Functional Topic
Supply Chain Operating Model, Org Design & Workforce Benchmarking
Industry
Energy & Utilities
Support Needed
Organizational Benchmarking & Operating Model Consultant
Duration
12 Weeks
A leading U.S. energy utility wanted to assess whether its supply chain organization was structured appropriately to support current spend and future growth. Leadership needed clarity on:
The objective was to create a fact base for workforce planning and operating model decisions.
I led the benchmarking assessment across supply chain structure, role allocation, and functional capacity. My responsibilities included defining the benchmarking approach and peer comparison framework; assessing spend supported per FTE across the organization; reviewing sourcing, procurement operations, PMO/CoE, and planning coverage; and translating findings into executive-level structural implications.
Peer distribution shown as box-and-whisker (min–Q1–Q2–Q3–max) · Illustrative
So what: the utility supports more spend per FTE than the peer range — a lean, broad-scope structure, not an over-resourced one.
Each row = peer box-and-whisker (Q1–Q3 IQR + whiskers); ◆ = this utility · Illustrative
So what: every core role sits at or above the peer upper quartile — spend responsibility is concentrated, with limited dedicated execution headroom.
Overall structure
The organization operated above peer benchmarks for spend supported per FTE, enabled by broad role scope within a compact structure.
Role design
Category Managers and Sourcing Specialists each carried higher spend responsibility than peers, with execution work embedded within manager roles.
Functional footprint
Procurement/Ops and PMO/CoE supported higher spend per FTE — a lean footprint, limited centralized enablement, and no standalone planning function.
Sustaining this position as spend scales requires targeted structural reinforcement: clearer ownership of spend- and coordination-heavy activities, added execution support in Procurement/Ops, incremental PMO/CoE capacity, and formal planning capability where variability is highest.
Illustrative & anonymized. Client identity withheld; benchmarking data is directional and demonstrates the framework rather than reports exact figures.