Yesterday's OEE Was 78%. What Should You Ask Next?

Yesterday's OEE Was 78%. What Should You Ask Next?

Yesterday’s OEE was 78%. Is that good or bad? More importantly, what should you do with that information today?

An OEE figure can tell you that production did not perform as planned, but the percentage itself does not explain what happened. If yesterday’s OEE was 78%, the useful conversation does not end with the number.

It starts there.

Was the loss caused by Availability, Performance or Quality? Did one machine create most of the problem? Was the loss concentrated in one shift? Did a particular work order perform differently from the others? Was there a maintenance intervention? And is this the first time it happened?

This is the difference between measuring OEE and using OEE to manage production.

First question: Where did we lose the other 22%?

The first step is to stop treating 78% as one number and understand what is behind it.

OEE combines three components: Availability, Performance and Quality. Two production days can therefore both finish with an OEE of 78% for completely different reasons.

Consider two illustrative examples:

	Factory A	Factory B
Availability	82%	95%
Performance	97%	84%
Quality	98%	98%
OEE	~78%	~78%
Main problem	Downtime	Slow production

The final OEE is almost identical.

The action should not be.

Factory A needs to investigate why equipment was unavailable. Factory B should look at cycle times, micro-stops, production speed or other Performance losses.

This is why an OEE software solution becomes significantly more useful when OEE is connected with actual production information.

Was the problem everywhere—or somewhere specific?

A factory-level OEE can hide a production problem that exists on only one line, machine or shift.

Yesterday’s overall OEE may have been 78%, but perhaps Line 1 achieved 87%, Line 2 achieved 85% and Line 3 finished at 63%.

Now we have a much better question:

What happened on Line 3?

The same principle applies to shifts. An acceptable daily average can hide several hours of poor performance during one part of the day.

Production managers therefore need the ability to move from the high-level KPI toward the underlying production information.

The objective is not to create more KPIs.

It is to find where attention is required.

Which work order was running when performance dropped?

OEE becomes operationally useful when it can be connected with what the factory was actually producing.

Suppose the performance loss on Line 3 occurred primarily while producing Work Order WO-3174.

That immediately opens another set of questions.

Was the expected cycle time realistic for that product? Did the line experience more stops during this work order? Was there a changeover before production started? Did Quality change? Was the same product associated with similar performance losses previously?

Without Production Management context, the information may simply say:

Line 3 — OEE 63%.

With production context, it can become:

Line 3 performed below target primarily during Work Order WO-3174, with the largest loss occurring in Performance.

That is much closer to information someone can act on.

Did a machine problem contribute to the loss?

When Availability drops, the next question is not simply how long production stopped, but what happened to the equipment.

This is where the Maintenance module provides another perspective.

In TAP Smart Factory, the graphical factory overview can provide a quick visual indication of machine status using green, yellow and red. From the overview, users can access individual equipment and the information associated with its operation, maintenance, interventions and repairs.

If yesterday’s OEE loss was connected with a particular machine, its maintenance history can provide important context.

Did this machine experience the same problem last week?

Has it required several interventions recently?

Is this an isolated event or something recurring?

Production Management, OEE and Maintenance are answering different questions about the same production environment.

How much production did 78% OEE actually cost?

Percentages become easier to prioritize when they are translated into production impact.

Imagine a line scheduled to produce 4,000 units during a shift. If production losses result in 500 fewer good units than planned, management can understand the consequence much more directly than from an OEE percentage alone.

The same principle can be extended to time, production capacity or—when the required business data is available—financial impact.

This matters because not every percentage point has the same operational importance.

A small OEE loss on a bottleneck producing an urgent order may deserve more attention than a larger loss on equipment with available spare capacity.

OEE provides the measurement.

Production context provides the priority.

Should you wait until tomorrow to ask these questions?

The best time to understand a production loss is while there is still an opportunity to influence the result.

Yesterday’s OEE is valuable for reporting and analysis. Real-time production monitoring adds another possibility: asking the same questions while the shift is still running.

If Performance begins to decline at 11:00, the production team does not necessarily need to wait until tomorrow morning to discover it.

If Availability suddenly decreases, the relationship between machine status, downtime and production can already be investigated.

This is where a MES system moves beyond reporting what happened and becomes part of daily Production Management.

For Lean Manufacturing and Kaizen activities, historical information remains essential because recurring losses need to be identified over time. But real-time visibility creates the opportunity to prevent today's problem from simply becoming tomorrow's report.

Where does Reporting fit into the picture?

A good report should help generate the next question—not simply present yesterday’s numbers.

Reporting can bring together OEE, production quantities, downtime, work orders and equipment information so that managers can move from an overview toward the cause of a production loss.

ERP systems provide another important part of the environment. TAP Smart Factory is not an ERP solution. It can complement systems such as SAP and Microsoft Dynamics 365 Business Central (formerly Navision) while communicating with PLCs, machines, sensors, cameras, printers and other production equipment.

The result is a connected Smart Manufacturing environment where business planning and actual shop-floor performance can be compared.

What should you ask after seeing 78%?

TAP Smart Factory is a modular MES system for real-time production monitoring developed by T3Soft.

By connecting OEE with Production Management, Maintenance and Reporting, TAP allows a production KPI to become the beginning of an investigation rather than the end of a report.

So tomorrow morning, if somebody says:

“Yesterday's OEE was 78%.”

the next question should not simply be:

“Is 78% good?”

Ask:

Where did we lose the other 22%?
Which line, shift or machine caused the loss?
Which work order was affected?
Was it Availability, Performance or Quality?
Has the same problem happened before?

Because 78% tells you what happened to OEE.

The questions behind it tell you what to do next.