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Success
[PRO SERVICES / BUILD]

Dashboard
Development

A larger business can own several reporting tools and still lack one trusted view of performance. We build around agreed measures, permissions and decisions, then connect the sources needed to keep it current.

HOW IT WORKS
1

Connect the systems

2

Agree each measure

3

Show live decisions

Everyone reads the same number in the same way.

Named owners

FOR EVERY IMPORTANT METRIC

Clear costs

BUILD, LICENCES AND HOSTING

Yours

CODE, DATA AND IP

[THE OPERATING PROBLEM]

Choose the reporting tool around the work

Power BI, Tableau and Looker all have different user, platform and commitment costs, and those prices change. We compare the current licence cost, currency, tax and access model during scoping instead of assuming custom software is the answer.

Before commissioning a custom dashboard, check whether the problem is the interface, the source data or the definitions. A new screen will still be wrong if it uses the wrong calculation.

The review compares improvements to your existing tools with a custom build, including access, maintenance and running costs.

TODAY'S REPORTING

  • Per-seat licences that creep every renewal
  • Friday spreadsheet rebuilt by hand each week
  • Numbers from Xero, Stripe and the CRM that disagree
  • Calculation rules without a named owner
  • Dashboards nobody opens between board meetings

BESPOKE DASHBOARD

  • Agreed build and running costs
  • Numbers update themselves overnight
  • Reconciled views of connected sources
  • Rules in code, named, tested, in version control
  • Built for the role, not for the tool's idea of a chart
[THE PATTERN]

What a useful dashboard needs

When a dashboard gets ignored, we check these five parts first. The colour palette comes later.

01

The question

One named decision per dashboard. "Do we hire next month?" "Which job is losing money?" If the dashboard doesn't answer one, it gets closed.

02

The pipes

Xero, HubSpot, Stripe, Shopify, your job tracker, your timesheets. Pulled overnight into one warehouse, reconciled, deduped.

03

The model

"Revenue", "active customer", "gross margin", defined once. Same number in the board pack, the sales meeting and the accountant's email.

04

The view

Built for the role that opens it. The MD sees three numbers and a trend. Ops sees the job board. Finance gets the cash position. Nobody sees everything.

05

The alert

The dashboard pings you when something matters. Margin drops below threshold, a customer goes quiet, cash dips. You don't need to log in to find out.

[HOW WE WORK]

How we take it into live use

Digbeth Events and Olton Bedrooms use operational dashboards built around booking, revenue, project, workshop and stock decisions. We apply the same decision-first approach to the systems in scope.

We work in fixed-scope phases and you own the custom software. Hosting, maintenance and any third-party licences are set out in the proposal.

BOOK A DATA REVIEW
01

Data review

A working session with the people who own the decisions, definitions and source systems. The output lists the measures worth building first, their owners and the data work required.

02

Plumb the data

We connect Xero, HubSpot, Stripe, Shopify, your job tracker, your warehouse system, your timesheets, whichever apply. Data lands in your own warehouse (BigQuery, Postgres or Snowflake), refreshed overnight or every few minutes if you need it live.

03

Model it once

Revenue, active customers, gross margin and utilisation need agreed definitions. We record them in code and review them with the people responsible for the figures before building dependent reports.

04

Launch the views

Built on Metabase, Evidence.dev, Lightdash, Cube or a hand-rolled Laravel and Livewire app, whichever fits your stack and your team. Alerts wired to Slack or email. You can carry on adding views without us.

[THE STACK]

Choosing the right reporting stack

We pick the lightest stack that fits the job. Sometimes that's self-hosted Metabase. Sometimes it's a hand-built Laravel app because the dashboard has to write back to your operational systems. We tell you which, and why.

BI LAYER

Metabase, Lightdash, Evidence, Superset

We compare self-hosted and managed options, checking the edition, licence terms, access controls and maintenance required.

SEMANTIC LAYER

dbt and Cube

Metric definitions can live in version-controlled code. Reports and AI tools connected to those definitions can then be checked against the same calculations.

WAREHOUSE

Postgres, BigQuery, Snowflake

We choose storage against data volume, refresh requirements, access controls and operating costs.

CUSTOM

Laravel + Livewire

When the dashboard needs to be inside your own product, branded, multi-tenant, or able to trigger workflows, we build it bespoke. Same team, same hosting, same login as the rest of your software.

[THE BORING IMPORTANT BIT]

UK data and accessibility requirements

We document hosting regions, provider access and any international transfers before connecting personal data. Access logging and retention rules are part of the agreed design.

UK GDPR and DPA 2018

Role-based access, an audit trail and retention rules support the people responsible for data protection. We agree how suspected breaches are escalated so they can assess notification duties promptly.

Finance reporting definitions

If a dashboard feeds financial reporting, its definitions need to match the records used by finance. Your accountant or compliance lead should approve those definitions and the reconciliation checks.

Hosted where you want

UK or EU regions on AWS, Google Cloud, Azure, Hetzner or DigitalOcean. If you have FCA obligations, NHS procurement rules or another sector requirement with views on where data lives, tell us in the review and we'll work to it.

[RELEVANT VU WORK]

We build dashboards around the operating process

Digbeth Events uses live booking and revenue reporting. Olton Bedrooms links project progress to workshop time and stock. The dashboard is useful because it shares the same data and ownership as the work.

[A USEFUL FIRST CONVERSATION]

When this is worth discussing

We work best when there is a real operating problem, enough volume to measure and people from the affected teams who can make decisions.

Usually a good fit

  • An established UK business, usually with annual revenue above £10m
  • A repeated process with a known cost, delay, error rate or capacity problem
  • A senior sponsor and a day-to-day owner who understand the work
  • Access to the relevant staff, systems, sample records and security requirements

We may point you elsewhere

  • A standard product already covers the process well
  • The requirement is a one-off small build with no wider operating case
  • There is no owner or access to the people and data needed to test the result
  • The plan relies on AI making high-impact decisions with nobody responsible for review
[QUESTIONS]

Questions before connecting the systems

Q.01

Can't we just use Power BI or Tableau?

Yes. We compare the existing platform with a custom build against access requirements, licences, data connections and support costs. Both approaches need someone to own the definitions and check the results.

Q.02

How long does it take?

The first phase covers data review, agreed definitions, permissions and one useful view. The timetable depends on source access and whether the business already agrees how the measures are calculated.

Q.03

How much does it cost?

We issue the first commercial proposal after reviewing the data sources and user groups. Software, platform and hosting costs are separated so finance can see the full running cost.

Q.04

What if our data is a mess?

We identify duplicates, conflicting definitions and missing records during the review. Cleanup rules need your approval, and unresolved records remain visible. The proposal separates source-data work from building the dashboard.

Q.05

Who owns it after?

You do. Source code, warehouse, dbt models, dashboards. In your accounts, on your hosting, in a repo with your team in it. We can keep maintaining it on a retainer or hand it over to your in-house developer. No lock-in.

Q.06

Can it talk to AI?

Yes. Once the metrics live in a semantic layer, an LLM can be wired to answer "how did we do last month?" in plain English from signed-off definitions. We add that when you want it.

Q.07

What if the team won't use it?

That's why step one is naming the decision. If nobody can name the question a dashboard answers, we don't build it. And we wire alerts so the dashboard comes to people, not the other way round.

Vu Agency working session

Talk to us about your dashboard

Bring the management pack, the dashboards people avoid and the questions leadership still asks by email. We will identify the first view worth consolidating and the definitions that need agreement.

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