The situation
A financial services group operating under regulatory scrutiny, where HR data quality was not an operational nicety but a compliance obligation. The job architecture was inherited and inconsistent. New-hire onboarding took two weeks to reach data completion, which meant new employees spent their first fortnight unable to do parts of their job.
There was no People Analytics function. Workforce questions from the board were answered by whoever had most recently exported a spreadsheet.
The work
The job architecture came first, because almost everything else depends on it. A new global structure was designed and then implemented end to end in Workday, alongside expansions to Compensation, Absence and Recruiting. Job architecture work is unpopular because it is slow and invisible and touches everyone's title. It is also the thing that determines whether any subsequent analytics mean anything.
The onboarding data problem turned out to be a sequencing problem rather than a system limitation. Rebuilding the flow around what the platform could already do brought data completion from two weeks to one day, which in practice meant Day 1 productivity for every new joiner.
A People Analytics function was then built from scratch, including platform selection and implementation. Its output was a monthly workforce insight session presented to the Management Board jointly with the CHRO and CFO — which is the detail that matters, because analytics functions that report into HR alone tend to produce interesting numbers rather than decisions.
Throughout, the work was conducted in partnership with Finance, IT and Risk & Compliance to hold data quality and governance to a regulated standard.
What changed
A coherent global job architecture, Day 1 productivity for new joiners, and a workforce analytics capability with a standing seat at the Management Board.
The fifth measure
Regulated environments punish the wrong kind of simplification. The measure held here was whether the organisation could still answer a question it had not anticipated — which is what a job architecture is actually for, and why it was built before the analytics rather than after.