The costly risks of transformer failure — and how to avoid them

25 April 2025

For asset and operations managers alike, few things are more disruptive than transformer failure.

When a unit fails, it’s never just a maintenance issue — it’s a chain reaction of lost productivity, emergency costs, and reputational risk.

But here’s the good news: most of these failures are predictable. And with the right strategy in place, they’re also preventable.

Why transformer failure is so disruptive

The cost of failure isn’t just financial — it’s operational.

When a critical transformer goes offline, entire sections of a power network may be affected. Response teams are pulled off planned work. Replacement parts are sourced at premium prices. Customers or internal stakeholders demand answers. In regulated environments, penalties can follow.

For operations managers, it creates scheduling chaos. For asset managers, it drives up risk profiles and long-term costs. Even short outages force reactive decision-making, where time, money, and resources are stretched thin.

Most failures don’t happen overnight

What’s frustrating is that transformer failure rarely comes out of nowhere. Research shows many breakdowns follow patterns of early warning signals:

elevated gas levels
insulation degradation
thermal stress
partial discharge activity — the signs are there, if you’re tracking the right data.

The problem? Most organizations aren’t.

Routine tests might only happen annually. Results are filed away in spreadsheets or isolated systems. The full picture — across time, across assets — is missing.

Without that visibility, both asset and operations teams end up responding after the damage is done.

From time-based to condition-based: a better approach

The traditional, time-based approach to transformer testing assumes all assets need attention on the same schedule. But transformers don’t age at the same rate. Some remain healthy for decades. Others deteriorate faster due to load, environment, or manufacturing variation.

That’s why many teams are shifting to condition-based maintenance (CBM) — a smarter strategy that prioritizes intervention based on actual risk, not calendar dates.

CBM combines:

Historical test data

Real-time monitoring (where available)

Fleet-wide health scores

Asset criticality and usage profiles

For operations managers, this means fewer surprises. For asset managers, it means more strategic use of resources.

The role of MTIC in risk reduction

Megger’s Transformer Intelligence Centre (MTIC) supports this shift. It’s a cloud-based platform that centralizes transformer test data, calculates condition scores, and helps teams make better decisions faster.

With MTIC, you can:

Track trends across your entire fleet

Identify high-risk units early

Justify replacements with data

Align maintenance with real-world priorities

By reducing the guesswork, you reduce the risk and avoid costly surprises across both daily operations and long-term planning.

Avoiding failure starts with better visibility

If you’re managing transformer assets today, risk isn’t just about ageing equipment — it’s about blind spots in your data.

The more clearly you can see what’s happening inside your transformers, the earlier you can act.

With a condition-based approach — and the right tools to support it — you can plan ahead, stay ahead, and protect the performance of your entire network.