Your Total Maintenance Spend Last Year: One Number. What That Number Doesn’t Tell You — and What a Real Dashboard Does

Here’s a question that sounds simple: was your maintenance spend last year well spent?

Not how much — you have that number. It’s in the P&L, it was reviewed, someone may even have been congratulated or scolded over it. The question is different: was it well spent? Which sites consumed more than their square footage and asset age justify? Which assets are absorbing repair money that should be capital-replacement money? Which trades came in over market, and which vendor’s invoices drifted upward without anyone noticing?

Why does this question matter more than it seems? Because every other financial decision in the operation sits downstream of it. Next year’s budget, the capital plan, the repair-versus-replace calls, the vendor renegotiations — all of them assume somebody knows whether current spend is healthy. If nobody does, those decisions aren’t being made. They’re being repeated.

What most operations would answer

Honestly? Something like: “We came in about 6% over budget, mostly because of the chiller situation at the Hampton site and some plumbing surprises. Overall, normal year.”

There’s no deception in that answer. There’s also almost no information. “The chiller situation” is doing the work of an entire analysis. Was the chiller a one-off, or the fourth event in a pattern that a repair history would have flagged two years ago? Were the “plumbing surprises” surprises, or the predictable output of deferred PM? Is 6% over budget good or bad, given what the assets are and how old they are? Nobody is dodging these questions. The data to answer them was never captured in a form that can be queried — it exists as invoices in accounting, categorized for tax treatment, divorced from assets, sites, and causes.

What a well-run operation can answer

A different class of answers exists, and the operations that have them aren’t smarter — they capture data at a different point in the process:

• Spend per site: Normalized by square footage and asset count, so outliers surface as outliers.
• Spend per asset: Over the asset’s life, so the chiller’s fourth repair triggers a replacement analysis instead of a fifth repair.
• Reactive-versus-preventive ratio: The single most diagnostic number in commercial building maintenance, since a site drifting toward reactive is a site whose costs are about to accelerate.
• Spend per trade: Tracked against contracted rates, which is where invoice drift becomes visible.
• Cost per work order: Including the coordination time most operations never track at all.

None of these are exotic metrics. They are all simple arithmetic — if every work order carries its cost, asset, site, trade, and type at creation. That’s the entire difference.

The gap between the two — and why it persists

The gap isn’t analytical talent. It’s that in most operations, maintenance data is born in the wrong place: an invoice arriving weeks after the work, entered by someone who wasn’t there, into a system built for paying bills. Everything you’d want to know was knowable at the moment the work order was created and closed — and was never written down in queryable form.

This is the precise gap that work-order-level financial tracking closes: the dashboard isn’t a reporting layer bolted onto accounting data; it’s a consequence of capturing operational data operationally. Each work order in Sweven FM carries its full financial identity from creation, which is why the questions above take seconds instead of a quarter — but the principle holds with or without us: the answer has to be captured where the work happens, or it doesn’t exist.

Sources:

• McKinsey & Company — maintenance cost structure research, 2024: https://www.mckinsey.com
• IFMA — FM Pulse Survey, Q4 2025: https://www.ifma.org
• BOMA — Experience Exchange Report (operating cost benchmarks): https://www.boma.org