This is a recap of the Data Best Practices Breakout Session from Unlock Live Boston event with leaders from Motion Industries, Thomson Reuters, and Flagstar Bank
"The work is mysterious and important."
Fans of the show Severance may recognize the quote. I opened the Data Best Practices Breakout Session at Unlock Live with this line because for anyone responsible for managing incentive compensation data, it likely feels uncomfortably accurate.
It's important because as we all know, comp is usually the largest line item on an organization's budget sheet. But it's mysterious because the plans and calculations and communications around comp can be maddeningly opaque - even to the people who work on them.
Anyone working in sales compensation, sales operations, or revenue operations knows the challenge. Compensation data rarely starts out clean, centralized, or traceable. It lives across inherited systems, upstream processes no one fully owns, and, sometimes, on a sticky note attached to someone's monitor.
At Unlock Live Boston, leaders from Motion Industries, Thomson Reuters, and Flagstar Bank shared what it takes to build a data foundation teams can trust, and what happens when organizations move beyond spreadsheets, inconsistent definitions, and manual workarounds.
Here’s how they’re making things less mysterious.
For many enterprise teams, the fact that their data foundation is fragile can be demonstrated by looking at where institutional knowledge lives.
As Trisha Mitschke, Manager of Sales Effectiveness at Motion Industries, described, "Sometimes the source of truth isn't a system. It's a person. Or a sticky note."
At Motion Industries, compensation logic had become spread across spreadsheets, with different teams owning different parts of the process. Month-end firefighting had become routine. Because compensation logic lived outside governed systems, every change depended on institutional knowledge. That approach becomes harder to sustain as organizations add plans, integrate acquisitions, and support more participants.
Justin Rosenblum, Director of Commissions Transformation at Thomson Reuters, described the challenge at a larger scale. Supporting nearly 3,000 sellers means managing dozens of upstream data sources and coordinating stakeholders across multiple functions. Questions that once lived within a single team can begin crossing multiple systems and functions.
Sandra Carvalho-Maroudas, Senior Manager of Incentive Compensation and Vice President at Flagstar Bank, pointed to another decision that often creates complexity over time.
"One of the biggest things I see in immature organizations is that they build to plan versus build for scalability."
Organizations frequently design their data structures around the compensation plans they need to support today. As those plans evolve, new rules and calculations are layered onto existing logic. Over time, the system can start reflecting years of workarounds instead of the structure the business needs to support.
As Sandra put it, “Design for today's plan, and you'll likely rebuild every time the plan changes. Design for scalability, and the system can grow with you.”
Sandra Carvalho-Maroudas, Senior Manager of Incentive Compensation and Vice President at Flagstar Bank, Justin Rosenblum, Director of Commissions Transformation at Thomson Reuters, and Trisha Mitschke, Manager of Sales Effectiveness at Motion Industries at Varicent's Unlock Live Boston.
Most organizations want a single source of truth. The challenge is that different teams need different views of the same data.
Sellers want daily visibility into performance. Finance and compensation teams need month-end accuracy. Leadership wants consolidated reporting, and compliance needs auditability. None of those unreasonable.
The problem happens when no one has defined what each version represents, or who owns the handoff between them.
Motion Industries' Trisha Mitschke framed it simply, "The data isn't wrong. It's just incomplete."
Flagstar Bank’s Sandra Carvalho-Maroudas described a solution. At Flagstar, the same underlying data serves multiple business lines. Rather than duplicate datasets for each use case, Flagstar builds shared structures with standardized definitions, applied differently by each team depending on what they need to see. One foundation. Multiple views. No fragmentation.
As Thomson Reuters' Justin Rosenblum put it, “A source of truth isn’t a magical system. It's consistent definitions, clear ownership, and governance the organization actually trusts.”
Getting the number right is only part of the job. Sellers also need to understand how the number was produced.
Motion Industries' Trisha Mitschke described a situation that's familiar to most comp teams. Often the final payout number is right, but adjustments and true-ups create confusion for sellers. Even when the math is correct, when reps can’t easily understand how the result was calculated, they don’t trust it.
"When sellers don't trust the system, they build their own," Justin Rosenblum, Thomson Reuters shared.
The audience knew exactly what "their own" meant: spreadsheets. Flexible, powerful, and nearly impossible to govern across the organization. (The room laughed. Probably because it was more true than funny.)
Thomson Reuters’s Justin Rosenblum pointed out that transparency at the order level, not just the payout level, is what drives adoption. A seller who can trace the logic before payout understands outcomes, disputes less, and trusts the process.
For Flagstar Bank’s Sandra Carvalho-Maroudas, the stakes extend beyond seller confidence. In a regulated environment, trusted compensation data functions as a risk-control mechanism. Audit trails, explainable payouts, and clear ownership help ensure the organization can demonstrate how decisions were made and who is accountable for them.
There's a shift that happens once the data foundation is reliable. When teams trust the data, they spend less time validating information and more time using it to make decisions.
At Thomson Reuters, Justin Rosenblum described how compensation data evolved beyond reporting. Sellers can now see opportunity-level compensation, model different scenarios, and think strategically about where to focus before a deal closes.
"Compensation becomes a decision-support tool."
Trisha Mitschke described a different type of impact at Motion Industries when they centralized the calculations, not just the data.
"Centralizing calculations helped reduce payout risk and made it easier to integrate acquisitions without rebuilding compensation processes from scratch."
Flagstar Bank’s Sandra Carvalho-Maroudas connected having trust in the data to leadership confidence.
“When executives trust the data foundation, decisions can move faster, reconciliation often drops, and reporting can become easier to validate. The operations model scales without adding headcount.”
That’s where data best practices become business best practices.
The final discussion looked ahead to what happens as organizations grow more complex.
At Motion Industries, Trisha Mitschke manages acquisitions, multiple systems, and early conversations around AI investments. Her advice for organizations navigating the same complexity: build repeatable onboarding playbooks, respect that different systems may serve different business models, and resist forcing standardization where it hurts accuracy.
"Trust still matters more than automation."
As more organizations explore AI in comp workflows, having data teams can trust becomes more significant. AI tools can surface insights, guide sellers, and simplify complex work. But they can only do this if the data they rely on is reliable and trusted. According to Trisha, “AI makes a strong foundation stronger. A weak one, worse.”
Flagstar Bank’s Sandra Carvalho-Maroudas encouraged organizations earlier in the journey to start with discovery and focus on the highest-risk populations first. Waiting for perfect source systems or perfect conditions often delays work that becomes harder to tackle later.
Thomson Reuters’s Justin Rosenblum described a future that includes AI-enabled seller guidance, proactive insights, and more intelligent reporting across a global salesforce. The organizations best positioned for that future are the ones building the foundational work now.
Trusted revenue data isn’t a technology purchase, but an organizational capability built through governance, transparency, and intentional design.
Get the foundation right and everything built on top of it compounds. Reporting gets faster, sellers get more confident, and leaders make better decisions. AI becomes useful rather than aspirational.
And maybe, just maybe, the source of truth stops being a sticky note.