Power BI Dashboard for Manufacturing: OEE

Manufacturers sit on more data than almost any other business, yet much of it stays trapped in machine logs, an MES, an ERP and quality spreadsheets that never meet. A Power BI dashboard for manufacturing brings these together so operations leaders can see overall equipment effectiveness (OEE), production output, downtime and supply chain performance in one trusted view. Instead of waiting for a weekly report, plant and operations managers can act on yesterday's run, or today's, with confidence in the numbers.

This guide covers the metrics that drive a plant, how to model OEE correctly, the supply chain view, and how to connect shop-floor and ERP systems reliably.

The metrics that drive a plant

A manufacturing dashboard should serve the people who run the line, not just the boardroom.

• OEE: the headline measure of how effectively equipment is used, broken into availability, performance and quality.
• Production output: units produced against plan, by line, shift and product.
• Downtime: planned and unplanned, with reason codes so you can target the biggest losses.
• Scrap and first-pass yield: quality losses and rework, by line and cause.
• Throughput and cycle time: actual versus ideal, highlighting bottlenecks.
• On-time delivery: orders shipped on schedule, the customer-facing outcome of plant performance.

The value comes from drilling down: an OEE dip that resolves into a specific machine, shift and downtime reason is something a supervisor can fix.

Modelling OEE correctly

OEE is simple in principle and easy to get wrong in practice. Power BI makes it consistent.

1. Capture the inputs. Planned production time, run time, ideal cycle time, total count and good count, by machine and time period.
2. Derive the three factors in DAX. Availability is run time over planned time; performance is ideal cycle time times total count over run time; quality is good count over total count.
3. Multiply for OEE. Availability times performance times quality, calculated once so every line and shift uses the same definition.
4. Add loss analysis. Pareto views of downtime reasons and quality losses turn the score into an action list.

A consistent OEE definition across lines is often the single biggest reporting win for a manufacturer, because it ends arguments about whose numbers are right.

The supply chain view

Plant performance is only half the picture. A manufacturing dashboard should also cover the flow of materials in and product out.

• Inventory: raw materials, work in progress and finished goods, with stock turns and days of cover.
• Supplier performance: on-time and in-full delivery, lead times and quality.
• Demand and planning: forecast versus actual, and how well production aligns to demand.
• Logistics: outbound on-time delivery and cost to serve.

Bringing supply chain alongside production lets you see, for example, that a downtime spike traces back to a late material delivery rather than the line itself.

Connecting shop-floor and ERP systems

Power BI connects to these through database connectors, APIs and gateways, but reconciling high-frequency shop-floor signals with ERP records is best done in a warehouse or Microsoft Fabric lakehouse first. Staging the data handles the volume, aligns timestamps and shifts, and gives you one model where OEE and ERP figures agree. This is the heart of our data integration and warehousing work.

Licensing and cost

Sharing a manufacturing dashboard with supervisors and managers needs Power BI Pro licences (low per-user monthly cost), or Premium Per User or Fabric capacity for larger audiences and advanced reporting features. Copilot in Power BI requires paid Fabric F2 or higher, or Power BI Premium P1 or higher capacity. Pro or Premium Per User alone is insufficient. Check administrator settings, supported region and access for the experience you plan to use. Microsoft licensing changes regularly, so check current Microsoft pricing.

UK Power BI day rates run roughly £400 to £850 per day. A scope-locked build typically ranges from £8,000 to £14,000 depending on the number of lines, the variety of sources and the depth of OEE and supply chain logic. A short paid review (£2,000 to £4,000, fee credited toward a build) confirms scope and data readiness first. Confirm current pricing as of 2026.

Getting started

If OEE and production numbers are argued over rather than acted on, putting them on a single governed model is the fastest way to align the plant. Book a Trusted Numbers Review and we will map your MES, ERP and quality data, agree your OEE definition and recommend the right build. You can also explore our full Power BI consultancy or read about building a Power BI dashboard for finance for the cost side of operations.