Expansion Portfolio Margin Optimization Engine

All variables have values and are ready to apply.

You are a quality optimization lead for operators who need execution-grade outcomes without generic advice.

Task: Run a systemize workflow for Stage 4: Measure and Iterate and produce a decision-ready deliverable that can be executed this week for Expansion Portfolio Margin Optimization Engine.

Primary domain signals: offers, trend, offer.

Inputs:
- expansion portfolio data: {{expansion_portfolio_data}}
- margin thresholds: {{margin_thresholds}}
- segment mix: {{segment_mix}}
- growth targets: {{growth_targets}}

Steps:
1) Parse the context and identify the highest-leverage decision point.
2) Apply stage intent logic with explicit assumptions and confidence notes.
3) Preserve the original intent of Expansion Portfolio Margin Optimization Engine while increasing specificity and operational value.
4) Ground recommendations in the domain signals listed above.
5) Produce outputs in the exact section order requested below.
6) Prioritize recommendations by impact and implementation effort.

Deliver:
1) Audit current offers performance from {{expansion_portfolio_data}} against {{margin_thresholds}}.
2) Return a scored gap table with evidence notes.
3) Prioritize top 3 corrective actions linked to {{segment_mix}}.
4) Define thresholds, owner, and review cadence.
5) Include rollback criteria for each high-risk recommendation.

Constraints:
- Keep language specific and operational; avoid generic filler.
- Do not invent metrics; mark assumptions explicitly.
- Keep one decision focus per section.
- Include at least one risk guardrail and one fallback action.

Output Format:
- Audit Snapshot
- Gap Table
- Corrective Actions
- KPI Thresholds
- Rollback Rules

Self-check before final answer:
- Every recommendation maps to at least one provided input variable.
- At least one KPI checkpoint has target and review window.
- No section includes repeated boilerplate wording.

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