Starting point, timeline, and executive priorities

• Tell me your IRP filing target date and any commission or board deadlines attached to it.
• List the executive outcomes this filing must achieve, ranked by priority Options: Commission approval without major conditions, Least-cost portfolio over study period, Reliability assurance, Emissions reduction targets, Political or community acceptance, Legal defensibility, Other
• Who in your executive team will sign off on the final IRP and who will be the day-to-day decision owner for modeling assumptions? Options: VP Resource Planning, Chief Strategy Officer, Regulatory Affairs Lead, Director of Operations, Cross-functional committee, Multiple roles, Other
• Which filing outcomes would represent failure in the eyes of commissioners or the board? Options: Rejection or remand, Significant discovery demands that delay filing, An intervenor alternative adopted, Financial penalty or directive to refile, Requirement for supplemental analyses, Other
• How much schedule slack do you have between draft submission and final filing, in weeks? Options: Less than 4 weeks, 4 to 8 weeks, 8 to 12 weeks, More than 12 weeks

Where uncertainty makes or breaks your portfolio

• Which single assumption in your current planning, if it shifted by 20 percent, would most likely change the preferred resource portfolio? Options: Load growth, Natural gas price forecast, Carbon price trajectory, Renewable capital cost, Demand-side program uptake, Capacity factor of renewables, Other
• Estimate your historical peak and energy forecast error over the last five years as a percent, and note whether errors were systematic or random. Options: Under 2%, 2% to 5%, 5% to 10%, Over 10%
• If a mid-term carbon price were introduced in your jurisdiction, who is responsible for updating scenarios and approving that policy assumption? Options: Regulatory affairs, Resource planning, Executive leadership, Legal, Cross-functional committee, Other
• Describe the data and model artifacts you use today to represent intermittent generation variability and ramping limits.
• Name the fuel or market price forecasts you consider most uncertain when defending portfolios to commission staff. Options: Natural gas price curves, Renewable PPA price projections, Coal fuel costs, Capacity market prices, Carbon allowance costs, Other

The trade-offs you are implicitly accepting

• If you had to reduce the study scope to stay on schedule, which modeling modules would you cut first and why? Options: Capacity expansion optimization, Production cost simulation, Reliability and loss-of-load analysis, Distributed resource integration, Demand-side program screening, Scenario sensitivity matrix, Other
• What single consequence of compressing the timeline would be a non-starter for you and force a delay?
• Who on your team typically absorbs scope changes mid-project, and do they have the bandwidth and authority to do so? Options: Planning team, Regulatory team, Modeling team, Operations, External consultant, No clear owner
• When you present a preferred portfolio, which trade-off do commissioners probe most: cost, reliability, environmental outcomes, or local economic impacts? Options: System cost and net present value, Reliability and reserve margins, Environmental and emissions outcomes, Local economic and community impacts, All of the above

Stakeholders who will make or break the filing

• Name the external stakeholders—commission staff, intervenors, municipalities—whose objections have previously forced material changes to an IRP. Options: Commission staff, Consumer advocates/intervenors, Local governments, Large customers, Environmental groups, Tribal or community groups, Other
• Identify the internal and external stakeholders you plan to engage in advisory sessions and indicate whether they have decision authority. Options: Planning group, Regulatory affairs, Operations, Finance, Commission staff (advisory), Intervenors (advisory), Other
• What escalation path exists if a key stakeholder refuses to share critical data or access and how quickly can that path be executed?
• List the stakeholder viewpoints that, if not addressed in the IRP, have historically triggered rejections or remands. Options: Resource adequacy concerns, Environmental justice issues, Cost allocation disputes, Local siting impacts, Modeling transparency concerns, Other
• How frequently does your executive leadership expect stakeholder advisory summaries during the engagement? Options: Weekly, Biweekly, Monthly, At major milestones only, Other

Operational readiness and gating constraints

• Can your team provide cleaned hourly load shapes and generator dispatch data for the last five years in a useable format within four weeks? Options: Yes, ready now, Partial, some cleanup required, No, needs significant preparation, We need vendor assistance
• Provide the list of third-party systems your modeling environment must integrate with and note whether APIs or scheduled exports exist.
• Confirm whether your procurement or legal process requires a formal RFP, executive approvals, or special contracting steps before a consulting SOW can be executed. Options: Formal RFP required, Executive approval required, Standard PO process suffices, No additional approvals, Unsure
• Tell which team owns historical metering, fuel burn, O&M, and outage records and whether they can grant secure access for modeling. Options: Planning, Operations, Asset Management, IT/Data Services, Fuel Procurement, Other
• Estimate the minimum internal headcount you can allocate to data preparation and decision reviews during peak modeling phases. Options: Less than 1 full-time equivalent, 1 to 2 FTEs, 3 to 5 FTEs, More than 5 FTEs

Obstacles that have broken timelines before

• Recall the last time an IRP timeline slipped, what single operational failure caused the largest delay?
• On average, how often do discovery or discovery-response cycles add more than four weeks to your review timeline? Options: Almost every filing, Occasionally, Rarely, Never
• Identify the governance gap that, if not closed before modeling begins, would force a pause in the work.
• Provide the top three data quality issues you anticipate and indicate which ones will require vendor remediation.
• Are there regulatory windows, hearings, or utility board events during the modeling period that could prevent schedule changes? Options: Yes, critical hearings, Yes, routine windows, No blocking events identified, Unsure

The competitive landscape and internal alternatives

• Describe the alternatives you are actively considering right now, including incumbent consultants and internal options, and which option is currently leading. Options: Incumbent consultant, New external vendor, Keep work internal, Hybrid (internal + vendor), No decision yet, Other
• Under what conditions would your current internal approach be sufficient so you would not hire an external partner? Options: Sufficient staff capacity, Clean and accessible data, Low regulator scrutiny, Shortened scope, Prior internal experience, Other
• Has anyone on your team proposed solving this entirely with internal staff, and if so what timeline and budget did they estimate? Options: Yes, plan exists with timeline, Yes, rough estimate only, No internal proposal, Unsure
• Assuming the incumbent remains the vendor, what single outcome would you expect they deliver better than a new partner?
• Select the most important reason you might choose an external partner instead of keeping the work internal. Options: Faster delivery, Proven commission acceptance record, Specialized modeling expertise, Independence for stakeholders, Lack of internal capacity, Total cost, Other

Decision triggers, acceptance criteria, and next steps

• Pinpoint the acceptance criteria that must be met for your leadership to approve moving from planning to full modeling. Options: Modeling scenarios agreed, Data access granted, SOW and commercial terms signed, Budget/funding secured, Governance and signoff roles assigned, Other
• Reveal the single missing document or approval that would prevent you from signing a SOW this quarter.
• Outline the billing or milestone trigger your finance team requires before releasing funds for the engagement. Options: SOW signature, Delivery of draft IRP chapters, Commission filing, Regulatory acceptance sign-off, Other
• Explain which internal obstacles could still stop you from signing quickly even if a pilot modeling run produces the expected result.
• Within what timeframe after receiving a draft SOW would your team be able to provide a signed copy? Options: Immediately, Within 2 weeks, Within 4 weeks, Within 6 to 8 weeks, Longer than 8 weeks

• Planning Framework Kickoff
• Modeling Assumptions and Data Requirements Workshop
• Scenario Matrix and Sensitivity Design
• Stakeholder Advisory Approach and Charter
• Planning Stage Sign-off and Next Steps

• Publish the stakeholder map and advisory group charter with confirmed meeting dates and materials expectations.
• Configure the modeling run plan with scenario assignments and expected output metrics per run.
• Document sensitivity trigger thresholds and the protocol for when additional analysis will be executed.
• Map stakeholders and advisory roles
• Signed-off advisory group charter that lists members, objectives, outputs, and meeting cadence.
• Clear list of deliverables and decision authorities for each advisory touchpoint.
• Documented protocol for triaging and responding to external data requests and public input during planning.
• Confirm stage scope and success criteria
• Prepare the template advisory meeting packet for the first advisory session.
• Create the external inquiries triage workflow and contact list for tracking discovery and public input.
• Review compiled planning outputs
• Formal sign-off on planning-stage artifacts or a documented list of required changes prior to final sign-off.
• Named owners and deadlines for all outstanding planning-stage open items.
• Confirmed date and prerequisites for the Engagement Scope kickoff meeting.
• Publish the planning-stage sign-off package including the assumptions register, scenario matrix, data request list, and advisory charter.
• Record the outstanding open items with owners and deadlines and distribute to stakeholders.
• Schedule the Engagement Scope kickoff and circulate the prerequisite checklist for that meeting.
• Confirmed list of required workshop outputs and measurable success criteria for the planning stage.
• Agreed schedule of sessions, required participants, and pre-work with deadlines.
• Established communications protocol for tracking decisions, questions, and data items between sessions.
• Publish the planning-stage schedule, participant list, and pre-work package with explicit due dates.
• Circulate the decision register template that will capture outputs and owners from each workshop.
• Collect and log outstanding questions and data gaps identified during kickoff for the next session.
• Recap baseline assumption categories
• Ratified assumptions register with each item marked as ratified, deferred, or requiring additional evidence.
• Prioritized data request list with formats and deadlines sufficient to meet the first modeling run schedule.
• Clear list of evidence or analyses needed to resolve deferred assumptions, with target resolution dates.
• Publish the ratified assumptions register and flag deferred items with required evidence and dates.
• Issue the prioritized data request package with explicit file formats and submission deadlines.
• Schedule follow-up detailed review for any assumption categories flagged as requiring more analysis.
• Present candidate scenario framing
• Approved scenario matrix with primary and alternate scenarios assigned for modeling runs.
• Documented list of sensitivities and clear trigger thresholds that will drive supplemental analysis.
• Confirmation of how scenarios map to regulatory acceptance criteria and stakeholder questions.
• Record finalized scenario definitions and parameter values for use in the modeling templates.
• Review timeline and decision milestones
• Define advisory group objectives and deliverables
• Identify and assign resolution steps for open items
• Apply acceptance criteria and regulatory considerations
• Propose recommended values or ranges for each assumption
• Decision exercise, mark assumptions as ratified, deferred, or require-data
• Select primary and alternate scenarios
• Lock engagement scope for modeling and deliverables
• Confirm participant list and roles
• Set cadence, materials, and decision authorities
• Finalize pre-work and data deliverables
• Establish protocols for handling external discovery and public input
• Agree immediate next steps and milestone for next stage kickoff
• Build prioritized data request and delivery schedule
• Define sensitivities and conditional triggers
• Agree meeting logistics and communications protocol

• Ingest and Clean Utility Load, Asset, and Market Data
• Produce 20-Year Load Forecast Dataset
• Run Multi-Scenario Capacity Expansion Optimization
• Run Production Cost and Dispatch Simulations
• Perform Resource Adequacy and Reserve Margin Study
• Model Renewable Integration and Operational Impacts
• Develop DSM Cost-Effectiveness Models
• Prepare Ownership vs PPA Financial Pro Forma
• Execute Stress Tests and Sensitivity Portfolio Runs
• Generate Model Transparency Package and Run Logs
• Draft IRP Filing Chapters and Technical Appendices
• Assemble Commission Filing Package and Regulatory Exhibits
• Support Commission Review: Discovery Responses and Hearings

Ingest and Clean Utility Load, Asset, and Market Data

• Do you have granular historical load data available (hourly or sub-hourly) from AMI or SCADA for the past 5 years? Options: Yes, No, Partial / only monthly or annual
• Which asset registries or lists will we receive (generator unit master list, nameplate capacity, commercial online dates, forced outage rates)? Options: Generator unit list, Distribution-connected DER inventory, Planned retirements, All of the above
• How many distinct fuel contracts or indexed fuel-price curves need to be ingested (e.g., coal supply, pipeline gas tolls, long‑term LNG index)? Options: None, 1-3, 4-10, More than 10
• When do you require a data completeness report that flags missing hours, suspicious zeroes, or meter time-zone issues for the historical load series? Options: At data kick-off (week 0), After initial ingest (week 1), After cleaning pass (week 2)
• Who on your team can provide generator heat rates, start-up profiles, and minimum-load constraints for thermal units?
• Describe any data access constraints we must plan for (e.g., VPN access to SCADA historian, restricted FTP, non-exportable PDFs of contracts).

Produce 20-Year Load Forecast Dataset

• Which baseline load forecast approach do you expect (trend-based econometric, end-use/disaggregated, weather-normalized hourly), and which historical drivers must be included? Options: Econometric trend, End-use/disaggregated, Weather-normalized hourly, Hybrid
• How many demand‑side scenarios should be included (e.g., high EV adoption, high EE, distributed PV uptake)? Options: 1 (single), 2-3, 4-6, More than 6
• Are there commission-mandated assumptions or regional planning studies we must incorporate (e.g., prescribed growth rates, mandated DER adoption schedules)? Options: Yes, No, Pending / under review
• Provide the planning horizon start and end years for the forecast and any mid-horizon checkpoint years you require in the dataset.
• What acceptance criteria will confirm the forecast dataset is approved for downstream modeling (for example: documented calibration to historical load within X% and provided residual diagnostics)?
• Which geographies must the forecast cover (service territory aggregated, county split, or substation/zone-level), and how should load be mapped to your network model? Options: Territory aggregate, County/zone split, Substation-level mapping, Custom mapping provided

Run Multi-Scenario Capacity Expansion Optimization

• Which candidate resource types should be modeled (utility-scale wind, utility-scale solar, battery energy storage, new combined-cycle, DSM portfolios, distributed PV)? Options: Utility-scale wind, Utility-scale solar, Battery storage, New thermal (CCGT/OCGT), DSM portfolios, Distributed PV
• Which scenario matrix dimensions must be included (fuel-price trajectories, carbon price ramps, technology capital-cost declines, load-growth variants)? Options: Fuel price, Carbon price, Capital cost, Load growth, Regulatory constraints
• How many optimization runs do you expect per scenario (single deterministic, stochastic realizations, or reliable optimization ensembles)? Options: Single deterministic, 3-10 realizations, More than 10 stochastic realizations, Reliable optimization
• Who will own constraint inputs such as local interconnection limits, transmission transfer capabilities, and resource eligibility screens?
• Which deliverables do you require from this module (capacity expansion tables by year, candidate build schedules, present-value revenue requirement curves)? Options: Annual build schedule, PV Revenue Requirement, Candidate rank order list, All of the above
• Do any procurement or policy constraints need to be hard-coded into the optimizer (e.g., must procure X MW of solar by year Y, retire unit Z by date)? Options: Yes, No, Conditional / discuss

Run Production Cost and Dispatch Simulations

• Which chronological resolution do you require for dispatch runs (hourly chronological, 5‑minute downsampled, representative weeks), and which nodes/zones must be simulated? Options: Hourly chronological, Representative weeks, Sub-hourly 5-minute (downsampled), Custom nodal/zone mapping
• Are there fuel-delivery or pipeline nomination constraints, merit-order rules, or bilateral PPA dispatch priorities that must be represented? Options: Yes, No, Some contracts only
• How should intermittent resource curtailment and must‑take contracts be treated when modeling dispatch and redispatch costs? Options: Curtailment allowed with penalty, Minimize curtailment, Must-take honored before dispatch
• Which reliability products or ancillary services must the simulation track (regulation, spinning reserve, non-spinning reserve, ramping reserve)? Options: Regulation, Spinning reserve, Non-spinning reserve, Ramping reserve, All listed
• Provide the expected thermal unit forced outage rate inputs and start-up cost conventions or indicate if we should use industry-standard default curves. Options: We will provide unit FO rates, Use industry defaults, Hybrid — provide some units
• Do you require production cost outputs formatted for the IRP appendices (hourly LMP proxy, hourly generation by unit, fuel burn by unit) or only aggregate cost metrics? Options: Full hourly outputs, Aggregate annual metrics only, Both detailed and aggregate

Perform Resource Adequacy and Reserve Margin Study

• Which adequacy metric do you require (Loss of Load Expectation LOLE, Expected Unserved Energy EUE, or planning reserve margin), and what minimum standard must be met? Options: LOLE target, EUE target, Reserve margin percentage, Regulatory-prescribed metric
• How should demand response and behind-the-meter solar be counted toward effective load carrying capability (ELCC) or capacity contributions? Options: Use ELCC curves, Fixed capacity credit, Do not count BTM resources
• Are there interconnection or import capability assumptions from neighboring balancing authorities that we must model in the adequacy assessment? Options: Yes, No, Limited seasonal interties only
• Which years should be used for probabilistic adequacy simulations and what weather-year set is preferred (most recent 10 years, 20-year climate sample, or synthetic extremes)? Options: Recent 10 years, Recent 20 years, Include synthetic extreme years, Custom set provided
• Who will validate the adequacy study inputs such as deratings during extreme heat, generator forced outage rates, and outage coordination windows?
• Are there mandatory planning reserve margin levels or commission guidance that define acceptance for adequacy outcomes? Options: Yes — commission-specified, No —utility-defined, Guidance pending

Model Renewable Integration and Operational Impacts

• Which renewable integration issues do you want quantified (ramping needs, curtailment frequency, system inertia, transmission constraints)? Options: Ramping needs, Curtailment frequency, System inertia impacts, Transmission constraints, All of the above
• Which solar and wind resource datasets should be used for stochastic profiles (satellite-derived time series, regional reanalysis, or vendor-provided resource files)? Options: Satellite-derived, Regional reanalysis, Vendor-provided, We will provide resource files
• How should distributed solar behind-the-meter exports be modeled for net load shape changes and midday duck curve impacts? Options: Explicit BTM export profiles, Apply aggregate PV reduction factor, Ignore BTM for planning
• Do you require operational solutions quantified, such as required fast-ramping capacity, storage sizing for ramp support, or curtailment mitigation costs? Options: Yes — storage sizing, Yes — fast-ramping capacity, No operational solutions required
• Provide the transmission constraint maps or transfer capability tables we should use to evaluate renewable deliverability and curtailment risk.
• Are any inverter-based resource requirements (e.g., synthetic inertia, frequency response settings) mandated by reliability entities that must be represented? Options: Yes, No, Unknown — need guidance

Develop DSM Cost-Effectiveness Models

• Which demand-side measures should be analyzed (EE measures, time-of-use pricing, direct load control, EV managed charging)? Options: Energy efficiency measures, Time-of-use pricing, Direct load control, EV managed charging, All listed
• Which cost-effectiveness test(s) are required by the commission or preferred by your team (Total Resource Cost TRC, Utility Cost Test UCT, Societal Cost Test SCT)? Options: TRC, UCT, SCT, Multiple tests required
• How should avoided costs be represented (long-run marginal cost, regionally adjusted avoided energy & capacity, time-varying avoided rates)? Options: Long-run marginal cost, Time-varying avoided rates, Regionally adjusted values, We will provide avoided cost inputs
• Estimate the annual program budget caps and implementation timeline that constrain DSM deployment in the modeling runs.
• Do you need measure-level participant assumptions (adoption rates, rebound effects, persistence) modeled, or is aggregate program-level modeling sufficient? Options: Measure-level detail, Aggregate program-level, Hybrid approach
• Are there existing evaluation, measurement, and verification EM&V studies we must incorporate as baselines for measure savings? Options: Yes — EM&V available, No — use literature defaults, Partial EM&V available

Prepare Ownership vs PPA Financial Pro Forma

• Which financial perspectives are required (levelized cost of energy LCOE, net present value NPV for utility ownership, contract comparators for PPAs)? Options: LCOE, NPV ownership, PPA contract comparators, All listed
• How should tax, depreciation, and financing assumptions be handled (assume utility tax status, provide project-level tax equity, or use a specified discount rate)? Options: Utility tax status, Project-level tax equity, Use specified discount rate
• Which contract structures must be modeled for PPAs (fixed price, escalating price, tolling arrangements, energy + capacity)? Options: Fixed price, Escalating price, Tolling, Energy + capacity
• Provide the expected capital-cost ranges and O&M assumptions for candidate owned resources or indicate if we should use industry benchmarks. Options: We will provide costs, Use industry benchmarks, Hybrid — provide some
• Do you require sensitivity runs for financing terms (different interest rates, debt/equity splits, or tax-equity structures)? Options: Yes, No, Conditional
• Which deliverable format do you need for comparison tables (year-by-year cashflow, levelized cost table, or executive summary pro forma)? Options: Year-by-year cashflow, Levelized cost table, Executive summary pro forma, All

Execute Stress Tests and Sensitivity Portfolio Runs

• Which stress-test scenarios must be included (extreme cold snap, prolonged heat wave, prolonged fuel-delivery disruption, rapid load shock from EV adoption)? Options: Extreme cold snap, Prolonged heat wave, Fuel-delivery disruption, Rapid EV load shock, All of the above
• How many sensitivity dimensions should be run against the preferred portfolio (fuel price ±20%, capex ±30%, forced outage rates ±50%)? Options: 1-2 dimensions, 3-5 dimensions, More than 5
• Do you need probabilistic portfolio risk metrics delivered (probability of meeting reserve margin, distribution of present-value revenue requirement)? Options: Yes — probabilistic metrics, No — deterministic only, Limited probabilistic outputs
• Who should be the technical contact for sign-off on contingency assumptions used in stress tests (fuel-curtailment rules, emergency imports, load-shedding order)?
• List any historical extreme events or blackouts we should replicate in stress tests and the relevant years for those events.
• Are there regulatory or board risk-tolerance thresholds we must report against (maximum acceptable EUE, mandated reserve margin floor)? Options: Yes — provide thresholds, No thresholds, Thresholds under review

Generate Model Transparency Package and Run Logs

• Which artifacts must be included in the transparency package (model input CSVs, run configuration files, seed random numbers, solver settings, and full run logs)? Options: Input CSVs, Run configuration files, Random seeds & solver settings, Full run logs, All listed
• What acceptance criteria will validate the transparency package is sufficient for commission review (reproducible run that yields provided results with documented inputs and solver versions)?
• Do you require an audited model reproducibility check where we re-run a selected scenario in your environment and produce matching outputs? Options: Yes — reproducibility check, No, Optional upon request
• How should sensitive or commercially confidential inputs (PPAs, fuel contracts) be redacted or provided under confidential exhibit procedures? Options: Full redaction per commission rules, Provide under NDA/CX procedure, No redaction required
• Provide preferred file formats and naming conventions for packaged deliverables (CSV naming, README with field definitions, folder structure).
• Are there preferred reproducibility metadata standards we should follow (e.g., versioned run manifest, checksum for key files)? Options: Yes — provide standard, No preference, We will accept consultant recommendation

• Non-Disclosure Agreement (NDA)
• Master Services Agreement (MSA)
• Statement of Work (SOW)
• Commercial Terms & Billing Milestone Schedule
• Data Access & Secure Transfer Authorization
• Data Processing Agreement (DPA)
• Security & Compliance Addendum
• Regulatory Compliance Addendum (conditional)
• Governance & Change Control Agreement
• Modeling Platform Access & License Confirmation
• Filing Authorization (conditional)

• Post-filing Transition Health Check (weeks 1-4)
• First Measurement Review, Discovery & Response Metrics (weeks 4-10)
• Regulatory Comment Burn-down Review (around day 60-90)
• Operational Monthly Check-in, Issue & Enhancement Tracking (monthly while review active)
• Lessons Learned and Close-of-Review Period Summary (end of review period)

• Update the enhancement tracker with delivery status and revised estimates for in-flight items.
• Schedule model reruns or data extractions needed to resolve outstanding comments, listing required inputs and expected delivery dates.
• Add newly requested supplemental analyses to the tracker with estimated completion windows.
• Status of open issues and enhancements
• Ensure the open enhancement request count and percent delivered are progressing toward targets recorded in Engagement Scope.
• Keep discovery SLA performance within agreed targets and address any SLA misses within the next reporting period.
• Maintain a prioritized 30-day action list for outstanding items and enhancements.
• Re-confirm post-filing roles and cadence
• Document root causes for any missed discovery SLAs and implement corrective steps with target dates.
• Publish the 30-day prioritized action list for the buyer's review and comment.
• Final metric summary
• Produce a final status on open issues remaining and percent of enhancement requests delivered versus targets recorded in Engagement Scope.
• Agree and capture the top 5 lessons learned with concrete, timebound improvement items for the next IRP cycle.
• Define the backlog retention plan and the artifacts to be handed over to ongoing planning or regulatory teams.
• Publish the final review-period report with metric summary, lessons learned, and backlog disposition.
• Deliver the archived model and dataset package and document the data retention location and access method.
• Create a short improvement plan containing the top 5 lessons with proposed changes for the next IRP cycle.
• Confirm the support cadence, meeting schedule, and escalation path for the review period.
• Validate that model access and required datasets are available to the buyer's reviewers.
• Create a prioritized list of immediate blockers with agreed target resolution windows.
• Publish the post-filing cadence calendar and escalation contact list.
• Deliver a short access validation report confirming datasets and model versions available to reviewers.
• Circulate the prioritized blocker list with target resolution dates for tracking in the ongoing cadence.
• Present discovery and supplemental analysis metrics
• Determine whether open discovery request count and average response time to discovery requests are trending toward targets recorded in Engagement Scope.
• Agree a set of corrective actions with delivery dates to close any metric gaps before the next review.
• Ensure the open-issue tracker is current and contains target resolution dates for each discovery item and supplemental analysis.
• Publish a metric dashboard extract showing discovery request counts and average response times with baseline targets from Engagement Scope.
• Document and schedule the corrective actions required to meet targets, with target completion dates.
• Add any emergent discovery items to the shared tracker and set target resolution dates.
• Present regulatory comment burn-down status
• Confirm whether regulatory comment closure rate and average days to close are meeting targets recorded in Engagement Scope.
• Produce a timebound burn-down plan that closes all prioritized regulatory comments within the agreed review period.
• Ensure all supplemental analysis requests are captured and prioritized in the shared tracker.
• Publish the burn-down plan with prioritized regulatory comments and target close dates.
• Validate data access and model environment
• Discovery SLA performance
• Lessons learned workshop
• Identify blockers to closure
• Diagnose root causes for any metric gaps
• Agree corrective actions and timelines
• Agree a burn-down plan
• Document backlog and retention plan
• Early adoption signals and usage checks
• Risk and dependency review
• Open issues triage
• Update priorities and next steps
• Agree follow-through artifacts
• Update the open-issue tracker
• Document supplemental analysis requests
• Agree immediate remediation actions