How do you select the right OEE system?

You choose the right OEE system by starting with the outcome you want to achieve, not with a feature list. Look for eight things in a system:

1. is easy to use on the shop floor,

2. has reliable data,

3. provides deep loss analysis,

4. provides real-time insights,

5. matches your machine park,

6. can be integrated with other systems,

7. supports daily management,

8. is scalable so you can start simple and then grow into more advanced features.

Then test the suppliers against your actual production, not against polished demos.

Choosing an OEE system is one of the more strategic decisions a production or plant manager makes. The right system becomes the engine for improvement work in the factory for many years to come. The wrong system becomes a reporting burden that no one uses and, at worst, is replaced after a couple of years.

Throughout, we base our approach on a principle that is often missing from comparisons. An OEE system should not just be a measurement tool. It should be a tool for driving improvement work.

The difference sounds small, but it determines the outcome of the entire investment.

Where do you start when choosing an OEE system?

Start with the result you want to achieve, not with a feature list. The most common pitfall in an OEE project is starting with a list of requirements. Operator interfaces, dashboards, integration possibilities and report formats. The list grows long; suppliers tick off the items, and the choice falls to whoever ticks off the most.

The final tally shows something else. The plants that get the most out of their investment have started at the other end. They have asked themselves what they want to achieve. More capacity from existing equipment. Shorter changeover times. Less scrap and rework. Better maintenance insight. Clearer priorities in improvement work. More reliable production data for shifts, lines, and teams.

Once you know what result you are chasing, the requirements list becomes a consequence rather than a starting point. You can evaluate each feature by asking, "Does it help us get where we want to go?" rather than "Does it have that feature?"

What should you look for in an OEE system?

1. Easy to use on the factory floor

This point, more than any other, determines whether the system will create value. If operators find the interface complicated, data quality drops quickly. Stops are coded incorrectly, or not at all. The "Other" category grows. Improvement work stops.

Good operator tools do four things easily. They let operators classify stops without having to search through menus. They let them leave comments in just a few seconds. They handle scrap and rework in the same view. They make uncoded stops visible immediately, so they are not forgotten.

At Orkla Nidar, a confectionery manufacturer in Norway since 1912, one of the clearest insights was that operators could eliminate the "Other" category from reporting as soon as they were given a tool that made it easy to code the correct cause immediately. That is how data quality is built, not with discipline from above.

2. Reliable OEE logic and trustworthy data

Beautiful dashboards are useless if the underlying data is weak. The system must correctly handle planned production time, run time, stops, speed loss, quality loss, changeovers, scrap, and rework. It should also make poor data visible. Missing stop causes, activity outside the schedule, incorrect order handling and unrealistic speed patterns.

A good question to ask the supplier: "How do I, as a superuser, see that data quality is lacking, and how quickly?" If the answer requires consulting, look elsewhere.

3. Deep loss analysis

A single OEE percentage is not enough. You should be able to break down the figure by stop cause, cause group, line, part, shift, machine component, and trend over time. You should be able to answer questions like these, quickly and yourself:

• Why does part A perform worse on line 1 than on line 2?

• Which stop causes have increased over the last month?

• Which losses are frequent but short?

• Which are rare but expensive?

• Which technical problems recur on the same machine component?

Deep loss analysis is the difference between reporting and acting. At Sibbhultsverken, OEE increased by 19,4% in one cell, and technical stops decreased by 73%, precisely because they could break down losses to this level of detail and prioritise the right measures.

4. Real-time visibility that supports action

Real-time data only matters if someone can act on it while the stop is ongoing. Stopped machines, missing cause codes, lost production, and current order status. This is the difference between follow-up and management. Follow-up happens after the shift, often the next day. Management happens while the shift is ongoing.

The question to ask: "What does the production manager see right now, and what action is being taken?"

5. Connectivity that matches your reality

Few factories have only new, connected machines. Most have a mix. Modern PLC-controlled machines. Older equipment with simple signals or no signals at all. Semi-automatic processes. Manual stations. The supplier must demonstrate how they handle the entire spectrum, not just the easiest case.

Concrete questions to ask:

• How do you connect new machines?

• How do you connect 20-year-old machines without modern interfaces?

• How do you handle semi-automated processes in which the operator performs part of the work?

• How do you support manual stations that require monitoring?

• What is required of us in terms of IT?

• Are you ISO 27001-certified (information security)?

Platforms built for reality often have their own easy-to-install IoT solution. At System 3R, a Swedish company in tooling and automation solutions, a manual CNC machine was connected via Good Solutions' IoT box, which connects to 230 V and is configured via smartphone, without IT support. The capacity of that machine could then be doubled.

6. Integrations that reduce manual work

The system should not become an isolated island. It should collaborate with the rest of your operations. Order data, part data, shift structures, BI tools, and potentially ERP, MES, or maintenance systems. Questions to ask:

• How do we sync production orders?

• How do we handle master data and part information?

• Support for shift structures and calendars?

• SSO and role-based access?

• Export to our BI tools?

• What do the API possibilities look like for future integrations?

h3 7. Support for daily management and improvement work

This is where most suppliers fall short. A system that only reports OEE once a day moves nothing. A system that operates daily does.

The platform should function well in shift handovers, daily pulse meetings, production follow-up, maintenance reviews, weekly improvement meetings, and management reporting. Different roles need different views. The operator wants to see the current order and stops.

The production manager wants to see the shift in real time. The improvement manager wants to see trends and prioritise losses. Management wants to see outcomes against targets over time.

This is where lean principles and OEE merge. Plan, Do, Check, Act only works if everyone in the cycle has the same facts to work from, at the right time. The platform should make it easy to see where standards are failing, where improvements have delivered results, and where the next effort should be focused.

8. Scalability over time

The best choice is rarely the one with the longest feature list. It is the one that meets today's needs and supports tomorrow's ambitions. Think beyond the pilot. Questions to ask:

• Can the system scale across multiple lines, teams, and sites?

• Can we keep definitions consistent across the entire group?

• How have other corporate customers rolled it out?

• What happens to the data if we grow?

At SCA Wood, the platform has been rolled out at five plants: Bollsta, Tunadal, Munksund, Gällö, and Stugun. The switch took place with parallel operations to verify the outcome, so that nothing was lost along the way. That is how a scalable solution should be managed.

What are the most common mistakes when purchasing an OEE system?

The most common mistakes are choosing dashboard design over usability, underestimating operators' workflows, assuming data quality will solve itself, and buying for monthly reporting rather than daily management. Experience from more than 300 factory implementations shows a recurring pattern. Avoid them.

Choosing dashboard design instead of usability. Demos are often idealised. What matters is what the operators do with the system on a rainy Tuesday afternoon in July.

Underestimating the operators' workflow. If the interface requires more clicks than absolutely necessary, data quality drops immediately.

Assuming data quality solves itself. It does not. Data quality requires tools, routines, and attention from day one.

Placing too little focus on machine connectivity. This is often the hidden cost of an OEE project. Ask concretely how the connection takes place, what you need to do yourselves, and what happens to the old machines.

Ignoring manual and semi-automatic processes. Many systems are built for fully automated lines. If a factory has manual elements, the system must support them from the ground up.

Valuing reports more than loss analysis. Beautiful reports improve nothing. It is the ability to understand and address losses that makes a difference.

Treating integration as something secondary. An OEE system that does not integrate with your other systems quickly becomes a parallel view, creating duplicate work.

Leaving out the maintenance, IT, or improvement team in the evaluation. All three will use the system. All three should be involved in the choice.

Buying for monthly reporting instead of daily use. The value lies in daily use. If the system is only used for monthly reports, you have bought the wrong thing.

Starting too broad instead of where the value is highest. Factories that succeed often start with one line or area where the value is clearest, prove the process, and scale from there.

How do you run a better evaluation?

Run the evaluation in three steps. Define your production challenges and business goals first, involve the right people from production, maintenance, improvement, and IT, and test suppliers against real production scenarios instead of polished demos.

Define production challenges and business goals first. What are you not doing today that a good system would allow you to do? Put it in writing before the first supplier meeting.

Involve the right people. Production, maintenance, continuous improvement, and IT should be involved. They are different parts of the problem.

Test suppliers against real scenarios, not polished demos. Ask them to show how the system handles concrete situations that you actually face:

• A stop occurs and is not coded immediately. What happens? Who sees it?

• The night shift crosses midnight. Can you get a continuous production day report?

• A part performs differently on two lines. How do we find out why?

• A recurring technical problem needs to be isolated and analysed. How do we do that?

• A manual station needs a meaningful performance follow-up. What do we get to see?

Polished demos say little. Real scenarios say everything.

What should you look extra closely at?

Look extra closely at three things: information security and ISO 27001 certification, support for sustainability reporting according to CSRD, and support for lean and continuous improvements in daily operations. These three points have grown in importance over the past year and now affect the choice.

Information security and ISO 27001

More and more buyers require ISO 27001 certification. For larger customers, this is a knock-out question. Ask for proof of certification, ask about data storage within the EU, and check how the supplier handles GDPR and access control.

Sustainability reporting and CSRD

Under the CSRD, factories will be obliged to report energy and climate data in a structured manner. An OEE system that also measures energy per produced unit, linked to parts and stop causes, becomes a powerful asset. This is something few systems do well.

Support for lean and continuous improvements in daily operations

This is not new, but more and more buyers realise that an OEE system that lives separately from daily improvement work creates little value. The platform should support morning meetings, shift handovers, and improvement workshops, and not be confined to a separate corner.

How does Good Solutions work with this?

The platform from Good Solutions is built on one principle. Measurement is the means, improvement is the goal. The platform combines machine connectivity, operator tools, dashboards, timeline, reports, quality management, maintenance, Andon, energy, and operational implementation into one cohesive tool. The idea is that everyone in the factory, from operator to CEO, should work from the same facts at the pace that suits their role.

Today, the platform supports around 300 factories. Among the results are Bostik, which improved OEE by 40% and shortened changeover times by 70% through systematic DMAIC work. Barilla Wasa increased net production by 15% while reducing CO₂ consumption by 28%. Willo in Växjö, where half of the factory, with 60 CNC machines, was set up in six weeks.

What ties these results together is not the software alone. It is the combination of the platform, a proven implementation process led by experts with production experience, engaged employees in the factory, a Swedish support organisation that follows you as a customer over time, and a clear focus on supporting lean and continuous improvements in daily operations.

Good Solutions' ISO 27001 certification, effective from April 2026, also meets the requirements of larger factories and industrial groups.

Read more about how others have increased their factory's productivity

FAQ

How long does it take to implement an OEE system?
It varies depending on size and complexity. A single line can get started in a few weeks. A whole factory with 60 machines has done it in six weeks when the implementation is well-planned. For multi-site groups, the implementation is often planned in phases, typically over six months or more, with parallel operations to verify the outcome at each step.

What does an OEE system cost?
The cost can depend on the number of machines, which modules you need, and how you want the implementation carried out. Most suppliers operate on a subscription model that includes software, IoT hardware if needed, cloud hosting, support and updates. Ask for a quote that covers both the first year and ongoing costs, so you can compare on equal terms.

How do we get a return on the investment?
The most common way is to start from an estimated improvement in OEE. Even a modest increase, from 50 to 55%, corresponds to 10% higher output from the same machine time. For a factory that would otherwise have had to run an extra shift or invest in new equipment, the savings are often significant. Add to that reduced scrap, reduced energy consumption per unit, and shorter changeover times.

Do we need to replace our current system?
Not necessarily. Many factories run in parallel during a transition period to verify that the new system provides the same or better data. Questions to ask a new supplier: Can we monitor the same KPIs? Can the history be transferred, and what happens to our existing machine signals?

Which roles should be involved in the evaluation?
At least four roles. Production, because they use the system daily. Maintenance, because maintenance data and OEE data must work together. Continuous improvement is where the value is realised. IT, because integration and security need to be managed. For larger companies, management and purchasing should also be involved from the start.