For numbers a leadership meeting can actually agree on
Business Intelligence Services
A number that two people read differently is worse than no number at all, because it turns a meeting into a dispute about whose spreadsheet is right. Business intelligence work here builds the dashboards and reports leadership actually opens, with every figure traceable to a single, agreed definition. Trust is the product, not the chart style.
How a trusted dashboard actually gets built
Metric definitions, source tracing and self-serve guardrails, walked through end to end.
80 secSample frame · video pending01Before any dashboard gets designed
A dashboard only helps if someone actually opens it.
Building a polished dashboard nobody trusts wastes the investment on both sides. Four questions settle whether the reporting problem is really a design problem.
Do two teams currently disagree on the same number?
If so, the problem is a metric definition, not a chart. Fixing the underlying calculation matters more than a redesign.
Is the underlying data pipeline actually reliable?
A beautiful dashboard on top of a broken pipeline just displays the wrong answer faster. The pipeline has to be solid first.
Who actually needs to act on this number?
A dashboard built for everyone often serves no one well. Naming the real decision-maker shapes what the view should show.
Does self-serve access respect data sensitivity?
Opening exploration to more teams raises the stakes on access control, which has to be designed in, not bolted on afterward.
| Reporting layer | Self-serve BI | Data pipeline | |
|---|---|---|---|
| What it answers | A fixed, known question | An open-ended question | Neither, it feeds both |
| Who touches it | Executives, decision-makers | Analysts and operators | Data engineering team |
| Change frequency | Stable, scheduled updates | Explored freely within limits | Changes with source systems |
| Owned by | This practice | This practice | Data engineering |
02Fixed before the build starts
What stays yours while the dashboard gets built
Every BI engagement is scoped the same way: the decisions you name, the dashboard we build around them, the numbers you receive, and the judgment call that always stays with you.
- Your side
You bring
- The spreadsheets and source systems currently in use
- The decisions leadership actually needs to make
- Who should see which numbers
- Our side
We build
- A single reporting layer sourced from the real systems
- Dashboards built around the actual decisions, not vanity metrics
- Role-based access so people see only what applies to them
- Your side
You receive
- One dashboard leadership can open and trust
- A defined metric catalogue with one owner per number
- Training so your team can build the next view themselves
Never leaves you
- Which metrics matter to the business
- The decisions made from the numbers
- Ownership of the underlying source systems
Where the line sitsWe carry the dashboard build. Which numbers matter to your business is a call only you can make, and we build around it.
03From a disputed number to a trusted one
Four stages, each closing on an artefact
Reporting projects fail quietly when a metric's definition was never actually agreed. This system makes each definition explicit and closes every stage with something you can inspect.
Define the metrics that matter
Every figure gets one agreed definition and one accountable owner before a single dashboard gets designed around it.
A metric catalogue with one owner eachDesign around the decision, not the data
Views are scoped to what a named decision-maker needs to act, not to every column the source system happens to have.
A dashboard built around real decisionsTrace every number to its source
Each figure on the dashboard links back to the calculation and source table behind it, so a dispute can be resolved in minutes.
A traced calculation behind every figureHand over training and ownership
Your analysts learn to build the next dashboard themselves, so growth in reporting needs does not require calling us.
A reporting layer your team can extend
04What actually drives the number
Four drivers, not a flat rate card
BI work is priced against the assessment, because these four factors change the effort by multiples, not by a small margin.
Number and variety of source systems
A single, clean source system reports cheaply. Several disagreeing systems need reconciliation work before a dashboard means anything.
State of the underlying pipeline
A well-modelled pipeline supports reporting quickly. A fragile one needs engineering fixes before reporting can be trusted.
Breadth of self-serve access required
A handful of fixed dashboards costs less than open self-serve exploration across many teams and data domains.
Governance and access complexity
Regulated or sensitive data needs row-level access controls that a purely internal, low-stakes dataset does not.
05Evidence and proof
Dashboards that end the argument, not restart it.
BI proof is adoption and decision speed, not chart count. Every record here waits for written client approval before production.
Explore case studiesFive spreadsheets became one dashboard leadership actually opens.
Nexa Foundry's plant leads compared conflicting spreadsheets before every review. A single reporting layer traced every figure to one agreed source.
- Spreadsheets retired
- Five into one view
- Time to a trusted figure
- Cut from days to minutes
A self-serve layer emptied a months-long report backlog.
Aster North's analyst team fielded every ad hoc question by hand. A guarded self-serve tool let most teams answer their own questions directly.
- Backlog reduction
- Substantial and sustained
- Reports opened without a ticket
- Most requests now
For the first time, finance and operations look at the same chart and agree on what it says.
Sample · pending client approval
06Read this first
When BI work is the wrong spend
Selling a dashboard project onto a pipeline nobody trusts costs more than it earns in credibility. The exits are marked before the pitch. When the build is justified, it runs on modern BI and warehouse tooling matched to your existing stack.
- Data engineering
The underlying pipeline is not reliable yet
A dashboard cannot fix bad data underneath it. The pipeline needs attention first, or the new dashboard inherits the same distrust.
- Data governance
The real question is a governance question
Who is allowed to see which data is a policy decision, not a dashboard feature, and it needs to be settled separately.
- Team extension
Your team should own this build
If your analysts already understand the tooling and just need capacity, team extension gets you there without an added delivery layer.
| Shape | Best when | You direct | We carry |
|---|---|---|---|
| Scoped build | The metrics and pipeline are settled | Priorities and acceptance | Dashboard and catalogue delivery |
| Delivery pod | Reporting needs will keep expanding | Product decisions each cycle | Engineering, design, releases |
| Team extension | Your leads run delivery well | Standards and roadmap | Named analysts and continuity |
07Straight answers
Asked before a reporting budget commits.
01Does BI include building the data pipeline?
No, this practice builds the reporting and self-serve layer on top of an existing pipeline. Building or fixing the pipeline itself sits with the data engineering practice, scoped separately.
02How do you handle metrics two teams calculate differently?
By tracing both calculations to their source and resolving the disagreement explicitly, then publishing one agreed definition with a named owner so the dispute cannot resurface quietly.
03What BI tools do you work with?
Modern warehouse-native BI and visualisation tools chosen against your existing stack, rather than a default. The harder work is the metric catalogue underneath, which outlasts any single tool choice.
04Can self-serve access expose sensitive data by accident?
Only if access controls are treated as an afterthought. Row-level and role-based restrictions are designed into the self-serve layer before it opens to more teams.
05What does a business intelligence build cost?
Scoped engagements are priced against source system count, pipeline readiness and self-serve breadth from the assessment. Ongoing delivery runs as a monthly team commitment.
06Can you take over dashboards another vendor built?
Yes, starting with an audit of what the current dashboards actually measure rather than a rebuild pitch. Many inherited dashboards need targeted metric fixes, not a full replacement.
07Do you train our team to build new dashboards?
Yes, training is scoped alongside the initial build, so your analysts can extend the reporting layer themselves once the engagement ends.