Prologis, Inc. (PLD) Earnings Call Transcript & Summary

It's a really good point. And there's a couple of aspects there is, one, the quality of data. So you always hear people say garbage in, garbage out. Being data-centric is a commitment and it needs to be very intentional. And frankly, well, there's a couple of things. One, our IT department has built a world-class data infrastructure. I mean it is -- we've had technology companies come in and start patronizing us because we're a real estate company and explain it to us, and then Sineesh and the team get out and be like, no, here's our technology stack and in most cases, actually better than some of these major technology companies have. So we started with an exceptional foundation, but then it's incumbent on getting the right data in the system. Because if we're not entering data or it's incorrect, you have a Lamborghini without gas. We actually got to the point where last year where everyone's bonus in the company, 25% of it was tied to us hitting our data centricity goals. So accuracy across 6 different categories, and we measured it and send out e-mails every day updating people on it. Necessarily not every day, every week. This was a true commitment to getting it done, and we did. But it was really due to the fact that we, as a company, realized that we had to commit to it and hold people accountable to be truly data-centric. It took a lot of work, but now we have that it opens up all these possibilities. So now we're in the cool stuff of being able to go back to people and say, we know you put in the hard effort. But look, we can use a tool like TestFit and we can combine it with our [ costing ] data, we can combine it in some of our propriety data and suddenly you get insights that we didn't even know would be possible 2 years ago.

All right. So lots of effort to get AI on top of big data models and whatnot. The benefit, I think, of the partnership with you guys, like we learned a lot more about how we want to go about site planting industrial buildings. And that sort of AI ,already ready to go, every time we update it, it's not like you need people kind of making sure that the data is accurate. It's like plug and play, right?

Yes. No, it's -- I think one of the values in just how software is designed today, especially in the cloud, is you see continual improvement and that where the product was a year ago versus where it is now versus where it's going to be 2, 3 years ago. And the more people part of the ecosystem, the better the technology is going to become because you're gathering all these insights and improvements. So -- and with cloud-based software, it can be updated in real time. So I know that, that's something that we spent a lot of time with you guys in the past year, just really thinking through from a large institutional player how we would use the software, what our requirements were but ensuring that it wasn't designed for Prologis and a company of one, but it would be universal because we -- we get benefits, but we know the more people are part of it.

I remember some of those conversations. All right. So -- all right. Next big thing is like there is a finite amount of capital we go around, right? Your REIT, you've got to deploy capital, finite number of opportunities. With the rise of AI, do you think we're going to end up analyzing more things, less things, the same? I mean what's going to happen to sort of deal flow in the future?

I think it will be a lot more efficient. So it's something like theoretically, could you build more buildings to AI because it remove steps. Sure. But people are pretty careful about supply and demand metrics. I think what it will enable us to do is optimize faster to what the highest and best use is at a pacific -- specific site from even understanding the entitlement process and how past deals have gone through, how communities view different uses. I think there's going to be applications for AI there. When we're looking at designing buildings, the ability to run through iterations really quickly, as I've seen even in conjunction with sitting alongside a customer, you're going to end up making a much better decision about what could be built on there and how to maximize returns. And -- we've all, over the years, been in situations where we have tied up or we're looking to tighten up the land and some of you run into zoning restrictions or entitlement issues or weird layouts. And to be able to flesh that out and test it at a much more rapid pace, will allow people to make better decisions earlier. And rather than spending 2, 3 months to discover a problem, if I can discover it in 10 minutes, there is a huge benefit to everyone involved.

Yes. I mean I kind of started thinking about like years of development out, right? Like the last several years has been like, how do you focus on solving this one site for this one developer and kind of the multifamily space. When you go on meet Prologis, they've got sort of a generational approach to how they want to attack real estate and seeing sort of planning over time and how we can be more intelligent -- because like these are hard assets. The moment you build them, they're done, right? They're a limited kind of editing. So we want to be a lot sharper about the kind of assets we build in the future.

Yes. And I mean one thing that's very important for us as a company is our net zero commitment. And we've got the second largest operator of rooftop solar in the world right now. We're building up the EV charging infrastructure I mentioned. An area we're spending a lot of time is an alternative materials, green steel, green concrete, et cetera. I think the ability to use AI tools to validate tests and project how these materials will perform and figure how to fit in. And there's a huge value proposition that's going to allow us to adopt these things quicker. And there's challenges now of just cost differences between newer materials and established. And we have to be able to move quickly on a lot of these things to continue to make a difference. And I think AI and tools that people can use to ahead of time, restimulation, et cetera, are going to be just increasingly valuable as companies -- I mean, it's not just us that has made this commitment. It's all our customers and our brethren across real estate because it's important and the right thing to do. But we need to be able to -- I'm not going to put a faulty material in a building and put employees' lives at risk or our customers' lives, like -- this is really important. So AI is a really cool tool to be able to help accelerate the adoption because we can pull data sets and that we haven't been able to do in the past.

Yes. I mean, like the promise in my view is, I think we talked about this, like you have the sort of level of development that you do on the design is so much deeper. And you're considering things like, hey, portfolio-wide, we have these water penetration issues in these markets with this kind of material. And like you all actually have the data to then go like, hey, we're going to go inform the front of the process and say, hey, these are the lessons learned. The AI is hopefully picking up on OpEx issues that drastically impacts what's your NOI is at the very beginning of the deal.

I mean we are using AI right now for roof and paving inspections. So historically, we've had to have people go off on the roofs and they take photos, et cetera. Now we can use your [indiscernible], but you can then have [indiscernible]. So there's immediate benefit of being able to understand a quicker basis. But over time, we're going to have all this digitized information. And roof [indiscernible] Chicago performed very different than they won in Arizona for a whole host of factors. If we can get better insights about improvements in the type of materials, how it performed, it's just going to make everyone better and smarter. So that's, again, being able to digitize this information in a format that we can apply models against. There's a huge amount of value. And I think frankly, one of the challenges that we almost face is we don't know what the article [indiscernible] is because we haven't done this before as an industry. This is all new. So there's a lot of effort we spend both internally to free ourselves of constraint. So thinking, okay, what could be done, being super curious trying to bring in different perspectives. And that's why I think DEI is very important because why do you want to hire diverse people. At the end of the day, it's the diverse perspectives that they bring. And if I have 20 people in the room who have been doing the exact same job for 20 years, you kind of know the answer, but if you can bring in diverse perspectives, one, your talent pool is going to be bigger because you're now going after the entire world versus a small subset. So you can hire the best talent. Two, they're going to bring in a different perspective and they're going to see things different. And then you need an inclusive culture that allows them to ask those questions. So it's actually something to the [indiscernible], 70% of my team of Venture side is female. And so in real estate, supply chain and venture, which aren't necessarily but we went after and wanted to hire the smartest people. And we opened up the pool to find the best candidates and smartest people who came through happened to be the women, which is awesome. I think the second aspect is really important is adjacent learnings. So just because someone in real estate hasn't done this, how do we look at other industries and see how they might be using AI and what they're doing to be able to pull it back and try to apply it to our situation. So it's something we talk about as a company is like how do we be really intellectually curious and challenge existing norms, especially if we know those norms may have changed because technology or constraints have been removed.

Yes. I think diversity is really -- test is not where it is without diversity. And another thing is like getting our start-up to stretch from being high-density multifamily to, oh my gosh, these are 200,000-foot buildings and they have like a grading problem, and they have logistics challenge inside the cycling. That causes us upscale like the problems that we were solving ourselves. And having done 2 kind of core markets now, like our team is probably more equipped to handle any kind of building type coming forward. So what's the future look? What's kind of our closing moment here for you. Paint an ideally good picture.

I mean I think -- and I'll tell this specifically the AI because there's a lot of ways like in the future. I think -- where it's going to be really powerful is -- I've done my job for 20 years, and I know I'm kind of -- like I'm good at my job, but I've also tied to the constraints in my -- what my past behaviors because that's what I know. AI suddenly gives me the ability to connect dots across data sets that I never would have thought possible. And it's going to give me some very unique insights that will make me better at my job than I ever could, if I continue doing it. And that's where I think the future, especially from an AI point, the more we can define real problems applied against and enhance people's decision-making, you're going to end up with people who are -- situations where you're being able to be much more collaborative. We're removing people from tedious tasks of reading through 10,000 pages of environmental reports to really focusing on the outcomes and then how do I strategically build plans to deal with that. I think there's going to be a lot more cooperation between people in the sector, whether it's the developers, whether it's the architects, whether it's the consultants, whether the construction because in real time, people can share ideas and take actions on those ideas versus having to spend time processing or collecting or pushing paper. It's kind of like an office space, which is that data -- moving from like the early '90s, but there is the guy who -- his job was to take the fax to the engineers because he was a people person, right? Like those are the jobs that we waste time on now, and we really want to be able to have our people at the highest and best use, and you hire the best talent to get their ideas. So how do we give them more data and more insight to be able to even come up with better ideas. And that's a future I see. And that's where we get excited and a little plug on TestFit. I mean, it's part of -- a big reason our excitement there is that it's going to enable our construction and development teams to really spend more time on strategic outlets and really driving value and be able to make faster, better decisions.

Yes. All right. That concludes our kind of interview with Prologis. Do you have any thoughts or questions, feel free to e-mail me, clifton@testfit.io or you can find me on Twitter or LinkedIn. You can download our ROI with 6 or 7 companies that kind of give us some case studies. So we have a fairly confident return on investment, but I can say like you figure out how many people at Prologis were counting parking spaces last year compared to how many are counting this year. It's going to be a pretty solid ROI.

Yes.

All right. Thanks, Will.

Yes, this is great, Clifton. Thank you, and I appreciate the time here today. So I look forward to continuing our partnership and seeing how the world is going to continue to evolve. So have a good one, and I appreciate this.