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Business Intelligence
Two departments, two numbers, one meeting spent arguing about which is real.
Most organisations do not lack reporting. They lack agreement. We build the governed metric layer and the dashboards on top of it so that revenue, margin and churn mean the same thing in every room.
1
definitionPer metric, versioned and owned
−73%
reporting effortManual preparation hours removed
9 days
faster closeTypical improvement in month-end reporting
The board pack with three different revenue figures.
We were asked to review a board pack before a funding round. Revenue appeared three times, in three sections, with three different values. Each was defensible — one recognised on invoice, one on cash, one including a subsidiary consolidated differently — and each had been produced by a competent person in a separate spreadsheet.
The problem was not arithmetic. It was that no definition existed anywhere except inside individual analysts' formulas. Every report was a fresh interpretation, and the interpretations diverged quietly until they collided in a document that mattered.
We built a semantic layer where each metric is defined once, in version-controlled code, tested in the pipeline and reused by every dashboard and model downstream. Month-end reporting went from a fortnight of assembly to a governed process, and the arguing stopped. One truth, tested, with a name against it.
We stopped starting meetings by reconciling numbers and started them by deciding things.
Reporting that people trust enough to act on.
A dashboard nobody believes is worse than no dashboard, because it consumes attention and produces suspicion.
Semantic & metric layer
Every core metric defined once in code, tested, documented and owned, so downstream reports cannot quietly disagree with each other.
Executive & board reporting
Board-grade packs assembled automatically from governed data, with commentary structure, variance analysis and drill-through to source.
Operational dashboards
The live views that frontline managers actually use: pipeline, occupancy, queue, generation, collections, utilisation, service levels.
Financial & margin analytics
Unit economics, cost to serve, product and customer profitability, and the margin view that pricing decisions genuinely require.
Governed self-service
Certified datasets and templates so analysts across the business can answer their own questions without inventing new versions of the truth.
Forecasting & scenario analysis
Forward-looking views — demand, cash, occupancy, staffing — with scenario modelling that connects to the same governed definitions.
What agreement on the numbers is worth.
Each of these is written into the engagement as a number with an owner, a baseline and a review date.
OUTCOME 01
Decisions get made sooner
Removing the reconciliation ritual from every meeting returns hours to the most expensive people in the organisation and shortens the path from question to decision.
OUTCOME 02
Reporting stops consuming analysts
When assembly is automated, analytics teams move from producing reports to producing insight. Clients typically recover the majority of a full-time role per reporting cycle.
OUTCOME 03
AI becomes possible
Predictive work needs consistent historical definitions. Clients who build this layer first find their subsequent AI programmes materially faster and cheaper to deliver.
A reporting layer with owners and tests.
- Documented metric definitions in version control with named owners
- Tested transformation pipelines feeding certified datasets
- Executive, operational and financial dashboards in your BI tool
- Automated distribution of scheduled reporting and board packs
- Data quality monitoring with alerting before anyone sees a wrong number
- Analyst training so your team extends the layer without us
The engineering underneath.
Numbers from work already in production.
Measured against the baseline agreed with the client before the engagement started.
9 days
Faster month-end closeAutomated assembly on governed data
−73%
Manual reporting hoursAcross finance and operations teams
3 → 1
Revenue definitionsIn a board pack, before and after
What finance and analytics leaders ask.
- 01. We already have dashboards nobody uses. Why would this be different?Usually because the existing ones answer questions nobody was asking, or report numbers people do not trust. We start by asking which decisions need support, then build only what serves them.
- 02. Which BI tool should we use?Largely whichever your team already knows. The value sits in the governed layer beneath, which is tool-agnostic on purpose — you can change visualisation tools later without rebuilding the definitions.
- 03. Can you work with our finance team's spreadsheets?Yes, and we treat them as the specification. Those spreadsheets usually encode years of hard-won business logic, and our job is to move that logic into a tested, governed layer rather than to discard it.
- 04. How long before we see something?First governed dashboards typically land in six to ten weeks, starting with the metrics attached to the most consequential decision rather than attempting complete coverage.
Where to go next.
Bring us your last board pack. We will find the numbers that disagree.
The assessment reviews your current reporting, identifies conflicting definitions and prices the governed layer against the hours and decisions it would recover.
