Situation
HR teams needed a consistent way to monitor job pipelines, candidate volume, stage conversion, and workload, instead of fragmented operational checks inside the ATS itself.
Data Analytics
Recruitment Analytics
A Power BI reporting layer that transforms recruitment operations into pipeline, workload, progress, and performance indicators.
Why it matters
Gives HR teams a consistent view of recruitment performance and candidate-flow health.
My role
BI developer and HR analytics designer
- 01Mapped Odoo recruitment entities, stages, candidate activity, and ownership fields into an analysis-ready reporting model.
- 02Defined pipeline, workload, progress, sourcing, and recruitment-performance measures with Power Query preparation and DAX logic.
- 03Connected the analytical layer to the operational ATS workflow so HR teams could move from a KPI to the underlying jobs, stages, and candidates.
Task
Build a Power BI reporting layer on top of the Odoo recruitment workflow that turns pipeline activity into shared, trustworthy indicators for managers and recruiters alike.
Action
- Operational Odoo fields, including jobs, candidates, stages, owners, activity, and time, are cleaned, standardized, and reshaped through Power Query into analysis-ready reporting entities.
- DAX measures calculate pipeline movement, workload, ageing, sourcing, and recruitment-performance indicators under controlled filters.
- Totals and stage logic are checked against the operational source before the measures are trusted for reporting.
- The reporting layer connects conceptually back to the underlying ATS Pro workflow, so a KPI can be traced to its jobs, stages, and candidates.
Result
Managers get an aggregate view of recruitment performance while recruiters can still trace any signal back to the underlying workflow, replacing fragmented operational checks with one shared monitoring view.
Technical implementation
How the solution was built.
Each layer connects an implementation choice to the decision or workflow it supports.
05 layers| Layer | Implementation | Operational purpose |
|---|---|---|
| Operational source | Odoo jobs, candidates, stages, owners, activity and time fields | Preserve the recruitment process behind each reported metric |
| Preparation | Power Query cleaning, typing, reshaping and relationship-ready keys | Convert operational records into analysis-ready reporting entities |
| Data model | Related job, candidate, stage, recruiter and calendar structures | Support consistent slicing by role, stage, owner and period |
| Measures | DAX indicators for pipeline volume, progress, conversion, workload and ageing | Make recruitment flow and bottlenecks measurable |
| Workflow connection | Aggregate Power BI views linked conceptually to underlying ATS records | Let managers monitor performance while recruiters retain operational detail |