Operational Decision Optimization Review (ODOP) — Utilities (Sample Detailed Deliverable)
Example work product for a mid-market electric distribution utility. All data is illustrative but realistic.
Executive Summary Cost • Uptime • Safety • Auditability
This ODOP review identifies where NorthRiver’s highest-impact operational decisions are slowed by fragmented inputs, unclear thresholds, and inconsistent governance. The deliverable provides a defensible decision model: inputs → constraints → tradeoffs → governance → audit trail.
Assets in Scope
31,750
Poles, transformers, switches, feeders
Customers
212,000
Mixed urban / rural; winter storm exposure
Annual O&M Budget
$94.5M
Ops + maintenance + vegetation + field services
Top Value Gap
Capital
High risk + low clarity + weak governance
Engagement scope (sample)
- Duration: 5 weeks
- Stakeholders: 15 interviews (COO, VP Ops, Asset Mgmt, Finance, Control Room, Safety)
- Workshops: 4 (maintenance, capital, outages, inventory)
- Systems reviewed: CMMS/EAM, GIS, OMS/SCADA, ERP/Finance, Inventory
- Deliverables: heatmap, visuals, tradeoff model + workbook, governance & audit trail, 90-day roadmap
Baseline performance snapshot (illustrative)
| Metric | Observed | Target |
|---|---|---|
| Backlog aging (WOs > 90 days) | 38% | < 20% |
| Repeat outages (same device, 30 days) | 11% | < 5% |
| Capital decision cycle (median) | 7.4 weeks | < 3.5 weeks |
| SAIDI (rolling 12 mo) | 132 min | < 110 min |
| Regulatory evidence turnaround | 10–15 days | < 3 days |
0) Sample Charts Example Data
Illustrative charts commonly included in an ODOP package (utilities context).
Decision latency by domain (Pre vs Post target)
Illustrative: Maintenance 21d → 10d; Capital 18d → 9d; Inventory 5d → 3d; Outage escalation 2d → 1d.
SAIDI drivers (rolling 12 months, illustrative)
Illustrative split of 132 min SAIDI: storms 54, equipment 34, vegetation 24, planned 16.
1) Decision Heatmap Diagnostic
Risk exposure vs clarity vs governance strength — leadership alignment view.
| Decision Domain | Risk Exposure | Decision Clarity | Governance Strength | Decision Latency |
|---|---|---|---|---|
| Maintenance Prioritization Backlog triage • deferrals • PM vs corrective | High | Medium | Weak | 7–21 days |
| Capital Allocation Renewals • replacement vs repair • benefit sizing | High | Low | Weak | 6–12 weeks |
| Outage Escalation Thresholds • comms cadence • incident commander | Medium | Medium | Moderate | 15–60 min |
| Inventory Replenishment Critical spares • min/max • lead-time risk | Medium | High | Strong | 1–5 days |
2) Visual: Decision Flow Architecture Before vs After
How decisions typically move today vs a structured ODOP model.
Current-State (Unstructured)
Structured Decision Model (Post-ODOP)
3) Visual: Tradeoff Curve Risk + Cost Reduced
Post-ODOP point is lower risk and lower cost (down-left) due to reduced rework and emergency spend.
4) Escalation Architecture Outage Response
Time-bound escalation with clear authority eliminates ambiguity and supports audits.
5) Governance + Audit Trail Controls
Authority matrix (sample)
| Decision Type | Owner | Approver | Evidence | SLA |
|---|---|---|---|---|
| Maintenance deferral (critical asset) | Maint Mgr | Ops Director | Risk score + inspection + mitigation | 24h |
| Capital reprioritization | Asset Mgmt | CFO + COO | Risk reduced/$ + constraints | 5d |
| Outage escalation S1/S2 | Control Room | Incident Cmdr | Severity criteria + ETR | 10–20m |
Decision log (sample)
6) 90-Day Roadmap Implementation
30 / 60 / 90 days
- 30: publish thresholds + authority matrix; start decision logs
- 60: CMMS mandatory deferral fields + standard failure codes; simple decision dashboard
- 90: tradeoff model v1 + sensitivity analysis; automate approvals + evidence attachments
Data dictionary (minimum)
- Asset_ID, Criticality_Class, Risk_Score
- Constraint_Band, Lead_Time_Weeks
- Decision_Rationale, Approver_Role
Client Context (Sample) Utility
Quick reader view for executives and stakeholders.
NorthRiver Electric — Snapshot
- Industry: Electric distribution utility
- Service territory: mixed urban/rural; storm exposure
- KPIs: SAIDI/SAIFI, safety incidents, regulatory evidence turnaround
- Systems: CMMS/EAM + GIS + OMS/SCADA + ERP/Finance
Top pain points (sample)
- Backlog prioritization varies by depot/supervisor
- Capital decisions slow and hard to defend
- Deferrals not consistently documented (audit friction)
- Lead-time risk not surfaced early (schedule slips)
Primary ODOP deliverables
Value statement
“We reduce downtime and budget shocks by making operational tradeoffs explicit, repeatable, and auditable — using your existing CMMS, GIS, OMS/SCADA and finance data.”