Discover how facility teams are moving from preventative to predictive maintenance using AI and integrated data to improve asset performance and efficiency.
What if facility maintenance didn’t just react to problems, but predicted them before they happened?
In today’s episode, host Yonatan Rouache joins his colleagues from Office Space, Andres Avalos and Steph Austin, to explore how facility teams are moving from preventative to predictive maintenance using AI and integrated data. They break down why digitizing data matters, how connected systems can reduce costs and improve efficiency, and what AI-powered tools could mean for the future of maintenance in facility management.
Andres Avalos: [00:00:00] I think folks are mostly looking for ways to connect different pieces of data to answer the most basic questions about their core responsibilities. What was my utilization last week, last month, or last quarter? What will it be? So that way I can start planning and where the future of AI has taken us. To what Steph just mentioned is that these systems are gonna be able to notify you or prompt you instead of you prompting the system. About ideas in the future very soon.
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Today we're asking the question, what if facility maintenance didn't just react [00:01:00] to problems but predicted them before they even happened? Host Yonatan Rouache joins his colleagues from Office Space Andres Avalos and Steph Austin to explore how facility teams are moving from preventative to predictive maintenance using AI and integrated data.
They break down why digitizing data matters, how connected systems can reduce costs and improve efficiency. And what AI powered tools could mean for the future of maintenance and facility management. Now, let's get into it.
Yonatan Rouache : All right. All right. My name is Yonatan Rouache I'm the, uh, chief's Revenue Officer at Office Space, and we wanna spend a little bit of time today talking about how do we make the workplace operate a bit more like your personal life. And let me explain before we get a little too weirded out by that.
Um, we all have in our personal life, tons of reminders, ways to ensure that we're staying on top of things, right? Whether it is your workout plans, whether it's your [00:02:00] bills for me, it's a reminder to go to sleep. And so we're gonna talk a little bit today about how do we kind of bend that into being more effective in the workplace and finding ways to drive, you know, knowing what's coming to help us make better decisions and really interoperate within the workplace more effectively.
And, you know, trying that into the workplace, there's a lot of benefits in kind of seeing what's coming and forecasting forecasting what the space and the needs of the space look like, what our assets look like, and. Um, really driving unavoidable costs out of our cost profile. And, you know, we've heard from clients around the industries that there's tens to hundreds of thousands of dollars in savings in that.
Um, because the cost to replace is often a lot more expensive than the cost to repair. And then when we make decisions on repair or replace, we're often doing that with really incomplete data. And so we'll spend a little bit of time talking about that today. But before we go further in that, I want to introduce.
My co-panelists here talking about this [00:03:00] first to my left here is Andres Avalos. He is the chief, uh, product officer at Office Space. Aside from being our head of innovation within our company, he also spent time, with IBM actually developing and being the product lead for IBM Watson, which is now Watson X, which is, you can imagine they were talking about AI more before.
Probably most people in this room were thinking about ai. So excited to kind of hear your perspective on how that impacts the workplace. And then to Andres's left is Steph Austin who is really leading kind of the emerging products technologies and, ability to drive kind of the value of managing assets and the workplace into the field.
So, thank you all both for joining me. Absolutely. To start off the conversation, I want to talk about just kind of the evolution of preventative maintenance because that's been around for a while and we're now trying to think about, well, how do we get even more preventative and how do we look at like.
What does preventative maintenance look like in the future? So, and maybe start with you on what are some of the trends and the challenges that you're hearing around preventative maintenance, and [00:04:00] what are some of the ways the market is trying to evolve to with that?
Andres Avalos: Yeah, I think we want to start by detailing out what preventative maintenance actually is.
Preventative maintenance has been really good for making sure that you stay ahead of any potential issues that might arise from your most precious and most expensive assets. And preventative maintenance is really tied around the idea of scheduled tasks, right? You want to, every quarter, once a quarter, have someone come in service, a particular asset of importance, and that's good to stay ahead of repairs, but if something happens in between those times, it's a lot harder to then come in repair with urgency to make sure that downtime of the service doesn't impact.
The downstream value propositions of having that asset in the first place, whether that's employee productivity, in-office attendance, et cetera. So where the market's really going moving, [00:05:00] not away from preventative maintenance, but more in addition to is the idea of predictive maintenance, tapping into the data behind the capital asset or the assets, the IT equipment, and actually monitoring the data in real time.
And having that be the trigger to operate and start services for particular assets. So you're using realtime data to influence when a repair or service needs to happen for assets. So you can imagine an HVAC unit. You have it scheduled every 90 days for maintenance but then there's anomalies that start to happen around the energy consumption, predictive analytics and maintenance.
Really monitor the historical behavioral patterns of the data of that particular HVAC unit. And when an anomaly occurs that hasn't happened before, it can then trigger a workflow or a notification to personnel that can then do something [00:06:00] or act upon it before it becomes a bigger issue. And I think that's where the future of asset maintenance is going to go.
Yonatan Rouache : Gotcha. Thank you. And, and we'll get to the predicted port in a second. But Steph, how are we seeing that kind of actually in the field in terms of just kind of step one of preventative maintenance? You know, it sounds like on paper, a fairly simple and straightforward thing to do. What are you hearing from kind of clients and prospects around Right, the ability to manage that and manage that scale?
Steph Austin: When I was first having conversations with folks here, spreadsheets, spreadsheets, spreadsheets a lot, and I thought, man, that is an antiquated way of doing things. And then I found out that that is a more modern way than a way that a lot of people are doing things. 'cause now I get answers, like, sticky notes.
I've got sticky notes of varying colors around my office and the my, my old time favorite. How are you keeping track of these things today?
Yonatan Rouache : Yeah,
Steph Austin: yeah. Just remembering it all in their head. So, uh, that's what's standard in the field. So the first thing that we need to do to modernize the way that they're tracking these assets and, and get smart around predictive is.[00:07:00]
Get it into a digital environment to begin with. Most people are not in a, a fully digital environment for their maintenance. If they are, more than likely they are for their point in time tickets. So like for an emergency, but not for recurring. And so we're seeing a ton of lost time and lost value on those assets just 'cause folks aren't able to stay on top of it when, when everything is up here or in a spreadsheet.
Yonatan Rouache : Gotcha. Uh, and how does that also translate to maybe those who do have a system but are looking at it? Versus the diversity of what's, you know, what the assets that they have to manage, right? There's IT assets, there's physical assets, there's assets that your business relies on. All those have different degrees of data and information that's required.
What's the complication of trying to do that all in one place and being able to manage that, you know, in a single fluid manner?
Steph Austin: Yeah, there's a lot of, again, like single threaded systems for tracking. So think about like safety devices. Your, your fire extinguishers, your a ED devices that you might have.
Sometimes when you purchase them, there has like a single tracker that comes with that. So there's a lot of like. One time it [00:08:00] does one thing. Systems or your IT department has something for laptops and monitors and systems and they say you could just use that, it's fine. You can use it. And you go to try to use it to track an HVAC system and you're like, dude, this is, doesn't have anything that I need.
Um, so getting everything into a single pane of glass involves one, being able to have lots of different. Types of information tracked within the system based on what asset you're looking at. And then also being able to integrate in where needed, uh, the information that is gonna be tracked in a different system that's required for the type of asset that it is, or, um, you know, compliance regulation reasons you know, all sorts of different reasons why it might need to be in a different system and then push in.
Those are kind of the two, two main things that we see.
Yonatan Rouache : Gotcha. And it sounds like part of that value is having all the data in one place. Yeah. But Andres back to you on the predictive component. Predictive maintenance. We've been talking about predictive analytics forever, right? You know, we were both worked at IBM at the time, and as you were ideating on Watson Next, predictive analytics had already been probably in its decade of the market.
So what makes [00:09:00] now time that we're talking about this, why did it take so long? And also why is now the time to start thinking about really predictive maintenance?
Andres Avalos: It really comes down to the digitization of information and getting everything into centralized repositories that can then be used to create intelligent reporting.
And now agents with some of the larger LLMs. One big key component of this whole paradigm is, and it's often overlooked, is the user experience for the entry of assets. To tag along with what you're saying, you know, a lot of challenges that I've heard over the course of the last year talking with CRE professionals and asset managers across the space is that it's very hard to get all of my assets into a centralized location that people then use to update consistently.
So if it is a spreadsheet, a lot of folks don't like spreadsheets, therefore information in it to get them to become stale. If you're using an older. Vendor solution and the user experience hasn't been updated. It's hard [00:10:00] to get those assets in. Now. There are real budget and p and l impact to making sure that people are using these systems to record all of the different assets that could exist inside an organization.
And that's important because the more clean the data is, the more centralized it is. The easier it is to make sure it's of high quality and governed, so that way it can be used for predictive analytics, but more comprehensive reporting as well, and now for agent use. Gotcha.
Yonatan Rouache : Yeah. And uh, it sounds, so we were in a client conversation a couple months ago at Infotech where it was a state agency and they said, if the commissioner asked me today can I get a full list of all my assets across every agency, they told us it would take a full year.
To get that information. And so you're talking about getting the data in, but also what about getting the data out and the ability to be able to make it digestible for, you know, the population that we have at World Workplace?
Andres Avalos: Yeah. And in a way [00:11:00] that's consumable and optional for the downstream user.
Some folks love seeing reports and building custom dashboards, and they know exactly where their favorite report is. That shows how much your carbon footprint is, or your energy usage is. And more commonly, and what I'm hearing more out in the space is they just wanna be able to ask a chatbot like, Hey, what was my energy consumption for this HVAC unit on this floor last week, last month, or last quarter?
What do we think it's going to be next quarter for planning purposes? We have a big event coming up. I need to make sure everything is working to the T, or we're planning a big move, we're shutting down this particular floor or this building. All of those are. Questions that people are more commonly expecting to get quick natural language answers to and save the time of moving away from having big, comprehensive dashboards, individual reports.
People need quick answers and fast.
Yonatan Rouache : Yeah. And so, Steph, you mentioned. The [00:12:00] ability to have all the data accessible and the variety of type of data. What is the value in what Andres is mentioning about, are we talking about assets often in like how many laptops and you know, iPads do you have, but there's also clearly the assets that like drive revenue for your business.
And so when we able to put it into one place, like what have you seen in the market really drives that value and like how does that actually translate into, you know, better outcomes for a business?
Steph Austin: Yeah, I think. A big part of it is gonna be uptime. And that can be the assets that are actually driving your business.
For example, like one of the clients we work with is, WWE. So their stages, their lighting equipment, that's like what they do. That's their business. And then there's also, you know, the assets that keep your business running. 'cause let me tell you. And HVAC being out impacts the CEO just as much as it impacts your interns.
Um, and if you wanna have a positive employee experience, you have to be on top of maintaining what those, uh, assets look like around the, the company. So I think one of the big impacts that we're seeing is keeping that uptime, being able to replace valuable [00:13:00] assets less often. I mean. I, I don't have an exact stat on it, but the number of capital assets that a company has tracking has got to have just skyrocketed.
I mean, it used to be, you know, your HVAC systems and some water heaters, and now everybody has smart fridges within their office. We've got, things that we're bringing in for employee experience that are very expensive. And all of those things are not gonna get a full useful life if you're not keeping up on that preventative maintenance.
And simply like, who has the time to, to sit down and, and roll through the Rolodex in your mind of everything that might need some action taken to it. So today things are falling into disrepair. They're needing emergency repair or replacement, and so we're bleeding money by not just staying up on top of what these things are.
So a lot of times what we find is that clients are able to get, you know, really. In incredible information that allows them to, to save money rather than spending money. And I think that's the future.
Yonatan Rouache : Yeah. Um, I, I couldn't agree more. And you talk about the future, about an hour ago, I was talking to a client who, I'm not sure if this is a, an industry term, but asked, when do we get to self-op optimization?
Mm-hmm. Right? We're talking about [00:14:00] data in a system that's easy to get data in, get data out, and be able to make decisions, but also at what point do we need to, can, can we remove. Our own barrier to be able to making those decisions and have the system optimize itself. Yeah. And so Andre said, kinda maybe some shed some light on, you know, whether it's within managing the assets in a workplace, managing the workplace itself, how do we connect the data that we have access to, into then actually optimizing things to ensure that we're getting ahead of maintenance issues, but also optimizing how and when we address challenges, and also kind of where the next L level of self optimization comes into play.
Host: IFMA's Knowledge Library is the largest digital collection of quality content specific to the built environment, featuring hundreds of articles, case studies, research reports, videos, and templates. It has helped thousands of facility management professionals learn and leverage FM best practices. It's also 100% free to IFMA members.
Visit Knowledge library.ifma.org to learn [00:15:00] more.
Andres Avalos: Alright, great questions. Self optimization starts with the centralization of data and to start that journey, you gotta inventory all of the different factors that you're gonna need in order to make informed decisions about what to do with assets. And have an idea of how you want your systems to notify you when important factors are arising.
So when it comes to asset management, tapping into BIM systems, BMS systems, occupancy. Utilization so we can tie energy consumption to the population of the spaces that are recurring and have that data be structured and centralized in a way where it can talk to each other and therefore create the downstream report or dashboards or agents, however you wanna interact with this data, to then notify you.
But the, there has to be a system that is an integrator of these different tools, solutions, and data sources. [00:16:00] That is absolutely key. 'cause then that's what agents or BI tools reference in order to make comprehensive outputs. Whether reports are, again, uh, natural language responses from your favorite chat bot.
And nowadays it's getting easier now more than ever to implement a chatbot experience on top of these integrated systems. So the effort to work with your IT teams to make sure that there are these. Data lakes or data repositories, or that you're using vendors that pick up a lot of the hard work for you to integrate different sources together is an extremely worthwhile venture.
Yonatan Rouache : Real quick, you mentioned the word agents. Yeah. What, and how do those, could those operate within the intersection of assets, people, and the workplace? And like, what is, what does an agent, what does it do and how, how could it actually like impact Yeah. The lives of facilities management.
Andres Avalos: The great thing about today's agents is they're large language models, so they take the context of being able to have a [00:17:00] conversation with the user, asking a question with the context and the data from your data repository or your data system, and then be able to answer questions where historically data that siloed wouldn't be able to get answered without a massive amount of work by your data or BI teams to create the reporting structures to report on it.
So now. You can ask a chat bot. You know, I expect our utilization to be at nearly 100% because our CEO is coming into a town for, uh, into town for an event. What is the expectation of our HVAC energy, energy for that week or day? And then have it then recommend or autos suggest where thresholds need to be.
Or if hey, you have a service that's coming up the week following, maybe move it up. A week before to ensure no issues arise. So you're the chat bot and these LMS are able to reference different data points in its responses to you. And again, that can only happen with an integrated system of data. [00:18:00]
Yonatan Rouache : Yeah, I think, I think it's great to have that kind of view and vision of where we're going.
Steph, lemme bring it back to you real quick on, you know, what is the, if we're looking at the intersection of people and the place and the assets within it what are you hearing in the market is probably the biggest ask or demand. The mo most unique thing that. People are looking forward to kind of bring all those things together.
Steph Austin: Yeah. I think people are in a place now where, and I, and I think this is near term horizon, they want the technology to tell them, right? We have, we've spent a long time getting pieces of technology together where I can go and find the information that I need to find, right? The Google, Google is before, right.
How can I find something easily? We're getting past that. What I'm hearing from folks now is I want the tech to tell me. What should I think about replacing? What would I save a serious amount of money and energy by replacing based on its efficiency? What should I be thinking about for my, you know, upcoming budget year?
What, what different types of devices, you know, might really offer a lot of efficiency for my workplace, or, uh, [00:19:00] improve the employee experience. Just make it better to, to come into the office and they are wanting the software to push in more, right? I would not remember to go track a, a, a app on my phone that would tell me, Hey, you need to remember to go to this meeting.
I wouldn't remember. I get a notification, I get it pushed in. And that's what we're hearing more from the facilities folks, is tell me, push me. I want some, an operating system for my life that helps me be better at my job.
Yonatan Rouache : And then, uh, Andreas back to you then as well. A lot of the agents, you're talking to me, sound like a run in the crawl, walk, run phase.
How about in the crawl and walk phase? Like what are some of the most highest demanded kind of components? Clients are looking for when in the intersection of people, places, and then the assets that they manage.
Andres Avalos: Yeah. I, I, I think folks are mostly looking for ways to connect different pieces of data to answer the most, most basic questions about their core responsibilities.
What was my utilization last week, last month, or last quarter? What will it be? So that way I can start planning and where the future of AI has [00:20:00] taken us to what Steph just mentioned. Is that these systems are gonna be able to notify you or prompt you instead of you prompting the system about ideas in the future very soon.
So the system is gonna continuously look for anomalies, look for interesting facts that are happening inside your data, and then send you a notification saying, Hey, maybe you should take a look into what's happening with this particular HVAC unit on floor 11 of this building before you had to even think about it.
Right. And so that's where the future is really going with, uh, with the agent world.
Yonatan Rouache : Great. A rapid fire question before we close to each of you, , one, since we're talking about assets quite a bit, what is your favorite asset, that you have? Number two is what's your favorite part about being able to make an impact on kind of this marketplace?
And what most excites you most about where this is going? I'll start with Steph.
Steph Austin: My favorite asset has to be, company technology. 'cause I don't know about y'all, but I have like four company laptops still from different jobs [00:21:00] at my house that I'm calling people constantly being like, who do I send this to?
I want, I don't wanna steal it. So that's my favorite one 'cause it walks out the building a lot, sometimes not even when you're trying. And I think one of the things I love most about, um, getting to work with the clients we get to work with is like, this is a thankless job. Most, most folks are. Yelling at the only times that they're, uh, interacting with the people that are in this room, and they really make everything happen.
So talk about like salt of the earth, humble people doing really hard and important work. It just inspires me to, to get, to make their life a little bit easier. They say things like, I just need two of me. And I'm like, well, I, I might have that for you here soon.
Andres Avalos: Yeah, absolutely. All right. Really quickly, my favorite asset is the fridge.
Because I go in there at least 10 times a day throughout the day for quick snacks and hopefully meals when there's not too many meetings interrupting that. But my favorite thing about what I do is the impact that our users can have on the holistic experience that someone has to spend so much of their [00:22:00] life interacting with A lot of folks, whether you're a hybrid or fully in office, you spend a large part of your life in these spaces.
The worst thing that can happen is you walk in for a day full of work that's ahead of you. You got your lunch, and then you get to the fridge and see that it's out of order. Right? And that's what we want to help prevent for the future.
Yonatan Rouache : Awesome. Thank you both for spending the time together and, for sharing in this.
And kinda to summarize what I heard is number one is the ease of experience of getting data in and out of a system is what's gonna help drive, making all of our lives easier. And then it's once the data's in there, what do we do with that? And how do we help have that help us make better decisions, help make our work life more like our personal life and be able to ensure that, you know, we're always thinking about that future of work.
Thank you all very much. Thank you. Cheers.
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