Public Health solutions
Workforce Analytics for Public Health
Beryl Analytics has spent the better part of a decade building workforce analytics systems for public health agencies across New Zealand and Australia. We know which patterns generalise, which break, and how to ship value in weeks rather than quarters.
Why public health teams choose Beryl Analytics for workforce analytics
- Deep-domain models. Every workforce analytics model we build is tuned to the realities of public health agencies — not the synthetic benchmarks you see in vendor pitches.
- Production-ready, not throwaway. We ship pipelines, monitoring, alerting, and runbooks — the boring stuff that decides whether the system survives contact with reality.
- Operator-first design. Insights live inside the tools your team already uses, with thresholds and ownership matched to how decisions actually get made.
- Governance built in. Lineage, explainability, and access controls aren't an afterthought — they're scoped from day one and signed off with your security team.
- Outcomes measured in dollars. We track impact in revenue, cost avoided, or risk reduced — never in dashboard counts.
How we deliver workforce analytics engagements
- 01
Discovery sprint (week 1)
Two days on-site with your operators to map the workflow, half a day with leadership to align on the dollar metric, and an afternoon writing the scope memo we'll work to.
- 02
Spike the riskiest assumption (weeks 2-3)
Before committing to the build, we attack the assumption most likely to kill the project — usually data availability or operator adoption. A negative result here saves months.
- 03
Build, in public (weeks 4-8)
Daily commits to a shared repo your engineers can read. Weekly demo to the operator group. Nothing is built in private.
- 04
Production cutover (weeks 9-10)
A planned cutover with a rollback plan, monitoring, and a human in the loop for the first fortnight. We don't walk away from cold launches.
Frequently asked questions about Workforce Analytics for Public Health
How long does a typical Workforce Analytics engagement take for a public health business?
Most workforce analytics projects for public health agencies land a working production slice within 4-6 weeks, then harden and expand over the following 8-12 weeks. Larger public health programmes that touch multiple business units take 4-6 months end-to-end.
What data do you need to start a Workforce Analytics project in public health?
Minimum viable inputs are 12-18 months of historical transactional or operational data, basic entity reference tables, and access to the systems that will consume the output. We can work with messy data — cleaning is part of the engagement.
Can Beryl Analytics integrate workforce analytics with our existing public health agencies systems?
Yes. We're tool-agnostic and have integrated with Snowflake, BigQuery, Databricks, Salesforce, SAP, Oracle, custom in-house platforms, and dozens of public health-specific systems. Insights surface inside the tools your operators already use.
How do you measure success on a Workforce Analytics engagement?
Before we model anything, we agree the business decision the output will change and the dollar metric we're targeting — revenue lifted, cost avoided, or risk reduced. Workforce Analytics engagements in public health typically return 4-12x within the first year.
Do you work with public health businesses outside major NZ and AU cities?
Yes. We deliver remotely across New Zealand and Australia and visit on-site for discovery, key workshops, and go-live. Distance is not a blocker — many of our highest-impact workforce analytics engagements have been with regional public health agencies.