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Utility CFO

Manage storm and disaster cost recovery

Enhances✓ Available Now

What You Do Today

Track restoration costs during major weather events, ensure proper cost capture and documentation, file for regulatory recovery of prudently incurred storm costs, and manage the cash flow impact.

AI That Applies

Storm cost AI tracks restoration spending in real-time by category, ensures costs are captured in the correct accounts, and generates regulatory filing documentation automatically.

Technologies

How It Works

The system ingests restoration spending in real-time by category as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — regulatory filing documentation automatically — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Cost capture during the chaos of storm response is more complete and accurate. AI categorizes costs in real-time, preventing the documentation gaps that complicate recovery filings.

What Stays

You still manage the cash flow crisis during major events, negotiate recovery terms with regulators, and make the strategic decisions about securitization vs. traditional recovery.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for manage storm and disaster cost recovery, understand your current state.

Map your current process: Document how manage storm and disaster cost recovery works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: You still manage the cash flow crisis during major events, negotiate recovery terms with regulators, and make the strategic decisions about securitization vs. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Cost Tracking AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long manage storm and disaster cost recovery takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your CFO or VP Finance

What's the biggest bottleneck in manage storm and disaster cost recovery today — and would AI address the bottleneck or just speed up something that's already fast enough?

They're prioritizing which finance processes to automate first

your ERP or finance systems admin

If we automated the routine parts of manage storm and disaster cost recovery, what would the team do with the freed-up time?

They know what automation capabilities exist in your current stack

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.