Your Power BI dashboard is gorgeous and the Aurora plant manager ignores it because the inventory number is wrong
For Aurora manufacturers, the BI problem is rarely the chart, it's the data feeding it. Custom BI work makes sense when dashboards must run on live, trustworthy floor and inventory data, not a stale nightly extract. Expect $40,000 to $110,000 and 3 to 6 months. If your data is already clean and Power BI just needs configuring, buy the license and skip the build.
Tableau, Power BI, and Looker draw beautiful charts on whatever you feed them, and that's the trap. An Aurora plant manager opens a slick dashboard, sees an inventory or OEE number that contradicts what he knows is on the floor, and quietly stops trusting the whole thing. The visualization isn't the problem; the data is stale, stitched from a nightly extract, and reconciled differently in three source systems.
You can buy the most powerful BI tool on the market and it won't fix a number that's wrong before it's plotted. The work that matters is upstream: a trustworthy live data layer that the dashboard can sit on, which is exactly what off-the-shelf BI assumes you already have.
Where the off-the-shelf tools fall short
- Power BI charts a stale nightly extract, so live floor metrics like OEE are already wrong when plotted
- The same metric is defined three ways across ERP (Enterprise Resource Planning), inventory, and spreadsheets, so dashboards contradict each other
- Managers stop trusting BI after one wrong number and revert to their own spreadsheets
- Real-time shop-floor KPIs can't reach Tableau because nothing exposes them cleanly
Custom business intelligence dashboards: what Aurora teams actually get
Custom BI work is worth it when the fix is the data layer, not the chart. You build a trustworthy pipeline that pulls live floor, inventory, and order data, reconciles each metric to a single definition, and exposes it so a dashboard, whether Power BI or a custom one, finally shows numbers the plant manager will trust. The visualization is the easy last mile; the value is the live, single-source-of-truth layer underneath.
- Dashboards run on stale extracts and contradict each other
- Managers don't trust the numbers and revert to spreadsheets
- You need live floor KPIs no nightly extract can deliver
- Your data is already clean and single-sourced
- Power BI or Tableau just needs configuring on good data
- You don't need real-time floor metrics
- Dashboards on a live, reconciled data layer instead of a stale nightly extract
- One definition per metric, so dashboards stop contradicting each other
- Real-time floor KPIs like OEE and throughput that managers actually trust
- Self-serve views for leadership without re-pulling spreadsheets
- A data layer that also serves your ERP, inventory, and reporting needs
- The hard, costly work is the data pipeline, which is invisible to stakeholders who only see charts
- If your data is already clean, you may just need Power BI configured, not a custom build
- A live pipeline needs monitoring; a broken feed silently poisons the dashboard
- Defining a single metric across departments is as much politics as engineering
Feature priorities for Aurora teams
What we build under business intelligence dashboards in Aurora
The engagements Aurora teams bring us most often: embedded analytics, business intelligence dashboards, BI development, data visualization, Tableau alternative and Power BI.
The honest cost picture for Aurora
| Project scope | Typical cost | Timeline |
|---|---|---|
| Data layer + core dashboards | $40k to $70k | 3 to 4 months |
| Live pipeline + reconciled metrics | $75k to $110k | 4 to 6 months |
| Enterprise data platform | $120k+ | 6 to 10 months |
Timeline: what happens, and when
Exactly what you get
A trustworthy data layer first, dashboards second: a live pipeline from your floor, ERP, and inventory, each metric reconciled to a single governed definition, real-time KPIs like OEE and throughput, and self-serve views leadership will actually trust. Whether the front end is Power BI or a custom UI, it sits on data that's right. It draws from your ERP software, inventory management software, and supply chain software so reporting matches operations.
How to choose a developer in Aurora
Hire a team that talks about the data pipeline before the visuals, because that's where BI succeeds or fails. Ask how they'll reconcile a metric that's defined three ways and how they expose live floor data. Make sure they monitor feeds for staleness. The strongest builds tie into your ERP software, inventory management software, and project management software so the dashboard reflects one operational truth instead of three.
- !They focus on chart design; ask how they make the underlying data trustworthy
- !No metric-governance plan; ask how one definition gets agreed across departments
- !No real-time floor plan; ask how OEE reaches the dashboard live
- !No feed monitoring; ask what happens when a pipeline goes stale
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 don't our Power BI dashboards get used?
Usually because the data is stale or contradicts what managers know is true on the floor. One wrong number and trust is gone. The fix is upstream: a live, reconciled data layer, not a better chart.
Do we need to replace Power BI?
Often no. Power BI or Tableau can stay as the front end. The custom work is building the trustworthy live data layer underneath that off-the-shelf BI assumes you already have.
Can dashboards show real-time floor metrics?
Yes, once a live pipeline exposes them. KPIs like OEE and throughput can update in near real time instead of waiting for a nightly extract that's wrong by the time it's plotted.
What does custom BI cost in Aurora?
A data layer with core dashboards runs $40,000 to $70,000. A full live pipeline with reconciled metrics runs $75,000 to $110,000.
How long does it take?
Three to four months for a data layer and core dashboards, four to six for a full live pipeline.