Production & OEE
Overall equipment effectiveness split into availability, performance, and quality by line, asset, and shift — so you can see at a glance whether stoppages, speed loss, or scrap is costing you output.
Power BI for Manufacturing & Logistics
Power BI OEE and downtime dashboards for the plant floor
We turn MES, ERP, SCADA, and WMS data into Power BI OEE and downtime dashboards — with scrap, supply chain, on-time delivery, and throughput beside them — so plant managers and logistics leads act on facts, not end-of-week guesses.
Representative dashboard — sample data
Power BI for manufacturing & logistics
One view of every line, shift, and shipment
On a plant floor or in a distribution center, the data already exists — it is just trapped. Production counts sit in the MES, machine states in a SCADA historian, work orders and cost in the ERP, quality results in a separate LIMS or spreadsheet, and shipments in a WMS or TMS. Supervisors print shift reports, schedulers keep their own trackers, and the morning standup runs on whiteboards and gut feel. We build Power BI dashboards that pull those systems into one governed model, so the plant manager, the quality lead, and the logistics director are all looking at the same OEE, the same scrap rate, and the same on-time number.
This is a productized service for discrete and process manufacturers, contract manufacturers, and the warehousing and fleet operations that move their product. We concentrate on the metrics that decide whether a site hits its numbers — overall equipment effectiveness, downtime by cause, scrap and first-pass yield, supplier and inventory health, and order-to-delivery performance. Everything is built on a clean model with auditable DAX, and you own the report, the data model, and the credentials at handover.
The metric that anchors the plant floor
OEE, in one line
OEE = Availability × Performance × Quality — and alongside it we track OTIF so delivery performance is measured with the same discipline as production.
Common operations dashboards
Six views that run a plant and a network
Each is anchored to a decision a shift or scheduling team makes daily — not a screensaver of gauges.
Quality & scrap
First-pass yield, scrap and rework rates, defect Pareto by reason and station, and cost of poor quality — so quality engineers attack the few causes driving most of the loss.
Downtime & reason codes
Planned versus unplanned downtime, MTBF and MTTR, and a ranked list of stoppage causes by machine and shift — turning “the line keeps going down” into a prioritized fix list.
Supply chain & inventory
Raw, WIP, and finished-goods stock, days of inventory, supplier on-time and defect rates, and shortage risk against the production schedule — so material never stops a running line.
On-time delivery (OTIF)
On-time in-full by customer, lane, and carrier, with late-order root causes and promised-versus-actual ship dates — so service-level slips are caught while there is still time to recover them.
Fleet & warehouse throughput
Pick, pack, and ship rates, units per labor hour, dock-to-stock and dwell times, and fleet utilization and cost per mile — so warehouse and transport managers balance labor against demand.
The KPIs we model for manufacturing and logistics
Operations metrics only earn trust when their definitions are fixed and the data behind them is clean. We agree the formulas with your team up front — how planned time is counted, what an ideal cycle is, what counts as on-time — and build them as governed DAX measures (opens in new tab) so the numbers hold up in a continuous-improvement review. The measures that consistently matter include:
- OEE and its three components — availability, performance, and quality, by line, asset, product, and shift, with the loss buckets behind each one.
- Downtime, MTBF and MTTR — planned versus unplanned minutes lost, ranked by reason code, machine, and crew.
- First-pass yield, scrap and rework — defect rate and cost of poor quality by station, reason, and product family.
- Schedule adherence & throughput — actual versus planned output, takt attainment, and units per labor hour.
- Inventory & supplier health — days of inventory, stockout risk, supplier on-time and defect rates against the build plan.
- OTIF, cycle times & cost to serve — on-time in-full, dock-to-stock and pick-to-ship times, and freight cost per order or mile.
The data sources we connect
We integrate the systems that already run your operation. Typical connections include ERPs such as SAP Business One, Microsoft Dynamics 365, Oracle JD Edwards EnterpriseOne and World, NetSuite, Epicor, and Infor SyteLine and CloudSuite Industrial for orders, inventory, and cost; MES and historian platforms such as Ignition, Wonderware, and OSIsoft PI for production and machine states; quality systems and LIMS for defects and inspections; and WMS and TMS platforms for warehouse and transport data. Where machine data lives behind OPC UA or a SCADA layer, we ingest it through a staging database or gateway rather than disturbing controls systems. Every transformation is documented so engineering and audit can trace any number to source. Microsoft documents the connectors and gateway options we build on. (On-premises data gateway reference (opens in new tab).)
The pain points this solves
Manufacturers and logistics teams call us when OEE is calculated three different ways across three sites; when downtime is logged on paper and never analyzed; when scrap is only discovered at month-end close; when material shortages stop a line that the schedule said was fine; and when a key customer reports a service-level miss before the team even knew an order was late. We replace that with one model, one agreed definition of every metric, and an automated refresh, so problems surface in hours not weeks. Teams spend less time assembling shift reports and more time eliminating the losses those reports used to bury — fewer stoppages, less scrap, and more orders shipped complete and on time.
Operations dashboards at a glance
A quick reference for the operations views plants and networks rely on, the kinds of metrics each one surfaces, and the systems we typically connect for them.
| Dashboard | Key metrics | Typical source systems |
|---|---|---|
| OEE & production | Availability, performance, and quality, actual vs planned output, takt attainment, by line, asset, and shift | MES, ERP, SCADA / historian (Ignition, OSIsoft PI) |
| Downtime & reasons | Planned vs unplanned minutes, MTBF, MTTR, ranked stoppage causes by machine and crew | MES, SCADA / historian, downtime logging |
| Scrap & quality | First-pass yield, scrap and rework rates, defect Pareto by station and reason, cost of poor quality | Quality systems / LIMS, MES, ERP |
| OTIF / supply chain | On-time in-full by customer, lane, and carrier, days of inventory, supplier on-time and defect rates | ERP, WMS, TMS |
Dashboards we ship most
- Production & OEE by line, asset, and shift
- Scrap, first-pass yield & cost of poor quality
- Downtime by reason code, machine & crew
- On-time in-full (OTIF) by customer, lane & carrier
- Warehouse throughput & units per labor hour
How it works
From shift reports to a live operations view
- 1
Scope & connect
On a free demo we map your lines, sites, and systems and agree how each KPI is defined. You submit the task, we reply with a scope estimate and the hours needed, and once you approve we connect ERP, MES, historian, quality, and WMS data into one reconciled model — hours deducted only for approved work.
- 2
Build & validate
We design the model as a star schema (opens in new tab), write DAX for OEE, downtime, scrap, inventory, and OTIF, and build each view. You validate the numbers against your own shift and quality reports until the dashboard is trusted on the floor.
- 3
Launch & hand over
We deploy to your workspace, set scheduled refresh and row-level security by site or line, and train supervisors and analysts. You own the report, model, and credentials — with optional ongoing support.
Representative perspective
We had OEE on three sites and none of them agreed. One model with one definition gave the plant managers a number they trusted, and the downtime Pareto pointed straight at the changeovers we needed to fix.Operations director, contract manufacturer
Representative perspective
Before, a late shipment was a phone call from the customer. Now OTIF by lane and carrier is on a screen every morning, so we catch the slips while we can still recover the order.Supply chain manager, third-party logistics provider
Put OEE, scrap, and on-time delivery on one screen
Book a free demo. We’ll map your lines, sites, and systems, then scope the task and tell you the hours it needs before any work begins. Your prepaid Flex hours cover this — and they never expire.
Built on the same foundations as the rest of our work
An operations dashboard lives or dies on the model beneath it, so every build draws on our core services. The integration and OEE logic come from our data modeling and DAX work; the floor-ready layout and visual clarity from report design; and where you are leaving spreadsheets or a legacy reporting tool, our migration to Power BI service carries your history across. If your ERP is NetSuite, our NetSuite Power BI dashboard pulls production, inventory, and cost straight from it. Plants running Epicor Kinetic or Epicor ERP 10 should start at our Epicor Power BI dashboard page, which covers job costing, production tracking, and scheduled refresh in place of manual BAQ exports. Shops on Infor SyteLine or CloudSuite Industrial should read our SyteLine job costing and margin dashboard page, which covers getting data out of CSI and the multi-site and job-suffix traps that skew ERP cost reporting — the financial and delivery counterpart to the OEE and downtime work described here. For a multi-site rollout, governance, and gateway strategy, Power BI consulting covers the wider deployment. Plants and freight operations across Georgia can read how the same work is delivered on Eastern-time hours on our Power BI consultant Atlanta page. You can review the full build process and Flex pricing model. If your ERP is Business Central, our Business Central Power BI dashboard page covers item ledger, production, and inventory reporting. Businesses that distribute rather than manufacture should start at Power BI for wholesale distributors. Freight forwarders, customs brokers, and 3PLs moving the goods rather than making them should start at our CargoWise Power BI dashboard page, which covers job profitability, trade-lane margin, and customs-entry throughput. Operations that rent their machines out rather than run them — equipment, aerial, pump and power or event fleets — measure the same assets on utilization and return on original equipment cost instead of OEE, and that build is covered on our Power BI for equipment rental companies page. Asset-based carriers and private fleets hauling the freight — owning the tractors and employing the drivers — measure miles rather than machines, and that build is covered on our Power BI for trucking companies page, which handles revenue and cost per mile, deadhead and profit per truck. Producers whose asset is a wellbore rather than a production line have no OEE to measure at all — the equivalent question is deferred volume against a well's estimated potential, alongside lease operating expense per BOE and AFE against actual capex — and that build is covered on our Power BI for oil and gas companies page. Every task is scoped before work begins from your prepaid block of senior-led hours — no project minimums, no surprise change orders — and hours are deducted only for work you approve. Your hours never expire, so you spend them when you need them.
Why it's low-risk
Prepaid hours, you own everything
Every task is scoped and approved before work starts, with hours deducted only for approved work — and at handover the report, model, and credentials are yours. Hours never expire, and there's a full refund within your first 4 hours.
FAQ
Manufacturing & logistics Power BI questions
We model OEE as availability times performance times quality, using your definitions for planned time, ideal cycle, and good units. Data comes from your MES, SCADA historian, ERP, or machine logs via API, OPC, or scheduled extracts. Every component is broken out so you can see whether downtime, speed loss, or scrap is dragging the number down.
Yes. We map downtime events to reason codes, machines, shifts, and operators, then rank causes by total minutes lost and frequency. That turns a vague feeling that line three is slow into a ranked list of the changeovers, breakdowns, and material waits actually costing you output.
We routinely connect SAP, Microsoft Dynamics 365, NetSuite, Epicor, and Infor for orders, inventory, and cost, plus MES and historian systems for shop-floor data. Where there is no native connector we ingest by API, OPC, or staged database, and document every transformation so the data lineage is auditable.
Yes. We build on-time in-full (OTIF) measures, dock-to-stock and pick-to-ship cycle times, units per labor hour, and dwell or transit times from your WMS, TMS, and order data. You see which lanes, carriers, and shifts hit service targets and which quietly erode them.
You buy a block of prepaid senior-led hours that never expire, then spend them on any Power BI task. We scope each request by email and tell you the hours needed before any work begins, and hours are deducted only for work you approve. Most production or supply-chain tasks are delivered within 3–5 business days of your approval; larger multi-system builds get a clear timeline up front. See full Flex pricing on our how-it-works page.
Book a free demo
Get senior Power BI help, on demand
Tell us the task. We scope it, you approve, and a senior consultant delivers — typically in 3–5 business days. Prepaid hours that never expire.
- Prepaid hours from $100/hour — and they never expire
- Senior-led delivery — 20+ years on the Microsoft platform
- Typical 3–5 business day turnaround
- Full refund if you’re unhappy in your first 4 hours
The fastest way to reach us is the form — tell us the task and we'll reply within one business day.