Your Wrexham dashboard is beautiful, refreshes nightly, and missed this morning's scrap spike
Custom BI dashboard work for a Wrexham manufacturer runs £25,000 to £80,000 over 2 to 5 months, and the value isn't the charts, it's the plumbing underneath. Tableau, Power BI, and Looker draw lovely dashboards on top of clean, single-source data. A North Wales operation's data is anything but: it's spread across the ERP (Enterprise Resource Planning), a line system, a quality spreadsheet, and a despatch tool, and it's refreshed nightly when the line moves by the minute. The build that matters is the data integration and near-real-time pipeline; the dashboard is the easy last 10%.
You bought Power BI or Tableau to get visibility, and the dashboards look great in the board meeting. The trouble is what they sit on. Your real operating data lives in four places, the ERP, the line, a quality spreadsheet, a despatch tool, and getting it into one dashboard means an analyst spending Mondays stitching exports together. By the time the dashboard refreshes overnight, it's showing yesterday, so this morning's scrap spike or the line that stopped at 9am isn't there when you need to act on it.
Power BI and Tableau aren't the problem; the assumption is. They assume someone has already merged your sources into a clean model and that nightly is fast enough. For a Wrexham manufacturer chasing OEE, scrap, and on-time despatch, neither holds. The work that delivers value is the integration layer that pulls those sources together reliably and the pipeline that keeps it close to real-time, so the dashboard reflects the floor as it is, not as it was last night.
The problems nobody warns you about
- Real data is split across ERP, line, quality spreadsheet, and despatch, so an analyst stitches exports by hand
- Nightly refresh means dashboards show yesterday, missing a scrap spike or a line stop when it matters
- Each new metric means another manual data-prep job, so reporting never quite keeps up
- Off-the-shelf BI assumes a clean single source you don't have, so the hard part is left to you
The case for owning your business intelligence dashboards
You invest custom when the data integration and freshness are the real problem, not the visualisation. A build for a Wrexham manufacturer creates the pipeline that pulls ERP, line, quality, and despatch data into one reliable model and keeps it near-real-time, then drives dashboards for OEE, scrap, on-time despatch, and margin off that. The charts can be in Power BI or fully custom; the value is that they reflect the floor now, not last night, with no analyst stitching exports. That integration layer is exactly what off-the-shelf BI assumes already exists.
Budgeting a business intelligence dashboards build in Wrexham
| Project scope | Typical cost | Timeline |
|---|---|---|
| Data integration pipeline feeding existing Power BI or Tableau | £25k to £45k | 2 to 3 months |
| Pipeline plus near-real-time operational dashboards | £45k to £65k | 3 to 4 months |
| Full BI with alerting, drill-down, and custom front-end | £65k to £80k | 4 to 5 months |
What your build should include
Wrexham business intelligence dashboards: the full scope
Everything a business intelligence dashboards build here can cover: real-time analytics, KPI dashboards, data warehouse, embedded analytics, business intelligence dashboards, BI development and data visualization.
Exactly what you get
The unglamorous, valuable part: a data integration pipeline that merges your ERP, line, quality, and despatch sources into one reliable model, refreshed near-real-time, with dashboards for OEE, scrap, on-time despatch, and margin on top. You get drill-down to the batch or shift behind a number, alerting on threshold breaches, and no more Monday-morning export stitching. The charts can live in Power BI or a custom front-end. This reads from your ERP, inventory management software, and warehouse management system, and turns the data those systems capture into decisions directors and shift leads can act on.
How to choose a developer in Wrexham
Find a team that talks about your data sources before your chart colours. If they lead with dashboard design, they're solving the easy 10% and leaving you the integration problem you actually have. Ask how they'll pull your ERP, line, and spreadsheet data into one model, how fresh they can keep it, and who maintains the pipeline. A good partner treats the integration as the project and the dashboard as the output, the same way a strong ERP or inventory management software team treats data plumbing as the real work.
- !They focus on chart design; ask how they'll integrate your four data sources
- !They assume nightly refresh; ask how a line stop shows up within the hour
- !No data-model plan; ask how new metrics get added without re-stitching exports
- !They ignore source-system change; ask who maintains the pipeline as schemas shift
- !All front-end, no pipeline; ask where the clean data actually comes from
If business intelligence dashboards is on the roadmap, helpdesk & ticketing, erp, custom software usually follow within the year. Budget them as one conversation.
Rohan advises mid-market and enterprise teams on ERP, CRM and custom software, and has led delivery on dozens of business-software builds.
Writes for Digital Heroes, shipping business software for 2,000+ brands across 55+ countries since 2017.
Frequently asked questions
Why isn't Power BI or Tableau enough on its own?
They're excellent at drawing dashboards on clean, single-source data, and that's exactly what a Wrexham manufacturer doesn't have. Your data is split across the ERP, the line, a quality spreadsheet, and a despatch tool, and it refreshes too slowly to catch a problem when it happens. The hard, valuable work is the integration pipeline that merges those sources and keeps them fresh. The dashboard is the easy last step once that exists, which off-the-shelf BI assumes you've already done.
Can dashboards show what's happening on the line right now?
Close to it, if the pipeline is built for near-real-time rather than nightly. Instead of a refresh that shows yesterday, the data flows continuously enough that a scrap spike or a line stop appears within the hour, while you can still act. True millisecond real-time is rarely needed; near-real-time is, and it depends on your source systems exposing data cleanly. That freshness is a core reason to build the pipeline rather than rely on a nightly Power BI refresh.
What manufacturing metrics should the dashboards track?
The ones that drive a plant: OEE (availability, performance, quality), scrap and yield, on-time-in-full despatch, and per-part or per-contract margin. The point is to connect those top-line numbers to the batch, shift, or line behind them, so a bad figure leads straight to a cause. Generic BI templates show generic charts; a manufacturer's dashboards should answer operational questions and let you drill from a KPI to the production reality that created it.
Who maintains the data pipeline over time?
You do, via your build partner or in-house skill, because source systems change their schemas and the pipeline has to keep up. That ongoing maintenance is a real cost and the main downside of building, but it's what keeps the dashboards trustworthy. The alternative, an analyst re-stitching exports by hand every week, is a worse and less reliable cost. A good partner documents the pipeline so it isn't a black box when people change.