 Live from San Francisco, it's theCUBE, covering Informatica World 2016. Brought to you by Informatica. Now, here are your hosts, John Furrier and Peter Burris. Okay, welcome back everyone. We are here live in San Francisco for Informatica World 2016. Exclusive coverage from SiliconANGLE Media is theCUBE. It's our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier with my co-host, Peter Burris. Our next guest is Sri Potanini, who's the chief technology officer in applications and data with JLL. Welcome to theCUBE. Thank you, thanks for having me here. So, real estate, big opportunity for a lot of data. It's a challenge when you think about the IoT opportunity. You guys have done some work. Share with us what you guys are doing and how you're using data. So we're doing many things with IoT, right? It's not about just redoing. Everyone's doing everything about IoT with the buildings. You talk to the carpet manufacturer. They're embedding devices into that so you can know the food traffic. The lighting people, there's IoT sensors in that. You talk to the furniture makers, there's sensors in that, right? So pretty soon it's not about what we are doing in IoT as the engineering hardware side of it, but it becomes how are we analyzing this data to create new workplace strategies, right? So that's the focus on now. So there are, of course, there's many, many things that you will see. There's a lot of videos that you will see. We have made buildings smarter. We have done building efficiencies, smarter buildings, et cetera, et cetera. But what I am pushing for is how do you analyze this data? So it's a great thing. One of the experiments that I did for a small suburban office, we put about 400 sensors. And every sensor, every five seconds is telling about itself. The temperature, if this room's occupied, whatever, right? It's doing that. Now that generates terabytes of data over the day. It's a small office. Now look at downtown LA, a downtown San Fran with all these buildings. Think about the chatter, the ones and zeros that are coming up from our building, right? Now the building itself is a data platform. Now when the buildings are generating so much of data, a set of buildings in the market, in downtown market, look at the data, look at the utilization and how the market's using. There's so many, many, many products, intelligent products that you can create. Intelligent workplace strategies you can create. You can create fluid occupancy structures between building to building. You can kind of remove the boundaries of office space. So there's many things that we can do. And I think I'm very passionate about it, not just about what we have done in the past but where it can take us in the future. So the progress bar relative to the sensors, how would you peg the progress bar? Because are our sensors proliferating now in building standard or is that mostly you guys have to provision the sensors to get the data, get the data flowing? Is it, where are we on that right now? From your view? So yes, we need to provision the sensors right now. So right now it is, we need to put the sensors. On the building automation, on the smarter buildings, energy efficiency play, there have been solutions for many years. We have a solution called IntelliCommand where we go advice and make the building smarter. So that's what it is today. But if you talk to some of the lighting manufacturers, some of the newer buildings where we are doing a refit, as part of the lighting procurement, they already have the sensors. So we are at a stage where now it's a project to make the building smarter. But very soon it will be built into the building. What kind of real estate portfolio do you guys have just from a scope standpoint, order and magnitude? How big, just to get a sense for the folks watching? It's not like you have one little strip mall, I mean our office building, how big is the portfolio? It's about three billion square foot of management. This is just management. This is the billions of square foot that we manage. But we also handle billions of dollars of transactions through us. And if you think about the industry itself, annually, I don't know how accurate this number is, trillions of dollars of real estate exchanges hands in commercial real estate, right? So that's the vast amount of real estate work we do. And if you think about office, when you said that, if you think bubble charts, since we are in the data side, the biggest bubble would be the office. Office, we do many things around office. So office is obviously industrial, retail, residential, all aspects of it. We are a global company. We operate in 80 countries, 60,000 employees. So what we do in US with the focus area can be different from what we do, let's just pick another country like Philippines, right? So think of it, different markets, different maturity, different local needs. So just because the big bubble is office, that doesn't mean we're not doing something in Philippines which helps the local Philippines real estate or India, for that matter. So you also have some responsibilities over architecture as well. So you're doing a lot of the innovation and thinking about the role that data can play in the services that JLL provides through commercial real estate business. You also have architecture. Architecture in building has historically been associated with the physical layout of the building. How is architecture, how is the digital and the physical coming together? Because that could be one of the places where these two sides actually start to touch and create conventions for how we think about the digital and the physical at the same time. I have two great examples for that. One example is, have you ever been in a building in an office building, a corporate headquarters of some kind, where you think there's congestion? Have you ever been in a building but you have a nine o'clock meeting and then you need to be at the elevator bank at 8.45. Otherwise you'll never get the elevator peak time, you can't get it, so you had to almost take the conference call in the lobby, right? You can do that. So there's a lot of traffic within the building which is an issue, right? So now you take data through sensors, let's relate the previous topic together too. If you have the sensors, you don't have to have purpose fit sensors, right? Even through devices connecting to wireless access points. You can understand how the traffic is moving. And if you think, let's take a little bit different example to that, if you think there's a lot of congestion at Starbucks which is leading to a lot of bottlenecks and people getting into the building efficiently, right? That means what you do is you put another coffee shop on the other side of the building so you distribute the traffic. So that's architecturally- It's like a load balancer. It's a load balancer, it's a load balancer. But you're physically changing the architecture of the building. That was one example. If you have time on the second one, now if you all remember there was a time that we used to have meeting rooms, now we still have meeting rooms, a calendar, booking of meeting rooms, et cetera. At least the way I work and many people nowadays work is you don't really have a meeting one week in advance. You're talking to the team and all of a sudden you want to huddle, right? So now the way conference rooms are getting used, you can look at that and say do we really need the old style meeting rooms or do we need more collaborative huddle rooms, right? So the new build-outs architecturally will be a lot more open space, collaborative and will enable this huddle room culture and not the meeting room or corner offices culture. So yes, the physical data, IoT can all lead to those architectural decisions. So that the data literally can be employed to configure a space for a purpose that perhaps it was originally intended. I'm curious, if you ever read Christopher Alexander's a timeless way of building, have you ever heard of that book? No, I haven't, no. So Christopher Alexander, just as a quick aside, it was a professor here at Berkeley who wrote about, who's one of the originators of the concept of pattern languages and in many respects, one of the popularizers of the concepts of architecture and much of his work then came into the technology industry as a way of thinking about usability and whatnot. And so it's kind of fascinating that architecture, physical architecture through Christopher Alexander, Zachman and others, became seminal to IT architecture. And now we're seeing it come back and the sole notion of digital and how it affects the physical layout and how we think about configuring spaces in response to a particular purpose. It's interesting to see how it's coming back. That's brilliant, that's a cycle. Yeah. That's just fantastic. And so I strongly recommend it. It's an interesting book. Absolutely, we'll do it now. But when we think about this notion of how digital and physical in commercial real estate are coming together and your role, is that becoming part of the business proposition that JLL has to its customers? The idea that we can create more flexible space, more agile space, space that can reconfigure more easily with greater predictability. Is that becoming part of the promise you're making to your customers at this point? Workplace strategies is a very important of what advice that we provide to our customers to understand the current state and to create this modern workplace strategies and use IoT to understand. Definitely, it's the core of what we do for any occupants, large fortune-finding companies. This is the advice that we constantly provide to them. So your competitors' building may be similar to yours from a physical standpoint, but you hope that your building will be perceived as superior to by your customers because in part of the digital capabilities that you can bring. Absolutely, absolutely. It's not only just the building. Very often, people look at us as B2B. We are, right? The way I relate to everybody is, you are going into office. You, you, we are all going into office. Ultimately, somebody's decided, but you and I are saying whether this office is good or bad. Through the data. Yeah, it's about the data. It's not only about the building differentiating, but the people who are in the building eight to five, they like the building. Steve, this is a great point because this brings back down the point. We hear this all the time in IoT. Oh, the physical plant, in this case, commercial real estate, the buildings, they're telling a story through the footprints and the digital footprints, if you will, literally in this case on the carpet. But that creates optimization for the physical plant or the building and then there's optimization of that asset. Can you share some examples of where that data is driving off property value? Because that would, I can almost see like, okay, you now have data on, are they happy with congestion in the building? But what about people who have to drive to work every day? Is that a good location for the building? If there's other new processes that kick out of the data, new insights, they can say, hey, well, people are very unhappy because they're stuck in traffic. So there's other things that you can glean out of the data that go off the property or the plant or in manufacturing or real estate. This is the new thing that's enabled. These new processes are developing where the data can optimize. Can you share anything that you've seen there? Absolutely, and let me relate that outside of the buildings too, right? So labor, drive time, et cetera, yes, yes, yes. But let's talk about us, something more personal to us, right? If you're bought a home, building is definitely important, how it looks, layout, et cetera. But you're also looking at the school district, which is not, right? Yeah. You're looking at the market. Where is your family? Where does your family live? Amenities, hospitals, et cetera, et cetera. So commercial buildings are similar. Building is part of the answer, but not the entire answer. It's the labor loss, it's the tax loss, it's the drive time, right? It's about the occupants and also about the business. Why do companies move from one state to another state? There's many, many reasons, not just because the building is nice, there's a lot of other data, right? So to answer your question, yes. It's not just building, the other data is also very important. So how does it impact us, right? We've always, always, analysts have always for many, many years, have used various desktop tools to put together these models, labor, drive time, et cetera, et cetera, weather, et cetera. But what we are trying to do is create a data library with thousands of data sets that our analysts, not only the poor people with the desktop skills, but our broader definition of analysts can tap into with some of the modern tools and modern architecture, mash it up with their internal data and create new insights. Not just to say, hey, building, there's some problem with this building product, maintenance assets. But to say... That's low-hanging fruit, they get that immediately, right? Yeah, absolutely. But to say, wait a second, it's not only the asset, but it's the weather. We've had unusually certain type of weather. And in this weather, these kind of assets fail. So we should have predicted this failure ahead of time and we should have prevented this as against waiting for it to fail. That kind of decision-making needs to happen. So let me run a scenario by you. So I can imagine that in any given time, a building might be 100% occupied, but only 70% of the people show up because of traffic or people are out visiting customers or whatever else it might be. And so you might be able to say, oh, a certain, there's 70% occupancy, we've got 30% open, people show up and they reveal or they pull down information and says, okay, my counter is this, I'm meeting with these people today, I am here, they declare themselves to the building. And the building might say, why don't you sit over in this side because it's going to be cooler over here than it is going to be over here. Therefore, we don't have to, or air-condition this part, keeps the cost low. We can also set up services for you so that you'll be sitting near the people you're going to be working with so you don't have to deal with the up and down of the elevator. So is it that kind of a stuff that we're talking about ultimately? Absolutely, that's all the things that you just said is definitely possible. Of course, there's a cost angle to that, right? So to optimize where the people are, but there's also flexibility, right? More and more people, I mean, Hotelling's been there for about five, six years now, but Hotelling still is within a boundary, like what you just said, right? On Fridays, this department sales function is not there or Friday sales function is there, something like that. So yes, that kind of optimization is definitely possible. We are seeing those trends in the data. Now, we haven't really closed the loop to act that way, but definitely the future version of Hotelling can be more fluid, can be more liquid. Do you anticipate that your buildings will have APIs that occupants will write to so that they can start, you can provide services through a common set of interfaces and they can consume those services through a common set of interfaces and add data to them? Yes and no, you're kind of really going a little ahead, yeah? But yes, but the concierge services. So there's many people, the buildings are ecosystems. I mean, if you look at some of the large buildings, it's like a small city, right? So buildings potentially can have their own group on, they have their own Facebook, have their own LinkedIn within the building, right? Because that's where you spend a lot of your time. It's your own personal LinkedIn, personal Facebook and everything else. So we are doing a lot of that concierge services that's interacting with not only the building, but the community of the building, right? Can there be APIs where other people can tap into it? The answer is yes, I see why not, but we're still at the concierge level. Tree, one minute left, I would like you to share with the folks watching what you've learned over the past few years and most recently, the past two years in how data is transforming your business and the value you're providing to customers and what should they be thinking of like and what approaches should they take? It's very simple. It's very simple, just enable your employees. So our, in our case, it's 60,000 employees. Don't group them, empower them. Empower them through self-service. It's plausible today, not only self-service on the data visualization, but empower them by providing all data that they can potentially imagine to create the decisions. They may not use it today, but this thing will catch on, especially the millennials that used to exploring on their own. So to allow them to give them access to the data, I think is what you need to think of. Yes, the traditional artifacts like data warehouse, data mods, ODSs, your big BI infrastructure will all continue to exist, but please look beyond that, not just for a few reports, but enable everybody with data. Self-service is very important. Please do that. Trey, thanks so much for sharing the insight. Congratulations. Love the story. I really think you guys are on really the front edge of an amazing transformation. Congratulations. And thanks for sharing. Well, thank you. Thanks for having JLL at this table. Thank you very much. Appreciate that. Thank you very much. You're watching theCUBE here live in San Francisco, part of Informatica World 2016. I'm John Furrier with SiliconANGLE, with Peter Burris, General Manager of Wikibon Research, Head of Research for SiliconANGLE Media. We'll be right back with more. You're watching theCUBE. Hi, this is Chris Devaney from Dataro...