Rate Analyst
Conducting cost-of-service studies
What You Do Today
Allocate utility costs to customer classes based on cost causation — who causes the generation costs, transmission costs, distribution costs, and customer costs. This is the foundation of fair rates.
AI That Applies
AI automates cost allocation modeling, tests sensitivity to different allocation methods, and identifies which methodological choices have the biggest rate impacts.
Technologies
How It Works
For conducting cost-of-service studies, the system identifies which methodological choices have the biggest rate impacts. 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.
What Changes
Cost-of-service analysis that used to take months of spreadsheet work can be iterated in days. Sensitivity analysis is comprehensive instead of limited.
What Stays
The methodological choices — which allocators to use, how to handle joint costs, and how to resolve competing fairness principles — are 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 conducting cost-of-service studies, 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 conducting cost-of-service studies 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 are the top 5 reasons customers contact us, and which of those could be resolved without a human?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“How do we currently measure service quality, and would AI-assisted responses change that measurement?”
They understand the workflow dependencies that AI tools need to respect
a frontline supervisor
“Where are we spending the most time on manual budget reconciliation or variance analysis?”
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.