Imagine driving a car with no dashboard. You don’t know your speed, how much fuel you have, or if your engine needs attention. That’s how many organizations operate their facilities, without visibility into the data that matters most.

Facility managers today are expected to deliver better performance and lower costs, often with aging infrastructure and limited tools. The challenge isn’t just collecting more data—it’s identifying which data truly drives decisions.

This is where the idea of data materiality comes in. Borrowed from accounting and ESG, it helps organizations cut through the noise and focus on what’s truly impactful. In facility operations, it’s about identifying the data that’s most important to stakeholders and has the biggest effect on business outcomes.

Understanding the Challenge: Too Much Guesswork, Not Enough Insight

Across industries, facility teams can fall under pressure to deliver more with less: greater uptime, better occupant comfort, lower emissions, and tighter budgets. But without a clear data strategy, many still rely on gut instinct, spreadsheets, and responses to failure.

This reactive approach may seem easier or more cost-effective in the short term. In reality, it leads to:

• Unpredictable capital expenses
• Missed opportunities for efficiency
• Comfort or safety complaints from occupants
• Inability to report performance or mitigate facility-related risk. 

Even worse, organizations often don’t know what data they need or are overwhelmed by what they’ve already collected.

A Strategic Shift: From Reactive to Predictive

The good news? You don’t need a massive digital overhaul to start using data more strategically. The best facility management programs begin with asking a simple question:

“What am I trying to manage, and why does it matter to my business?”

For example:

• A student housing operator might focus on HVAC system performance because tenant comfort affects retention and revenue.
• An industrial property owner may prioritize roof condition and lifecycle planning, since those systems represent significant capital exposure.
• A national discount retailer might monitor refrigerated case temperatures across its portfolio to prevent product loss and comply with health regulations.

Not every organization needs a fully predictive model for every system. But every organization can improve performance by identifying the assets that matter most and capturing the data needed to make informed decisions about them.

Setting Priorities with a Data Materiality Framework

To help facility teams focus their data strategies, we use a simple framework built around the concept of data materiality. It helps connect what clients value most, like comfort, uptime, or cost control, to the specific data and systems they rely on to manage it. By evaluating both how important a data point is to internal stakeholders and how much it impacts business outcomes, organizations can make clearer, more confident decisions about where to focus their efforts:

• Importance to stakeholders: This considers how essential a given data point is to people across the organization—whether that’s facility managers on the ground, regional directors, executive leadership, or even board members. The more stakeholders rely on a data point to do their job, make decisions, or meet reporting needs, the higher its importance rating.
• Impact on the business: This measures how much a data point influences operational outcomes. Does it help keep buildings running? Enable proactive maintenance? Prevent lost revenue or improve tenant experience? The more ways a data point supports efficiency, savings, or value across a site—or across an entire portfolio—the greater its business impact.

Using these two lenses, we help clients prioritize data into three levels:

• Level 1: Foundational
  These are the basics, like facility lists, asset inventories, and static condition assessments. They don’t generate debate over their value; they’re essential starting points for understanding what you own, where it is, and how old it might be. Often stored in spreadsheets, this data forms the foundation for smarter planning but offers limited insight on its own.
• Level 2: Point Solutions
  At this level, things become more sophisticated. Tools like CMMS platforms and energy dashboards begin to capture data on maintenance workflows, projected capital costs, and operating expenses. These systems give teams a clearer picture of performance over time and enable more proactive decisions across a growing portfolio.
• Level 3: Integrated Intelligence
  This is where high-frequency, high-context data enters the picture. Think real-time system analytics, predictive diagnostics, and building-level integration platforms that pull from multiple sources. These data points might refresh every minute and are often customized to serve a specific use case, like monitoring refrigerant loss, verifying HVAC setpoints, or forecasting energy demand. The result is a portfolio-level view that supports smarter forecasting, deeper insights, and continuous optimization.

For example, tracking HVAC work orders might be Level 2 because this is part of any good maintenance program deployed at the portfolio level , while live temperature monitoring in refrigerated assets (to prevent compliance violations and product spoilage) is Level 3 because this is an expanded data point that’s unique to the business. 

This framework helps facility leaders stop chasing “all the data” and instead focus on what matters most, strategically, operationally, and financially.

Data Collection That Drives Decisions

You don’t need a digital “twin” to make smart moves. It’s easy to get caught up in the complexity of data infrastructure, but the fundamentals are simple. 

First, you need to know which data points are worth collecting across the three levels of materiality described above. For HVAC, this might include unit age, refrigerant type, or run-time hours. For roofs, it could mean tracking condition ratings, warranties, or projected replacement years.

Next, you need to understand where that data will come from. Inputs might be gathered through manual assessments, CMMS logs, or building automation systems. Connected devices like smart thermostats increasingly capture this data in real time, often across hundreds or thousands of locations.

Then comes the question of storage and analysis: 

• Is your data centralized in a platform or scattered across different systems? 

• Are you using a data lake, a capital planning tool, or spreadsheets? 

• Most importantly, what decisions does this data support? 

Whether you’re building a predictive maintenance schedule, planning major replacements, or tracking energy performance, the real value comes when data drives timely, confident decisions.

Common Barriers and How to Overcome Them

Even with smart tools in place, many facility teams struggle to translate data into action. Common pitfalls include:

• Data overload: Collecting more than you can interpret or use
• Disconnected systems: Tools that don’t talk to each other
• Lack of clarity: Not knowing which metrics inform decisions
• No storage strategy: Sensor data that’s never captured or analyzed

The solution? A focused strategy that aligns technology with goals and an expert partner who can help map out the path.

Making the Case to Expand

Already collecting data for one asset class? Now may be the time to extend that intelligence further.

Many of our clients start by monitoring high-value systems, like roofing or HVAC, and then realize the value of expanding that strategy across the full facility. If you’re already tracking roofs, it might be time to look at HVAC. If you're already collecting HVAC data, you might next look at lighting or controls—other systems that impact occupant comfort, cost, and maintenance needs. As your dataset grows, capital planning becomes essential to ensure the information you’re gathering translates into long-term strategy and investment priorities.

Data collection is not an all-or-nothing proposition. It’s an ongoing opportunity to deepen understanding, improve performance, and reduce risk.

In Conclusion: From Information to Impact

Smart, connected buildings don’t start with software; they start with strategy. A good plan starts with knowing what data to collect, how to manage it, and how to use it to guide real-world decisions.

At Mantis Innovation, we help clients go from scattered spreadsheets or isolated systems to connected, capital-efficient portfolios. Our proprietary tool, Perform, supports asset inventory, condition assessment, and capital forecasting across portfolios, acting as both a standalone solution and an integrator. Whether you’re building a foundational asset inventory or layering analytics across your entire facility ecosystem, we can meet you where you are and help you get to what’s next.

Ready to find out where your data can take you? Connect with Mantis Innovation today about your goals and how the right data strategy can support them.