Workforce data lives in many places. Payroll runs in one system. HCM in another. Position management in a third. Spreadsheets fill the gaps. Each system has its own keys and its own definitions. Headcounts disagree and nobody can say which figure is right.
We bring this data together into one model. Every employee once. Every position once. Every pay component with a defined meaning and a date. The model is documented so that the next analyst can reproduce every number.
How we work
- Inventory the sources. Which systems hold which data and who owns them. Payroll, HCM, position management, time, the spreadsheets nobody mentions.
- Map keys and histories. Employee, position, job, organisational unit and cost centre. Which keys are stable and which are reused with a different meaning.
- Define the measures. Pay components, full-time equivalents, reference dates and periods. One written definition per figure.
- Transform into one model. Documented rules turn the sources into one table per entity. Blanks stay blank and zeros stay zero.
- Reconcile. Headcounts, payroll totals and full-time equivalents are checked against every source before anyone sees a chart.
- Provision. Power BI datasets, HRIS loads and reporting extracts with a data dictionary. Repeatable pipelines in Power Query or SQL.
What you get
- One documented workforce data model with stable keys
- Reconciliations against every source system
- A data dictionary that states what each figure means
- Repeatable pipelines and the Excel template for Compensation Explorer
Where it usually starts
- Three systems report three different headcounts.
- Payroll totals do not match the HCM extract.
- A new HRIS needs clean positions and jobs before it can go live.
- A pay analysis stalls because nobody trusts the input table.
