The real cost of unplanned downtime, and the data problem behind it

Most organizations react to downtime as it happens: send a technician, fix the fault, move to the next one. That resolves the incident, not the cause. Fixing the root cause is wishful thinking when asset data is fragmented or unreliable. Better data doesn't solve downtime on its own, but it does make visible where risks are building up before they turn into a failure. And a solid data foundation is the prerequisite on which compliance, operational excellence, governance, interoperability, and efficient daily operations get built.

Anyone who wants to improve structurally has to stop managing symptoms and start at the essential prerequisite needed to fix the cause: a proper data foundation.

The numbers from the Siemens Senseye True Cost of Downtime report (Opens in new tab) (2024) are stark. Unplanned downtime costs the world's 500 largest companies $1.4 trillion a year, equivalent to 11% of their revenue. An average large plant loses 27 hours a month to unplanned downtime. In heavy industry, the cost per hour of downtime is now four times higher than in 2019.

The way most organizations structure their asset information is itself part of the problem. Data is scattered across systems, departments, and formats: a spreadsheet here, an outdated EAM system there, knowledge that lives only in the heads of experienced technicians. Without addressing this, a vicious cycle of firefighting takes hold. Every failure gets resolved incident by incident, without the underlying pattern ever becoming visible.

Poor asset performance and fragmented data are two sides of the same coin. Fragmented asset information is the root cause of underperformance. It shows up as unplanned downtime and production loss, but the cause usually lies much earlier in the process: information is incomplete or impossible to find at the moment critical decisions need to be made.

No grip on information, and therefore on unexpected downtime, forces organizations into reactive mode. You solve whatever comes up instead of planning ahead. That's not just an operational problem, it's a business problem: it affects lead times, costs, and the ability to make well-founded investment decisions.

Asset-intensive organizations are under growing pressure on multiple fronts at once: performance, compliance, interoperability, governance, and daily operations all have to be right. Good Asset Information Management across the full asset lifecycle is therefore no longer a nice-to-have, it's a prerequisite for operational excellence.

A reliable data foundation delivers a lot: operational excellence, regulatory compliance, governance and risk management, interoperability, efficient daily operations, and the basis for AI and advanced analytics.

Unreliable asset data doesn't just slow your team down: it costs money, increases risk, and limits your ability to make well-founded operational decisions. If you want to improve your operational excellence, start with a reliable data foundation and governance. That way you gain full control over your asset information: accurate, accessible, reliable, and structured to support every phase of the asset lifecycle.