Start Here — Who's in the Room and What Matters?

• Please select your role and the primary teams you expect to involve in evaluating underwriting modernization Options: Chief Underwriting Officer, Head of Commercial Lines, CIO/CTO, Head of Operations, Lead Underwriter / Squad Lead, IT Integration Lead, Data/Analytics Lead, Procurement, Other
• Which lines of business and product types would you want a pilot to target first? Options: Commercial Property, Commercial Auto, General Liability, Professional Liability (E&O), Workers' Compensation, Specialty / Excess, Package / SME, Other
• Roughly how many underwriters, triage staff, and submission processors touch broker submissions across the targeted lines today?
• Which systems do your teams reference most during submission review (policy admin, rating engine, loss history portals, CRM, spreadsheets)? Options: Policy administration, Rating engine, Loss runs / CLUE / ISO, Property data providers, CRM / pipeline tracking, Document management, Spreadsheets/email inboxes, Other
• How would you describe the appetite for change among your underwriting leadership—cautious, curious, or urgent? Options: Cautious, Curious, Urgent

Are You Comfortable Letting Manual Work Define Your Rates?

• What would it cost — in lost premium, speed, or stress — if manual intake and spreadsheet work continued to set underwriting priorities for another year?
• What percentage of broker submissions are still processed with manual data entry or copy/paste into rating systems? Options: 0–10%, 11–25%, 26–50%, 51–75%, 76–100%
• Which steps of your intake-to-quote flow are most manual today (select all that apply)? Options: Submission triage/screening, Data entry into rating/admin, Loss run reconciliation, Third-party data lookup, Underwriter worksheet preparation, Routing to correct underwriter, Quote generation/bind
• How long has your current manual-first operating model been the norm for these lines? Options: Less than 1 year, 1–2 years, 3–5 years, More than 5 years
• Tell us about a recent case where manual steps caused a missed opportunity, delayed quote, or rework — what happened and how did it feel for the team?
• Would you be willing to share 10–50 anonymized broker submissions for an intake accuracy and routing proof-of-value? Options: Yes—10–50 sample set, Yes—larger dataset available, Not yet, but we can prepare, No

What's Costing You the Most: Hidden Drag or Obvious Leak?

• Which single metric do you believe is being most negatively impacted by your current intake process (cycle time, hit ratio, premium per underwriter, accuracy, or something else)? Options: Underwriting cycle time, Hit ratio / quotes to binds, Premium per underwriter, Data accuracy / errors, Underwriter throughput, Other
• What is your current average time from submission receipt to first priced quote for the target lines? Options: Under 1 day, 1–3 days, 4–7 days, More than 7 days, Not measured
• How often do underwriters need to request additional broker information due to missing or inconsistent data? Options: Daily, Weekly, Monthly, Rarely, Not tracked
• Estimate the proportion of submissions that require manual reconciliation of conflicting data (e.g., inconsistent revenue, occupancy, loss runs). Options: 0–10%, 11–25%, 26–50%, 51–75%, 76–100%
• How does this friction affect your commercial goals—pricing discipline, speed to market for new products, or underwriter morale? Share a concrete impact.

What If AI Got the Hard Stuff Right — Would You Trust It?

• If an AI could extract the critical fields from broker submissions at 90% accuracy today, would your team rely on it to pre-populate underwriting work that leads to quotes? Options: Yes, with human spot-checks, Yes, for low-complexity risks only, Not yet—need higher accuracy, No, we prefer manual
• Which fields must be right every time for you to trust automation (select all that apply)? Options: Named insured/Entity, Payroll / Revenue / Exposure, Location / Property address, Coverage limits/deductibles, Loss history / prior claims, Policy effective dates, Broker contact
• What accuracy thresholds would you accept per field (e.g., >95% for limits, >85% for narrative extraction)? Please specify if you have different thresholds by field.
• Do you currently use any automation or AI for submission intake, extraction, or routing? If yes, what works and what fails? Options: No current automation, Rules-based triage only, Third-party AI extraction, Vendor solution in pilot, Homegrown scripts
• How important is a human-in-the-loop review for final decisions versus fully automated pre-population? Options: Always required, Needed for complex risks, Optional but preferred, Not required
• Describe a past extraction or automation failure that eroded trust—what went wrong and how was it resolved?

Who Really Decides If This Changes How You Underwrite?

• If the pilot drives clear efficiency but a vocal group of experienced underwriters resists, who ultimately decides whether to scale? Options: C-level (CUO/CIO), Head of Commercial Lines, Underwriting Governance Committee, Operations/COO, Board/Executive Sponsor
• Please identify the stakeholders who must sign off on a pilot and on a rollout (select all that apply). Options: CUO / Head of Underwriting, CIO / IT leadership, Head of Ops / COO, Security / Risk, Procurement, Legal / Compliance, Pilot underwriters / front-line leads, External broker partners
• Who would make the day-to-day decisions during a pilot—who will act as the pilot owner and operational contact?
• What success signals will convince leadership to move from pilot to scale (select up to three)? Options: % extraction accuracy, Cycle time reduction, Increase in quotes per underwriter, Improved hit ratio, Underwriter satisfaction/adoption, Reduction in manual FTE hours
• What internal friction or political dynamics should we anticipate that could slow adoption, and how have you handled similar changes before?
• What is your expected procurement and legal timeline for vendor pilots and proofs of value? Options: Immediate (weeks), 1–2 months, 3–6 months, 6+ months

Where Do Your Systems Need to Hold Hands?

• Would you prefer deep, API-based integration with your policy and rating systems or a lighter file-based approach to start? Options: API-first/full integration, File-based (SFTP/CSV) to start, Hybrid (APIs for critical flows), Undecided/depends on effort
• Which core systems must be integrated for the pilot (select all that apply)? Options: Policy administration system, Rating engine, Document management, Loss history providers, CRM / broker portal, Accounting / billing, Underwriter worksheets / internal tools
• What connectivity and security controls will we need to meet—SAML/SSO, VPN, IP allowlisting, data encryption, SOC2, or others? Options: SAML/SSO, OAuth 2.0 / API keys, VPN / private network, IP allowlisting, Encryption at rest/in transit, SOC2 / ISO27001, Other
• Are there data residency, PII masking, or regulatory restrictions we should plan for during sample ingestion? Options: Yes—specific restrictions, Some restrictions but manageable, No
• How mature are your test environments and sandboxes for policy and rating systems (suitable for end-to-end pilot testing)? Options: Fully mature and available, Partially available with work, Not available—requires setup
• Who in IT/security will be our integration approver and what lead time do they need for onboarding?

If We Only Get One Thing Right in a Pilot, What Must It Be?

• What's the one outcome from a pilot that would make you champion scaling this platform across other lines?
• Which pilot KPIs should we track and report daily/weekly (select all that apply)? Options: Extraction accuracy by field, Average time to first quote, Quotes per underwriter, Percentage of fully automated triage, Broker response time, Underwriter satisfaction score
• For each selected KPI, what is your minimum acceptable threshold to consider the pilot successful? Please list KPI → threshold pairs.
• What sample size and pilot duration do you consider statistically and operationally persuasive (e.g., 500 submissions over 8 weeks)? Options: Small sample (100–250) / 4–6 weeks, Medium (250–1,000) / 6–12 weeks, Large (>1,000) / 12+ weeks, Undecided—need vendor recommendation
• Who will own pilot governance, day-to-day issue triage, and the final go/no-go recommendation?
• What would be your rollback or mitigation criteria if the pilot produces unexpected risks or lower-than-expected outcomes?

How Would Success Actually Feel in Six Months?

• Assuming we meet the technical goals, what would you notice first that tells you underwriting is truly modernized?
• What specific improvements would you like to see in underwriter productivity or pipeline metrics within six months (select all that apply)? Options: 50% reduction in manual data entry time, 25% faster time to quote, Increase in premium per underwriter, Fewer data-related declinations, Higher underwriter satisfaction
• How do you plan to measure adoption and behavior change among underwriters (surveys, usage logs, quota tied KPIs)? Options: Usage analytics, Underwriter surveys, Performance KPIs, Manager observations, Other
• What training cadence and format would help underwriters adopt a new workbench (in-person workshops, recorded micro-lessons, embedded help, shadowing)? Options: In-person workshops, Live virtual training, Recorded micro-lessons, Embedded in-app guidance, Shadowing/mentorship
• If the pilot delivers expected gains, what is your ideal timeline to begin a phased roll-out across additional product lines? Options: Immediate (0–3 months), Short (3–6 months), Moderate (6–12 months), Longer (12+ months)
• What ongoing support and governance model would make you comfortable (managed services, co-managed, handoff to internal teams)? Options: Managed services, Co-managed partnership, Full handoff to internal teams, Hybrid

• Experience Kickoff & Current-State Confirmation
• Live Sample Processing & AI Extraction Validation
• Routing, Pricing & Underwriting Worksheet Simulation
• Integration Impact Review & End-to-End Test
• Experience Validation, Decisions & Next Steps

• Secure required IT approvals and identify any remaining blockers to pilot integration.
• If needed, customer provides additional edge-case submissions for targeted retraining/config tuning.
• Secure underwriter feedback that pre-populated worksheets reduce manual work and support decision-making.
• Agree the estimated impact on cycle time and throughput for pilot scope.
• Recap Accepted Extraction Outputs
• Validate routing accuracy and that submissions are assigned to the correct underwriter/queue.
• Confirm pricing outputs are explainable and within agreed tolerances versus the current process.
• Seller produces a side-by-side report of pricing outputs vs baseline and highlights variances for review.
• Customer nominates pilot underwriters who will validate worksheet usability and routing logic.
• Seller and customer adjust routing rules and thresholds based on underwriter feedback.
• Document exception types that require manual review and define handling rules for the pilot.
• Integration Points Review
• Confirm all integration mappings and that payloads meet downstream system requirements.
• Validate end-to-end flow in test systems with demonstrable logs and reconciliation.
• Agree on error handling procedures, SLAs for retries, and owners for remediation.
• Introductions & Objectives
• Seller provides detailed integration mapping document and sample payloads to customer IT.
• Customer IT confirms test endpoint availability and provides production cutover checklist requirements.
• Create integration tickets for any mapping changes and assign owners with target due dates.
• Seller delivers reconciliation and error log templates to be used during the pilot.
• Concise Recap (State, Consequence, Future)
• Obtain explicit customer validation that the experience proves the defined future-state or capture precise gaps.
• Agree a clear decision (proceed to pilot, proceed with conditions, or require further work) and document next steps.
• Assign owners and deadlines for any remediation required prior to pilot go-live.
• Ensure all stakeholders know acceptance criteria, pilot scope, and timeline for the next phase.
• Document final decision and circulate signed validation summary and agreed pilot acceptance criteria.
• If remediation required, create a prioritized remediation plan with owners, deliverables, and dates.
• Schedule pilot planning meetings (Deployment readiness) and transfer relevant artifacts to deployment team.
• Customer to provide formal approval or list of outstanding issues needing resolution before pilot.
• Create and confirm a single-sentence current state that everyone endorses.
• Make consequences explicit with baseline metrics the customer accepts.
• Agree future-state sentence and measurable acceptance criteria to validate during the experience.
• Secure delivery of representative broker submissions and test access for the next session.
• Customer provides anonymized set of representative broker submissions and sample metadata by agreed date.
• Seller prepares baseline metrics report and ingestion plan for chosen samples.
• IT owners exchange test credentials and confirm data access method (SFTP/API/email) for live processing.
• Document and circulate the agreed one-sentence current state, consequence statement, and future-state sentence.
• Recap Preconditions & Success Criteria
• Demonstrate extraction accuracy against real broker submissions and compare to the agreed KPI.
• Identify root causes of extraction failures and apply immediate configuration or rule-based fixes.
• Obtain customer confirmation on whether extraction outputs satisfy underwriting needs for the sample set.
• Produce a prioritized list of extraction improvements and additional sample requirements.
• Seller logs each extraction mismatch with root cause and proposed fix, and shares within 48 hours.
• Customer reviews and signs off on whether field-level outputs meet underwriting acceptance for the sample set.
• Seller implements agreed configuration updates and schedules a short re-check session for any unresolved samples.
• Ingestion Setup & Rules
• One-Sentence Current State
• Summary of Extraction, Routing, Pricing, Integration Results
• Payload & Mapping Confirmation
• Routing Rules Mapping
• Automated Risk Scoring & Rules Engine
• End-to-End Test Run
• Live Ingestion (Batch of Representative Samples)
• Consequence Quantification
• Outstanding Risks & Remediation Plan
• One-Sentence Future State
• Pricing/Rating Output Comparison
• Customer Validation Questions
• Field-by-Field Extraction Review
• Error Handling & Reconciliation

• Broker Email Intake Connector
• Portal and API Submission Intake
• AI-Powered Submission Data Extraction
• Pre-Populated Underwriting Worksheets
• Automated Risk Scoring Engine
• Underwriter Assignment and Routing
• Configurable Underwriting Rules Engine
• Quote Generation and e-Bind Workflows
• Policy and Rating System Integration APIs
• Third-Party Data Enrichment Connectors
• Underwriter Workbench UI and Tools
• Management Dashboards and Real-Time Reports
• Document Management and Versioned Storage
• Audit Logging and Compliance Trail
• Bulk Submission Import and Migration

Broker Email Intake Connector

• Which email delivery patterns do you receive from brokers? Options: Shared inboxes (e.g., submissions@), Direct emails to underwriters, Distribution lists, Automated system emails, Other
• What is your average daily volume of email submissions? Options: Less than 50, 50-200, 200-500, 500+
• Which email platforms or providers must the connector support? Options: Exchange/Outlook (on-prem), Exchange Online/Office365, Gmail/Google Workspace, Other (please specify)
• Do you require parsing of email threads, inline replies, and attachments as separate submission entities? Options: Yes, No
• Are there security, compliance, or data residency constraints for ingesting broker emails? If yes, specify (TLS requirements, scanning, retention limits, geolocation).

Portal and API Submission Intake

• Do you plan to accept submissions via a broker portal, API, or both? Options: Portal only, API only, Both
• Which authentication and security methods are required for APIs/portal (e.g., OAuth2, mTLS, API keys, SSO)? Options: OAuth2, mTLS, API keys, SAML/SSO, Other
• What data formats must be supported for intake (e.g., multipart form, JSON payloads, PDF uploads, XML)? Options: PDF, JSON, XML, Multipart/Form-Data, Other
• What expected peak submission rate should the intake handle (requests per minute)? Options: Low (<10/min), Moderate (10-60/min), High (60-200/min), Very high (>200/min)
• Are there portal UI requirements for brokers (e.g., templates, validation, file size limits, progress indicators)? If yes, describe.

AI-Powered Submission Data Extraction

• Which document types must the extraction model support (e.g., ACORD, PDF schedules, Word docs, email bodies, photos)? Options: ACORD forms, PDFs (scanned), PDFs (digital), Word/Excel, Email body, Images/photos
• What are the critical fields to extract for underwriting and pricing (e.g., named insured, limits, effective dates, exposure details)?
• What minimum extraction accuracy/confidence thresholds do you require per field (e.g., 95% for insured name)? Options: >99%, 95-99%, 90-95%, <90%, Custom (please specify)
• Do you require human-in-the-loop validation or correction workflows for low-confidence extractions? Options: Yes, for all low-confidence fields, Yes, for selected fields only, No, automated only
• Will you provide labeled training examples or allow access to anonymized historical submissions to improve model accuracy? Options: Yes, we will provide examples, No, we cannot share data, We need guidance on anonymization

Pre-Populated Underwriting Worksheets

• Which underwriting worksheet templates or field groups do you need pre-populated?
• Should worksheets include integrated third-party data (loss history, property details, financials) inline with extracted fields? Options: Yes, inline, Yes, as separate panels, No, separate lookup only
• Do underwriters require editable fields, calculated fields, or both in the worksheet? Options: Editable fields, Calculated fields, Both
• Do you need multiple worksheet versions per line of business or product with conditional fields? Options: Yes, per LOB/product, Single universal worksheet, Custom mapping required
• Are there required approval or sign-off steps built into the worksheet workflow (e.g., peer review, manager sign-off)? Options: Yes, No

Automated Risk Scoring Engine

• Do you want a vendor-default risk scoring model, a configurable rules-based score, or a custom statistical/ML model? Options: Vendor-default, Configurable rules-based, Custom ML/statistical, Hybrid
• Which input sources should feed the score (extracted fields, third-party data, historical loss records)? Options: Extracted fields, Third-party data, Historical submissions/losses, Underwriter inputs
• What score outputs and thresholds matter for routing and auto-decline/auto-quote decisions?
• Do you require explainability for scores (field contributions, human-readable reasons)? Options: Yes, required, Nice to have, No
• How often should the scoring model be retrained or tuned (monthly, quarterly, on-demand)? Options: Monthly, Quarterly, Annually, On-demand

Underwriter Assignment and Routing

• Which routing rules should determine assignment (line of business, territory, capacity, specialty, manual rules)? Options: Line of business, Territory, Underwriter capacity/availability, Specialty/experience, Custom tags/skills
• Do you require dynamic load-balancing and capacity thresholds per underwriter/team? Options: Yes, No, Pilot only
• Should routing support manual overrides and reassignment workflows for exceptions? Options: Yes, with audit trail, Yes, without audit trail, No
• What notification channels are required for assignments (email, in-app, SMS, Slack)? Options: Email, In-app notifications, SMS, Slack/MS Teams, Other
• Are there SLA targets for assignment and acknowledgement (e.g., assign within X minutes)? If so, specify.

Configurable Underwriting Rules Engine

• How many active underwriting rules do you anticipate initially (estimate)? Options: 1-10, 11-50, 51-200, 200+
• Do rules require nested logic, thresholds, lookups to external data, or temporal conditions? Options: Nested logic, Thresholds, External lookups, Temporal conditions (e.g., date ranges)
• Who will own rule creation and maintenance (underwriting team, operations, central admin)? Options: Underwriting, Operations, Central IT, Vendor-assisted
• Do you need versioning, testing/sandbox for rules, and rollback capabilities? Options: Yes, all three, Partial (specify), No
• Should rules trigger automated actions (decline, auto-quote, route, flag for review)? Options: Yes - automatic actions, Yes - alert only, No

Quote Generation and e-Bind Workflows

• Does quote generation require integration with an external rating engine, or are quotes derived from platform rules? Options: External rating engine, Platform rules, Hybrid
• Do you require e-signature / e-bind capability as part of the workflow? Options: Yes, integrated, Yes, via third-party connector, No
• What approval gates should exist before binding (underwriter approval, manager approval, automated thresholds)? Options: Underwriter approval, Manager approval, Automated binding below threshold, Other
• Which document templates and outputs are required (quotations, binders, bind confirmation, policy docs)?
• Should the system produce auditable bind trails and production-ready policy packets to feed the PAS? Options: Yes, No

Policy and Rating System Integration APIs

• Which policy administration and rating systems must be integrated (vendor names and versions)?
• Preferred integration pattern for each system (real-time API, batch file/SFTP, message queue)? Options: Real-time API, Batch (SFTP/flat files), Message queue (Kafka/SQS), Other
• Which data objects require synchronization (policies, endorsements, payments, cancellations, submissions)? Options: Policies, Endorsements, Payments, Cancellations, Submissions, Other
• Are there existing API specs, sandbox credentials, or integration guides available to share? Options: Yes - full specs, Partial docs available, No, vendor access required
• Do integrations require field mapping or transformation rules (describe complexity or sample mapping needs)?

Third-Party Data Enrichment Connectors

• Which third-party data providers do you currently use or plan to use (loss runs, property, credit, sanctions)? Options: ISO/Verisk, LexisNexis, CoreLogic, Loss run vendors, Other
• What data elements do you need enriched (claims history, property attributes, financials, sanctions, registries)? Options: Claims history, Property attributes, Financials, Sanctions/Watchlists, Other
• What frequency and latency expectations exist for enrichment lookups (real-time, batched nightly, cached)? Options: Real-time, On-demand with caching, Batched nightly, Other
• Do you have existing contracts or credentials for these vendors or will vendor onboarding be required? Options: We have contracts/credentials, We need vendor onboarding assistance, Unknown
• Are there cost constraints or limits per lookup that should be enforced? Options: Yes - enforce limits, No

Underwriter Workbench UI and Tools

• Which user roles will use the workbench and what differing UI capabilities are required (underwriter, manager, triage analyst)? Options: Underwriter, Manager, Triage/Intake, Ops/Admin, Other
• Do underwriters require custom layouts, saved views, or role-based dashboards in the workbench? Options: Custom layouts, Saved views, Role-based dashboards, None
• Are there specific collaboration features needed (comments, handoffs, redlines, shared notes)? Options: Comments/mentions, Handoffs/assign, Shared notes, None
• Do you need mobile or offline access to parts of the workbench? Options: Mobile responsive, Dedicated mobile app, Offline support, No
• What training and change management support will be required for underwriter adoption (classroom, digital guides, shadowing)? Options: Classroom training, Digital guides/on-demand, Shadowing/pilot sessions, All of the above

Management Dashboards and Real-Time Reports

• Which KPIs and metrics must be visible on dashboards (submission volume, cycle time, hit ratio, underwriter productivity)? Options: Submission volume, Cycle time, Hit ratio, Underwriter productivity, Custom
• Do you need role-based dashboards (executive vs operations vs underwriter)? Options: Yes - role-based, No - single view
• What reporting cadence is required (real-time, hourly, daily, weekly)? Options: Real-time, Hourly, Daily, Weekly, Monthly
• Do you require scheduled report delivery and export formats (CSV, PDF, dashboard links)? Options: CSV, PDF, Dashboard link/portal, Other
• Are there compliance or audit reports that must be produced regularly (e.g., for regulators)? If so, specify.

• Non-Disclosure Agreement (NDA)
• Master Services Agreement (MSA)
• Statement of Work (SOW)
• Pilot Agreement & Acceptance Criteria
• Commercial Terms & Pricing Schedule
• Payment Schedule & Invoicing
• Roles & Responsibilities (RACI)
• Governance & Steering Committee Charter
• Underwriter Adoption & Training Commitment
• Data Access, Integration & Test Environment Consent
• Security, Compliance & Data Processing Agreement (DPA)
• Service Level Agreement (SLA) & Support Commitments
• Change Control & Scope Management
• Termination, Exit & Data Return Plan

• Success Outcomes Review
• Underwriter Feedback & Adoption Workshop
• Integration & Operations Health Check
• Roadmap & Continuous Improvement Council

• Opening & Objective Alignment
• Update training materials and quick-reference guides addressing top 3 friction points; assign author.
• Create tickets for UX/extraction improvements with acceptance criteria tied to underwriter examples.
• Nominate and onboard 2 underwriter champions to drive adoption and collect ongoing feedback.
• Integration Status Snapshot
• Confirm which integration or data issues materially impacted success signals and require fixes prior to scale.
• Set clear ownership, timelines, and verification criteria for operational fixes.
• Agree a repeatable verification process (test cases, sample data) and sign-off authority.
• Log prioritized technical fixes into the backlog with owners, ETA, and test case references.
• Produce a verification checklist and sample dataset to validate each fix post-deployment.
• Update runbooks and incident response contacts for production onboarding.
• Review Pilot Decisions & Approved Actions
• Produce an agreed roadmap with prioritized enhancements, timelines, and cross-team owners.
• Establish a KPI monitoring cadence and reporting owners to track ROI and adoption post-rollout.
• Define governance, change-control, and approval process for ongoing improvements.
• Publish the prioritized roadmap with owners, milestones, and dependencies to all stakeholders.
• Configure dashboards and automate weekly KPI reporting for cycle time, hit ratio, and underwriter productivity.
• Set recurring Continuous Improvement Council cadence (monthly) and assign chair and scribe.
• Confirm which success signals (cycle time, hit ratio, productivity) were met and which require remediation.
• Make a clear decision on pilot outcome: scale, iterate (with defined fixes), or extend.
• Assign owners and deadlines for all remediation actions and follow-up validations.
• Publish a one-page outcomes summary comparing metrics to agreed success criteria and share with stakeholders.
• Create a remediation list for missed targets with owners, required changes, and target verification dates.
• Schedule required follow-up deep-dive sessions (data, UX, integration) within 7 business days.
• Surface concrete underwriter objections and validate their frequency and impact.
• Define a prioritized set of adoption and UX interventions (immediate fixes and roadmap items).
• Set Context & Pre-work Review
• Assign training and change-management owners and establish champion network among underwriters.
• Data Extraction & Quality Metrics
• User Stories: What Worked / What Didn't
• Enhancement Backlog Prioritization
• One-sentence Current State
• Roadmap & Release Plan
• Map Friction to Root Causes
• Operational Incidents & SLAs
• Quantitative Outcomes Presentation
• Brainstorm & Prioritize Interventions
• Gap Analysis vs Success Criteria
• KPI Monitoring & Reporting Cadence
• Prioritization of Fixes & Escalation Paths
• Verification Plan & Sign-off Criteria
• Root-Cause Discussion
• Adoption Plan & Champions
• Governance & Funding Decisions
• Decision & Next Steps