Fortune 1000 Insurance Company
New Organizational Operating Model
A new internal consulting group with unknown demand and no buy-in. Naming the demand was the definitional work.
Results
Demand-Based Scaling
Fixed Overhead Cost
Faster Knowledge Transfer
A group with no agreed purpose
Multiple acquisitions had left system integration problems, and leadership responded by standing up an internal consulting group. The group existed. What it was for did not, in any form the rest of the organization had agreed to.
That is the same failure in a different costume. Nobody could say what the group did, so nobody could say whether it was working, and the other leaders had not bought in because there was nothing specific to buy into.
Name the demand first
Lightweight discovery identified the high-priority initial services: not everything the group could theoretically do, but the small set there was real demand for.
A prioritization framework then sequenced those services, and skill set identification established what delivering each one actually required. Defining the service is what makes the staffing question answerable.
Scaling on demand rather than on headcount
The resulting model scales with emerging demand rather than carrying fixed overhead, which is the practical consequence of having defined the services rather than the department.
Where the AI went
Demand forecasting agents predicting service needs, automated prioritization by business impact, and knowledge transfer automation to support scaling, with knowledge transfer running roughly three times faster.
What repeats
A new internal function fails on definition before it fails on delivery. Naming the specific services there is demand for, rather than describing the department, is what makes it possible to sequence the work, staff it, and tell whether it worked.
This was not a manufacturer, and we are not going to pretend it was. What carries across is the failure, not the industry: an organization could not agree what its own numbers meant, so nothing built on top of them held.
The same failure elsewhere
Fortune 1000 Software Product Company
ERP Program Management Uplift
A company-wide SAP S/4HANA upgrade with no reliable read on its own status, because the reporting was only ever going to be as good as the definitions underneath it.
Midmarket B2B/B2C Company
eCommerce and Product Data After an Acquisition
Two companies, two product data models, one catalog that had to ship. The platform work landed six months early because the data model got settled first.
Where do your own definitions stand?
Twelve questions, and a note on what each bad answer costs you downstream.
Get the Definition Audit→