Overall Equipment Effectiveness (OEE) Dashboard – Your KPIs, Visualized

In manufacturing, Overall Equipment Effectiveness (OEE) is a KPI that represents the overall productivity of a machine. OEE compares the performance of a machine to its relative capacity, resulting in a score metric for a specific scheduled run. Manufacturers generally consider OEE to be one of the most critical measurements to gauge the efficiency of machines and industrial equipment.

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An OEE Dashboard is a production visibility tool that displays real-time OEE scores in a public, easy-to-understand visual format.

These operations dashboards aggregate OEE calculations across the shop floor and provide relevant analytics (like downtime reason and first-pass yield) to monitor and improve the performance in your operations.

Dashboards for one machine, dashboards for the whole shop

Typically, OEE is measured at a few levels.

1. The machine-level
2. The department level
3. The shop level

OEE dashboards can be as granular (single machine) or as holistic (full machine shop) as you like. The purpose of any manufacturing dashboard is to help you put production in context by making performance data available at a glance.

Displaying OEE for a single machine

Measuring OEE at the machine level provides insight into the specific utilization and efficiency of a machine. If you are implementing changes in your process, machine-level monitoring of OEE can provide valuable insight into bottlenecks and efficiencies.

Displaying OEE for the whole shop

Measuring OEE at the shop level provides a comprehensive view of your entire operation, returning a single value to summarize all of your individual machine OEE metrics. This is a useful tool for measuring the overall productivity of your shop, as well as for identifying bottlenecks.

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Calculating and monitoring OEE in a dashboard at these different levels can get complicated. Especially if you’re running manual time studies and recording on paper.

Shops with many machines would need a small army of monitors to keep track of uptime and downtime as operators are focused on performing their tasks. And then the math would need to be aggregated and updated regularly.

Manufacturing Execution Systems and SCADA systems can have some functionality built in to report on OEE dashboards. But these systems aren’t designed with end-users in mind. As a result, configuring simple dashboards can be enormously complicated.

No-code digital dashboards provide a middle ground, eliminating the burden of collecting and analyzing OEE data by hand without the complexity of monolithic systems.

By letting you connect data streams to visualizations without having to write any code, digital dashboards transform the way you measure OEE.

Putting OEE in context

Ultimately, OEE’s value is diagnostic. In other words, it gives you an overview of the various factors that contribute to operational efficiency.

To get the most out of OEE, you need to combine it with other metrics.

Here are some of the ways that OEE dashboards let you put machine performance in context.

OEE over time

Dashboards can display OEE data on a real-time, daily, quarterly, or another cadence. This lets you see if there are any persistent problem areas, and can help you track whether or not your improvements are making a difference. When you combine time data with machine type, machine OEE by type, or by program, you can get a detailed view of production.

OEE with other analytics

Dashboards let you place different types of data side-by-side, making new insights possible. For example, you could display pareto charts next to OEE to see the most common causes of downtimes and quality defects together. You could also place OEE next to a performance tracker to view goals, track shift progress, and gather insights into data for reporting and informed decision-making.

OEE with human-centric data

Often, low OEE isn’t a result of poor machine performance. It’s a result of human activity around a machine. Also known as Overall Process Effectiveness (OPE), OEE dashboards can help you gather downtime reasons, changeover times, tool status, and other human-centric metrics to help you determine the root cause of low OEE.

OEE dashboard only helps if it drives action. Plenty of systems show numbers, but few show what those numbers mean or how to respond. A solid OEE dashboard gives the team what they need to see problems early and make decisions fast.

Real-Time Machine Data
Live data is the heart of it. Without direct connections to machines, sensors, or PLCs, you’re looking at old information. The best setups pull data straight from the line so what you see on the screen matches what’s happening right now. No manual uploads. No waiting until the end of a shift to find out something went wrong.

Views That Fit the Role
Not everyone needs the same picture. Operators care about cycle times, downtime events, and target pace. Supervisors want shift performance. Managers need trends across lines or sites. Dashboards work best when you can change what’s shown without digging into code or calling IT.

Built-In OEE Calculation
Hand-calculating OEE leads to confusion. A good dashboard handles the math automatically and uses one consistent formula for availability, performance, and quality. That way everyone i.e. from the line lead to the plant manager, is speaking the same language about efficiency.

Alerts That Catch Issues Early
You shouldn’t have to hunt for problems in the data. When cycle time drifts or scrap creeps up, the system should flag it. Simple alerts like emails, texts, or on-screen prompts help people react before small issues turn into downtime.

Links to Other Systems
An OEE dashboard isn’t a standalone tool. It should connect with your MES or ERP so the numbers carry context: what order’s running, who’s operating, when maintenance last happened. That’s how you turn data into decisions instead of just another report.

Most teams don’t lack OEE data, they lack the right way to see it. An OEE dashboard changes that. Instead of drowning in spreadsheets or stale reports, manufacturers get a living window into how their operations are running, moment by moment.

Here’s what a well-built dashboard unlocks:

Real-time visibility into operations
Whether you're monitoring a single machine or an entire line, dashboards surface production trends the moment they happen. This allows supervisors to catch slowdowns early, rather than react hours later. For teams running multiple shifts, that visibility ensures nothing slips through the cracks between handoffs.

Data-driven decision-making
Dashboards connect the dots between availability, performance, and quality (OEE's core metrics), so teams can make smarter calls faster. Rather than guessing why output dipped on Line 3, a dashboard reveals if it was due to unplanned stops, reduced speed, or scrap. It replaces hunches with hard evidence.

Root cause identification
Downtime is expensive. But the bigger cost is not knowing why it happened. With historical and real-time OEE data in one view, teams can quickly trace losses back to a specific machine, shift, or process step. This precision enables targeted fixes instead of broad assumptions.

Cross-functional alignment
OEE dashboards serve as a shared reference point for operators, engineers, and managers alike. Everyone sees the same numbers, the same trends, and the same priorities. That transparency builds trust and drives better collaboration on root cause analysis and continuous improvement initiatives.

You don’t need a team of analysts or a long project plan to build an OEE dashboard. With the right tools and a clear idea of what you’re tracking, you can have something working in days, not weeks. The real work is knowing what to measure and how to make the data useful.

1. Pick the Metrics That Actually Matter
Start with the problem you’re trying to solve. Maybe downtime is creeping up, or you’re losing yield on a certain line. Figure out which numbers tell that story, it can be availability, performance, quality, or a mix of all three. Keep it focused. Too many metrics just create noise.

2. Get Reliable Data From the Source
Everything depends on the data. Connect directly to machines, sensors, and operator inputs so the information is real-time and accurate. PLC signals, barcode scans, or touchscreen entries are all fair game. Automate as much as you can; manual data entry should be rare.

3. Link Machines and Systems
Don’t let each machine or software system sit on an island. Tie them together so the dashboard pulls from one version of the truth. MES, ERP, and line equipment data should feed into a single platform. That’s how you see what’s really happening instead of juggling spreadsheets.

4. Make the Data Easy to Read
Numbers alone don’t help much. Charts, gauges, and timelines give context and show patterns at a glance. Operators might need cycle time, downtime causes, and current OEE. Supervisors care more about shift trends and bottlenecks. Everyone should be able to see what matters without hunting for it.

5. Use It to Drive Improvement
Once the dashboard’s running, treat it as part of the daily routine. Review it during shift handoffs. Look for trends. Start small improvement projects based on what the data shows. A good dashboard doesn’t just report, it guides action.

Getting There Faster with Tulip
Tulip’s dashboard tools make setup straightforward. Drag, drop, connect your data, and go. No coding, no waiting in the IT queue. Engineers and team leads can build their own dashboards and adjust them as needs change.

Tulip’s no-code operations platform makes getting started with OEE dashboards simple. Our machine shop app suite includes all of the applications you need to display meaningful machine data out of the box.