Purpose
Turn raw fulfillment metrics from a 3PL partner into a clear compliance scorecard against contracted SLAs, then generate ranked accountability actions with named owners and deadlines — so a fulfillment operations manager can walk into any partner review or escalation with evidence instead of anecdotes.
When to Use
Invoke this skill when the user asks to:
- Summarize daily or weekly 3PL SLA performance against contracted targets
- Prepare a partner business review or QBR from operational data
- Identify which SLA breaches happened, how severe they were, and who owns the fix
- Build an accountability trail for a chronically underperforming fulfillment partner
- Escalate a recurring problem (late shipments, high error rate, damage claims) with documented severity
- Track whether prior corrective actions actually moved the metrics period-over-period
Inputs Required
Before starting, collect:
- Reporting period: The date range being evaluated (e.g., "Week of Mar 3–9" or "Mar 12 daily")
- SLA targets: The contracted thresholds for each metric (e.g., on-time ship ≥98%, order accuracy ≥99.5%, dock-to-stock ≤24h)
- Actual performance data: The raw numbers for the period — can be pasted metrics, a table, or a data dump
- Order/unit volume: Total orders or units for the period (needed to weight breach severity and dollarize impact)
- Cost/penalty context: Per-unit cost of a miss, chargeback rate, or SLA penalty clause if defined
- Prior period data: Last period's numbers, if available, to show trend
- Known context: Any peak events, weather, systems outages, or excused exceptions
If SLA targets are missing, apply standard fulfillment benchmarks (on-time ship 98%, order accuracy 99.5%, inventory accuracy 99%, dock-to-stock 24h, RTS/damage <1%) and flag them as assumed. If cost context is missing, report volume-based severity without dollar figures and note the gap.
Instructions
Step 1: Build the Compliance Scorecard
For every metric provided, produce a row with:
- Metric name
- SLA target
- Actual result
- Variance (percentage points or absolute, signed +/-)
- Status: ✅ Met / ⚠️ At Risk (within 1 point of target) / ❌ Breached
Cover the core 3PL SLA categories where data exists:
- Speed: On-time ship rate, dock-to-stock time, order cycle time, same-day cutoff adherence
- Accuracy: Order accuracy (right item/qty), pick accuracy, inventory record accuracy, shipping label accuracy
- Quality: Damage rate, return-to-sender rate, mis-ship/reship rate, claims rate
- Availability: Backorder/OOS incidents attributable to 3PL, receiving delays
- Responsiveness: Ticket resolution time, exception notification timeliness
Step 2: Rank Breaches by Severity
Score each ❌ Breached and ⚠️ At Risk item on a composite of three factors:
- Magnitude: How far below target (variance size)
- Volume exposure: How many orders/units the miss touched
- Trend: Improving, flat, or worsening vs. prior period
Assign a severity tier:
- Critical: Large variance × high volume, or a metric worsening for 2+ periods
- High: Meaningful variance on high-volume flow, or first breach on a customer-facing metric
- Moderate: Small variance or low-volume exposure
- Watch: At-risk items trending toward breach
Step 3: Categorize Root Cause
For each breach, assign the most likely root-cause bucket based on the data pattern (state it as a diagnosis, not a certainty):
- Labor/capacity: Misses cluster on high-volume days or specific shifts
- Process/SOP: Accuracy or damage issues consistent across volume levels
- Systems/integration: Sync errors, inventory mismatches, EDI/order-flow failures
- Inbound/receiving: Dock-to-stock and OOS issues trace to receiving delays
- External/excused: Peak surge, carrier failure, weather — flag as candidate for exception review
Step 4: Dollarize the Impact
Where cost context exists, estimate the financial impact per breach:
- Missed shipments × per-miss cost (expedite, chargeback, or penalty)
- Accuracy misses × reship/return cost
- Damage/claims × unit cost + claim handling
- SLA penalty clauses triggered, if applicable
Present a period total and per-metric breakdown. Where cost data is absent, quantify in affected-order counts instead.
Step 5: Generate the Accountability Action List
Produce a ranked list (Critical first) where each action has:
- The issue (one sentence, tied to the specific breach)
- The action required (specific and verifiable — "Provide RCA on the 47 mis-shipped orders from Mar 6," not "improve accuracy")
- Owner: 3PL partner / internal ops / joint
- Deadline: Concrete date or SLA-standard response window (e.g., RCA within 48h)
- Verification: How next period's data will confirm the fix worked
Step 6: Trend & Escalation Flags
- Note any metric breached in 2+ consecutive periods → mark as chronic and recommend formal escalation per contract terms
- Note any metric that recovered vs. prior period → credit it, so the record is balanced
- Recommend one escalation path if a Critical or chronic issue exists (documented notice, penalty invocation, QBR agenda item, or partner-change evaluation)
Output Format
- Structure: Scorecard table → severity-ranked breach summary → root-cause + dollar impact → accountability action list → trend/escalation flags
- Length: 500–900 words plus tables (scales with number of metrics)
- Format: Compliance scorecard as a table; breaches and actions as ranked structured lists; a short executive summary paragraph up top
- Sections: Executive Summary (2–3 sentences) → SLA Compliance Scorecard → Breach Severity Ranking → Root Cause & Financial Impact → Accountability Action List → Trend & Escalation Flags
- Tone: Operations manager — factual, evidence-first, non-emotional. Written to survive being forwarded to the partner. No hedging on numbers, no blame language beyond documented cause.
Quality Checklist
Before delivering output, verify:
- [ ] Every metric provided appears in the scorecard with target, actual, variance, and status
- [ ] Each breach has a status, severity tier, and root-cause category — none left unclassified
- [ ] Severity ranking accounts for volume exposure, not just variance size
- [ ] Every accountability action has an owner, a deadline, and a verification method
- [ ] Financial impact is dollarized where cost context exists, or stated in order counts where it does not
- [ ] Any assumed SLA target (used because none was provided) is explicitly flagged as an assumption
- [ ] Metrics breached across consecutive periods are flagged as chronic when prior data is available
Notes
- The single most useful output for partner reviews is the accountability action list — resist the urge to bury it under analysis; keep actions specific enough that "done / not done" is unambiguous next period.
- Always credit recovered metrics. A scorecard that only lists failures loses credibility with the partner and weakens escalation leverage when a real Critical issue arises.
- For daily runs, keep the scope tight (scorecard + top 3 actions). Reserve full root-cause and dollarization depth for weekly and QBR-level reviews.
- When data is ambiguous about cause, state the most probable bucket and request the specific data that would confirm it — this itself becomes an accountability action on the partner.
How to use this skill
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- Drag this file into a new chat, or copy and paste its contents
- Send your task or request as your next message — the AI will apply the skill where it fits
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