Persistent service failures
Assesses unsuccessful remediation, service-level commitments and repeat escalations linked to the same root cause. Provides a policy-backed recommendation with an owning team and the authority required.
— Operations & Process
Escalation Decision Engine
Weighs an open case against your escalation policy, its risk and its commercial exposure, then returns a governed recommendation to hold, monitor, escalate or take it to executive level, with the reasoning shown and an owner sign-off required — nothing is escalated automatically.
- Operations & Process
- Traceable reasoning
- Runs anywhere
1–2 hours → ~5 minutes
For one document, brief or record at a time
No coding required
- Input
- Escalation request and service case details
- Output
- Hold, monitor, escalate or executive escalation recommendation
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 hours per run
— USE CASES
What people use Escalation Decision Engine for
Sensitive customer relationships
Weighs customer sentiment, formal complaints, churn notices and commercial exposure. Distinguishes cases requiring closer monitoring from those warranting escalation or executive involvement.
Serious risk indicators
Applies mandatory policy triggers for regulatory, safety, data-loss and legal-threat concerns. Identifies the relevant trigger and policy clause while preserving mandatory owner approval.
Executive escalation requests
Tests requests for executive involvement against contract-value thresholds and delegated authority. Produces a defensible rationale for the recommended escalation level rather than relying on the urgency of the request alone.
What it works from
- Escalation request and service case details
- Account context and commercial exposure
- Escalation policy and authority matrix
- Remediation history and related escalations on the same root cause heading
What you get back
- Hold, monitor, escalate or executive escalation recommendation
- Assessment breakdown across remediation, customer sentiment, commercial exposure and service-level position
- Applicable mandatory risk triggers and cited policy clauses
- Required authority level and owning team
Why this is expensive by hand
Escalation decisions become difficult to defend when customer pressure, commercial exposure and operational risk compete for attention. Persistent service failures is the typical trigger — assesses unsuccessful remediation, service-level commitments and repeat escalations linked to the same root cause. Provides a policy-backed recommendation with an owning team and the authority required. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 hours of manual work.
How this Skill produces it
As a Skill, the work is already sequenced. You bring the evidence, and the run produces hold, monitor, escalate or executive escalation recommendation plus assessment breakdown across remediation, customer sentiment, commercial exposure and service-level position. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. The practical effect: 1–2 hours of manual work becomes a ~5 minutes run, held to an identical standard on the tenth engagement as on the first.
Who it's for
- Operations and continuous improvement leads
- Transformation and automation teams
- Service delivery and shared services managers
- Consultants running process diagnostics
Run it in Skillsize — or export it anywhere
Escalation Decision Engine exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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