TEEP vs OEE: Formulas, Differences and When to Use Each
Most factories measure OEE and stop there. But OEE only looks at the hours you scheduled for production ā it can't tell a plant owner whether the real constraint is the machines or the calendar. Total Effective Equipment Performance (TEEP) closes that gap. It takes the same effectiveness math as OEE and measures it against every hour on the clock, so you can see how much of your true capacity is actually producing ā and how much is sitting idle on nights, weekends, and unscheduled shifts.
This guide covers what TEEP is, the TEEP formula with a worked example using a 15-machine wood factory, how TEEP compares with OEE and OOE, and when each metric earns its place.
What is TEEP?
TEEP, or Total Effective Equipment Performance, measures how much good output your equipment produces compared with what it could produce if it ran perfectly every hour of the calendar ā 24 hours a day, 7 days a week.
It builds directly on OEE. Where OEE asks "how well did we run during the time we planned to produce?", TEEP asks the bigger question: "how much of all available time turned into good product?" The difference is the time you never scheduled in the first place ā the nights, weekends, and idle shifts that OEE simply ignores.
That makes TEEP a strategic number. A high OEE paired with a low TEEP is not a failure; it usually means a factory is running its scheduled shifts well but leaving large blocks of calendar time unused. For a plant owner deciding whether to invest, that gap is the most important thing on the dashboard.
The TEEP formula and how to calculate it
TEEP combines two ideas: how effectively you run when you're running, and how much of the calendar you're running at all.
TEEP = Utilisation Ć OEE
The two inputs break down as:
OEE = Availability Ć Performance Ć Quality
Utilisation = Planned Production Time Ć· All Time
A quick note on the time terms, because mixing them up is the most common TEEP mistake:
All Time is every hour in the period ā a full week is 168 hours, whether or not a single machine runs.
Planned Production Time is the time you actually scheduled for production in that period.
Fully Productive Time is the slice of planned time that produced good parts at full speed ā and that is already captured inside OEE.
So OEE tells you how well the scheduled hours went, Utilisation tells you how much of the calendar those scheduled hours covered, and TEEP multiplies the two.
TEEP calculation step by step
Let's extend the same 15-machine wood factory used in our OEE calculation guide. That shift came out at 74.1% OEE (86.7% Availability Ć 90.0% Performance Ć 95.0% Quality). Now we add the utilisation layer.
The factory runs one 8-hour shift, five days a week. After a 30-minute break, that is 450 minutes of planned production per machine per day, or 7.5 hours.
Step 1 ā Planned Production Time for the week: 7.5 hours Ć 5 days = 37.5 hours per machine.
Step 2 ā All Time for the week: 24 hours Ć 7 days = 168 hours.
Step 3 ā Utilisation: 37.5 Ć· 168 = 22.3%.
Step 4 ā TEEP: 22.3% Ć 74.1% = 16.5%.
So machines running at a respectable 74.1% OEE deliver a TEEP of just 16.5% ā because they are only scheduled to about a fifth of the week. Put plainly: more than 80% of this factory's calendar capacity is untapped, and almost none of it is a machine problem.
Here is where it gets interesting for capacity planning. Add a second shift ā same machines, same 74.1% OEE ā and Planned Production Time doubles to 75 hours a week. Utilisation rises to 44.6%, and TEEP climbs to 33.1%. The factory roughly doubles its real output without buying a single machine.
TEEP vs OEE vs OOE comparison table
OEE, OOE, and TEEP are the same calculation viewed through three different windows. All three multiply availability, performance, and quality ā the only thing that changes is the block of time you measure against.
| Metric | Time it measures against | The question it answers | Best used for |
|---|---|---|---|
| OEEOverall Equipment Effectiveness | Planned production time ā scheduled hours only, with breaks and planned maintenance removed | How well do we run during the hours we planned to produce? | Day-to-day and shift-level performance |
| OOEOverall Operations Effectiveness | Total operating time ā all staffed hours, including breaks, meetings, and planned stops | How well do we run across every hour the operation is actually manned? | Bridging daily performance and scheduling decisions |
| TEEPTotal Effective Equipment Performance | All calendar time ā 24 hours a day, 365 days a year | How much of every possible hour becomes good product? | Strategic capacity and invest-or-optimise decisions |
Because each metric divides by a larger block of time as you move down the table, the same factory will almost always show OEE ā„ OOE ā„ TEEP. The wider the gap between OEE and TEEP, the more capacity is hiding in your calendar rather than in your machines.
When OEE is the right metric
OEE is the right tool for running the floor day to day. When the goal is to improve what happens inside the hours you have already scheduled, OEE points straight at the problem.
Use OEE when you are:
Managing daily performance ā tracking availability, speed, and quality shift by shift.
Hunting specific inefficiencies ā frequent breakdowns, slow cycles, or rising scrap show up in the OEE component breakdown before they show up anywhere else.
Driving short-term improvements ā the changeover, maintenance, and quality fixes a production team can act on this week.
A simple example: a line sitting at 60% OEE with 70% availability (20% of it unplanned downtime) can lift availability to roughly 76% with predictive maintenance, pushing OEE to about 65% ā a realistic gain with no new equipment. That is an OEE conversation, not a TEEP one.
For the full step-by-step math, see our OEE calculation guide, and for the availability component specifically, our machine availability guide.
When TEEP matters: finding hidden capacity before buying machines
TEEP answers the question a plant owner actually asks: do I buy another machine, or get more out of the ones I already have?
Go back to the wood factory. At one shift it runs 74.1% OEE but only 16.5% TEEP. A natural reaction to a full order book is to quote a new machine. But the TEEP number says the existing machines are idle more than three-quarters of the calendar. Adding a second shift took TEEP from 16.5% to 33.1% ā roughly doubling output ā for the cost of labour and scheduling, not capital equipment.
That is the trade every owner should price out before signing a purchase order: the monthly cost of a second shift against the capital cost, financing, floor space, and installation of a new machine that would also sit idle most of the week if the scheduling problem is not fixed first.
This is where measuring against the full calendar pays off. One GlobalReader customer, JABS, used utilisation data to prove they were genuinely running near 95% of their realistic capacity ā which is exactly what gave them the confidence to buy a new machine, knowing the demand was real and the existing fleet was truly maxed out, not just under-scheduled. TEEP turns "we feel busy" into hour-by-hour proof.
The honest version of this number only exists if you measure utilisation against true 24/7 calendar time ā which is the next problem.
What good TEEP looks like
There is no single "good" TEEP, because the ceiling depends on how many shifts you intend to run. A plant that deliberately runs one shift cannot compare its TEEP to a 24/7 continuous operation ā and should not try.
As a rough orientation: a world-class continuous operation that runs nearly all the calendar at high OEE can reach a TEEP in the region of 80%. Many factories running one or two shifts at typical OEE land somewhere around 30ā40%, with substantial headroom left in the calendar. A single-shift operation like our wood factory can be performing well on OEE and still post a TEEP in the teens ā and that is expected, not alarming.
The useful comparison is always against your own baseline and your own scheduling intent, not a universal benchmark. The real signal is the gap between your OEE and your TEEP: a wide gap means the opportunity is in the schedule; a narrow gap means it is in the machines.
How to track TEEP automatically
TEEP is only honest if it is measured against real, round-the-clock data. The moment utilisation depends on someone remembering which hours a machine ran ā and which short stops or idle nights went unlogged ā the number drifts, and a drifting TEEP leads to exactly the wrong capacity decision.
That is why 24/7 automatic measurement is what makes TEEP trustworthy:
Real-time monitoring captures running state, downtime, and output as they happen, across every hour ā not just the hours someone was watching.
Production analytics surface the patterns that matter for TEEP: underused shifts, idle weekends, and the true utilisation rate against the full calendar.
Predictive maintenance lifts the OEE half of the equation by cutting the unplanned downtime that quietly drags both numbers down.
GlobalReader connects directly to your machines and measures all of this continuously, so OEE and TEEP come from the same trusted data instead of two different spreadsheets. If you want to see your own hidden capacity, see how it works.
āGlobalReader is so simple that an operator who had never seen it immediately understood what to do.ā
No financial commitment needed. Log in using your Google account and youāll be guided through everything with ease!
FAQ
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In almost every real factory, yes. OEE measures performance against planned production time, while TEEP measures it against all calendar time ā and since the calendar is always at least as large as your scheduled hours, TEEP comes out equal to or lower than OEE. They would only be equal in a true 24/7 operation with no unscheduled time at all. If you ever see TEEP higher than OEE, it is a sign your time buckets are defined inconsistently and need standardising.
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Utilisation is only one ingredient of TEEP. Utilisation measures time alone ā what share of the calendar your equipment was scheduled to run (Planned Production Time Ć· All Time). TEEP multiplies that utilisation by OEE, so it also accounts for how well those scheduled hours actually went in terms of availability, speed, and quality. High utilisation with poor OEE still produces a low TEEP, and the reverse is equally true.
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Start with OEE. You need trustworthy availability, performance, and quality data before TEEP means anything ā TEEP is built on top of OEE, so a shaky OEE makes for a meaningless TEEP. Once your OEE data is clean and your team is acting on it, add the utilisation layer to get TEEP and bring the calendar into your capacity decisions. Build the foundation, then widen the lens.
