Decisions
The test of a dashboard isn't how it looks in the handover meeting. It's whether anyone is still using it in March. We build Power BI around the decisions your business actually makes — and we're equally happy fixing the estate you already have.
01 What changes
Most abandoned dashboards were built the same way: someone asked what metrics you'd like to see, made a list, and put all of them on a page. The result is technically accurate, visually busy, and answers no question anyone was actually asking.
We start from the opposite end. What decisions do you make, how often, and what would you need to see to make them faster? A report designed around a recurring decision gets used, because opening it is the fastest route to an answer someone already needs.
Power BI is where we spend most of our time. Executive views that fit on one screen and survive a phone. Operational reporting people work from all day. Self-service models a business user can slice without breaking anything. And, often, unpicking an existing implementation that's become slow, unreliable, or quietly wrong.
02 What we build
One screen, the handful of measures that indicate whether the business is on track, and a clear route into the detail behind any of them. Built to be read in ninety seconds on a phone before a board meeting, not studied for an hour.
The reports a team lives in — dense, fast, filterable, refreshed often enough to act on. Designed for someone using it forty times a week, which is a genuinely different design problem to an executive view.
The board deck, the regional summary, the weekly exception report — generated and distributed on schedule, with alerts when a measure crosses a threshold. This is usually where the first week of every month goes back into your team's calendar.
A certified model business users can explore for themselves, with the guardrails that stop self-service becoming fourteen conflicting versions of the truth. Fewer requests in your analyst's queue, without losing control of the definitions.
03 Rescue work
This is one of the most common reasons people call us, and it's usually cheaper to fix than to replace. Failing implementations tend to fail for a small number of recognizable reasons.
We'll assess what you have, tell you plainly whether it's worth repairing or rebuilding, and give you the reasoning either way.
04 For the technical reader
Import is fast and the right default for most mid-sized businesses. DirectQuery earns its place when data volumes are genuinely large or latency requirements are genuinely tight — and costs you real performance and DAX flexibility in exchange. Direct Lake, on Fabric, increasingly gives you much of both. We pick per model, based on volume, refresh window and how fresh the data honestly needs to be, rather than applying one pattern everywhere.
Most Power BI performance problems are modeling problems that surfaced late. We keep cardinality down, remove columns that exist only because they were in the source, push transformation upstream of Power Query wherever possible, and measure with Performance Analyzer and DAX Studio rather than guessing at what's slow.
Consistent layout and visual grammar across a report set. Restrained color used to carry meaning rather than decoration. Charts chosen for the comparison being made. Enough context on the page — target, prior period, direction — that a number means something without the reader having to remember what good looks like.
Development, test and production workspaces with deployment pipelines between them, source-controlled definitions, and documented refresh schedules. Changes get tested before they reach the audience that acts on them.
Pro, Premium Per User and Fabric capacity solve different problems at very different prices. Plenty of organizations are on capacity they don't need, and a few are on per-user licensing that's quietly costing more than capacity would. We'll do that arithmetic with you honestly — it isn't in our interest to have you overspend on a platform instead of on outcomes.
05 Elsewhere in the chain
Pipelines and warehousing so reports refresh without anyone intervening.
Explore 02 / TrustThe semantic model that makes every report agree with every other one.
Explore 04 / LeverageIncluding AI-assisted Power BI and DAX development for your team.
ExploreNext step
Bring an existing dashboard to the call, or just describe the decision you can't currently get a straight answer for.