Facilities Data Made Simple: What to Track, What to Ignore, and How to Act on It
Facilities leaders today are drowning in data. Dashboards, reports, and KPIs pile up faster than most teams can interpret them. The problem isn’t a lack of information - it’s knowing which numbers actually matter. Too often, organizations invest in sensors, CMMS platforms, or analytics tools only to end up with pretty charts that never influence a single decision.
The truth is this: more data isn’t better - better use of data is.
In this post, I’ll break down the three categories of data that consistently drive results, highlight what you can safely ignore, and share a framework for turning numbers into action.
Why More Data Isn’t Always Better
When every piece of equipment is feeding metrics into your system, the temptation is to track everything. But “tracking for the sake of tracking” quickly leads to analysis paralysis.
Take HVAC systems as an example. Many teams track monthly run hours but never connect that data to energy usage or preventive maintenance schedules. Without context, run hours are just noise.
Data should exist to serve a purpose: improve reliability, reduce costs, or prevent downtime. If it doesn’t tie to one of those outcomes, it’s clutter.
The 3 Types of Data That Matter Most
1. Asset Health Data
Metrics like vibration, temperature, and run hours are the early-warning system for your most critical assets. These readings help predict failures before they happen.
One example from the field: a $10 temperature sensor on a compressor identified overheating early. Addressing the issue cost a few hundred dollars in labor and parts. Left unchecked, it would have escalated to a full replacement—costing over $50,000 and a day of lost production.
Bottom line: Asset health data prevents catastrophic failures and keeps operations moving.
2. Work Order Data
Work order metrics—such as Mean Time to Repair (MTTR), backlog percentage, and response times—tell you how effectively your team is performing.
If response times are slipping, that’s not just a number; it’s a signal that resources or processes need adjustment. Similarly, a growing backlog may reveal chronic understaffing or an over-reliance on reactive work.
Bottom line: Work order data helps you measure efficiency and identify staffing or process gaps before they hurt performance.
3. Cost Data
Every facilities leader eventually faces the same question: “What is this costing us?”
Tracking repair vs. replace costs, energy consumption, and overtime spend equips you to answer that question in terms leadership understands - DOLLARS. Cost data translates facilities management into business language, making it easier to justify investments or defend budget requests.
Bottom line: Cost data builds credibility with decision-makers by tying facilities performance directly to the bottom line.
What You Can Safely Ignore (for Now)
Not all metrics are created equal. Some look impressive on a report but rarely drive action. A few examples:
Downtime hours without context. A machine may log downtime, but unless it’s tied to lost production or service delays, it doesn’t tell the full story.
Raw PM completion percentages. High completion rates mean little if the quality of work is poor.
Detailed parts usage logs. Unless you’re actively managing supply chain risk, hyper-granular tracking often wastes more time than it saves.
If a metric doesn’t help you make a decision, avoid downtime, or justify costs—it’s not worth your focus.
How to Turn Data Into Decisions
Collecting the right metrics is only half the battle. The real value comes from acting on them. Here’s a simple framework you can apply:
Simplify your dashboard. Focus on three to five core metrics.
Set thresholds for action. For example: if backlog exceeds 10%, add contractor support or authorize overtime.
Review regularly. Monthly with your team, quarterly with leadership.
Always connect back to ROI. Frame the conversation in terms of cost savings, risk reduction, or uptime gains.
At one pharmaceutical manufacturing facility I managed, we shifted from calendar-based filter changes to tracking differential pressures across the 40-ton rooftop units. Instead of replacing filters on a fixed schedule, we replaced them only when the data showed it was necessary—or extended their life when performance remained within spec. With 16 units in operation and costly HEPA filters in each, the change protected the equipment, reduced unnecessary material spend, and saved the facility thousands of dollars annually.
It’s a clear example of how even straightforward data, when applied with intent, can deliver outsized results.
Common Pitfalls to Avoid
Analysis Paralysis: Don’t chase every metric—focus only on those that matter.
Chasing Vanity Metrics: Completion rates and downtime numbers look nice on a slide deck but mean little without context.
Reporting Without Action: Data that doesn’t change decisions is wasted effort.
Final Thoughts
Facilities data doesn’t need to be overwhelming. By focusing on asset health, work orders, and cost data, you’ll get the clearest picture of performance—and the most leverage with leadership.
Start small: pick one asset health metric, one work order metric, and one cost metric to focus on this quarter. Review them consistently, act on what you learn, and build from there.
If you’re ready to simplify your approach and build a facilities strategy that’s truly data-driven, let’s talk. I help organizations design systems that make data work for them, not against them.
