Lorri Rowlandson of BGIS explores AI’s impact on FM and corporate real estate, outlining a three-layer approach to integration. With examples like a finance bot and HVAC optimization, she highlights practical innovation, responsible AI, and continuous learning.
Lorri Rowlandson, head of strategy and innovation at BGIS, outlines a three-layer approach to AI integration: individual level desktop AI for job reengineering, operational level AI for enhancing internal efficiencies and client value-driven AI for service improvement. She emphasizes the importance of practical innovation, responsible AI use, employee engagement and continuous learning.
This episode is sponsored by Envoy.
Lorri Rowlandson: [00:00:00] You will never be able to control all of the different AI tools that are coming up. What we really need to do is teach people how to use AI responsibly.
Make sure you're testing accuracy of information, you're asking for references . Make sure you're complying with laws and regulations, be aware of contract and legal obligations and just make sure you're not doing things like representing real people without their permission.
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. Today, Lorri Rowlandson, Senior Vice President of Strategy and Innovation at BGIS. Outlines a three layer approach to AI integration, individual level desktop AI for job [00:01:00] reengineering, operational level AI for enhancing internal efficiencies, and client value driven AI for service improvement.
She emphasizes the importance of practical innovation, responsible use, employee engagement, continuous learning, and much more. Now, let's get into it.
Lorri Rowlandson: My name is Lorri Rowlandson and I have an opportunity to speak with you for a few minutes from the perspective of a lead of strategy for a facilities management service provider. I'm speaking here at World Workplace about a strategic guide to transforming facilities management and corporate real estate using artificial intelligence.
So, I just wanted to give you a little bit of an insider's view from a head of strategy as to how we approach such a an enormous topic, an overwhelming topic, and break it down into pieces. Let me just start by [00:02:00] saying, I work with a company of engineers. Engineers like to measure everything. They value results, not necessarily ideas.
If you really want to relate to an engineer, you Don't talk about an idea. You show them the evidence. So a lot of what I do as the sponsor of innovation is around a term we have coined practical innovation. And so we really need to make sure we're not only strategic. But we have quick hit successes.
We have practical fundings that deliver benefits and short horizons. And I really need to speak to our leadership and our clients about real examples. So, we don't engage in what I call innovation theatre. We're really a company of practitioners and it's a wonderful fusion. of innovation and engineering that really keeps us grounded.
I'm the head of strategy and innovation for BGIS, as I mentioned, a company that's technically led. [00:03:00] And my role is amongst other things to support our clients and ourselves in how we continue to keep up with all the innovative influences. And of course, artificial intelligence is one of them, and that is a huge theme here this week at World Workplace.
So what I thought I'd do is spend a couple of minutes just sharing with you, how does the head of strategy create a plan of attack for artificial intelligence in the organization? And I'll follow it up with some real examples of things that we have either implemented or near implementation.
So, as I mentioned, we're not into innovation theatre, we actually implement things. So a lot of the use cases that I'm going to share with you are things that we're actually doing or have completed. So first, I'm just going to give you a bit of a bird's eye view as to how do we do a plan of attack on an artificial intelligence strategy inside an organization.
And I like to think of it as a three layer cake. [00:04:00] The first is what I call desktop AI, and that is at an individual level. There's nobody more qualified to re engineer their own job than the individual performing that job. So We spend a lot of effort to turn our team members into digital champions and digital natives of, and breed familiarity with technology.
So that's the first one. I'll get into a little bit more detail there in a second. The second is around operational benefits. So that's really around how we drive efficiencies inside of our organization. Remain competitive and cost effective. And we're getting rid of the Low hanging fruit of the busy work and not the strategic work.
That's the second category, operational. And the third is around client value. Doing things that matter to our clients and how we're transforming our industry. I'm just going to spend a couple of minutes giving you examples within each of those, because again, we're practical innovation. So I mentioned the first category is at the [00:05:00] individual level, and we have spent a huge amount of time and focus on A.
I. Literacy in our company and creating digital citizens at every level in our organization. So the head of innovation is not in an ivory tower off to the side. This is very much everybody in the boat rowing. Everybody is responsible for transformation and innovation and the model that we have. Is very much a crowdsourced approach to innovation. We start by having a policy that makes sure that people are exploring AI safely, and doing so without creating additional risk to the organization. And I know talking two years ago, I can remember talking to some people in IT and they were contemplating blocking chat GPT sites and a number of the different sites that were popping up and I said this is going to be the worst game of whack a mole you've ever played in your life.
You will [00:06:00] never be able to control all of the different AI tools that are coming up. What we really need to do and by the way, we're going to be left on the platform and the train is going to pull away. What we really need to do is teach people how to use AI responsibly. So we created a policy that gave them guidance, no confidential information, no intellectual property.
Make sure you're testing accuracy of information, you're asking for references, citing references. I know not everything on the internet is true, so get them to cite what those references are, so that you can validate them yourself. Make sure you're complying with laws and regulations, because the laws around the world are changing depending on If you're in Europe, Asia, North America, et cetera, be aware of contract and legal obligations and just make sure you're not doing things like representing other people like real people without their permission.
And so what we did was we launched that policy. We spent some time hands on talking to them about the risks of AI. And then what we did [00:07:00] was we showed them the potential. It was amazing. It was like doing magic tricks for the first time in front of our audience. And I went around to each department and showed them.
Got them to bring up examples of what, what did you do in the last week? And then we used AI live to be able to show them how they could accelerate certain tasks. And that was just amazing. And it gave people the idea of how they could re engineer their, their jobs. McKinsey, fun fact, interesting statistics says that 60 percent of employees could save 30 to 40 percent of their time through using AI and that desktop AI.
And so that's not going to come from somebody else. That means re skilling, rethinking how we're working at a desktop level. So really thinking of how you can use those tools and extension of yourself to accelerate what your purpose is at a desktop level. So that puts every single person in the driver's seat towards innovation.
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Lorri Rowlandson: Fun fact about me, what I do is I actually have my chat GPT. I use quite a number of different AI tools, but I talk to my chat GPT in the car and I do research. So that's kind of fun. I'm doing a demo on that at tomorrow's talk. [00:09:00] Okay, so that's around individual AI literacy and getting individuals to hack their jobs from within and at a desktop level and getting them responsible.
And then we have team leads in the different departments who share success and help each other. The second level that we look at, the second category of how we tackle the strategy of AI is looking at the operational. And that's really around driving internal efficiencies. One of the greatest sources of inspiration I think is frustration.
So, you know, everybody has one of those companies and there's something inside some process or something that's irritating or it's very high volume and low value and it wastes time. Those are the things that are perfect to target. And we've developed a magic quadrant matrix so that you can plot high volume, low, low value, lower risk activities and look at targeting those [00:10:00] first and prioritizing or mitigating the risks if necessary.
And I'll give you some real examples. We developed a bot in finance that we named Daryl. That we process millions literally of invoices a year, and it's literally the 80 20 rule. 80 percent of our invoices are very small and under, you know, 1, 500, but those are the ones that are problematic.
They don't match the PO, the numbers don't match, et cetera. And our larger, more sophisticated vendors are much better at this. Their invoices work perfectly, but from a volume perspective, they're much lower volume. So we have this enormous team in finance trying to manage a whole bunch of lower dollar value invoices.
So we developed A bot that looked at, and we could train what are the reasons and root causes for the invoices to not match our system. And we had it automate, automate out re education or re submission, and we saved a [00:11:00] huge amount of time and money. So, and vendors can get paid a lot faster, so we saved a huge amount of resource effort.
In our finance team, another area that's a really great target internally is marketing and communication, and that's becoming even more important. It's not what you know, it's how you influence. So everybody needs some marketing skills, even outside of the marketing department. So some of the tools that you can get in AI just remarkable on how you can really finesse your message and much, much faster.
One of the one of the other things that we did was we started developing bots to solve certain activities. So we wanted our employees to start doing Truth and Reconciliation. Land acknowledgments at the beginning of meetings, and that depends on, it, it, the script changes depends on your location.
So we created ChatGPT, and it's available, by the way, if you go into the ChatGPT store, it's open, anybody can use it. You just type in your [00:12:00] location, and it will tell you what land acknowledgment is appropriate for where you are. So I know for the Canadians that are attending this conference, that's very relevant for you, but it works anywhere in the world.
The third category, just to close things off, is around clients. And that's around looking at use cases of what matters to clients. And we've got a long list of things here, but the most exciting thing about AI is that it really allows us to look at integrating broader ecosystems of data, and therefore, at value.
So we can look at things from a total cost of ownership perspective. An example is, we looked at HVAC units. And what are all of the decision points and stakeholders that are involved with the entire spectrum of an HVAC unit? And we found it was very secular. It was very divided. So, you might cheap out on the cost of a unit and it, but it might, Create a huge amount of work orders downstream, or it [00:13:00] doesn't work as manufactured promises related to sustainability.
So we were able to take all the data points from each of the different aspects of the life cycle of an HVAC unit and really optimize it's the decision process. The maintenance process into a complete total cost of ownership view. That was very interesting. Another example is around climate assessments.
And we were able to not only proactively assess the risks related to each location based on climate instances. Of course, this is a big topic right now. But we were able to better harden the site and better forecast what mitigations we should do using AI. The last thing I'll say is this has been great from a self serve perspective to her clients because now they have an LLM or a text.
Based interface into a huge amount of data so they can type into a box. Hey, can you tell me all of the branch locations that [00:14:00] do not have accessibility ramps or, or up to code? And it can just provide, you know, provide the output in this format and it can do that for you. So, the amount of interface, the ease of the interface with a language, just asking a simple question, and it can synthesize that information, is really incredibly powerful, whether you're looking at it for an individual use, an operational use, or for your client value proposition.
I've got a lot more case studies, but I'll just leave you with this, is think in new ecosystems. We have The ability to really quickly understand and overlay and connect information at an unprecedented level. And that makes us really powerful as facilities managers.
And I guess the last thing I'll say is when you have all the answers, what questions do you ask? And we, there's a reason that prompt engineering has become a big topic. We have to really be much more sophisticated in what questions do we want to ask to create the [00:15:00] output. Because we have a lot more of the answers at our fingertips.
So we need to be better at bigger, more broader questions that address ecosystem thinking. And then the last, last thing I will say is please develop a love of learning. There's so much change coming. I read every day and I still feel like I can't keep up. So please develop a love of learning. And keep re skilling upwards because there's so much excitement and opportunity of things that we can do if we could keep up.
Anyway, thank you so much. If you have any questions, please reach out to me anytime. Lorri Rowlandson at BGIS and happy to have a conversation. Thank you.
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