From System of Record to System of Evidence: The Next Competitive Advantage in Vertical Software

Executive Summary:

Competitive advantage in vertical software is increasingly driven by ownership of proprietary data and evidence that supports reimbursement, compliance, and operational decisions. This shift transforms software platforms from mere systems of record into systems of evidence embedded across multiple stakeholders in the ecosystem.

The Shift: How Competitive Advantage Is Evolving

Across a growing number of vertical software markets, competitive advantage is increasingly shifting toward ownership of data and evidence that underpins reimbursement, compliance, and operational decision-making. 

Across service-based industries such as auto repair/collision, property restoration, and field service/facilities management (among others), software increasingly sits at the intersection of work performed, work validated, and work reimbursed. The most strategic platforms no longer simply manage workflows, but instead are generating evidence that insurers, payors, regulators, and other risk-bearing entities rely upon to make decisions. 

As insurers, payors, and other risk-bearing entities demand greater documentation, auditability, and outcome validation, software platforms are evolving from systems of record into systems of evidence. The combination of first-party workflow data, AI-enabled decisioning, and ecosystem influence is creating a form of competitive advantage that traditional software diligence frameworks often underappreciate. 

Forces Reshaping Competitive Advantage: 

Throughout our engagements at Grant Thornton Stax, we’ve observed several forces driving software markets: 

• Documentation Has Become a Strategic Asset: Documentation has become a core component of value creation. In many verticals, the ability to prove that work was completed (and completed correctly) and to provide a standardized record of that work has become as important as performing the work itself. Documentation drives reimbursement, supports compliance, enables automation, trains AI and creates defensibility. 

• First-Party Workflow Data Creates Durable Advantage: Durable software assets increasingly generate proprietary datasets through day-to-day workflow participation. The greatest value comes from data that is difficult to replicate, standardized across customers, and directly linked to operational outcomes. 

• AI Amplifies the Value of Proprietary Data: The emergence of AI has amplified the importance of first-party workflow data. While AI capabilities are becoming increasingly accessible, the underlying data required to train, refine, and validate those models remains highly differentiated. The competitive advantage therefore shifts from access to AI models themselves toward ownership of unique workflow data and closed feedback loops that continuously improve model performance. 

• Platform Power Shifts Beyond the Operator: Historically, platforms focused on the operator performing the work. The most influential platforms are increasingly creating value for multiple stakeholders simultaneously. Insurers, payors, TPAs, regulators, OEMs, and compliance organizations all depend on information generated within operational workflows. Software that facilitates decisions across these stakeholders becomes increasingly embedded in the broader ecosystem. As platforms become embedded in reimbursement, authorization, compliance, and risk management, their strategic importance expands beyond the direct customer relationship. 

• Ecosystem Alignment Creates Flywheel Effects: Platforms embedded within insurer and payor workflows benefit from reinforcing adoption dynamics. As documentation standards become standardized and reporting becomes embedded within downstream workflows, insurers increasingly influence software selection. Over time, software purchasing decisions become driven not only by operators, but also by the organizations that rely on the evidence those platforms generate. 

What This Means for Investors:

For investors, this changes the diligence lens. The primary questions shouldn’t only be about whether or not a platform is sticky, but whether its data compounds in value as usage scales, whether third parties increasingly rely on that data, and whether that reliance strengthens pricing power, retention, and long-term competitive positioning. 

• Reframe the Source of Competitive Advantage: Traditional sources of defensibility (switching costs, platform stickiness, integration depth) remain important. Investors should also evaluate the quality, uniqueness, scalability, and strategic importance of the first-party data generated within the platform. 
• Evaluate Ecosystem Position: Software influence extends beyond the direct customer relationship. The closer a platform sits to reimbursement, authorization, compliance, or risk decisions, the more strategically important it becomes. 
• Evaluate Data Fly-Wheels: The strongest platforms connect workflow inputs to downstream decisions and outcomes, creating feedback loops that continuously improve automation, AI performance, and customer value. 



Together, these dynamics can provide a more complete view of long-term competitive positioning and value creation potential.

Questions Diligence Should Explore:

• Who controls/influences adoption: The operator, the economic buyer, or downstream stakeholders such as insurers, payors, regulators, etc.? 
• What proprietary data is being created, and how difficult is it to replicate? 
• Is there a data flywheel; does more data improve outcomes? 
• Does the platform create measurable value for multiple stakeholders across the ecosystem? 
• What data advantage underpins current and future AI capabilities? 

The Bottom Line:

For private equity investors, understanding who controls that data/evidence, and how it compounds over time, may become as important as understanding the workflow itself. To learn more about the value of data and workflows, visit our Insights page or click here to contact us directly.