A worked example of the program's change-control process at full depth. The Change Control Log is the register of all changes; this is the underlying document for a single request — the artifact that a Tier 2 change actually requires before any board will consider it. CR-003 was raised in Week 4 of Phase 0, when legacy claims data profiling surfaced fragmentation materially worse than the estimate the BRD-01 schedule was built on.
1 · Request Header
| Change Request ID | CR-003 |
| Title | Legacy claims data remediation — additional scope and effort to support BRD-01 model training |
| Change type | Scope addition with cost and schedule impact |
| Tier | Tier 2 — exceeds Program Director standing authority (scope change of any size; budget > $500K) |
| Status | Under review |
| Date raised | 10 September 2026 (Week 4, Phase 0) |
| Requested by | Data & Cloud AI Platform Lead |
| Change owner | C. Tyrrell, Program Director |
| Approval authority | Executive Steering Board (cost/schedule) with AI Governance Board endorsement (model data quality) |
| Target decision date | 25 September 2026, alongside the AI Readiness Assessment Report |
| Linked risk | RSK-01 — Legacy claims data fragmentation (inherent rating: Likely × High) |
2 · Background & Description of Change
The Phase 0 AI Readiness Assessment includes a data-quality profiling exercise across the claims and prior-authorization source systems that will feed BRD-01. Profiling is substantially complete and has established that source data is materially more fragmented than the planning assumption used to build the BRD-01 schedule.
Specifically, profiling has found: inconsistent provider identifiers across three claims platforms arising from historical acquisitions; incomplete diagnosis and procedure coding on a significant proportion of older records; no reliable linkage key between prior-authorization requests and their resulting claims; and inconsistent handling of adjustment and reversal records. Individually each is manageable. Together, they mean that the training dataset assembled from these sources would not be fit to train a prior-authorization decisioning model to the standard the program's Master Test & QA Strategy requires — specifically dimensions 1 (data quality and representativeness) and 5 (fairness), since coding gaps are not evenly distributed across the member population.
This request seeks approval for a dedicated data remediation workstream — additional engineering effort, tooling, and elapsed time — to establish a governed, linked, quality-assured claims dataset before BRD-01 model development begins, rather than discovering the problem during model training.
3 · Reason for Change & Consequence of Not Acting
The program's planning assumption was that source claims data would require standard cleansing within the effort already provided in WBS element 2.0. Profiling has disproved that assumption. This is not a scope preference; it is a correction to a factual estimate, surfaced by the Phase-0 activity designed to surface exactly this class of problem.
4 · Options Analysis
| Option | Description | Cost | Schedule Impact | Residual Risk |
|---|---|---|---|---|
| Option A Do nothing | Proceed on existing data with in-flight cleansing during model development | $0 | None initially; high probability of 3–5 month rework later | Unacceptable — near-certain IMV failure on data quality and fairness |
| Option B Partial remediation | Remediate identifier linkage only; accept coding gaps and handle statistically during modelling | $740,000 | 3 weeks to BRD-01 requirements sign-off | Moderate — linkage resolved, but coding gaps still create sub-population bias exposure |
| Option C Full remediation Recommended | Dedicated remediation workstream: identifier resolution, coding completion where recoverable, PA-to-claim linkage, adjustment/reversal normalization, plus a permanent data-quality rules engine | $1,240,000 | 6 weeks to BRD-01 requirements sign-off; no impact to the 30 Sep 2027 production milestone (absorbed within BRD-01 float) | Low — dataset fit for training and for fairness assessment |
| Option D Defer BRD-01 | Re-sequence so BRD-02 leads and BRD-01 follows after remediation | $2,100,000 | Re-baselines the entire program; BRD-01 production slips ~9 months | Rejected — sacrifices the flagship, disrupts CMS-0057-F coordination, poor value |
5 · Impact Assessment
Assessment below is for the recommended Option C.
| Dimension | Impact | Detail |
|---|---|---|
| Scope | Addition | New deliverable "Legacy claims data remediation" added under WBS 2.0 Data & Cloud AI Platform. No existing scope removed. |
| Cost | +$1,240,000 | Funded from contingency reserve, not from a budget increase. Reserve reduces $9.0M → $7.76M (7.8% of authorized baseline, remaining within acceptable range for the risk profile). |
| Schedule | 6 weeks | BRD-01 requirements sign-off moves 18 Dec 2026 → 29 Jan 2027. Platform Foundation (12 Mar 2027) and BRD-01 Production (30 Sep 2027) milestones are unchanged — the six weeks are absorbed within existing float on the BRD-01 path. |
| Resources | +6 FTE, 14 weeks | 4 data engineers (offshore, synthetic/de-identified work), 2 onshore data analysts for PHI-bearing linkage work. Sourced through existing Pulaski SOW-01 capacity; no new vendor. |
| Quality | Positive | Directly improves the evidence base for test dimensions 1 and 5. Reduces probability of an IMV failure at the BRD-01 production gate. |
| Risk | Reduces RSK-01 | Moves RSK-01 from Likely × High toward Possible × Moderate once remediation completes. Introduces minor new delivery risk around remediation duration, tracked as a sub-risk. |
| Benefits | Neutral to positive | No change to the $27.2M steady-state benefit case. Protects the largest benefit stream (PA automation, $12.8M/yr) from a delayed or degraded launch. |
| Compliance | Positive | A governed, lineage-traceable dataset strengthens the program's position under NAIC and state AI-in-insurance scrutiny. |
| Contractual | None | Within SOW-01 scope and envelope; no amendment required. Milestone payment schedule unchanged. |
6 · Recommendation
7 · Implementation Plan (if approved)
| Step | Activity | Owner | Duration | Completion |
|---|---|---|---|---|
| 1 | Mobilize remediation team; confirm onshore/offshore data-access boundaries with Data Privacy Office | Platform Lead / HR | 1 week | 2 Oct 2026 |
| 2 | Provider identifier resolution across the three claims platforms | Data engineering | 4 weeks | 30 Oct 2026 |
| 3 | Prior-auth to claim linkage key construction and validation | Data engineering | 3 weeks | 20 Nov 2026 |
| 4 | Diagnosis/procedure coding completion where recoverable; gap documentation where not | Data analysts + Clinical | 4 weeks | 18 Dec 2026 |
| 5 | Adjustment and reversal normalization | Data engineering | 2 weeks | 8 Jan 2027 |
| 6 | Data-quality rules engine deployed; sub-population coverage verified for fairness testing | Platform + IMV | 2 weeks | 22 Jan 2027 |
| 7 | Dataset governance sign-off; BRD-01 requirements sign-off | AI Governance Board | 1 week | 29 Jan 2027 |
8 · Affected Baselines & Artifacts
If approved, the following are updated under configuration control within five business days of the decision:
| Artifact | Change required |
|---|---|
| Program Budget | Contingency ledger entry: $1.24M drawn, reserve balance $7.76M. Category and workstream views updated; total authorized baseline unchanged at $99.0M. |
| WBS Budget Rollup & Resource-Loaded WBS | New deliverable and seven work packages under element 2.0; resource assignments and dates added. |
| Program Management Plan | Milestone table: BRD-01 requirements sign-off 18 Dec 2026 → 29 Jan 2027. |
| RAIDD Log | RSK-01 updated to "mitigation in execution" with revised residual rating; new sub-risk for remediation duration. |
| BRD-01 | Data requirements section updated to reference the remediated dataset and its governance sign-off. |
| Change Control Log | CR-003 status moved to Approved with decision date and approver record. |
| Program Dashboard | Contingency drawdown reflected; RSK-01 heat-map position updated at next reporting cycle. |
9 · Approval Routing & Decision Record
Tier 2 changes require the relevant board's approval. Because this request affects both the cost baseline and model data quality, it is routed to both the Executive Steering Board and the AI Governance Board, with Program Finance and SOX review preceding the decision.
| Reviewer / Approver | Role in decision | Status | Date |
|---|---|---|---|
| Program Finance (A. Rodriguez) | Cost validation and contingency impact | Reviewed — supports | 12 Sep 2026 |
| SOX / Financial Controls | Controls review (contingency drawdown) | Reviewed — no objection | 15 Sep 2026 |
| Data Privacy Office (E. Sato) | PHI access boundaries for remediation work | Reviewed — conditions noted | 16 Sep 2026 |
| Chief Enterprise Architect (D. Chen) | Architecture impact — data-quality rules engine | Reviewed — supports | 17 Sep 2026 |
| AI Governance Board (S. Khurana) | Endorsement — model data quality and fairness basis | Scheduled | 25 Sep 2026 |
| Executive Steering Board (Chair: M. Kavanagh) | Approval authority — cost and schedule baseline | Scheduled | 25 Sep 2026 |
Decision block
| Decision | ☐ Approved ☐ Approved with conditions ☐ Rejected ☐ Deferred |
| Conditions (if any) | |
| Executive Sponsor signature | |
| Date |
10 · Audit Trail
| Date | Event | Actor |
|---|---|---|
| 08 Sep 2026 | Profiling findings escalated from the AI Readiness Assessment workstream | Data & Cloud AI Platform Lead |
| 10 Sep 2026 | CR-003 raised and logged; tier assessed as Tier 2 | PMO (T. Valdez) |
| 11 Sep 2026 | Options analysis and impact assessment drafted | Program Director + Platform Lead |
| 12–17 Sep 2026 | Functional reviews completed (Finance, SOX, Privacy, Architecture) | Respective functions |
| 25 Sep 2026 | Scheduled for joint ESB / AIGB decision | PMO |