Measuring Manual Burden: The KPI Most Insurance GRC Teams Don’t Track

Most insurance GRC dashboards show findings, issues, and closure rates. Very few show the manual hours poured into chasing audit evidence, answering questionnaires, and coordinating vendor reviews across security, privacy, legal, and HR teams. For many multi-line carriers and health insurers, that invisible workload quietly adds up to the equivalent of a full headcount—or more—spread across GRC, security, and engineering. You feel it during every NYDFS or state DOI exam, every HIPAA or HITRUST cycle, and every time a major broker, reinsurer, employer group, or health system sends over another security questionnaire.

You cannot reduce what you do not measure. Treating manual burden as its own KPI is the first step toward staying continuously audit- and questionnaire-ready, instead of spinning up a new fire drill every time scrutiny ramps up.

The Most Expensive KPI You Don’t Track

A typical quarter for a multi-line carrier or health insurer includes NYDFS and other regulator exams, SOC 2 and ISO 27001 cycles, HIPAA or HITRUST assessments where PHI is in play, PCI DSS reviews anywhere cardholder data flows, and a steady stream of questionnaires from brokers, MGAs, reinsurers, hospital systems, and large employers. 

On paper, the program looks healthy: controls pass, issues close, frameworks stay in scope. Underneath, teams are rebuilding similar evidence packages for NYDFS, SOC 2, ISO 27001, PCI DSS, HIPAA/HITRUST, NAIC-aligned expectations, and GLBA in slightly different language. 

They are answering new versions of SIG, SIG Lite, CAIQ, and custom forms that ask for the same control story in different formats. They are gathering artifacts from tools like Archer and ServiceNow, reviewing them, and manually re-entering data into spreadsheets or GRC systems every cycle.

None of that effort shows up in standard KPIs. Dashboards highlight findings closed and frameworks in scope, but they do not show the weeks lost to spreadsheet-driven audit prep, inbox-based routing, and questionnaire backlogs. That gap is the manual compliance tax most insurers underestimate.

What Manual Burden Looks Like in Multi-Line and Health Insurance

Manual burden tends to cluster around a few recurring patterns. Evidence collection becomes a recurring fire drill: even mature programs end up chasing screenshots, exports, tickets, and access reviews, pushing last-minute policy updates, and tracking down attestations whenever an exam or audit kicks off. In property and casualty and multi-line businesses, teams must show how the same operational reality maps to NYDFS, PCI DSS, SOC 2, ISO 27001, NAIC-aligned expectations, and sometimes HIPAA where claim workflows touch medical information. In health insurance, HIPAA and HITRUST sit alongside SOC 2, ISO 27001, PCI DSS, and state requirements, each with its own structure and language. Frameworks differ, but the control families overlap heavily—the time sink is repackaging proof over and over, not doing the underlying security work.

Questionnaire overload is its own source of drag. Property and casualty carriers, multi-line insurers, and brokers describe a flood of SIG, CAIQ, RFP/RFI sets, and bespoke “security” questionnaires—many poorly formed or duplicative. Health plans and managed care organizations face high-volume third-party assessments with explicit expectations like “done in a week,” while those same questionnaires routinely pull in privacy, legal, and HR question sets that land on the security team’s desk by default. Intake is often tracked in spreadsheets, routed manually via email, and coordinated through ad-hoc follow-ups. The result is constant follow-up churn, cross-functional sprawl, and a growing backlog that competes with core risk work.

Third-party artifact handling adds another layer. Many insurers still collect documents from vendors, review them one by one, then manually re-enter details into a GRC system. Teams describe the “collect → review → re-enter” loop as a permanent tax they pay every cycle. On top of that, NDA gates, group rules, and contract or renewal windows are enforced through email chains and shared folders instead of governed access windows. A renewal delay can mean outdated access persists, or staff must manually track extensions to avoid overexposure. None of this is captured as a KPI, but it quietly drains capacity and introduces access risk.

Turning Manual Effort Into a Measurable KPI

You do not need a new tool to start measuring manual burden. You can get a credible baseline using systems already in place. The first step is to inventory recurring evidence and assessment work: the artifacts you produce for each NYDFS exam, each SOC 2 or ISO 27001 cycle, every HIPAA or HITRUST assessment, every PCI DSS review, and the materials you assemble repeatedly for major questionnaires, BAAs, and vendor due diligence. Focus on work that recurs quarterly, annually, or with each exam or assessment, not one-off projects.

Next, capture effort for one full cycle. You can use time-tracking fields, timestamps, or simple logs in Jira, ServiceNow, Asana, or your GRC platform to approximate how long teams spend on preparation, collection, formatting, and review for each evidence type and assessment. Preparation includes scoping systems, lines of business, and environments. Collection covers pulling data from cloud platforms, core policy and health systems, ticketing tools, and HR. Formatting encompasses mapping output to NYDFS, SOC 2, PCI DSS, HIPAA/HITRUST, NAIC, or internal templates. Review time reflects back-and-forth between control owners, GRC, security, legal, and privacy before anything is approved to leave your environment.

Once you have data for a cycle, annualize it by framework and counterparty. Multiply the effort associated with a given artifact by how often you produce it: quarterly samples for SOC 2, annual ISO 27001 and NAIC-aligned updates, HIPAA or HITRUST assessments, periodic NYDFS exams, and recurring partner and provider reviews. Add reviewer and coordination time—hours spent by SMEs and leaders clarifying, reworking, and approving evidence sets. Finally, convert those hours into cost by applying fully loaded rates, and compare the result to work that is currently crowded out: deeper vendor risk reviews, control improvements, new state filings, new product launches, or network expansion. That roll-up is your manual burden KPI: a simple but defensible view of how much labor and budget goes to staying afloat on evidence and questionnaires.

KPIs That Make Manual Burden Visible

Total manual evidence hours are the anchor, but a few additional metrics make the operational picture clear. One is mean time to evidence approval: the elapsed time from an evidence request—whether it comes from an exam, an audit, a questionnaire, or an internal control check—to final approval and delivery. When evidence is standardized and automated, simple requests move in a day or two. In manual programs, straightforward asks can stretch into a week or more as ownership questions, routing delays, and rework pile up.

Evidence reuse rate is another revealing indicator. It reflects the percentage of artifacts that can be reused across frameworks and counterparties without new collection or heavy reformatting. Low reuse rates suggest each framework or questionnaire is treated as a standalone project. Higher reuse rates indicate you have mapped core control families once and are using common evidence sets—such as an Insurance Trust Pack or Health Trust Pack—to serve many audiences, with controlled, permissioned access instead of bespoke bundles each time.

It is also useful to look at the percentage of supplemental evidence requests per exam or audit. A high volume of follow-up requests relative to the initial submission often signals fragmented, manual workflows where regulators, auditors, or partners must keep asking for missing context, updated versions, or clearer mappings. Lower supplemental rates indicate the base packages are complete, consistent, and easy to navigate. Finally, questionnaire and assessment efficiency brings attention to the treadmill many insurance teams are on: high volumes of SIG, CAIQ, insurer-specific forms, and health-system assessments; aggressive internal expectations such as “done in a week”; and cross-functional question sets that slow routing and review. Tracking average turnaround time, the portion of answers drafted from approved content, and SLA attainment for assessments helps quantify how much capacity is tied up in this work.

How Automation Changes the Manual Burden KPI

Manual evidence collection and email-driven sharing keep insurers locked in point-in-time cycles. Property and casualty carriers and multi-line insurers describe every audit season as an audit fire drill, where teams drop everything to chase screenshots, exports, and access reviews. Health plans talk about HIPAA and HITRUST cycles that feel like spinning up an “audit war room” every time, with weeks spent chasing artifacts across spreadsheets, tickets, and email threads. In both cases, the “collect → review → re-enter” artifact loop repeats for each exam, each assessment, and each major partner review.

Continuous, automated compliance changes the operating model. By connecting directly to cloud platforms, identity providers, endpoint tools, HR systems, ticketing workflows, and core policy and health systems, Drata continuously validates controls and collects evidence in the background instead of in screenshot sprints. Evidence stays tied to specific controls in a single system of record, with clear owners and a test cadence, rather than scattered across inboxes and shared folders. Control families are mapped once to NYDFS, NAIC-aligned expectations, SOC 2, ISO 27001, PCI DSS, HIPAA/HITRUST, and state-level requirements, so proof is reused instead of rebuilt.

A Trust Center provides a governed destination for commonly requested artifacts, where access is permissioned, time-boxed, and aligned to NDA and contract rules rather than controlled through email chains. Insurance organizations can publish what third parties ask for most—SOC 2 reports, policy sets, incident and DR/BCP summaries, access-management and vulnerability-management overviews—and share them through account-based, renewal-aware access windows. Health insurers can give hospitals, networks, and digital health vendors self-serve access to materials under NDA and contract constraints while reducing access creep.

AI Questionnaire Assistance then sits on top of this evidence and control spine. It uses information already stored in Drata—mapped controls, current evidence, and approved narratives—to draft responses to SIG, CAIQ, and custom questionnaires, so teams only handle questions that are not yet mapped or that genuinely require deeper judgment. Insurance buyers explicitly expect an AI questionnaire assistant to work this way: grounded in existing compliance content, not generic answers. Across carriers and health plans, this combination of automated evidence, cross-framework mapping, governed sharing, and AI-assisted questionnaires is how teams report eliminating up to 90 percent of manual compliance work tied to audits and assessments, reclaiming hundreds of hours a year on security reviews, and cutting security review cycles by days or weeks—without adding headcount.

FAQs: Manual Burden KPIs for Insurance GRC

How often should we measure manual burden?

Monthly measurement is usually enough to catch trends without adding significant overhead. Many insurers then use quarterly reviews to recalculate fully loaded costs and decide which frameworks, evidence types, or lines of business to automate next, based on where demand is growing or where pressure from regulators and partners is highest.

What if we do not have formal time tracking today?

You can begin with proxy data you already have. Ticket systems, workflow tools, and GRC platforms capture timestamps and assignees for request, assignment, and completion. Calendar data around exam prep, audit cycles, and assessment reviews can help estimate effort for a first pass. Even rough baselines for one or two cycles are more useful than guesses and can be refined as you introduce more structured tracking.

Will auditors and regulators accept automated evidence?

In practice, auditors and examiners often prefer evidence that comes directly from authoritative systems and includes complete, timestamped histories with clear ownership. What matters is that you can show how automated checks map to their requirements, how exceptions are handled, and how sampling works. Continuous collection and monitoring make those stories easier to tell and support requests for more targeted testing when controls are well instrumented.

Does manual-burden measurement apply to privacy and data-protection work too?

Yes. Data inventories, processing records, data-subject request logs, DPIAs, vendor agreements, and consent mechanisms all require recurring proof. Insurers operating across regions and product lines face similar duplication and rework here as they do in security frameworks. Tracking hours, approval times, and reuse rates for these artifacts will highlight where privacy work is caught in the same manual loops as security evidence, and where automation and standardization could have the most impact.

Where should we focus automation first once we have the KPI?

Most multi-line carriers and health insurers see early wins by targeting high-volume, high-churn areas. That typically means automating evidence collection for access, vulnerability, backup, and DR controls; standardizing intake and routing for assessments so requests move to the right owners without inbox triage; reusing approved answers for common questionnaire questions; and replacing email-based sharing with a Trust Center that enforces NDA and contract windows by design. These moves directly reduce manual hours and improve supporting KPIs like mean time to approval, evidence reuse rates, supplemental request rates, and assessment SLA attainment.

If you are ready to turn manual evidence collection from an invisible tax into a measurable, reducible KPI—and free your insurance GRC teams to focus on strategic risk and growth—you can see how peer carriers and health insurers are doing it with Drata. Request a demo to get started.