Pilot
Predictive diagnostics
Predictive diagnostics is the sensing layer. We identify the signals that precede failure — queue depth, confidence collapse, complaint pattern shifts — and wire them into thresholds that trigger action before a P1 happens. This is about telemetry and thresholds, not rehearsals.
Start here
Turn weak signals into practiced response.
Bring one service line into the pilot. We map early warning signals, define escalation thresholds, and craft an operator-ready response plan.
- Signal library and escalation triggers scoped to your telemetry.
- Rehearsal runbook with roles, timing, and documentation prompts.
- Pilot readout you can share with governance and operations leads.
Sample: Signal library excerpt
| Signal | Data source | Yellow threshold | Red threshold | Owner |
|---|---|---|---|---|
| API latency p99 | APM dashboard | >500ms for 5 min | >2s for 1 min | Engineering lead |
| Complaint sentiment shift | Support ticket NLP | Negative sentiment >30% | >60% or legal keyword match | Comms lead |
| Model output dispersion | Inference logs | Variance >2x baseline for 1 hr | >5x or empty responses >1% | ML engineer |
| Steward overtime | Time-tracking API | >12 hrs in a week for any person | >16 hrs or 3 consecutive days | Service owner |
What the program includes
- Signal mapping: Identify weak signals from operations, community support, and infrastructure that predict brittle stages.
- Threshold calibration: Set yellow and red thresholds that trigger escalation, not noise. We tune with your incident history.
- Alert wiring: Configure the pipeline from telemetry source to the person who needs to act.
Signal families we usually map
- Operational stress: Queue spikes, unresolved tickets, and repeated manual overrides.
- Model behavior drift: Precision/recall shifts, confidence collapse, and edge-case concentration.
- Care and trust indicators: Complaint tone, opt-out rates, and frontline reports of confusing outcomes.
Data inputs and collaboration cadence
- Week 1 intake: Pull telemetry snapshots, incident logs, and support data with your ops lead.
- Week 2 synthesis: Convert weak signals into thresholds, owners, and alert pathways.
- Week 3 rehearsal: Run one tabletop using real scenarios and refine the escalation model.
Typical outputs
- Signal library: A prioritized list of signals to monitor, with owners and escalation triggers.
- Diagnostic brief: A short report that summarizes failure modes, mitigations, and rehearsal priorities.
- Rehearsal runbook: A facilitation guide your team can reuse for tabletop drills.
Engagement length
- 2–3 weeks for an initial diagnostic and signal library.
- 4–6 weeks when paired with rehearsal sessions and a rollout support plan.
Engagement model
- Pilot review: Start with a scoped diagnostic across one service line to validate the signal library and action plan.
- Operator training: Facilitate tabletop scenarios that let stewards practice rotations, pauses, and recoveries.
- Rollout support: Stay on-call as you expand coverage, ensuring instrumentation and playbooks match real-world needs.
Request a session to shape the engagement to your sector and timeline.