How do you select the right OEE system?

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

1. is easy to use on the floor,

2. has reliable data,

3. provides deep loss analysis,

4. gives real-time insights,

5. matches your machine fleet,

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 vendors against your actual production, not against polished demos.

Choosing an OEE system is one of the more strategic decisions that 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, in the worst case, is replaced after just a couple of years.

Remember that an OEE system should not just be a measuring instrument. It is an important tool in the work of continuous improvements.

Where do you start when choosing an OEE system?

Start with the results you want to achieve, not with a feature list. The most common trap in an OEE project is to start with a list of requirements.

Operator interfaces, dashboards, integration options, report formats. The list becomes long, vendors check off the items, and the choice falls on the one who checks off the most.

The final tally shows something else. The factories 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.

When you know what result you are chasing, the requirement list becomes a consequence, not a starting point. You can evaluate every feature against the question "Does it help us get where we want to go?" instead of "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 clunky, data quality drops quickly. Downtime is coded incorrectly, or not at all. The "Other" category grows. Improvement work stalls.

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

At Orkla Nidar, a candy manufacturer in Norway since 1912, one of the clearest insights was that operators could eliminate the "Other" category from reporting as soon as they received a tool that made it easy to code the correct cause directly and to get better and more actionable information about losses.

2. Reliable OEE logic and trustworthy data

Fancy dashboards are useless if the underlying data is weak. The system must handle planned production time, run time, downtime, speed loss, quality loss, changeovers, scrap, and rework correctly. It should also make poor data visible, so you can find and adjust inaccuracies and thereby become more confident in your data. Missing downtime causes, activity outside the schedule, incorrect order handling, and unrealistic speed patterns.

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

3. Deep loss analysis

Having the system deliver an OEE number is not enough. You should be able to break down the figure by downtime cause, cause group, line, article, shift, machine part, and trend over time. You should be able to answer questions like these, quickly and by yourself:

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

• Which downtime causes have increased in the past month?

• Which losses are frequent but short?

• Which are rare but expensive?

• Which technical problems recur on the same machine part?

Deep loss analysis is the difference between reporting and acting. At Sibbhultsverken, OEE increased by 19.4 percent in one cell and technical downtime decreased by 73 percent, precisely because they could break down losses to this level of detail and prioritize the right efforts.

4. Real-time visibility that supports action

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

The question to ask: "What is the production manager seeing 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 vendor must show how they handle the entire breadth, 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-automatic processes where the operator performs part of the work?

• How do you support manual stations that need to be followed up?

• What is required from us in terms of IT?

• Are you ISO 27001 certified (information security)?

Platforms built for reality often have their own IoT solution that is easy to install. 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 cooperate with your other operations. Order data, article 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 article information?

• Support for shift structures and calendars?

• SSO and role-based access?

• Export to our BI tools?

• What do the API possibilities look for future integrations?

h3 id="63">7. Support for daily management and improvement work

This is where most vendors fall short. A system that only reports OEE once a day moves nothing. A system that lives in daily operations does.

The platform should work 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 downtime.

The production manager wants to see the shift in real time. The improvement leader wants to see trends and prioritized losses. Management wants to see outcomes against the goal 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 base their decisions on, at the right time. The platform should make it easy to see where standards are failing, where improvements have yielded 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 out?

• What happens to the data if we grow?

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

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

The most common mistake is choosing dashboard design over usability, underestimating the operators' workflow, assuming that data quality solves itself, and buying for monthly reporting instead of daily management. Experience from implementations in over 300 factories shows a recurring pattern. Avoid them.

Choosing dashboard design over usability. Demos are often polished. What matters is what 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 that 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 in an OEE project. Ask concretely how connection occurs, what you need to do yourselves, and what happens to 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. Fancy 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 talk to your other systems quickly becomes a parallel view with duplicate work.

Leaving the maintenance, IT, or improvement team out of 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. Successful factories often start with a single 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 vendors 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 provide? Put it in writing before the first vendor meeting.

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

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

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

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

• An article performs differently on two lines. How do we find out why?

• A recurring technical problem needs to be isolated and analyzed. How do we do it?

• 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 improvement in daily operations. These three points have grown in importance over the past year and influence the choice now.

Information security and ISO 27001

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

Sustainability reporting and CSRD

With CSRD, factories are obliged to report energy and climate data in a structured way. An OEE system that also measures energy per unit produced, linked to articles and downtime causes, becomes a powerful asset. This is something few systems do well.

Support for lean and continuous improvement in daily operations

This is not new, but more and more buyers realize 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 sit in 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 operations 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 over 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 got started in six weeks.

What binds the 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 organization 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 from April 2026 also meets the requirements of larger factories and 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, implementation is often planned in stages, frequently over six months or more, with parallel operation 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 to be carried out. Most vendors work with a subscription model that includes software, IoT hardware if needed, cloud hosting, as well as 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 investment? The most common way is to start from an estimated improvement in OEE. Even a modest increase, from 50% to 55%, corresponds to a 10% higher yield during the same machine time. For a factory that otherwise would 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 vendor: Can we track the same KPIs? Can history be migrated, 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, as that is where the value is realized. IT, because integration and security need to be managed. For larger companies, management and procurement should also be involved from the beginning.