The Proactive Campus: How Fault Detection & Diagnostics Can Transform Higher Ed Facilities

At 3:00 a.m. on a winter morning, while a university campus slept, an algorithm detected a faulty valve in a dormitory heating system. By dawn, the facilities team had corrected the issue, long before students felt a chill in their rooms. 

This scenario is increasingly common as Higher Education institutions turn to Fault Detection and Diagnostics (FDD) to keep aging campuses comfortable and efficient. For decades, college facility managers have battled surprise equipment failures and energy waste with limited staff and budget. Now, analytics-driven FDD software promises a new, proactive approach. Instead of waiting for the next complaint or catastrophe, universities are using data to catch problems early, saving energy and preventing downtime in the process.

This is the new reality emerging at places like the University of Iowa, where FDD caught 2,100 issues and saves $2.5 million per year in energy. Yet many Higher Ed facility managers and energy engineers haven’t figured out how to make the leap from reactive fixes to proactive fault hunting.

In 2023, we put together The Buyer’s Guide to FDD, which supports building owners in any vertical to improve their understanding of FDD and learn how to get started. 

As a follow-up to that guide, we wanted to get to the bottom of why this technology is a game-changer for some universities while others have failed to adopt it. We spoke with the technology vendors and service providers who implement FDD in Higher Ed facilities, including BuildingLogiX, Bueno, Clockworks Analytics, Altura, and kW Engineering. 

We also talked with multiple facility managers of Higher Ed institutions, like Scott Gesele, VP of Facilities at Embry-Riddle Aeronautical University. In total, this group represents FDD installations at over 34 universities that span 514 million square feet. The interviews contained no sales pitches — just real talk on what FDD is, why it matters, how it’s helping colleges today, and how it can be successfully adopted.

“Higher Ed is actually the most advanced segment [in FDD adoption]… but they’re also more likely to have skeletons in the closet, like ‘I tried this 10 years ago, and it didn’t work’,” said Alex Grace, Chief Commercial Officer at Clockworks Analytics. In other words, universities know FDD’s promise, but past false starts loom large. Throughout this article, we’ll break down the people, processes, ROI justification, and technology aspects that lead to the successful adoption of FDD in Higher Ed.

The goal: equip you with enough insight to take that first (or next) step toward smarter maintenance and operations. It’s time to catch faults before they catch you.

‍

What is FDD and Why It Matters

In The Nexus Marketplace, we define Fault Detection & Diagnostics (FDD) as software applications that automatically and continually mine data from building systems, meters, and sensors to identify anomalies or faults, and often point you to the likely causes. Think of it as a tireless virtual technician, always on duty. 

Why does this matter in a campus setting? Because universities are basically mini-cities. Maintenance teams are stretched thin (often understaffed and facing a retirement wave, in addition to mountains of deferred maintenance). Reactive “fix it when it breaks” mode is burning them out and busting budgets. FDD’s promise is to flip the script to proactive mode.

That pivot to a proactive approach to maintenance comes with real, quantifiable outcomes:

• Energy Savings: FDD targets things like stuck dampers, simultaneous heating and cooling, or schedules left in override. Catching these yields significant energy cuts. Many schools see payback in ~1 year purely from energy saved.
• Prevented Breakdowns: By flagging abnormal patterns (a chiller short-cycling, a fan drawing high amps), FDD lets you fix things before they fail catastrophically. This can be particularly important in lab environments where failed HVAC can ruin high-cost experiments. Dan Fink, VP of Engineering at BuildingLogiX, noted a situation in which “The FDD helped the university find blown duct leakage in an air handler that was connected to a high-visibility lab just two weeks prior.”
• Operational Efficiency: Crucially for strapped teams, FDD can be like an extra set of eyes that allows you to be proactive instead of reactive. Joe Fleshman, the Director of Energy Engineering at UC Irvine, has installed FDD with the support of Altura on 23 campus buildings. “We are now able to better identify issues with the buildings before users do. So for hot and cold calls, we’re able to diagnose them quicker, or even identify them before the users have the opportunity to call and complain,” stated Fleshman. 

UC Irvine’s installation has saved approximately $750,000 in reduced energy costs per year thanks to the FDD implementation and advanced control sequences campus-wide. (More on that FDD installation in our UC Irvine Case Study)

FDD matters because it targets exactly the pain points plaguing Higher Ed facilities: aging infrastructure, energy waste, reactive culture, and too many systems to watch manually. It’s not a magic wand, but it’s a proven lever to get more done with less.

‍

Obstacles to Adoption

Despite significant adoption and proven value, FDD is far from ubiquitous in Higher Ed. The experts we interviewed indicated that there are still implementations that stall or fizzle. Why? Our interviewees pointed to several common hurdles:

1. “We Tried That Already” Syndrome: Many facility managers have been burned by an early FDD attempt or witnessed a peer campus fail. Maybe a decade ago, they piloted a system that over-promised and under-delivered. These memories create understandable skepticism, but better processes and advances in technology warrant a second shot at FDD. Also, hearing success stories from similar universities helps counter the cynicism.

2. Organizational Siloes & Workflow Gaps: Perhaps the biggest non-technical barrier: Who will actually use the FDD outputs and how will fixes get done? When the FDD champion is someone who can’t directly create work orders, it becomes very difficult for outputs of the FDD tool to turn into real work being completed. Grace from Clockworks noted, “For an energy manager to create a work order, they have to go through, like, eight steps.”

Many universities have entrenched siloes—energy staff, controls shop, mechanical shop, district maintenance teams, etc. FDD will die on the vine if it’s not wired into the work execution process. A common scenario: FDD finds lots of issues but technicians ignore them because they weren’t involved or it’s “not how we do things.” We’ll address solutions, like empowering a core team and integrating with CMMS, in The People section below.

3. Change Resistance on the Front Lines: There can be cultural pushback from technicians or mid-level supervisors. One Higher Ed facility manager pointed out their own experience with a colleague who, “Relished in pointing out the errors of the system… more than the errors of the building.” Change is hard—FDD alters routines, surfaces uncomfortable truths (like “we’ve ignored this broken sensor for 2 years”), and requires learning new software. Overcoming this means involving the maintenance team early, demonstrating quick wins, and maybe even adjusting job roles. If field staff aren’t bought in, FDD becomes shelfware.

4. Alert Overload (Noise vs. Signal): One of the quickest ways to sour people on FDD is flooding them with false alarms or trivial findings. If everything is an alarm, nothing is a priority. Poorly executed FDD deployments often turn on hundreds of rules out of the box, leading to a deluge of notifications. Scott Gesele, VP for Facilities at Embry-Riddle Aeronautical University, recounted a horror story he was told about a company that auto-generated so many FDD work orders that their ticket count jumped 223%—many were false positives. Not only did this massively distract the facilities team, it caused the service level targets they were graded on to be trashed without their control. They quickly pulled the plug. 

5. Legacy Systems and IT Hurdles: Some campuses have older BAS that are not easy to tap into. If critical buildings aren’t digitized (no sensors or network controls), FDD can’t see them. Universities also face IT security reviews and network hoops to connect FDD tools. It’s solvable (especially with cloud tech and read-only data pulls), but a poorly planned IT integration can stall a project before it starts.

These obstacles might sound daunting, but the universities that succeeded treated them as speed bumps, not brick walls.

‍

The People (Champions, Buy-In, Change Management)

Any successful building technology implementation starts with people, not tech. FDD is no different. You need the right champions, team structure, and change management tactics to sustain it.

Empower the Champion’s Role: Like all successful smart building technology implementations, adopting FDD always starts with a champion inside the organization who has the vision for using new tech to improve the way things are done. For FDD in Higher Ed, the champion frequently sits in the facility management or energy management department. 

Wherever they are, they need juice in the org chart. A champion who is unable to influence or manage the work order process and prioritization will fail at implementation. The faults uncovered by FDD will be drowned out by the endless barrage of reactive “how-we’ve-always-done-it” tasks. Some schools embed FDD in the controls group (since a lot of fixes start there), others in mechanical maintenance. Either can work, but shorten the distance between FDD findings and wrench-turners. 

“The ones who are successful are the ones who say, hey, you know what? I'm not just going to champion this as an idea. We're championing this as a new part of our culture, our process, and our operations. Going forward, this is going to be baked into our standards. This is how we're going to reduce the amount of headaches when we turn over new construction buildings. This is how we're going to keep the amount of complaints and cold calls and tickets lower long term, and it starts now.”

 —Dan Fink, BuildingLogiX

Identify the Core Team: Lincoln Harmer, Principal at kW Engineering, refers to the FDD program’s core team as the “Navy SEALs of the FDD implementation”. Harmer emphasizes the need for a core group of technicians who are technical, curious, and deeply trusted in the organization. This core team must have the authority to act and the technical skills to fix the faults that arise. Sometimes, this means plucking top technicians out of their regular roles and dedicating them to the analytics program. The University of Iowa “stole top technicians from their shops” for the greater good.

While a core team of technicians is going to be the one to initially learn and adopt the tool, a successful implementation really shouldn’t change what the day-to-day for the average technician feels like. Leon Wufel, co-founder of Bueno Analytics, explained, “Your life doesn't change that much as a technician. If you look at the technician's daily life, they have a whole bunch of PM tasks given to them, and they have some emergency service calls. So they have preventative tickets and reactive tickets that they respond to. Now, in a mature implementation of FDD, the FDD platform is integrated with the CMMS, so that the technicians' day doesn't change. It just means that they get a different category of ticket to work on. Now they've got preventative, reactive, and proactive tickets that they're looking at.” 

Train and Communicate Relentlessly: Don’t assume that once FDD software is installed, folks will magically use it. Several interviewees noted that without ongoing hand-holding, even a good FDD implementation can “fade away.” Good FDD vendors will pair initial setup with monthly or quarterly consultations to keep momentum. Show technicians how FDD makes their life easier and celebrate the quick wins.

Allay Fear of Job Impact: Some technicians might quietly worry FDD is going to replace their job. It’s important to frame FDD as augmenting their skills, not automating them away. Gesele framed the perspective of facility mangers, “Some people will say, ‘FDD going to save you labor,’ but the truth is, I’m never going to give up that body. I’m just going to redeploy those labor hours elsewhere.” That message can reassure staff that FDD isn’t a downsizing tool; it’s a force multiplier. And given the skilled labor shortage, anything that eases the load is a friend, not a foe.

The coolest FDD tech will fail without the human groundwork. Invest in your people as much as the software. Get the org structure, champions, and culture in place so that when the pilot starts (next section), your team is hungry to prove it works.

The Pilot (Tips, Pitfalls, Scale, Vendor Selection)

When dipping your toes into FDD, a pilot project is the usual first step. But pilots can easily go wrong—too big, too small, wrong focus, unclear success criteria. Our experts offered practical tips to make a pilot a springboard (not a dead end):

Structuring a Winning Pilot

A good pilot has reliable meter data for baseline and savings calculations. This is often considered a prerequisite. If you don’t have good meter data, you’ll fail to show a real energy ROI.

A good pilot has a strategic selection of systems or buildings. Diverse system types help show versatility in what issues the FDD can catch. Building owners should focus on systems with known problems so you can verify FDD catches them, proving its worth.

BuildingLogiX recommends that customers take an a la carte approach, selecting systems to pilot instead of whole buildings. Fink described, “Let’s get some meters. Lets get some air handlers. Let’s get a couple chillers. Then, you can put together a pricing model that is more cost-effective and a manageable amount for a small team. They start to get the big savings, they get familiar with the tools, they get wins, leadership is happy.”

A good pilot tests multiple options. Many schools with a successful implementation of FDD, like The University of Rochester, piloted multiple FDD vendors side-by-side. When possible, most technology vendors recommend the multiple-vendor pilot approach:

“I think that you should pilot a couple of different solutions right at the start. This helps avoid that kind of runaway train of the emotional favorite becoming more of the emotional favorite over time. Also, it's pretty hard to know what FDD is as a product category. Being able to understand what features to ask for and how they will translate into a benefit for your specific needs as a client is important.” 

—Leon Wurfel, Bueno Analytics

A good pilot defines success upfront. Are you primarily after energy savings? Better maintenance responsiveness? Fewer complaints? Write down 3-5 specific KPIs or outcomes you expect. 

‍

A good pilot plans for scale. A common pitfall is treating the pilot as an isolated science experiment without thinking about how it would scale if it’s successful. Some customers try a tiny pilot and say, “cool, it worked,” but then stall on rolling it out campus-wide due to funding or internal hurdles. It’s wise to have a tentative roadmap (and stakeholder buy-in) that if the pilot hits targets, you have a path to phase 2. Often, this means including a line item in next year’s budget request for scaling FDD to more buildings and systems. Some universities do a multi-year plan: 5 buildings year 1, then 20, then full campus over 3-5 years. Avoid an indefinite pilot purgatory.

A good pilot doesn’t go too big or too small. Resist the urge to “boil the ocean” on day one. “I definitely look at bringing in just a handful of buildings and being selective,” said Harmer of kW Engineering. The typical pilot includes three to five buildings. If you go too big (trying 15+ buildings initially), you may overwhelm your team and the vendor, leading to poor implementation and rule tuning. Too small, and the results might be statistically or financially insignificant to convince anyone. 

This can become difficult when budgets are fixed. Gesele noted the difficulty of receiving a larger one-time grant that allowed his team to pilot FDD in a previous role. They wanted to maximize the grant, so they made the pilot fit the amount of money they had. In hindsight, the pilot covered too many buildings, which hindered adoption.

A good pilot documents & broadcasts the wins. Throughout the pilot, keep a running log of “great catches.” Did FDD find a stuck valve that was heating and cooling simultaneously? Document the energy waste avoided. Did it catch a failing sensor that would’ve caused complaints? Note the avoided downtime. Compile these into a simple report for leadership: “In 6 months, our small FDD pilot identified 42 issues, of which 30 have been fixed, saving an estimated $X and improving comfort in these ways.” Even if some findings weren’t cost-savers, if they solved chronic headaches, that’s value. This storytelling of pilot results is crucial to get the green light for expansion.

A good pilot has a planned handoff to operations. By pilot’s end, have a process in place for how FDD will be rolled into normal operations. This includes:

• Who gets alerted for what types of faults?
• How often the core team reviews dashboards (daily? weekly huddle?).
• How they decide what becomes a work order versus what needs more investigation.
• Training materials or SOPs for new team members to use the FDD system.

Basically, avoid the scenario Lincoln Harmer warns about: “Finding issues and reporting on them is great… but the real key is, alright, who’s going to do the work now? How do you integrate that into current workflows?”. Plan that integration so the pilot doesn’t end and it’s back to the regularly scheduled reactive maintenance.

When done right, a pilot gives you proof and a refined game plan. You’ll know which vendor fits, how your team responded, and what ROI is achievable. That sets you up to tackle the next big question: how to pay for this and justify it to the purse-string holders.

The Pricing and ROI Justification

Talking money is unavoidable. How do you fund an FDD system and prove its worth? Here’s the candid lowdown from our interviews and case studies:

There’s nothing special about it… most FDD software costs are simply carved out of existing O&M budgets. The advantage: no big capital request, you fly under the radar. But it can be tough if budgets are tight or if it’s a significant subscription.

Yet, there are some creative alternatives to funding. In many universities, energy/utilities budgets are separate from facilities. You may be able to charge FDD to an energy management budget on the basis of expected energy savings. Some schools also have internal green revolving funds that invest in energy-saving projects; FDD can qualify for those.

Depending on your region, there may be utility incentives for analytics (e.g., New York utilities have been known to support FDD projects). In a previous role, Gesele received a COVID-related fund that jump-started their FDD purchase. Keep an eye out for state or federal grants focusing on energy efficiency or smart campuses.

In terms of building the ROI case, energy savings is the easiest piece and the primary piece. Ideally, these figures will be directly correlated to meter readings on the systems you piloted. Most vendors have case studies like “X% HVAC energy reduction” – use those but validate with your own context.

However, there’s serious ambiguity of ROI when it comes to everything but meter data. Maintenance savings, deferred capital avoidance, catastrophic failure avoidance, and sustainability can all be brought into the discussion of cost benefits, but these metrics will always be difficult to assign hard numbers to without assumptions.

‍

The Technology (BMS Integration, Alert Fatigue, User Access)

(become a pro member to keep reading!)‍

We’ve covered people, process, and pricing; now, let’s talk about the actual tech. What do facility managers need to know about the nuts and bolts of FDD systems and how they fit into your existing tech stack?

Can’t my BAS do this? 

This is a common question: “I already have a building automation system with alarms. Why do I need FDD?” 

A traditional BAS alarm might tell you when a temperature exceeds a setpoint or a pump is failed. That’s fault detection (FD) in a narrow sense. But FDD goes further, using algorithms and data trends to detect subtle faults (like an economizer that’s gradually leaking) and diagnose likely causes. BAS alarms are also siloed per device; FDD correlates across systems. Additionally, FDD can actually allow teams to reduce alarm counts in the BAS, improving alarm management for the operators and putting the less critical energy and maintenance related items in the FDD workflow - this can be a huge selling point to break down push back from operators.

Big controls vendors now offer add-on analytics modules that can be quite helpful, but there can be mixed incentives. As Grace notes, many campuses are wary of letting the fox guard the henhouse: “If I’m paying my BMS provider millions and add their FDD… now I pay them to tell me where they screwed up, and then pay them again to fix it?”. Plus, if you have multiple BAS brands, a vendor-specific FDD only covers one. An independent FDD gives you an unbiased, campus-wide lens.

So while your BAS is great at real-time control and basic alarms, FDD is the layer on top that finds the unknown unknowns and optimizes performance in ways a BAS alone never would. Think of BAS as the body’s reflexes, FDD as the diagnostic doctor.

Getting Interoperability out of your FDD

An FDD platform will always integrate with building automation systems, IoT devices, and meters as sources to pull and analyze data from. That has become table stakes. 

The next common level of integration comes to the CMMS / work order system. But that’s the integration that facility managers need to tread lightly with. As discussed earlier, once you start pushing work orders from your FDD tool, you risk overwhelming your technicians with false positives and losing trust in the system.

Gesele brought up the importance of using the pilot to eliminate bad rules, “50-60% of the time it was no, the rule’s bad – nothing’s actually wrong” in early tuning. Turn off or adjust rules that aren’t proving useful. Many platforms let you adjust sensitivity or add custom logic. Calibration is part of the implementation – budget time for it. And keep it iterative; as seasons change, you might need to tweak thresholds.

IT Security and Cloud vs On-Prem 

The industry trend is cloud-hosted FDD (Software-as-a-Service). That means campus IT will need to approve outbound data streams from your BAS to the cloud. Early engagement with IT is wise—explain the data being shared (typically non-sensitive HVAC data), security measures, etc. Some universities with strict policies might opt for on-premise installation, but that can add complexity (servers to maintain, etc.). Most have found the cloud to be fine and more scalable. Just don’t let the project be derailed by a surprise IT veto; get them on board early.

Analytics vs. AI Hype 

You’ll hear buzzwords like AI, machine learning, etc. The truth: many FDD algorithms are rule-based (if X and Y, then fault Z). Some advanced ones do have machine learning for anomaly detection. The key for you is not the buzz, but results. Ask vendors for concrete examples: “How does your system detect a stuck valve? Show me. How does it differentiate a sensor error from a real problem?” Don’t be wowed by 3D graphs and talk of AI if they can’t show practical faults that matter to you. A pragmatic system that your team understands is worth more than a black-box AI that nobody trusts.

Scalability and Maintenance

Over time, as you add buildings or retrofit systems, keep the FDD models updated. Who will add new data points or commission new fault rules? You might need a service contract or internal resource for that. FDD isn’t “set and forget” forever—treat it as a living program. However, after the initial heavy lifting, adding buildings is usually easier (especially if you use standardized data point naming and implement standard tagging ontologies such as Project Haystack or Brick, etc.). Some universities train an in-house guru to manage the FDD platform day-to-day.

To sum up the tech: integrate FDD thoughtfully with what you have, tame the alerts, make sure real users can use it, and invest in system maintenance. The technology should ultimately fade into the background as just another tool in your facilities toolbox—like your BAS or your work order system—just one that brings an unprecedented level of insight.

‍

Conclusion: Why Now and What’s Next

Campus facilities face unprecedented pressure. Deferred maintenance backlogs are staggering. Energy costs aren’t going down. Sustainability commitments are coming due. And there’s a staffing crunch as veteran trades retire and new hires are hard to find. In short, doing nothing isn’t viable—something’s gotta give. FDD offers a way to alleviate these pains by getting smarter with existing resources. It’s timely because the technology has matured (learning from those early missteps) and peer success stories are accumulating to prove it out. FDD is no longer bleeding edge; it’s increasingly part of the standard toolkit for a modern campus.

Why now? Because the cost of waiting (in money, carbon, risk, and stress) is too high. Because your peers are figuring it out, and you can’t afford to be left behind. And because frankly, running a campus is hard enough, any tool that gives you an edge is worth a look.

So take that step. Start a conversation internally. Reach out to someone who’s done it. Maybe spin up a pilot. The path to a proactive campus is a journey, but as those who’ve walked it will tell you, the destination is worth it: fewer headaches for your facilities team. The future of campus facilities is proactive.