Managing Preventive, Corrective, and Breakdown Orders in SAP PM: A Practical Approach

At 2BM Software we are preparing the next major release of our Digital Maintenance Suite. We are integrating KPI’s across the maintenance process giving everyone from technicians to plant managers access to live insights – right from their mobile app. The key prerequisite for unlocking the power of this new functionality is a well structured digital maintenance process. In this post we explore one of the most fundamental decisions when adopting SAP Plant Maintenance: how to structure your order types.

Over the years, I’ve worked with many organizations that use SAP Plant Maintenance (PM), and I’ve seen almost as many different ways of structuring order types. Some use a very granular structure with separate order types for every maintenance scenario. Others go the opposite direction and use just one for everything.

Each approach has its pros and cons, but I’ve also seen some common pitfalls – especially when it comes to reporting accuracy, planning efficiency, and overall process clarity. Starting with the right order type strategy is essential. It’s a central part of how digital maintenance is structured, and if it’s not well thought through, it can create problems that ripple through planning, execution, and analytics – and into future digital maintenance excellence initiatives.

In this post I hope to inspire your with a simple and flexible approach – one that supports clean reporting, process scalability, and minimal complexity.

Preventive vs Planned

In many maintenance organizations, there’s a subtle but important distinction that often gets blurred: preventive vs. planned maintenance. These are often equated. While preventive work is certainly planned in advance – most often based on time intervals and sometimes based on usage – the reality is that corrective work is often planned too. For example, a fault might be reported today, assessed tomorrow, and scheduled for execution during a future shutdown. It’s corrective, but it’s also planned.

Keeping this distinction clear in SAP PM is more than just good practice – it’s foundational for reliable KPI reporting. Metrics like planned vs. unplanned work ratio, percentage of preventive maintenance, and breakdown frequency depend on a clean and consistent data model.

So how do you achieve that without creating a mess of overlapping order types?

Keep Order Types Simple and Purposeful

Rather than assigning a separate order type to every maintenance scenario, I recommend starting with just two core order types:

• PM01 – Preventive Maintenance
  Used exclusively for work generated from maintenance plans. This includes recurring tasks like inspections, cleanings, and overhauls that are planned by time or usage intervals.
• PM02 – Corrective Maintenance
  Used for all non-preventive tasks, whether they’re unplanned (e.g., breakdowns) or planned after evaluation.

This allows corrective work to evolve – from unplanned to planned – without requiring you to recreate the order. It keeps things simple, consistent, and scalable.

Use Master Data and Status to Capture Detail

Instead of using more order types to express variations, lean on SAP’s built-in classification options:

• User Status – Apply status profiles that reflect the planning lifecycle: unplanned, under review, planned, released, completed. This makes it easy to report on process maturity and backlog stages.
• Maintenance Activity Type – Use this to further classify the nature of the work (e.g., inspection, repair, improvement). It’s fully reportable and doesn’t affect order flow.
• Notification Type – Helps segment the origin of the work — for example, M1 for preventive, M2 for corrective.

What About Breakdowns?

Some organizations use a separate order type for breakdowns, but in my view, this is unnecessary and counterproductive. SAP provides the breakdown indicator in maintenance notifications for exactly this purpose.

If a piece of equipment fails and causes downtime, the breakdown indicator should be checked, and the malfunction start/end dates recorded. This supports key KPIs such as:

• Mean Time to Repair (MTTR)
• Mean Time Between Failures (MTBF)

You get all the insight you need, without introducing more order types.

Reporting Benefits of This Setup

This approach keeps your order management straightforward, keeps you close to standard and enables detailed and meaningful reporting:

• Preventive work: Orders of type PM01
• Corrective work: Orders of type PM02
• Planned vs. unplanned: Differentiated via user status
• Breakdowns: Captured via notification breakdown indicator
• Downtime and reliability data: Extracted from malfunction start/end times in notifications

It’s easy to filter, chart, and analyze — and it avoids the risk of inconsistent use of order types that can muddie your reporting.

Looking Ahead: What About Phased Based Maintenance And Process Types in S/4?

Looking ahead, SAP S/4HANA introduces new capabilities like processing types and phase-based maintenance that aim to simplify order classification and bring more structure to the maintenance lifecycle. These tools can help solve some of the challenges discussed here – especially around order type sprawl and process control – but they also bring their own considerations. For example, distinguishing planned vs. unplanned corrective work, or capturing downtime without a breakdown, still requires thoughtful design. I hope to explore these newer features and their practical implications in the future.

Final Thoughts

There’s no one-size-fits-all approach, but starting with a lean, flexible strategy is a solid foundation. Order types are central to how SAP PM operates — they drive cost control, reporting, and workflow. Getting them right early on sets the stage for an efficient and transparent maintenance process.

By limiting your order types to just what’s necessary, and leveraging statuses, indicators, and classifications for detail, you strike a balance between operational flexibility and analytical power. That’s the kind of model that scales well, supports continuous improvement, and gives stakeholders the data they actually need.