Energy Efficiency Manager
Evaluating program impacts and cost-effectiveness
What You Do Today
Measure how much energy your programs actually saved — through billing analysis, measurement and verification, and evaluation studies. Prove to regulators that ratepayer money was well spent.
AI That Applies
AI performs billing analysis with weather normalization, identifies free-ridership and spillover effects, and generates evaluation reports from program and billing data.
Technologies
How It Works
The system ingests program and billing data 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 — evaluation reports from program and billing data — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
Impact evaluation is faster and more rigorous. AI handles the statistical analysis that used to require months of consultant work.
What Stays
Evaluation design and interpretation. Choosing the right methodology and defending results to regulators requires professional judgment.
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 program impacts and cost-effectiveness, 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 program impacts and cost-effectiveness 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
“Where are we spending the most time on manual budget reconciliation or variance analysis?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“What spending patterns would we want to detect early that we currently only see in quarterly reviews?”
They understand the workflow dependencies that AI tools need to respect
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.