Problem
01
Every team reports different numbers.
02
Our dashboards are ignored.
03
We cannot answer basic questions quickly.
Outcomes
- Trusted, shared reporting
- Faster, better decisions
- Less time spent arguing about numbers
Scope
In scope
- Metric definition
- Dashboard and report build
- Adoption support
Not included
- Building the underlying data platform (see data engineering)
- Advanced predictive modelling (see AI)
Approach
Discovery
We agree the problem, the data and the constraints, and how success will be judged.
Delivery planning
We shape the approach, sequence the work and set out costs, risks and controls.
Build and test
We build in the open, test against real data and cases, and prove it before it goes near production.
Operational readiness, hypercare and closure
We hand over, support the first weeks of use, and confirm the outcome before we close.
Deliverables
Metrics layerDashboards and reportsAdoption plan
Technologies
Cloud data warehousesBI and dashboarding toolsSemantic and metrics layers
Controls
Every measure has a written definition and an owner. Row-level access is applied where data is sensitive. Charts do not rely on colour alone. Refresh failures alert a named owner.
Frequently Asked Questions
Which BI tool do you use?
Whichever fits your estate. The value is in the metric definitions and adoption, not the logo.
Can our team maintain it?
Yes. We build for self-service and hand over clear definitions.
Ready to scope this?
Tell us the decisions you need to support and we will build the reporting around them.