Operating Model Designer
Shared Services & Center of Excellence Design
What You Do Today
You design the shared service functions and centers of excellence that create economies of scale without losing business-unit responsiveness — defining what's centralized, what's federated, and what's fully distributed.
AI That Applies
AI-modeled cost-benefit analysis that simulates different centralization scenarios, projecting cost savings, service quality impacts, and organizational disruption for each option.
Technologies
How It Works
For shared services & center of excellence design, the system draws on the relevant operational data and applies the appropriate analytical models. Predictive models fit to historical outcome data identify which variables are the strongest leading indicators, then apply those weights to current inputs to generate forward-looking scores. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The political negotiation.
What Changes
Trade-off analysis becomes quantitative. AI can model the cost, speed, and quality impact of centralizing versus federating different capabilities, making the case with data instead of opinion.
What Stays
The political negotiation. Centralizing a function means taking control away from business units. Making that work requires negotiation, service level agreements, and ongoing relationship management.
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 shared services & center of excellence design, 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 shared services & center of excellence design 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
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.