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Dashboards built around a decision, not around the data.
Most dashboards are opened enthusiastically for a fortnight and then never again. The reason is almost always that they display what was available rather than answering a question somebody has to act on.
What makes a business dashboard actually get used?
A dashboard gets used when it answers a specific recurring decision for a named person, arrives where they already work, and makes the required action obvious. Dashboards fail when they present whatever data was available, serve no particular decision, require someone to remember to visit them, or quietly disagree with the finance figures.
- Built for one named person and one recurring decision.
- Delivered into email, Teams or the operational screen they already use.
- Reconciles to the ledger, so it is never argued with.
Why it matters
Dashboards fail for human reasons, not technical ones.
The build is rarely the problem. The failure is that nobody defined what decision the dashboard supports, so it becomes a collection of charts that are interesting once. Add a number that does not match finance, and its credibility is gone permanently.
We design backwards from the decision. Who has to decide something, how often, what would change their mind, and what they would do differently. If a metric cannot change an action, it is not on the dashboard — which is why ours tend to be smaller than the ones they replace.
Our design questions
Why dashboards get abandoned
We ask these before building anything, and they frequently reduce a twenty-chart request down to five that matter:
- The board pack is assembled by hand from several exports every month.
- A dashboard exists but people still ask for the spreadsheet.
- Figures do not reconcile to the ledger, so they get challenged.
- Nobody can say what action a given chart should trigger.
- Reports show last month when the decision needs yesterday.
- Different managers maintain their own private versions.
Scope
What reporting work covers.
Both halves matter: the operational screens that run the week, and the board reporting that runs the year.
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Decision mapping
Who decides what, how often, and on what evidence. The output is a short list of metrics that can actually change an action.
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Operational dashboards
Today and this week — orders, picks, OTIF, utilisation, exceptions — built for a wall screen or a phone and refreshed often enough to act on.
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Management & board reporting
The monthly pack generated rather than assembled, reconciled to the ledger, with commentary fields so the narrative lives with the numbers.
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Automated distribution
Reports pushed into email, Teams or Slack on a schedule, because a dashboard somebody has to remember to open is a dashboard nobody opens.
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Alerting on exceptions
Thresholds that notify the responsible person when something moves, so attention goes where it is needed rather than to a daily scan of normal numbers.
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Self-service, governed
A model business users can query themselves, with the definitions fixed centrally so self-service cannot quietly reinvent a metric.
Deliverables
What good reporting changes.
The honest measure is whether it is still open in six months, and whether anyone has gone back to their spreadsheet.
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Decisions made on current information
Operational numbers available in time to change the outcome, rather than confirming last month after the fact.
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Month end without assembly
The board pack generated from the model with commentary added, which typically returns several days of finance time every month.
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Numbers that stop being debated
Reconciled to the ledger and traceable to source. The conversation moves from whether the figure is right to what to do about it.
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Attention directed by exception
Alerts when something crosses a threshold, so managers are not scanning dashboards to discover that everything is normal.
Is this the right answer?
When dashboards & reporting is worth doing — and when it is not.
We would rather lose a project at this stage than six weeks in. If the right-hand column describes you, say so and we will tell you what we would do instead.
Worth doing when
- You can name a recurring decision and who makes it.
- The board pack is assembled by hand from several exports every month.
- Managers find out about a problem a month after it happened.
- The data underneath is already modelled and trustworthy.
Probably not when
- The data is not modelled yet — that work comes first or the dashboard lies.
- Nobody can say what action any of the proposed metrics would change.
- You want twenty dashboards delivered at once.
- The real requirement is a report nobody will read, for a meeting nobody acts on.
How we deliver
How we build reporting that sticks.
One decision, one dashboard, proven in use before we build the next. A twenty-dashboard programme delivered at once is a programme nobody adopts.
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Phase one
Map the decisions
Interviews with the people who actually decide things. Output is a ranked list of decisions and the metrics that would genuinely inform each one.
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Phase two
One dashboard, in use
The highest-value decision, built, reconciled and put in front of its owner. We watch how they use it, which always differs from how they described it.
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Phase three
Automate the recurring pack
The monthly or weekly reporting that is currently assembled by hand, generated instead, with commentary captured alongside.
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Phase four
Distribute & alert
Scheduled delivery into the tools people already have open, plus threshold alerts so exceptions find people rather than the other way round.
What you receive
The things that actually land.
Artefacts, not adjectives. Everything below is listed in the scope document before a phase starts, so “done” is a defined state rather than an opinion.
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A decision map
Who decides what, how often, and on what evidence. Produces a ranked shortlist of metrics that can actually change an action.
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Dashboards that reconcile
Built on the modelled data and checked against the ledger, so the numbers stop being argued with.
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Scheduled distribution
Reports pushed into email, Teams or Slack, because a dashboard somebody has to remember to open is one nobody opens.
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Threshold alerting
Notifications to the responsible person when something moves, so attention goes where it is needed rather than to a daily scan of normal numbers.
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An automated board pack
Numbers, charts and variance generated from the model with narrative fields for the people who write the explanation.
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A governed self-service model
A semantic layer business users can query, with definitions fixed centrally so self-service cannot quietly reinvent a metric.
Golden Triangle
What Midlands operations actually measure.
The metrics that matter in this corridor are operational and unforgiving, and most of them need data from more than one system.
- Service level OTIF On-time-in-full is the number retail and automotive customers judge suppliers on, and calculating it honestly needs order, despatch and delivery data reconciled together.
- Cost to serve Per drop, per line With margins this thin, cost per drop and cost per order line decide which customers are genuinely profitable. Few businesses here can produce it reliably.
- Capacity Labour and bays Pick rates, dock utilisation and agency hours against plan are the week-to-week levers in distribution, and they need to be visible on the floor rather than in a monthly pack.
We build reporting for distribution, manufacturing, logistics and professional services businesses across Birmingham, Nottingham, Northampton, Leicester, Derby and Coventry.
Technology
Reporting technology.
Usually whatever you already license. The tool matters far less than the model underneath it, and we will not sell you a migration you do not need.
- Power BI
- Looker Studio
- Metabase
- Grafana
- SQL & dbt models
- Scheduled distribution
- Threshold alerting
- Embedded dashboards
- Wall displays
- Row-level security
Where we deliver this
Dashboards & Reporting across the Golden Triangle.
35 locations, each with a page written for it — the sectors it is actually built on, and what that means for this work. See all areas we serve.
Northamptonshire 10
- Dashboards & Reporting in Brackley
- Dashboards & Reporting in Corby
- Dashboards & Reporting in Crick
- Dashboards & Reporting in Daventry
- Dashboards & Reporting in Kettering
- Dashboards & Reporting in Northampton
- Dashboards & Reporting in Raunds
- Dashboards & Reporting in Rushden
- Dashboards & Reporting in Towcester
- Dashboards & Reporting in Wellingborough
Warwickshire 5
West Midlands 5
Buckinghamshire 4
Leicestershire 4
Staffordshire 4
Derbyshire 1
Greater London 1
Nottinghamshire 1
Questions
Dashboards and reporting, answered plainly.
Asked by people who have paid for a dashboard nobody uses.
Why does nobody use the dashboard we paid for?
Usually because it was built from the data outwards rather than from a decision backwards, so it shows what was available instead of answering a question somebody has to act on. The other two common causes are that it requires people to remember to open it, and that one figure once failed to match finance, which permanently costs it credibility.
Should we use Power BI, Looker Studio or something else?
Whichever you already pay for, in most cases. If you are a Microsoft 365 business, Power BI is usually included and integrates with Teams; Looker Studio is reasonable for lighter needs; Metabase and Grafana suit self-hosted and operational use. The tool is the least important decision — the modelled data underneath determines whether any of them produce trustworthy numbers.
How often should operational dashboards refresh?
Often enough that the decision can still change the outcome. A despatch dashboard used to reallocate labour needs to be near real time; a monthly margin review does not. Refreshing more frequently than the decision cycle adds cost and load for no benefit, so we set it per dashboard rather than globally.
Can you automate our monthly board pack?
Yes, and it is one of the highest-return pieces of reporting work. The numbers, charts and variance commentary are generated from the model, with narrative fields for the people who write the explanation, and the whole pack reconciles to the ledger. It commonly returns several days of finance time every month.
Our data is messy. Can we still get useful reporting?
Partly, and we will be straight about where the limits are. Some metrics will be reliable immediately and others will not be until the underlying data is fixed. We prefer to show a smaller set of numbers you can trust, and name the ones that are not yet trustworthy, rather than publish a complete dashboard that is quietly wrong in places.
What does dashboard and reporting work cost?
A single well-scoped dashboard on data that is already modelled is a few thousand pounds. Where the data is not yet modelled, the pipeline work underneath it is the larger part of the cost, and we would rather tell you that at the start than deliver a dashboard built on numbers that will not survive scrutiny.
Which tool should we use?
Whichever you already pay for, in most cases. If you are a Microsoft 365 business, Power BI is usually included and integrates with Teams; Looker Studio is reasonable for lighter needs; Metabase and Grafana suit self-hosted and operational use. The tool is the least important decision — the modelled data underneath determines whether any of them produce trustworthy numbers.
How do we stop everyone building their own conflicting version?
With a governed semantic layer: the definitions live in one place and self-service queries that model rather than the raw tables. People keep the freedom to answer their own questions without the freedom to redefine revenue. Without that, self-service reliably produces the problem it was meant to solve.
Can you put a dashboard on a screen in the warehouse?
Yes, and operational wall displays are among the most-used things we build. They need designing differently — readable at distance, no interaction, refreshing often enough to act on, and showing the two or three numbers that change behaviour during a shift rather than everything available.
How do we know if it is working?
Whether it is still open in six months, and whether anyone has gone back to their spreadsheet. We ask that question at the three-month mark deliberately, because a dashboard that has quietly fallen out of use is a signal about the decision it was meant to support, not just about the chart.
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Next step
Tell us one decision you make every week.
One recurring decision, and what you currently use to make it. That conversation produces a more useful dashboard than any list of metrics ever has.