Allied Health Data Platform — 8 Brands, One Truth
Built a unified semantic data model across an 8-brand NDIS allied health group — consistent business rules and definitions, row-level security, compliance flags, and dashboards used from CEO to individual clinician. Also automated tiered bonus calculations that replaced a month-end spreadsheet nightmare.
Outcomes
CEO attributed 20% profitability improvement
8 brands, one platform: CEO to clinician
Automated NDIS bonus calculations
The Problem
An allied health group with 8 brands under one umbrella had no consistent way to measure performance across the business. Each brand tracked things differently — different definitions of 'active client', different revenue attribution, different compliance flags. Leadership couldn't compare brands. Clinicians had no visibility on their own performance. And every month, the finance team spent days manually calculating bonuses from spreadsheets held together with VLOOKUPs.
The Approach
Started by running discovery sessions with leadership across each brand — understanding not just the data, but how each part of the business actually worked and where the definitions differed.
Built a medallion architecture on Snowflake: raw ingestion, standardised staging with consistent business rule definitions, and a brand-agnostic mart layer that works for all 8 entities.
Implemented row-level security so the same report could be used at every level: a CEO sees the full group, a regional manager sees their brands, an individual clinician sees only their own data.
Built compliance identifiers and action flags directly into the data model — if a client record triggered a compliance risk, that flag surfaced in the dashboard with the context needed to act.
Automated the tiered NDIS bonus calculation entirely in SQL — every rule codified, version-controlled, and auditable. Finance went from 3-day reconciliation to same-day close.
The Result
One platform used by everyone from the group CEO down to individual clinicians, each seeing what they need and only what they're permitted to see. The CEO directly attributed a 20% profitability improvement to the visibility and insights the platform delivered. The bonus automation eliminated a recurring month-end crisis. More importantly: the business now has consistent definitions. When leadership asks why two numbers differ, there's a clear answer — not a two-day investigation.
Full Stack
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