Utility Planner
Evaluating and selecting resource options
What You Do Today
Assess generation, storage, demand response, and non-wires alternatives. Determine the best mix of resources to meet future needs at the lowest cost and acceptable reliability.
AI That Applies
AI optimizes resource portfolios across reliability, cost, emissions, and risk criteria simultaneously. Models millions of portfolio combinations that manual analysis can't explore.
Technologies
How It Works
For evaluating and selecting resource options, the system draws on the relevant operational data and applies the appropriate analytical models. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The strategic assumptions — technology costs, policy direction, risk tolerance — are human decisions.
What Changes
Portfolio optimization is comprehensive. AI evaluates resource combinations that human analysts wouldn't think to test, often finding non-obvious optimal solutions.
What Stays
The strategic assumptions — technology costs, policy direction, risk tolerance — are human decisions. AI optimizes within your assumptions; you set them.
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.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for evaluating and selecting resource options, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long evaluating and selecting resource options 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.
Start These Conversations
Who to talk to and what to ask
your VP Operations or COO
“What data do we already have that could improve how we handle evaluating and selecting resource options?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“Who on our team has the deepest experience with evaluating and selecting resource options, and what tools are they already using?”
They understand the workflow dependencies that AI tools need to respect
a frontline supervisor
“If we brought in AI tools for evaluating and selecting resource options, what would we measure before and after to know it actually helped?”
They see the daily reality that AI tools need to fit into
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.