Aligning Claims QA with 2026 Financial & Individual Goals

I've spent the better part of my career in and around contact centers and operations, and one of the most persistent frustrations I hear from claims leaders is this: "We have a lot of quality data. We just don't know what to do with it."

It's a fair observation. Most organizations build a quality assurance program, train reviewers, and start scoring claims files — but the data lives in a spreadsheet, a siloed platform, or a dusty folder that nobody opens between quarterly reviews. That's not a quality program. That's a compliance checkbox.

What I believe — and what we see working with leading insurance organizations — is that claims QA data is one of the most underutilized performance assets in your organization. When you align it properly with individual contributor goals and organizational financial targets, something powerful happens: quality stops being an audit function and starts being a growth engine.

The Disconnect Between QA Scores and Business Outcomes

Here's a question worth sitting with: if your adjusters improved their average quality score by 15 points this year, would your finance team notice? Would your claims leadership team be able to trace that improvement to a reduction in leakage, faster cycle times, or lower litigation costs?

For most organizations, the honest answer is no — not because the connection doesn't exist, but because the data pipeline was never built. Quality data sits in one system, financial data in another, and individual performance metrics in a third. Nobody has drawn the lines.

This is the problem worth solving heading into 2026. The technology now exists to operationalize quality data in a way that creates a clear, visible thread from an individual adjuster's daily work all the way up to the organization's financial goals. C2Perform's quality assurance tools are designed specifically to support this kind of data flow — not just scoring, but turning those scores into meaningful performance actions across the organization.

Building the QA Data Hierarchy

Think of claims quality data in three tiers:

• Individual contributor level: How did this adjuster or underwriter perform against defined quality criteria on their specific files this week? What did they get credit for, and where did they fall short?
• Department level: What are the quality trends across the claims unit? Are certain file types, coverage lines, or new hires driving aggregate score declines? Where are the coaching opportunities?
• Organizational level: How does quality performance correlate with financial KPIs — claims leakage, litigation rates, reserve accuracy, customer retention, and cycle time?

When these three levels are connected, you've built something rare: a claims quality program that speaks the language of the boardroom. VP-level claims leaders can walk into a budget conversation with evidence, not anecdotes.

"Quality data should flow upward — from the individual adjuster to the department to the executive suite — and inform decisions at every level."

Why Individual Goal Alignment Is the Missing Link

Here's something I've observed consistently: when an adjuster or underwriter understands exactly how their daily work connects to what they're being evaluated on — and ultimately to how their organization performs — engagement goes up. It sounds almost too simple, but it's true.

The problem is that most QA programs deliver a score. They rarely deliver context. An adjuster might see that they scored a 78 on their last file review, but they don't know which specific behaviors drove that score, how that compares to their peers, how it's trending over time, or what the path to improvement looks like.

Individual goal alignment changes this. It means:

• Each contributor has defined quality performance targets that roll up into team and organizational goals.
• Quality scores are reviewed in regular cadences — not just annually during a performance review.
• Improvement is tied to specific, actionable coaching rather than vague feedback like "needs improvement on coverage analysis."

This is where Dynamic Coaching becomes a critical part of the equation. When quality reviews automatically trigger structured coaching conversations — grounded in the actual behaviors assessed — adjusters get real-time, meaningful feedback that they can act on. Not six months later. Now.

Monthly, Quarterly, and Annual Visibility for Claims Leaders

One of the most impactful things a VP of Claims can do is establish a regular QA reporting cadence that surfaces the right data at the right time. Here's what that can look like:

Monthly

At the individual level, adjusters and underwriters review their quality scores against their personal targets. Where are they trending? Are there specific file types or coverage areas that consistently pull their scores down? This is the conversation that the frontline leader and the employee have together — supported by data, not driven by gut feel.

Quarterly

Department leaders roll up individual performance into team-wide quality trends. This is where you start to see systemic issues — a coverage change that nobody communicated clearly, a new product line that didn't get adequate training support, or a category of claims where root cause analysis reveals a consistent knowledge gap. This level of insight drives decisions about training, process improvement, and resource allocation.

Annually

The organization looks at how quality performance correlates with the financial KPIs that matter most. Did improved quality scores this year correspond to a reduction in claims leakage? Did lower error rates in underwriting translate into better loss ratios? This is the data that makes the case for sustained investment in quality programs.

Platforms like C2Perform's connected quality assurance tools are built to support this kind of multi-level visibility, giving leaders dashboards that matter — not just score reports.

Operationalizing QA Data: Beyond the Score

I want to be clear about something, because I think there's a tendency in this space to conflate "quality assurance" with "automated scoring." Scoring is a means to an end, not the end itself.

The real value in claims QA isn't the score — it's what you do with it. When an adjuster misses credit on a coverage analysis attribute, the question isn't just "what was the score?" It's: "What happened? Was it a knowledge gap? A process gap? A training gap? And what do we do about it now?"

That's operationalizing QA data. It means connecting a quality finding to a specific coaching action, an eLearning assignment through your Learning Management tools, or a refresher piece of content surfaced through a Knowledge Management system. The score is the trigger. The improvement is the goal.

Getting Started: Three Questions for Claims Leaders

If you're evaluating how well your current QA program aligns with your 2026 financial and individual goals, here are three questions worth asking:

1. Can every adjuster and underwriter articulate what quality standard they're being held to and how their score is trending? If not, the program isn't driving the behavior change you need.
2. Does your claims leadership team receive regular, actionable quality trend data — not just score summaries? The difference between data and insight matters enormously at the VP level.
3. Is there a direct line from a QA finding to a coaching conversation, a learning assignment, or a process change? If quality data isn't triggering action, it's not working hard enough for you.

These aren't easy questions, but they're the right ones. And the organizations getting the most out of their quality programs in 2026 are the ones asking — and answering — them systematically.

If you're ready to move beyond the score and start building a quality program that connects individual performance to organizational outcomes, explore how C2Perform's quality assurance tools are helping insurance claims and underwriting teams do exactly that.