A Quick Hello — Why We’re Talking

• In one sentence, what prompted you to explore a new claims platform right now?
• How many claims do you handle annually (all lines combined)? Options: <50k, 50k–200k, 200k–500k, 500k–1M, 1M–3M, 3M+
• Which lines of business should this initiative cover? Options: Personal Auto, Homeowners, Commercial Property, General Liability, Commercial Auto, Specialty/Other
• Which executive sponsors and business partners are already aligned behind this effort?
• If we could make one thing immediately easier for your team, what would that be?

Who’s Really Holding the Keys?

• What would it look like if decision-making on this project keeps getting in the way of progress?
• Who are the formal decision-makers (by role) and who has informal veto influence? Options: VP Claims, CIO/CTO, CFO, Chief Claims Officer, Transformation Office, Legal/Compliance, Procurement, Other
• What timelines are non-negotiable—regulatory deadlines, board milestones, or transformation windows? Options: Immediate (0–3 months), Short (3–6 months), Quarterly (6–12 months), Annual (12+ months), Flexible/Undetermined
• Which constraints would cause the project to pause or be re-scoped (budget, data risk, integration complexity, resource availability)? Options: Budget, Data migration risk, Integration complexity, Internal resource limits, Regulatory constraints, Vendor SLAs, Other
• How confident are you that the right stakeholders are at the table to make timely trade-offs? Options: Completely confident, Mostly confident, Unsure, Not confident

Where the System Feels Like a Leak

• When claims break or slow down today, what usually breaks first—and why does that matter to your customers or regulators?
• Can you describe one or two recent incidents where the legacy system caused measurable harm (compliance breach, payment delay, lost subrogation)?
• How often do these failure modes occur? Options: Daily, Weekly, Monthly, Quarterly, Rarely
• What manual workarounds do teams run today to keep claims moving? Options: Spreadsheets/manual reconciliation, Email/human approvals, Temporary system patches, External vendor workarounds, None/other
• If you had to rank the top three root causes (technology, process, people, data), what would they be and why?

If You Could Snap Your Fingers

• If you could cut one key metric in half overnight, which would it be and what would that mean to the business? Options: Cycle time (FNOL to close), Loss Adjustment Expense (LAE), Claims leakage/subrogation loss, Regulatory reporting lag/errors, Customer satisfaction
• What specific numeric targets would make this project a clear success for you (e.g., cycle time from X days to Y days; LAE reduced by Z%)?
• What are the non-negotiable acceptance criteria for a go-live (data fidelity, regulatory reporting, SLA thresholds)? Options: Complete historical claims migration, Regulatory report parity, End-to-end payment accuracy, UAT sign-off from claims ops, Performance SLA met
• How will different stakeholders (claims leadership, finance, compliance, IT) recognize success differently? Give one concrete example per stakeholder.
• What timeline for realizing business outcomes feels realistic versus aspirational? Options: 0–6 months, 6–12 months, 12–24 months, 24+ months

What Keeps Your Regulators Awake?

• If a regulator asked you to prove claims handling integrity tomorrow, where would you struggle to provide evidence?
• Which states or jurisdictions drive the most complex reporting requirements for you? Options: California, New York, Texas, Florida, Illinois, Multiple states, Other
• Have you faced regulatory findings or fines related to claims in the past five years? If yes, what were the causes? Options: Yes—data/reporting, Yes—timeliness, Yes—substantive handling, No, Prefer not to say
• What level of regulatory test coverage and sign-off will you require before cutover? Options: Full parallel reporting validation, Sampling-based validation, Post-cutover remediation allowed, Undecided
• Emotionally, what would regulatory compliance confidence allow your leadership team to do differently?

How Messy Is the Data Under the Hood?

• If your legacy data were a room, how cluttered would it be—organized chaos or overflowing storage? Options: Organized with known gaps, Significant inconsistencies, Highly fragmented and messy, Unknown until inspected
• Which core systems and data repositories will feed claims (legacy claims, policy admin, billing, payments, imaging, vendor portals)? List names where possible.
• Approximately how many historical claims records do you expect to migrate, and over what date range? Options: <50k, 50k–200k, 200k–1M, 1M–3M, 3M+
• Describe the quality issues you expect (duplicate records, missing fields, inconsistent coding) and which ones keep you up at night.
• Are you open to a phased history migration (e.g., critical recent years first) or does compliance require full historical parity at cutover? Options: Phased migration OK, Full history required, Hybrid—critical cohorts only, Undecided

Can This Fit With Your Existing Ecosystem?

• If integrations were the nervous system, where are the nerves most fragile—and what happens when they twitch?
• Which systems require real-time integration versus batch transfer (policy admin, billing, payments, imaging, vendor management)? Options: Real-time, Batch, Both, Unknown
• Do you have existing API standards or middleware we must conform to? If so, which ones?
• Who are the external vendors or clearinghouses we must coordinate with (e.g., payment processors, body shops, geo-imaging providers)?
• What SLAs or uptime requirements are mandatory for integrations on day one? Options: 99.9%+, 99%–99.9%, 95%–99%, Other/unspecified

Who Will Operate It Day‑to‑Day?

• Who in your organization will own operations, configuration, and product decisions after go‑live? Options: Claims Ops, IT/Applications, Shared ops (Claims+IT), Third‑party managed service, Undecided
• Which teams will need training and how do they prefer to learn (classroom, hands-on sandboxes, train-the-trainer, recorded)? Options: Classroom/onsite, Hands-on sandbox, Train-the-trainer, Recorded micro‑learning, Blended approach
• Where do you expect the strongest internal resistance to change—adjusters, managers, IT, or vendors—and why?
• What is your appetite for ongoing managed services vs in-house run (support tiers, upgrades, incident response)? Options: Fully in-house, Hybrid (managed upgrades + in-house ops), Mostly managed service, Undecided
• Describe one internal success you can point to where teams adopted a new tool well—what helped that succeed?

Where Are We Comfortable Rolling Back?

• If the first cutover phase encounters critical issues, what would an acceptable rollback look like to you?
• Which milestones must be green before progressing to the next phase (data validation, regulatory sign-off, integration smoke tests)? Options: Data validation, Regulatory reporting parity, Integration smoke tests, User acceptance, Performance benchmarks
• What contingency budget, timeline padding, or executive approvals are available if migration effort grows unexpectedly? Options: Contingency budget approved, Timeline buffer available, Executive escalation path only, None/unknown
• How should we structure governance and meeting cadence to ensure timely decisions during cutover? Options: Daily war room, Weekly steering committee, Ad-hoc escalation, Combination
• What legal or commercial terms would you insist on to mitigate your migration risk (liquidated damages, acceptance gates, rollback clauses)?

What Will Make This a Win You’ll Celebrate?

• Beyond metrics, what anecdote or change would make leadership say ‘that was worth it’ six months after go‑live?
• Which KPIs do you want visible on day one, and who needs to see them (claims leaders, finance, board)? Options: Cycle time dashboards, LAE trends, Regulatory reporting status, Customer NPS, Operational backlog
• How do you want to capture lessons learned and convert them into product backlog items post-launch? Options: Shared ticketing backlog, Quarterly retrospective, Dedicated enhancement board, Other
• What ongoing channel would you prefer for raising production issues or enhancement requests (Slack, ticketing, weekly call)? Options: Dedicated Slack/Teams channel, ITSM ticketing system, Weekly sync call, Email and escalation matrix
• If we deliver the agreed outcomes, what would you be willing to commit to publicly (reference, case study, joint webinar)? Options: Referenceable customer, Private case study, Co-marketing (webinar), No public commitment

Starting Here: Tell Us About Your Claims System

• In one sentence, how would you describe your current claims system to someone on the executive team?
• Which core platform(s) power claims operations today? Options: In-house legacy system, Vendor commercial off-the-shelf (COTS), Mainframe-based solution (COBOL/IMS/VSAM), Cloud-hosted modern platform, Hybrid (mix of legacy + cloud), Other (please specify)
• Which lines of business does the system actively support right now? Options: Personal Auto, Commercial Auto, Homeowners, General Liability, Commercial Property, Workers’ Comp, Specialty lines, Other (please specify)
• Roughly how many new claims do you process per year through this system? Options: <10k, 10k–50k, 50k–200k, 200k–500k, 500k–1M, >1M, Unsure / varies
• Who are the primary internal stakeholders responsible for this system (role or team names)?

Why Has 'Good Enough' Stayed Good Enough?

• What operational or regulatory risks are you knowingly tolerating by continuing with the current architecture?
• Which failure modes have you normalized—issues you expect but don’t escalate? Options: Batch delays, Duplicate claims, Lost attachments/images, Incorrect reserves, Integration timeouts, Manual reconciliation, Regulatory reporting gaps, Other (please specify)
• How often do these normalized failures materially affect customers, regulators, or financials? Options: Daily, Weekly, Monthly, Quarterly, Rarely, Unsure
• Tell us about a recent incident that surprised leadership—what happened and what was the business impact?
• Which internal KPIs or costs are most sensitive to these tolerances (select up to three)? Options: Cycle time (FNOL→closure), Loss Adjustment Expense (LAE), Regulatory fines/penalties, Customer satisfaction (NPS/CSAT), Operational headcount, Reinsurance reporting accuracy, Other (please specify)

Follow the Paper Trail: How Data Actually Moves

• Can you trace the lifecycle of a single claim—end to end—from intake to payment—without manual stitching? Options: Yes, reliably, Mostly, with caveats, Only after manual effort, No, not at all, Unsure
• Which systems feed or receive claims data in your environment? (pick all that apply) Options: Policy admin, Billing, Payments/ERP, Catastrophe modeling, Triage/telemetry, Subrogation systems, Third-party adjuster portals, Regulatory reporting engine, Data lake / analytics warehouse, Other (please specify)
• How are batch and real-time data flows handled today? Options: Primarily batch (nightly), Mixed batch + near-real-time, Mostly real-time/event-driven, Ad hoc file drops/API calls, Other (please specify)
• Who owns data quality and lineage for claims (team/title)? How do they validate integrity?
• Where historical claims live and how accessible are they for queries and conversion testing? Options: Relational DB (on-prem), Mainframe storage, Archived flat files, Cloud object store, Hybrid archive, Other (please specify)
• If we asked for a sample claim dataset and its lineage documentation for testing, how quickly could you provide it? Options: Within days, 1–2 weeks, A month, Longer, Not available / unknown

Where Integrations Break: Pain Points That Don’t Get Solved

• Which integration gaps cause the most hidden operational work—those you feel but rarely see fixed?
• Which specific integration endpoints are most fragile or high-risk (choose all that apply)? Options: Policy effective/coverage lookup, Billing status and cancellations, Payment disbursements, Third-party vendor scheduling, Medical records / PII exchanges, Fraud detection feeds, Regulatory report feeds, Other (please specify)
• What are your SLA/expectations for integrations (latency, success rate)? How often are those SLAs missed? Options: SLA: real-time / <1s, SLA: near-real-time / <1m, SLA: batch within X hours, No formal SLAs, Unsure
• Describe any manual reconciliation or workaround processes that run because an integration fails. How much FTE time does this consume weekly?
• Do you have monitoring, tracing, and automated alerts for integration failures today? Options: Comprehensive monitoring, Partial / some integrations monitored, Basic alerts only, No monitoring, Unsure

Compliance Under Pressure: What Keeps You Up at Night

• If a regulator asked for a complete audit trail for any random claim tomorrow, how confident are you in producing it quickly and defensibly? Options: Highly confident, Mostly confident with caveats, Low confidence, Not possible, Unsure
• Which regulatory regimes or state-specific rules are most difficult to satisfy with your current system? Options: State-specific reporting, Time-to-payment statutes, Privacy / data residency, Subrogation reporting, Reinsurance reporting, Catastrophe modeling requirements, Other (please specify)
• When was the last regulatory test or audit related to claims, and what were the key findings?
• Which reporting processes are manual, and how long do they take each reporting cycle?
• How do you currently validate regulatory report accuracy before submission? Options: Automated validation, Manual review, Hybrid automated + manual, No formal validation, Unsure

Migration Nightmares: Data You’re Most Nervous About

• Which data domains would you refuse to compromise on during migration (i.e., must be exact or fully reconciled)? Options: Open claims and reserves, Payment history, Policy coverage snapshots, Third-party liability records, Attorney/legal/litigation files, Medical records, Other (please specify)
• How do you currently handle in-flight claims that span a cutover—do you pause movement, continue on legacy, or convert mid-process? Options: Continue on legacy until closed, Convert in-flight during cutover, Hybrid by claim type/severity, Other (please explain)
• What specific data quality issues (duplicates, missing fields, mismatched keys) have caused conversion failures in past projects?
• What percentage of historical claims do you expect must be converted for business needs vs. archived only? Options: All historical claims, Majority (70–90%), Selective (30–70%), Minimal (<30%), Unsure
• Are there legal, contractual, or data residency constraints that restrict moving full datasets off your current environment? Options: Yes — strict constraints, Some constraints with approvals, No constraints, Unsure

People & Process: The Hidden Dependencies That Make Or Break Projects

• Which internal teams or individuals do you believe, today, are single points of failure for claims knowledge?
• How much overlap exists between legacy system SMEs and business operations—are SMEs still in operations roles or mostly in maintenance? Options: SMEs embedded in ops, Split between ops and IT, Mostly in maintenance/IT, Mostly left the organization, Unsure
• What is your plan to capture tribal knowledge (code, configs, procedures) before a migration? Options: Detailed documentation & runbooks, Shadowing & recording SMEs, No formal plan yet, Hybrid approach, Other (please specify)
• How ready is your operations and claims team to accept a new workflow — do they expect training, shadowing, or phased enablement? Options: Comprehensive training + shadowing, Light training + reference materials, Minimal training expected, Resistance likely, Unsure
• Who will have final sign-off for acceptance of migrated claims and production cutover? Options: VP Claims, Chief Claims Officer, CIO/CTO, Transformation Office, Compliance Officer, Cross-functional committee, Other (please specify)

If We Could Fix One Thing First, What Would It Be?

• If you could eliminate one recurring operational failure or compliance blind spot overnight, what would it be?
• Which measurable outcome would matter most to leadership in the near term (pick up to two)? Options: Reduce cycle time (FNOL→closure), Lower LAE per claim, Fewer regulatory exceptions, Faster reporting cadence, Reduce manual FTE hours, Improve customer NPS/CSAT
• What short-term timeline would your team consider acceptable for a low-risk pilot or proof-of-concept? Options: 30 days, 60–90 days, 3–6 months, 6–12 months, Longer / strategic program
• What evidence or artifacts would you need from a vendor to feel comfortable starting a phased migration (examples: conversion mappings, test scripts, rollback plan)?
• Who should be involved in a first pilot conversation from your side (names/roles)?

Before We Flip the Switch

• How confident does your team feel about the planned cutover window? Options: Very confident, Somewhat confident, Neutral, Somewhat concerned, Very concerned
• What is your target cutover date or window? Options: Next 30 days, 31-60 days, 61-90 days, 3-6 months, 6+ months, TBD
• Please describe any immovable business events, earnings blackout periods, or seasonal peaks that constrain your cutover timing.
• Which lines of business and claim types are in scope for phase one? Options: Personal Auto, Homeowners, Commercial Property, General Liability, Workers' Compensation, Specialty Lines, Other
• What is the expected average and peak daily claims transaction volume during the cutover week? Options: <100, 100-1,000, 1,001-10,000, 10,001-100,000, 100,000+, Unknown
• Who will be the single operational owner authorized to make the final go/no-go decision on cutover day? Provide name, role, and contact.

If We Cut Over Tomorrow, What Would Break First?

• Tell us the one dataset, integration, or workflow you suspect would fail first if we cut over tomorrow — why?
• Which in-flight claim states or processing stages are most vulnerable to migration errors? Options: Open investigation, Assigned to adjuster, Pending payment, Litigation, Subrogation, Closed but reopened, Other
• Have you observed recurring mapping or transformation errors in prior conversions? Describe a specific example and the time it took to detect.
• Which third-party integrations pose the highest delivery or compatibility risk for cutover? Options: Policy administration, Billing, Payments/ACH, TPA/vendor portals, Imaging/photo estimation, Medical bill review, Analytics/BI, State regulatory reporting feeds, Other
• If that failure lasted 24–72 hours, what business impacts do you expect (select all that apply)? Options: Regulatory reporting missed, Significant customer complaints, Payment delays >48h, Reserve misstatements, Operational backlog increase, Financial statement impact, Minimal impact
• What temporary controls or manual workarounds do you currently rely on to absorb these failures?

Who's Holding the Keys?

• If someone needed emergency access to restore claims processing at midnight on cutover day, could they get it — and who would be accountable?
• Which teams need environment access during pre-deployment testing, and at what privilege levels? Options: Claims operations - admin, Claims operations - limited, IT/DevOps - admin, Data conversion - write, Vendors/3rd party - restricted, Compliance/audit - read-only, Other
• Are contractual, privacy, or security policies currently blocking necessary vendor or cross-team access for testing? Options: Yes - vendor access restricted, Yes - data export restricted, Yes - environment isolation, No, Unsure
• List outstanding accounts, VPNs, certificates, service accounts or IAM roles still required and the estimated time to provision each.
• How will privileged access be audited, logged, and revoked after cutover? Options: Centralized IAM logs with retention, Manual spreadsheet review, Sporadic audits, Automated role revocation, Not defined, Other
• Who approves emergency access and how is that approval documented and stored?

Can We Prove the Numbers?

• What would it take for you to trust converted historical claims data enough to stop running parallel systems?
• Which reconciliation outputs must match exactly after conversion? Options: Claim counts by status, Reserve balances, Payment history, Document attachment counts, Loss run summaries, Financial GL mappings, Other
• What tolerance thresholds are acceptable for numeric discrepancies (reserves, payments) during validation? Options: Zero tolerance, <0.1%, 0.1%-0.5%, 0.5%-1%, >1%, Unsure
• Describe your sampling strategy for validating converted claims: number of samples, edge-case focus, and selection method.
• Who must sign off on reconciliations (role and evidence required)? Options: Claims leader with reconciliation report, Finance with GL tie-out, Compliance with audit trail, Program manager with runbook, Other
• Have prior migrations exposed particular classes of data loss or mismatch? Provide examples and how they were remediated.

Do Your Tests Actually Cover the Regulator?

• If a regulator demanded reports for the last 12 months tomorrow, could your post-cutover system produce them in the required formats? Options: Yes, Mostly, with manual workarounds, Partially, No, Unsure
• Which states or jurisdictions with unique reporting rules are in scope for phase one? Options: CA, TX, NY, FL, IL, Other state-specific, Multiple - see notes
• Share an example where legacy reporting deviates from modern regulatory formats and how you currently compensate.
• How comprehensive is your regulatory test coverage today? Options: Full automated tests for all reports, Automated for core reports, manual for edge cases, Manual testing only, Ad hoc and informal, Unsure
• What types of evidence will your regulators accept for the new system (select all that apply)? Options: Audit log exports, Test submission receipts, Signed attestation from IT, Third-party validation report, Other
• Who owns regulatory validation and what is the escalation path if a submission fails?

Cutover Day: Rehearse or Roll the Dice?

• Are you prepared to rehearse cutover until it breaks in testing, or are you relying on a near-flawless first execution? Options: Rehearse aggressively until issues found, Moderate rehearsals with targeted tests, Minimal rehearsals, No rehearsals planned, Undecided
• How many full end-to-end dry runs do you require before go-live? Options: 0, 1, 2, 3+, Undecided
• Describe the rollback and mitigation playbook you expect: triggers, data rollback steps, fallback timelines, and communication protocols.
• Which channels will you use to communicate status during cutover and who receives each channel? Options: Incident management tool, Email distribution list, SMS/pager for execs, War room / Slack channel, Customer portal notifications, Executive briefings
• What is your planned production freeze or blackout window for cutover activities? Options: <4 hours, 4-8 hours, 8-24 hours, 24-72 hours, 72+ hours, No freeze planned
• Who will lead the cutover war room and what pre-agreed decision rights do they have for go/no-go?

Signatures, KPIs, and How We'll Know We Won

• If we can't demonstrate measurable improvement in cycle time or LAE within 90 days, what contractual or governance consequences should apply? Options: Contract remediation clause, Extended vendor support, Re-scope and corrective plan, No formal consequence, Unsure
• Which three KPIs will define success for phase one? (select up to three) Options: Claims cycle time, Loss Adjustment Expense (LAE), Regulatory reporting accuracy, Payment timeliness, Claim closure rate, Customer satisfaction (NPS), System uptime
• For each KPI selected, state the current baseline and the target improvement you expect within 90 days.
• What monitoring, reconciliation cadence, and alerting will be in place during the first 90 days post-cutover? Options: Real-time dashboards, Daily reconciliations, Weekly executive reports, Automated anomaly alerts, Manual spot checks, Other
• How should post-launch operational issues and enhancement requests be triaged and routed? Options: Dedicated post-launch backlog in CustomerNode, Joint weekly triage with vendor, Direct to vendor support SLA, Escalation to transformation office, Other
• Who will own lessons learned, maintain the shared channel for ongoing issues, and schedule the first 30/60/90 day reviews?

Getting Started — Who's in the Room and What Matters?

• Please list the people joining this conversation and their primary decision area (title — area).
• Which of these groups will be most accountable for the platform decision? Options: VP of Claims, CIO/CTO, CFO, Transformation/Innovation Office, Head of Operations, Legal/Compliance, External Consultant/Integrator, Other
• What is the target decision timeline for selecting a solution and signing an agreement? Options: Immediate (within 30 days), This quarter (30–90 days), Next quarter (90–180 days), 6+ months, No firm timeline
• What's the single top business priority driving this evaluation right now? Options: Reduce claims cycle time, Lower loss adjustment expense (LAE), Regulatory compliance and reporting, Replace legacy risk of failure, Enable product/line agility, Improve customer experience, Other
• How confident are you that the stakeholders in this room are aligned on those priorities? Options: Fully aligned, Mostly aligned with minor gaps, Fragmented across groups, Alignment unknown — needs discovery

Are We Comfortable Migrating Live Claims?

• If I said we will migrate live claims in phases, what worries you most about the first 30 days?
• Have you executed a live-claims migration before, and what was the outcome? Options: Yes — smooth, Yes — manageable issues surfaced, Yes — serious problems, No — never attempted
• Which live-claim scenarios feel most fragile to you? Options: Open complex/litigated claims, High-reserve claims, Catastrophe surge claims, High-frequency, low-severity claims, Subrogation/recovery claims, Other
• What reconciliation tolerance would you accept immediately after migration (data and financial figures)? Options: Exact match required, <0.1% variance, <1% variance, <5% variance, Tolerances vary by dataset
• How are in-flight claims currently handoffed between systems, and where do manual interventions occur?
• Who would have the authority to pause or halt a migration phase if in-flight claim issues emerge? Options: VP of Claims, CIO/Program Lead, CFO, Steering Committee, Legal/Compliance, Other

Where the Claims Process Really Breaks — Betting on the Root Cause

• If you had to bet on where 80% of operational headaches originate, where would you place the wager?
• Which technical failure modes cause the most business disruption today? Options: Interface failures, Duplicate or orphaned records, Incorrect reserve histories, Missing/mislinked documents, Payment posting delays, Regulatory report mismatches
• How often do production integrations or data feeds fail in a way that requires manual reconciliation? Options: Daily, Weekly, Monthly, Rarely, Unknown
• Tell me about a recent incident that exposed a critical weakness — what happened, and who felt the pain?
• Which data elements are most frequently corrected or disputed (choose all that apply)? Options: Reserve history, Payment transactions, Claimant contact data, Policy linkage, Coverage determinations, Attachments/estimates

What 'Good' Actually Looks Like for Everyone at the Table

• If the press released a headline six months after go-live, what would you want it to say about your claims operation?
• For the VP of Claims, what single measurable outcome matters most? Options: Cycle time reduction, LAE reduction, Claim closure rate increase, Customer satisfaction improvement, Compliance stability, Other
• For the CIO, what operational metric will define success? Options: System uptime/integration uptime, Time to onboard integrations, Total cost of ownership, Operational automation rate, Data accessibility and analytics readiness, Other
• For the CFO, which financial measure will determine whether this investment pays off? Options: LAE reduction, Reduction in manual FTE hours, Faster recoveries/subrogation, Predictable OpEx, Avoided fines/penalties, Other
• What are the non-negotiable acceptance criteria for go-live (examples: regulatory sign-off, zero critical defects, reconciliation thresholds)? Options: Regulatory reporting validated, Zero critical defects, Data reconciliation within tolerance, Successful parallel run, Operational training completed, Other

Unseen Compliance and Reporting Landmines

• Which regulatory filing or state-specific requirement could stop cutover if it isn't validated exactly? Options: State statutory reporting, Catastrophe reporting, Worker's compensation filings, Reinsurance reporting, Rate/regulation-mandated disclosures, Other
• How frequently do you run end-to-end regulatory reports today? Options: Daily, Weekly, Monthly, Quarterly, Annually, On demand
• Which reports or filings must match legacy output exactly versus which can be transformed or restructured? Options: All must match exactly, Key statutory reports must match, Operational reports can evolve, Unknown — needs analysis
• Describe your audit trail, retention periods, and any legal holds that affect claim records.
• Who owns regulatory sign-off and what evidence do they require (examples: reconciliation logs, sample attestations)? Options: Internal Legal/Compliance, VP of Claims, CFO/Controller, External Auditor, Regulatory Affairs team, Other

Migration Scope — What's Sacred and What's Flexible?

• Which datasets or records would you rather not touch than risk altering — what is effectively 'sacred'?
• Roughly how many core claims and what historical data volume do you expect to migrate? Options: <100,000 claims, 100k–500k claims, 500k–1M claims, 1M–5M claims, >5M claims
• Which elements do you anticipate will be highest complexity to map and validate? Options: Attachments (photos, estimates), Reserve and payment ledger history, Custom workflow histories, External references and IDs, Policy endorsements and cancellations, Other
• Which migration approach do you prefer for your environment? Options: Big bang cutover, Phased by line of business, Phased by claim age (older first), Pilot then scale, Hybrid mix
• What window of read-only versus read-write during cutover would be acceptable for your operations? Options: Minutes, Hours, 1–2 days, 3–7 days, >7 days
• Are there legal holds, ongoing litigations, or reinsurer-specific requirements that force immutability on certain claims? Options: Yes — several, Yes — a few, No, Unknown

Integration Reality Check — The Few Systems That Could Break the Business

• If one external system failed on day one, which single system collapsing would cause the most business damage? Options: Policy administration system, Billing system, Payment processor/gateway, Reinsurance feeds, Third-party vendor platform (TPA, medical), Document management repository, Other
• List your critical integrations and the current connection pattern for each (real-time API, batch file, message queue, manual process).
• For each critical integration, what are the current SLAs, error tolerances, and owners?
• Which external partners must be actively coordinated for cutover (choose all that apply)? Options: TPAs/managed vendors, Medical vendors/IMEs, Salvage vendors, Payment processors, Reinsurers, Courts/legal partners, Other
• Do sandbox or test endpoints exist for each critical partner and do they reflect production behavior? Options: Yes — full parity, Yes — limited parity, No sandboxes, Unknown
• How do you currently detect and reconcile integration discrepancies when they occur?

Operational Readiness — People, Playbooks, and Panic Buttons

• If the phone rings with a critical outage on day one, who are we calling and why might they not be reachable?
• How many full-time equivalents must be trained and operational before go-live? Options: <10 FTEs, 10–50 FTEs, 50–200 FTEs, 200–500 FTEs, >500 FTEs
• What percentage of active users must pass acceptance testing before we proceed with cutover? Options: 100%, 95%, 90%, 80%, Other
• Do you have documented rollback and mitigation plans, and who needs to approve them? Options: Fully documented and approved, Drafts exist and need approval, No formal plan, Unknown
• Which training formats historically work best for your adjusters and supervisors? Options: Self-serve e-learning, Classroom/virtual instructor, Train-the-trainer model, Embedded in-app guidance, Blended approach
• How mature and rehearsed is your incident response and escalation governance for major operational incidents? Options: Mature and regularly rehearsed, Exists but rarely tested, Informal ad hoc process, None

Measuring Migration Success Day 1–90 — What Proof Seals the Deal

• What single metric outperforming legacy on day 30 would make your leadership declare the migration a success? Options: Cycle time reduction, LAE reduction, Payment accuracy, Regulatory reporting accuracy, Automation rate of low-complexity claims, Customer satisfaction
• Which KPIs will you monitor and at what cadence post-cutover? Options: Cycle time (daily), LAE (monthly), Avg payment accuracy (daily), Claim volume and backlog (weekly), Reopen rate (monthly), Regulatory errors (weekly)
• What sample size or confidence threshold do you require for data validation and reconciliation? Options: 100% reconciliation, 99%+, Statistical sample with 95% confidence, Executive spot-checks, Other
• How long should parallel runs or dual-entry validation continue after cutover? Options: No parallel run, 7 days, 30 days, 90 days, >90 days
• What automatic triggers (metrics or exceptions) should pause or roll back a migration phase?

Next Steps, Commitment Signals, and What Keeps You Up at Night

• What's the single unresolved question that, if unanswered, would stop this project tomorrow?
• What immediate decisions or commitment signals do you need from executive sponsors in the next 14 days? Options: Budget approval, Sign-off on scope and phases, Assignment of program lead, Regulatory engagement approval, Vendor contracting mandate, Other
• Who will be the day-to-day program lead from your side and what decision authority will they hold?
• What would a minimally viable pilot look like and which line of business should it include? Options: Personal Auto, Homeowners, Commercial Property, General Liability, Multi-line small pilot, Other
• When should we schedule a follow-up workshop to validate assumptions, review integration inventories, and agree success criteria? Options: Within 1 week, Within 2 weeks, Within 1 month, Within 2–3 months, TBD by your team