OEE, TEEP, and OAE aren’t interchangeable. They use different time bases and belong to different parts of your organization. Here’s how to tell them apart and pick the right one.
Introduction
While most plants track OEE, a few may have heard of TEEP, and even fewer know what OAE actually measures. What most plants fail in, is distinguishing which of the three you should actually be looking at a given day. This is probably why so many operations end up reporting all three and trusting none of them.
What people miss is that they’re not interchangeable. Each one uses a different time base, answers a different question, and belongs to a different level of the organization. If one uses OEE where TEEP belongs and they’ll make a capacity decision on incomplete information. If they use TEEP on the shop floor, they’ll confuse every supervisor who reads it. This post lays out exactly what separates them and gives you a straightforward way to decide which one fits the problem in front of you.
OEE vs TEEP vs OAE at a glance
Before getting into the detail, here is the full comparison. If you already know the basics and just need a quick reference, this table has it.
Comparison of OEE, TEEP, and OAE metrics across key dimensions
| Dimension | OEE | TEEP | OAE |
|---|---|---|---|
| Full name | Overall Equipment Effectiveness | Total Effective Equipment Performance | Overall Asset Effectiveness |
| Formula | Availability × Performance × Quality | Loading time × OEE | Asset utilisation × OEE |
| What it measures | Efficiency during scheduled production time | Efficiency across all available calendar time | Effectiveness across the total asset base |
| Time base | Planned production time | All available time (including unscheduled) | Total scheduled time (including idle assets) |
| When to use it | Daily line improvement, shift targets, operator accountability | Capacity decisions, capex justification, multi-shift strategy | Fleet-level benchmarking, asset rationalisation, site planning |
| Who reports it | Line manager, shift supervisor | Operations director, plant manager | Asset manager, VP Operations |
| World-class benchmark | 85% | No universal benchmark (context-dependent) | No universal benchmark (context-dependent) |
| OmniOEE tracks it? | Yes, in real time | Yes, when loading time is configured | Yes, across multi-asset and multi-site deployments |
Why do three metrics exist for the same thing?
They’re not measuring the same thing, exactly. OEE, OAE, and TEEP all look at how effectively you’re using your equipment, but they use different time bases, and that difference matters more than most teams realize.
Think of it this way:
- OEE asks: ‘During the time we planned to produce, how well did we do?‘
- TEEP asks: ‘If we ran around the clock, how much of that full calendar time were we actually producing?‘
- OAE asks: ‘Across our entire asset base, how effectively are we utilizing what we own?‘
Three different questions with three different answers. The issue is most plants treat OEE as a universal scorecard when it was only ever designed to measure what’s happening during scheduled production runs.
OEE: the metric you use every shift
OEE is the most practical of the three. It runs on a simple formula: Availability x Performance x Quality. It addresses the question plant managers actually ask every morning: why didn’t we hit target yesterday?
Availability captures lost time. Did the line run when it was supposed to? Equipment failures, slow changeovers, and unplanned stoppages all drag this number down.
Performance captures lost speed. Did the line run at the rate it should? Reduced speed and micro-stoppages show up here, not in availability.
Quality captures lost output. Out of everything produced, how much was first-pass good? Scrap, rework, and startup rejects go here.
The world-class OEE benchmark is 85 percent. Most plants run somewhere between 60 and 75 percent when they first start tracking honestly. The gap between where you are and 85 percent is where the money is.
One thing OEE doesn’t capture however, is time you didn’t schedule. If your plant runs two shifts and goes dark on weekends, OEE won’t tell you what’s happening to that idle capacity. That’s TEEP’s job.
TEEP: the metric you use when you're making capacity decisions
TEEP extends OEE by adding a fourth factor: loading time. The formula is Loading Time x OEE, where loading time is the ratio of planned production time to total available calendar time.
The practical effect: if you run one eight-hour shift five days a week, your loading time is roughly 24 percent of total available time. Multiply that by even a strong OEE score and your TEEP will look sobering. That’s the point. TEEP is designed to show how much of your theoretical capacity you’re actually using.
This is the metric you want in the room when you’re deciding whether to add a shift, buy another machine, or move production to a different facility. It answers a question OEE can’t: are we running out of capacity, or are we just running inefficiently during the time we’ve already allocated?
A plant with a 78 percent OEE running two shifts looks healthy. The same plant’s TEEP might be 37 percent. That tells leadership there’s still significant headroom before a capex investment is genuinely necessary.
OAE: the metric you use when you're managing an asset fleet
OAE, or overall asset effectiveness, shifts the frame from a single line to the full asset base. Where OEE looks at utilized time and TEEP looks at available calendar time, OAE looks at the total scheduled time across all your assets, including machines that aren’t running at all.
It’s the right metric when you have multiple production lines and need to compare them fairly, when you’re doing an asset rationalization exercise, or when you’re filing reports under an asset management standard like ISO 55001.
In practice, OAE doesn’t get reported to shop floor operators. It’s a planning and governance metric, sitting at the operations director or VP level. If someone on your team asks what your OAE is, they’re not asking about yesterday’s shift. They’re asking whether you’re getting enough work out of the assets on your books.
Which metric should you actually use?
Here’s a simple decision guide. Most plants end up reporting OEE to the floor, TEEP to operations leadership, and OAE occasionally for asset planning. Very few plants need to track all three on a daily basis.
Guide for choosing the best metric based on your situation
| Your situation | Best metric to lead with |
|---|---|
| You want to improve shift-by-shift performance on a single line | OEE |
| You're deciding whether to add a third shift or buy a new machine | TEEP |
| You manage multiple production lines and need to compare them | OAE |
| Your plant runs 24/7 with no scheduled downtime | OEE TEEP Will converge — track both, report OEE to the floor. |
| You're presenting to the CFO or board on capacity utilisation | TEEP Shows the true cost of idle capacity. |
| You want a metric for a regulatory or asset management report (e.g. ISO 55001) | OAE |
| You're benchmarking against industry peers | OEE The only one with widely published benchmarks. |
One thing worth saying plainly: if you’re not reliably tracking OEE yet, don’t start with TEEP or OAE. Get your availability, performance, and quality data clean first. TEEP and OAE are multiplication on top of OEE. If the OEE number is wrong, everything downstream is wrong too.
What this looks like in a real plant
Take a food and beverage plant running two production shifts. The question that usually starts an OEE conversation there isn’t about metrics at all. It’s about why resolution time on production issues is measured in days when it should be measured in hours. OEE is the right tool for that problem because it’s a shift-level performance problem. The plant isn’t under-scheduled. It’s losing time during production, and OEE tells you exactly where.
Contrast that with a multi-line operation where the operations director needs to compare output across four packaging lines with different run speeds and changeover profiles. Daily OEE still runs on the floor, but OAE becomes the relevant number at the planning level because it normalizes across the asset base and shows which lines are genuinely underperforming versus which ones are just scheduled less.
TEEP tends to enter the picture when someone upstream asks a capacity question. If the MD wants to know whether a third shift is worth running before signing off on new headcount, a TEEP figure makes the case far more clearly than OEE ever could. The pattern is consistent: start with OEE, bring in TEEP when capacity decisions arrive, and reach for OAE when you’re managing assets across lines or sites.
How OmniOEE handles all three
Real-time OEE is on by default. From the moment OmniOEE is connected to a line, it’s capturing availability, performance, and quality data and surfacing them live.
TEEP requires one additional configuration step: you tell the system what the production calendar looks like for each asset, and it handles the loading time calculation from there. Most teams set this up once during deployment and then forget about it, which is how it should work.
OAE is where multi-site clients tend to get genuinely surprised. Because OmniOEE aggregates from individual machine data up through line, plant, and site levels, OAE figures for the full asset base are already sitting in the platform. You’re not commissioning a separate report. You’re just changing the level of the hierarchy you’re looking at.
The same raw data powers all three numbers. When your MD needs a TEEP figure for a board pack and you’ve never pulled one before, you’re not rebuilding anything from scratch. It’s there. That’s not a small thing if you’ve ever spent a weekend before a board meeting manually reconciling shift logs.
Get OEE clean and trusted first. The questions that lead you to TEEP and OAE will arrive on their own. When they do, OmniOEE already has the numbers ready. Same data feed, different lens.
Sounds interesting? Talk to our experts to learn more about OmniOEE.