OEE that reconciles
Availability, performance and quality are calculated once, agreed with your production team, and applied the same way on every line so two reports never disagree.
Power BI consulting for manufacturing
OEE, downtime and scrap dashboards, built by a senior Power BI consultant for your manufacturing plant
A fixed-fee Power BI build for plants that already have the data but not the picture: OEE, downtime reasons, scrap and rework, throughput and cost per unit, in role-based views for plant managers, supervisors and finance. One written price, typical delivery in 2–4 weeks, 30 days of hypercare included.
Representative dashboard — sample data
What you get
Numbers the shop floor and the front office both trust
Every build covers the metrics a plant actually argues about, not a generic KPI template.
Downtime by reason code
Stops are grouped by reason, line, shift and asset, so the argument moves from whether downtime is up to which changeover or machine is causing it.
Scrap and rework in cost terms
Scrap rate is shown by part, reason and shift, and translated into cost per unit, so quality problems are ranked by what they cost rather than by how loud they are.
Throughput against plan
Actual output is compared with the schedule by line and shift, with drill-through to the orders and hours behind any gap, so planning meetings start from evidence.
Role-based views
Row-level security and certified datasets mean a supervisor sees their lines, a plant manager sees the plant, and finance sees cost — from one governed model.
Documentation and handover
A written record of the model, the measure definitions and the refresh setup, plus a live walkthrough, so your team can keep reporting running without us.
How it works
Three steps from machine data to a shift-ready view
- 1
Walk the metrics, then scope
A free consultation covers how you define OEE today, where downtime reasons are captured, and which decisions each role makes. We reply with a written scope, one fixed fee and a delivery date.
- 2
Connect, model, validate
We pull from MES, ERP and the spreadsheets in between, build the semantic model, write the measures, and reconcile them line by line against numbers your production team already trusts.
- 3
Deploy and stand behind it
We publish to your governed workspace with role-based access, walk supervisors and managers through their own views, hand over documentation, and stay on for 30 days of included hypercare.
What a plant reporting build actually covers
Manufacturers rarely lack data. The machines log states, the ERP holds orders and costs, and someone keeps a downtime spreadsheet on the shift desk — but nobody can put OEE, scrap rate and throughput on one screen without a morning of copy and paste. The work is engineering the layer underneath: connecting those sources, agreeing the measure definitions, and modelling them so the numbers hold up. Microsoft’s own Power BI documentation (opens in new tab) describes the platform’s data, model, report and service layers, and a plant dashboard that survives a bad week needs all four built deliberately.
Definitions are where these projects are won or lost. Whether a planned changeover counts against availability, whether rework is scrap, whether a short stop under two minutes is logged at all — each choice changes the headline OEE figure. We settle those with your production team first and encode them in DAX measures (opens in new tab) that every report page reuses, so the definition lives in one place instead of in six different spreadsheets.
Deliverables for a typical engagement: the report files and semantic model in your own tenant, tested measures for OEE, downtime, scrap, rework, throughput and cost per unit, workspace and row-level security configuration, a refresh schedule with monitoring notes, and written documentation. Timeline is typically 2–4 weeks from kickoff, stated in your scope before you commit, with 30 days of post-delivery hypercare included.
Who this is for
It fits small and mid-sized manufacturers — one plant or a handful — where the production meeting still runs on a spreadsheet somebody rebuilt at 6am. A plant manager who wants yesterday’s downtime by reason before the stand-up. A quality lead who suspects one part number drives most of the scrap but cannot prove it. A controller who needs cost per unit to move with actual output rather than a month-end estimate. If your reporting is accurate but arrives too late to change anything on the floor, that is the gap this closes. The same problem turns up well outside the plant — a Power BI consultant for nonprofits meets it in grant, donor and program numbers rather than downtime and scrap.
Two questions usually come up before the scope is signed, and we have written both up honestly: what a Power BI dashboard build actually costs, with the factors that move a fixed fee up or down, and which Power BI licences a smaller business really needs, since a plant with fifty occasional viewers and four report authors is not a Premium capacity story by default.
This page is the manufacturing-shaped version of our wider fixed-fee Power BI dashboard development service, so nothing here is a different engineering standard — only a different vocabulary, in the same way our job cost and WIP dashboards for construction companies speak cost codes and change orders instead of cycle times, and a Power BI consultant for healthcare works in no-show rates, chair utilization and claim denials. Plants that want the shift log or the downtime sheet replaced at source often pair the build with a custom Power App for shop-floor data entry, and many add Power Automate alerts when a line drops below target so the dashboard pushes rather than waits to be opened.
Fixed-fee project tiers
Three common shapes cover most manufacturing requests. Every fee is fixed and put in writing after your free consultation — the table shows scope and typical timeline, not prices, because an honest price requires seeing your sources first.
| Tier | Scope | Typical timeline | Fee |
|---|---|---|---|
| Line-level OEE & throughput starter | One or two lines from a single source: availability, performance and quality measures, downtime by reason code, throughput against plan, and refresh configured | About 2 weeks | Fixed fee — scoped after your free consultation |
| Shift handover, scrap and rework department pack | Several sources across a department: shift-over-shift handover pages, scrap and rework by part and reason, cost per unit, and role-based views for supervisors | 2–3 weeks | Fixed fee — scoped after your free consultation |
| Plant-wide governed rollout | Cross-department and multi-line models, row-level security, certified datasets, workspace and access governance, and admin documentation | 3–4 weeks | Fixed fee — scoped after your free consultation |
Whatever the tier, you own every artifact — report files, semantic model, measure definitions and workspace settings live in your Microsoft tenant from the first day.
Related services
Other ways we make Microsoft easy
Power BI Dashboards
The wider fixed-fee dashboard service: semantic models, DAX, governed reporting and Fabric migration for any industry.
Power Apps Consulting
Shop-floor and back-office apps that replace the shift logs, downtime sheets and paper forms feeding your reports.
Microsoft Azure Consulting
Migration and cost optimization for the cloud platform your production data — and your dashboards — ultimately run on.
What a dashboard really costs
An honest fixed-fee cost breakdown and the factors that move the number on a Power BI build.
Power BI vs Excel reporting
When it is worth moving the production spreadsheet — and when Excel is still the right tool.
How to choose a consultant
The questions to ask before you hand anyone your production and cost data.
FAQ
Plant reporting questions, answered
Every build includes discovery with your production and finance leads, connections to your MES, ERP or spreadsheet exports, a semantic model, validated OEE, downtime, scrap and throughput measures, role-based report pages, governed workspace deployment, and written documentation. The scope and the fee are agreed in writing before any work starts.
It means the person scoping your data model is the same person building it, working in US business hours, with no offshore handoff and no junior resource learning on your project. You talk directly to the engineer writing the DAX behind your OEE and downtime figures.
The fee reflects how many production systems we connect, how messy the shift and downtime data is, and how many role-based views your plant managers, supervisors and finance team need. After a free consultation you get a written scope with one price, and that price moves only if the scope does.
Typical delivery is two to four weeks from kickoff. A single line-level OEE and throughput starter lands at the short end; a plant-wide rollout with row-level security and certified datasets sits at the longer end. Your written scope states the delivery date before you commit to anything.
All three, in practice. We connect MES and historian exports for machine states, ERP tables for orders, scrap and cost per unit, and the spreadsheets supervisors keep for shift notes. Where a source cannot be reached directly, we agree a reliable export path during scoping rather than assuming one.
For 30 days after delivery we fix refresh failures, correct measures that disagree with your shop-floor numbers, adjust visuals your supervisors find awkward, and answer questions from named users. It is included in the fixed fee, not billed hourly, and it starts the day the reports go live.
Book a free consultation
Get more from the Microsoft tools you already pay for
Tell us what you’re trying to fix — a report, an approval process, an intranet, a Copilot rollout. We scope it as a fixed-fee project, you approve, and a senior engineer delivers in 2–4 weeks.
- Fixed-fee scope agreed before any work starts
- Senior, US-based Microsoft engineers — no handoffs
- Typical 2–4 week delivery
- 30 days of post-delivery hypercare included
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