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Utility Planner

Preparing integrated resource plans (IRPs)

Enhances✓ Available Now

What You Do Today

Develop the utility's long-term resource plan — a comprehensive document filed with regulators that lays out how the utility will meet customer needs for the next 10-20 years.

AI That Applies

AI generates scenario analyses, sensitivity runs, and visualization of plan outcomes. Automates the comparison of alternative resource portfolios across multiple criteria.

Technologies

How It Works

For preparing integrated resource plans (irps), the system draws on the relevant operational data and applies the appropriate analytical models. The simulation engine runs thousands of scenarios by varying each uncertain input across its probability range, building a distribution of outcomes that quantifies the risk. The output — scenario analyses — surfaces in the existing workflow where the practitioner can review and act on it. The narrative, stakeholder engagement, and regulatory strategy.

What Changes

Sensitivity analysis and scenario runs that used to take weeks happen in hours. The IRP explores more alternative futures more thoroughly.

What Stays

The narrative, stakeholder engagement, and regulatory strategy. An IRP is as much a political document as a technical one — that requires human skill.

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 preparing integrated resource plans (irps), understand your current state.

Map your current process: Document how preparing integrated resource plans (irps) works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The narrative, stakeholder engagement, and regulatory strategy. 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 IRP modeling platforms 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 preparing integrated resource plans (irps) 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 VP Operations or COO

How would we know if AI actually improved preparing integrated resource plans (irps) — what would we measure before and after?

They're prioritizing which operational processes to automate

your process improvement or lean lead

If we automated the routine parts of preparing integrated resource plans (irps), what would the team do with the freed-up time?

They understand the workflow dependencies that AI tools need to respect

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.