Facility management is becoming increasingly data-driven, but the “FM analyst” isn’t a role, it’s a mindset. In this episode, we explore how curiosity, storytelling and data confidence are reshaping the future of FM.
What does it mean to “think like an FM analyst”?
In this episode of Connected FM, Dr. Matt Tucker, Director of Knowledge and Insights at IFMA, sits down with Drew DePriest, Director of Workplace Services, Vendor Management at Salesforce, to unpack the evolving role of data, analytics and AI in facility management.
Drawing on insights from IFMA’s The Rise of the FM Analyst report, they explore why the FM analyst isn’t a job title, but a mindset grounded in curiosity, problem solving and cross-functional thinking. From fragmented data systems to the growing importance of storytelling in the C-suite, the conversation highlights what it takes to turn data into decisions that drive real business value.
They also dive into:
This episode is sponsored by TMA Systems! Discover more at https://www.tmasystems.com/ifmapodcast
Timestamps:
Matt Tucker: [00:00:00] One of the big kind of headlines from the report was that the FM analyst is not necessarily a job title. The idea of the FM analyst is, it is a mindset, it's a, it's kind of a concept of how perhaps contemporary FM might be thinking in terms of data and analytics. It produced a lot of human, human-centric challenges that we may be facing within the industry, and the report kind of culminates in.
Addressing six key traits that shaped this FM analyst mindset.
Host: Welcome to Connected fm, a podcast connecting you to the latest insights, tools, and resources to help you succeed in facility management. This podcast is brought to you by IFMA, the leading professional association for facility managers. If you are ready to grow your network and advance in your career, go to IFMA.org to get started.[00:01:00]
What does it mean to think like an FM analyst? In today's episode, Matt Tucker, the director of Knowledge and Insights at IFMA, sits down with Drew DePriest, the Director of Workplace Services and Vendor Management at Salesforce, to unpack the evolving role of data analytics. And AI in facility management.
Drawing on insights from if a's the rise of the FM analyst report, they explore why the FM analyst isn't just a job title, but a mindset. They also dive into the six key traits shaping modern FM professionals, how FM fits into the broader enterprise data ecosystem, the role of AI as a copilot for analysis.
And decision making and what the next five to 10 years of FM could look like in a digital first world. Now let's get into it.
Matt Tucker: Hello everyone. Uh, my name's Matt Tucker. I'm the director of Knowledge and [00:02:00] Insights for IFMA, and I am delighted to be joined by Drew dpr. Drew, I know you very well, but perhaps some of our listeners don't. Would you like to introduce yourself?
Drew DePriest: Absolutely, Matt. Good to see you. Thanks for having me. My name is Drew DePriest.
I work as a director of Workplace Services Vendor Management at Salesforce. So my role is global in nature. A lot of my job revolves around really aligning facilities management services worldwide.
Matt Tucker: Fantastic. And just general. All round tech FM guru, I would say. And I love that mug. Wow. I love data, which is perfect.
Did you, did you produce that just for this podcast?
Drew DePriest: It was, it was planned, right? Yeah. So there was a lot of thought that went into how you and I do these things and the
Matt Tucker: modest,
Drew DePriest: the little accent.
Matt Tucker: I love it. I love it. Well, we're here to, to to, to unpack how to think like an FM analyst. We're gonna look at things like skills, mindsets, the [00:03:00] future of fm, and the backdrop of this is a report that IFMA produced last year called the Rise of the FM Analyst.
That report was based on. 37 in depth interviews with specialists from all around the globe, some within the FM industry, some within the tech industry, some specific around AI or sustainability. But what the general premise was, was to try and. Understand what the kind of role and responsibilities and key kind of skills and traits that we would expect a facility manager to have in this data-driven world that we now live in and work in.
And one of the big kind of headlines from the report was that. The FM analyst is not necessarily a job title. What I wanna make clear from the offset is this is not about everybody scurrying away and trying to find a new person that they call an FM analyst. [00:04:00] The idea of the FM analyst is it is a mindset.
It's kind of a concept of how perhaps contemporary FM might be thinking. In terms of data and analytics. So what kind of struck me from this report as I was going through the research was I was expecting it to perhaps come out quite techie, you know, a lot of technological content within it, but it was quite the contrary.
It produced a lot of human-centric challenges that we may be facing within the industry, and the report kind of culminates in. Addressing six key traits that perhaps shape this, this FM analyst mindset, curiosity, being curious, just constantly being curious about why things look the way they do in terms of beta storytelling, being able to.
Speak the language of our internal and our external [00:05:00] stakeholders. If I'm talking to A CFO, I need to talk in their terms. Ultimately around money pattern recognition and problem solving kind of come together and, and curiosity into this. Just trying to spot things and ask why. Why we seeing this? Does that link to another set of data that we've seen, which we might come onto as well about that challenge of fragmented data sets.
Um, and then the last two are around data confidence. Just having the confidence to start interpreting data, seeing what it says and asking people questions that you may feel are silly, but actually they're not. 'cause other people are probably thinking on two. And then the last trait is about cross-functional thinking.
So trying to use other stakeholders who can benefit the story that is being told from your data. So you and I, for example, have spoken a lot in the past about the, the interaction between IT and FM and the [00:06:00] increasing importance of that, especially around operational technology. So that's what the report kind of unpacked.
But the reason why I was so keen to speak to you today. Was to get your thoughts on some of the, the, these insights from the report, but also we can broaden that out a bit and, and you, you definitely have your finger on a pulse about what's happening at the moment in the FM industry. And we can unpack whether some of these things are happening or whether that's something that's still, still to come.
So I suppose the first one is based on those six traits I just outlined. How active are they now in your view? Or is there still work to be done on some of those areas?
Drew DePriest: Yeah, I, I think it's a little bit of both. As I, I look at these bullets and I, I think about how they bore out in the report. I mean, some of the best just folks within workplace or FM in general to me, have always led with curiosity, with problem solving, thinking, with cross-functional thinking.
To me, those, those [00:07:00] three in particular. Really stand out as a hallmark of someone who's successful in this industry has figured out how to do those things very well. Generally on their own. They learn from others, but they recognize that they need to really lean into to those things. In particular, the ones that I've started to see more of and have had the fortune of working alongside and supporting others in the space have really evolved into more of a storyteller type role.
They recognize, to your point around if you're. Speaking with an SVP, with a CFO, someone that, that deals with, you know, let's, let's, let's think budgets, let's think capital planning. You, you have to be able to speak in that language. I think that's, that's spot on that analogy is, is excellent. I think the ones where I'm starting to see more, probably the last two years emphasis and focus on leveling up is really around data confidence.
There's, there's long been a. Less of a [00:08:00] focus on the data governance side of things in general. I know that's something you and I have talked about, spoken with many others in this world around that concept in general. But I think being able to, kind of tying that in with storytelling, acknowledging and recognizing that if we don't have confidence in the data points that we're analyzing and using to tell stories, then we, we kinda need to take a, a step back and go solve for that first.
I think in large part the majority of, of what you've identified is happening and, and happening. Well, there are areas that we can, we can help bring folks along to get to the full mindset.
Matt Tucker: Made about data confidence leads me nicely to, to try to leverage some of your vast technological e experience and, and general FM experience.
But if we take that kind of enterprise concepts, we look at data platforms integration. Where does FM sit in that wider kind of enterprise data [00:09:00] ecosystem? Is it standalone and isolated? Is it sufficiently getting integrated into that organization's data ecosystem?
Drew DePriest: I think the, the evolution, the folks and teams who are doing this well are much more of the latter.
The, the analogy that I was given probably a decade ago that I continue to repeat on regular basis is you, you think of it as a. It's a party, it's a potluck dinner of sorts. And the food, the menu is entirely data. So we, in the FM community, within our own areas of control, we act as, as stewards of specific systems of record.
Typically that's gonna be anything related to an asset and then any sort of performance activities that, that fall around that. There are others within the business that need to understand what that data looks and feels like. Just as we also need to understand things around, if it's portfolio, if it's lease administration, [00:10:00] if it's construction, project management, everything else that goes into the cycle of, of how we all iterate and evolve the bigger asset within the portfolio.
Every one of those groups and teams has their own sort of plate, if you will, of, of data. And no one wants to bring a a half-baked, you know, two week old sandwich to the party. It's, it's gotta be fresh, it's gotta be high quality, something that people will keep coming back for. And I, maybe it's just, I've been fortunate to work amongst teams that, that have gotten that and have put time and energy toward it.
I'm seeing a lot more of, of that model where we recognize that. In order for this, you know, the full picture and value of analysis within real estate and facilities. It's more than one data source and one team or set of people needs to own each thing. And then when we combine them, that's where the real, the real value happens.
Matt Tucker: When I introduced this, this. [00:11:00] Particular point during some of the presentations that I'll do at our, our global events, I do a quick poll in the audience and say, you know, how many people are operating under one system? And you'll, you know, there's normally really one sort of very confident person who puts their hand up says, yeah, me, then I'll move to, you know, how many people are using two systems?
Few more hands, three systems, but the vast majority are using kind of four plus systems to kind of manage all of their FM data. Is that commonplace? Is that, is that efficient, is that acceptable, or is there more work to be done there to try and make sure that we have this kind of interoperable set of, of knowledge available to us?
Drew DePriest: I think it's gonna, there's a spectrum to me, and it's gonna vary by the outcomes that. A company in particular it's, is trying to solve. I've worked in both cases, I've, I've, I've existed in a world where we had a [00:12:00] single IWMS more type system where we tracked everything from space to work orders, in some cases to show up rates, those kinds of things.
I've worked in others. Where did the philosophy of the team in place was, we're fine with point solutions. We want what works best for a particular set of outcomes, and then we'll leverage. Dashboards and data integrations to pull everything together. To me, what, what is critically important is how do you solve for that last piece of, in a given tech stack, if you will, and those are difficult to change if, regardless of which end of that spectrum that you fall on.
To me, the, the, the role of the FA analyst is to assess what are we using? Is it a single tool? Is it four or five tools? And then find ways to pull the right. Level of data that can help you make those better decisions, find the insights, the trends, the patterns in a way that that blends all that information from, from different areas.
So, [00:13:00] you know, I, I have my own ideas and thoughts. I know that doesn't fit with every team on the planet. I think the ultimate goal is just how do we find the right insights from every system to tell the same consistent story.
Matt Tucker: Yep. I sort, I'm leading on from that point, you know, I think. I've, I've been in many meetings where, you know, data is presented to perhaps some of the more C-suite representatives in a room, and the stuff that you see on the screen is quite overwhelming and very detailed, and a bit too much information that that C-Suite representative wants to see or hear about.
How are we moving away from sort of reporting data in that way to. Really get to the, the whole reason why you'd show that in the first place to try and influence decisions and to what extent are we, we successful in doing that within FM,[00:14:00]
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Matt Tucker: Does AI help raise the bar to think like that? Uh. It suggest, from what you've said, it sounds like you're saying, yeah, that you should, [00:15:00] you should make AI your buddy, you know, you should pick one of those various systems of choice for that given task and, and use it to your advantage. Would you say that's, that's what you would like to see from, from the FM industry?
Drew DePriest: 110%, yes. All day. We've talked about a game changer study last summer. The concept of. Those who accelerate and excel in this industry and in many others will be the one to learn how to use AI as a better tool. And it, especially in terms of analysis, because it's so good at you and I have talked about this in the past.
The sources of information within the FM space don't always just exist in a traditional platform. You're not always gonna have, here's a table of things that are important that we need to analyze. It's also gonna come in emails and direct messages between you and others and channels where you're discussing [00:16:00] projects and conversations like this where you may have a recorded transcript that you can leverage, and the ability of agen AI to process both that.
Structured and unstructured source of knowledge and combine and find the real contextual meaning behind it and what key themes are running like ribbons through each one is so much faster than any of us could ever do. I mean, I'm, I'm cutting down some analysis from weeks to probably hours. Not to say that we can't do it, which is then the caveat to the whole thing of you would better understand.
What the output means. You know, it's getting better over time, but some people just pouring in information into Gemini or copilot or what, what have, or Claude, what have you, and then just running with the output and not digesting it, not making sure they understanding it. So keeping that the human in the loop principle to me is super important because someone is gonna quiz you and grill you, especially in a, an executive [00:17:00] situation, to really understand that you know what you're saying.
So to me it's, it's a tool, it's a calculator on steroids to help you find the insights and you would, you would better understand what the output means.
Matt Tucker: Yeah. On that note, I mean, one of those traits is around beta confidence. Do we have in the FM industry AI confidence yet? Is that, is the workforce fully confident in going all in, like you're saying?
Or is there still some reservation about, you know, data protection? Where is this data, you know, where does we put it into Gemini Chat, GPT, Claude, whatever, where does it go? Uh, who can see it? Are these still valid concerns from the FM community or, or is it getting better in that respect?
Drew DePriest: I think they're still valid and, and it's why I continue to insist on the concept of human in the loop.
There are areas, I'm sure we've [00:18:00] all experienced it at home, at work with whatever our AI pal of choice happens to be, where it, it gives you a response and it just doesn't seem right, or I've asked it to generate spreadsheets before and it will leave certain cells blank for some reason. And. As you interact with it, if you ask the question, Hey, I noticed you left this particular row in column, empty, what's going on?
And typically it will apologize. It's very gracious and says, Hey, you're right. I, I didn't have that as a data source. Can you feed it to me? So I, I think it's just there's a healthy level of, of skepticism in interacting with it to really, I would treat working with an AI tool. Just imagine that you're in front of that senior executive that you need to tell the story to.
Where are they gonna poke holes? Where are they gonna pressure test? The more that you spend time going back and forth with prompts and really, you know, fine tuning to get to a hundred percent, [00:19:00] the better you're gonna be.
Matt Tucker: Fascinating discussion. We could probably have a dedicated podcast just on AI alone.
But yeah, I, I agree with you. It's here to stay. It's gonna keep getting more and more important within our roles. I mean, it was really drilled home to me during the interviews for this particular report when, you know, it was, it was noted more than once about the emergence of having digital colleagues, you know, and having actual AI agents.
Built into organizational structures or having like a mirror, like, like a twin organizational structure, a digital one. I'm a human one, and I think these things are gonna become more and more common in discussion. Like I wanna make sure I leave time before we close out to perhaps address, you know, an, an elephant in the room here about skills and training and talent.
Um, and I wanted to get your take on that. Someone who's, you know, senior in the industry. You've been in multiple large companies, you've been on the tech side, the FM side, everything. Where do, where do people actually [00:20:00] go to learn this way of thinking, this analytical way of thinking? And are we doing enough as an industry right now?
Drew DePriest: I've seen it exist in multiple places. I think there's a, a certain. Most companies, it's anecdotally speaking, I think at this point are offering some degree of, of internal training, of some sort around understanding data in general, the role of ai, how that applies to particular, particular roles. The ones that I get excited for, and I've, I've worked alongside, I've hired people who have done this in the past several years, are taking it upon themselves to go out and find external opportunities.
There's. Gentleman who comes to mind, who was an FM in a former life, worked with me as, as more of a, an analyst sort of systems administrator role, and took it upon themselves to go and find a, a university course that focused on, it went a little deeper. It went [00:21:00] on data processing and extraction techniques.
Python was, was introduced as part of it. And before long, this person started asking me, Hey, can I go shadow our data engineering team? Can I learn from them on what they're doing? And just, just observe and see how really the, the proverbial sausage get gets made in terms of data warehousing and how these things look.
And I I love that, that, that approach of someone who. Has worked as an FM in the past, now see a role evolving into, I need to understand the role of data, how it gets processed and stored and housed, and what that means to me. Especially looking at this increase that we've talked about of the AI as a co-pilot to understand the backend of how an agent is evaluating that level of information.
Is only gonna make you better and help you find the errors and call out things and really think about [00:22:00] other ways to leverage it. So I've, I've seen it a number of different ways. I think focusing more on those skills that we talked about at the, the top of this conversation of storytelling is another important one, but also the data confidence piece.
So I think if we focus more on those two things, you're gonna see a lot more of the shift to the analyst mindset.
Matt Tucker: So just to close out, we're we're, we're running out of time, sadly, and I could talk to you all day about these things, but if we were gonna fast forward, you know, five years, maybe 10 years in the context of what we're talking about, about FM's relationship with data and technol technological change, what does great FM look like in five years where we go, wow, we're, we're really doing some great stuff here.
Drew DePriest: Sure. I think current trajectory, I think your, your thought of. Agent as a co-pilot will be standard. That'll be a daily thing instead of, I've worked with some great FMS in the past who have said [00:23:00] the first thing they do when they, when they get to the office, to the workplace, they get their coffee and then they sit down with a handful of dashboards and reports.
They get emails that come in from, from overnight to see what alarms or, or any things may have, may have been reported. I think that transitions to more of. I sit down with, with my agent, whichever flavor that happens to be with a prompt that someone has probably written for you or that you've created yourself in 10 minutes because you understand how to do it now, it just says, what are the five to 10 most important things I need to know that happened since I logged in last.
That's coming up for today. That's happening now, and I see that now I, it's part of my morning routine as well. I think the pace of how this technology is evolving. It's hard to predict what may look 12 months out, let alone five years, but I think it's this hesitation and the data confidence piece, I think we'll be way beyond that in the next five years.
Matt Tucker: Yeah. [00:24:00] Fantastic stuff. I'm gonna say thank you, drew, always fascinating to speak to you. Love this conversation. I've certainly learned some more things I always do when I'm talking to you, and I hope our listeners have too. So thank you very much and see you again soon.
Drew DePriest: Agreed. Thank you so much, Matt.
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