Data Analytics
A dashboard nobody opens is a cost, not an asset. We start from a decision a real person makes on a real schedule, work backwards to the numbers it needs, and build only that. Usually it belongs inside the software your team already uses rather than in a separate tool they have to remember.
The first question is never which chart. It is who decides what, how often, and what they do differently depending on the answer. If no action changes, the metric is decoration and we will say so before building it.
That conversation usually shrinks the scope hard. A manager who needs to know which branch is behind on attendance this week does not need forty charts; they need one number, a comparison, and a way to see which members stopped coming.
For the multi-branch gym platform we built, management had no reliable view of attendance or revenue across locations — the data existed, but it was trapped in spreadsheets, manual check-ins and a till that did not know who the member was. The fix was not a separate BI tool. It was making the operational system record the right events, then surfacing them where staff already worked.
GoalEnvision, a strategy execution product we built, works the same way: progress is tracked across market, sales, operations, employees and finances inside the tool teams already use, rather than reported into a deck once a quarter.
Most analytics projects fail on trust rather than on charts. Two reports disagree, nobody can say which is right, and people go back to their own spreadsheet. We define each metric once, in writing, with the filters and the time window stated, and keep that definition next to the number.
We also make the lineage visible: which system the figure came from, when it was last refreshed, and what happens when a source is late. A number with no provenance gets argued with; a number that shows its working gets used.
Event and metric design so the product records what you will later want to measure. Reporting inside the application for the people running the day, and extracts or a warehouse connection for the analysts who want to go deeper.
Scheduled reports that arrive without anyone asking, alerts for the thresholds that matter, and role-based access so each branch, team or client sees only their own figures.
A short assessment: the decisions in scope, who makes them, what data exists today, and where it disagrees with itself. We will usually find that two or three numbers carry most of the value.
The output is a written recommendation with options, costs and risks, and an honest note on which questions your current data cannot answer yet and what it would take to change that.
While we scope this together, here's what's already a proven, dedicated service.
The answers are the same ones we give on a first call — including where the honest answer is "it depends, and here is what it depends on".
When a dashboard is the right answer, yes. Often it is not. If the decision is weekly and belongs to one person, a scheduled report or an alert gets used and a dashboard gets forgotten. We start from the decision and let that choose the format.
That is usually what we recommend. Analytics people have to remember to open tend to go unused, while a figure sitting next to the work gets looked at every day. We build reporting into the application and keep heavier analysis for a warehouse connection.
Yes, and it is the most common reason teams call us. It is fixed by defining each metric once in writing, with the filters and time window stated, then making every report derive from that single definition rather than its own copy of the logic.
We build reporting into web applications on the stack the product already uses, and connect to a warehouse where deeper analysis is needed. We are not tied to one vendor's BI suite, and we will not recommend a license you do not need.
The first useful number usually lands in weeks, because it is deliberately narrow — one decision, one metric, one audience. Breadth comes afterwards, once people trust what is already there.
Then we say so at the assessment rather than after a proposal. Sometimes the honest first step is fixing how the product records events, because no reporting layer can recover a measurement that was never taken.
You do — the code, the metric definitions and the documentation. We sign an NDA before detailed discussions.
Tell us what you're building and we'll be honest about whether we're the right fit.
Tell us what you're building and we'll get back to you within one business day.
Data analytics services: reporting and dashboards built around the decisions a team actually makes.
Download this card