal inventory of these critical data assets. Document the business processes they support, the teams that depend on them, and the regulatory implications if they change unexpectedly.
Establish Clear Ownership and Communication Channels
Someone needs to own the intersection of engineering data and financial reporting. In smaller companies, this might be a senior engineer who partners closely with the finance lead. In larger organizations, it could be a dedicated data governance team or a financial systems manager.
Whatever the structure, establish clear communication protocols. Engineering teams should know who to contact when changes might affect financial data. Finance should have a designated technical liaison who understands engineering workflows and can translate business requirements into technical specifications.
Implement Change Request Processes
For changes to critical data systems, require a lightweight but formal change request process. This doesn’t need to be bureaucratic—a simple form or ticket that captures the change description, affected systems, potential impact on financial data, and planned testing approach.
The key is visibility. Finance should be notified of proposed changes with enough lead time to assess impact and adjust downstream processes if needed. For high-risk changes, require explicit sign-off from both Engineering and Finance leadership.
Create Testing Requirements
Before changes to critical data systems go to production, validate that financial calculations remain consistent. This might include automated regression tests that compare pre-change and post-change metric calculations, reconciliation checks between source systems and financial reports, or sample invoice generation to verify billing accuracy.
Build these validations into your deployment pipeline where possible. The earlier you catch data integrity issues, the less expensive they are to fix.
Document Everything
Maintain comprehensive documentation of how usage data flows from source systems to financial reports. When changes occur, update this documentation immediately. Include data definitions, calculation methodologies, system dependencies, and change history.
This documentation serves multiple purposes: it helps new team members understand the landscape, supports audit and compliance requirements, and provides a reference point when troubleshooting discrepancies.
Making It Practical
The best control frameworks are the ones teams actually use. Here’s how to make change management practical rather than burdensome:
Start small. Pick one critical data flow—perhaps your primary usage metric for billing—and implement controls there first. Learn what works, refine the process, then expand to other areas.
Automate where possible. Use automated testing, monitoring, and alerting to catch issues without manual intervention. Build dashboards that Finance can check independently to validate data consistency.
Make it part of the culture. Help Engineering understand why these controls matter. Share examples of what can go wrong. Celebrate when the process catches issues before they impact customers or financial statements.
Keep it lightweight. The process should add days of lead time, not weeks. Use templates, checklists, and standardized approval workflows to minimize overhead.
The Payoff
When done right, change management controls create benefits beyond risk reduction:
Finance can trust the data they’re using for critical decisions. Engineering can deploy with confidence, knowing they won’t inadvertently break financial processes. The company reduces audit risk and compliance overhead. Customer billing becomes more reliable and disputes decrease.
Most importantly, Engineering and Finance develop a collaborative relationship built on mutual understanding rather than reactive firefighting.
Getting Started
If your SaaS company doesn’t have formal change management controls around usage data, start the conversation today. Bring Engineering and Finance leadership together to discuss current pain points and near-misses. Map your critical data dependencies. Then implement one control—perhaps a notification requirement for changes to your billing system—and build from there.
The goal isn’t perfection from day one. It’s creating a foundation of visibility, communication, and shared accountability that scales as your company grows. In the fast-moving world of SaaS, that foundation might be your most important infrastructure investment.
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About Herod CPA PLLC
Herod CPA PLLC helps SaaS founders and operators design, implement and assess internal controls that impact their key metrics.
Contact us at info@herod.cpa or follow us on LinkedIn for more information.