PROPTECH PANEL – Data Democracy: Where are the opportunities for data collaboration in commerical real estate

Guest Speakers:

Liam John Murray – Build-Apps

Dr. Stephen White – CSIRO

Chris Hanley – Tenant Advisory Group

Simon Fonteyn – Accurait


Scott Willson: (00:12)
Welcome everyone, to the next instalment of yet another exciting Proptech panel, brought to you by the Proptech Association of Australia and its foundation sponsors, Stone & Chalk, [inaudible 00:00:22] Macquarie Bank, The Real Estate Institute of WA, PEXA and Webit. My name is Scott Wilson, I’m a committee member of the Proptech Association of Australia. And this week we have a subject for you at the bleeding edge of debate across commercial real estate, data democracy, where are the opportunities for data collaboration in commercial real estate. Before I begin, in the spirit of reconciliation, Proptech Association of Australia acknowledges the traditional custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to the elders, past and present and emerging and extend that respect to all Aboriginal and Torres Strait Islander peoples joining us today.

Scott Willson: (01:05)
Many listeners will be well versed in the fundamentals, Australia’s enormous stock of commercial real estate, 300 billion US dollars of investible assets and counting, has attracted a global investment audience and support the professionalisation of commercial real estate. But as digital transformation agendas gather pace, the ripple effects on established work practises may mean what has worked in the past, is not what will work in the future. And the accelerated adoption of technologies that make the difference, will separate out-performers from the pack. These efforts are also likely to place data at the centre of new opportunities. And while there has been a broad enthusiasm in the ability of big data revolution to shake up the industry, so far there have yet to be significant shifts in established work practises.

Scott Willson: (01:49)
Joining us today to share their views on where the opportunity lie for the industry and how collaboration on data could be a win-win for commercial real estate professionals, are Liam Murray, CEO of Build-Apps, Simon Fonteyn, managing director of Accurait, Chris Hanley, national director, head of New South Wales Tenant Advisory Group, for Cushman and Wakefield, and Stephen White, Energy Efficiency Domain Leader for CSIRO. So let’s get into it, starting with you, Simon, how does your solution, or how does your suite of solutions rather, improve collaboration in the commercial real estate industry?

Simon Fonteyn: (02:24)
Thanks Scott, thank you for the opportunity to be here and thank you for the Proptech panel for having me on. So our company leasing information systems at the very heart of our modus operandi is data democracy. So for the last 15 years, we’ve been gathering data, mainly in shopping centres and strips, using whatever is available through public domain. So mainly through registered leases, but through gathering information memorandums and other data, to be able to share that across our network of landlords, tenants and investors. So that’s really been the heart of the business, and more recently we’ve combined with CSIROs Data61, to create the first machine learning tool called Accurait, which uses the smarts of Data61 to be able to read leases and create structured data out of unstructured PDFs.

Simon Fonteyn: (03:41)
All those tools combined create a platform for data democracy. However, I will state that up until today, we still face significant headwinds in achieving real available data across Australia. And those headwinds are mainly to do with regulatory issues, so not every state in Australia registers leases, Victoria doesn’t, South Australia, Western Australia, and Tasmania don’t really either. And the other significant barrier is landlords, as a general rule, have confidentiality provisions in their lease, which creates a significant impediment to be able to achieving true data democracy.

Scott Willson: (04:43)
Thanks Simon. I’m sure we’ll return to that shortly. Chris, from Cushman and Wakefield, you’re working closely with tenants on a regular basis, which data sets help you in your role?

Chris Hanley: (04:54)
Yeah, so we’ve worked with Simon for a number of years to get lease information for some of our retail tenants, and that’s been extremely helpful. There are other data sets that you can get access to for lease information across other asset classes as well, and those are very helpful just in terms of price discovery when you’re trying to provide recommendations around what’s a market deal look like, where are the opportunities for you to potentially get access to real estate if it’s currently under lease and those sort of things. We’re also looking at other market data in terms of who’s doing what in the market, that helps us in terms of understanding whether there might be some competition from other people that might be looking to potentially lease space that you’ve been speaking with another tenant about. And then other information, but because we’re working with tenants, a lot of what we’re trying to do is work out how much space they need and where should that space be, and so that then takes us into some other information.

Chris Hanley: (06:00)
So occupier based utilisation data, so how many people do they have visiting their locations at any one time? Where are those people coming from? And what’s the travel time look like going from their place of residence to their place of work? And what does that look like if you’re then moving them from one place to another? And again, the level of customization in the data that you start to lean on when you’re looking at different industry types, really starts to expand because you need to start to get your head around what performance looks like for an occupier within a particular industry, and that can lead you down some rabbit holes into industry specific data sets as well. So fortunately, there’s plenty of information out there, it’s just trying to decide which information you want to use to help create those insights that your tenants are looking to you for, and also whether or not that information is reliable.

Scott Willson: (06:58)
Yeah, right. Some interesting points there. Thanks Chris. Liam from build-Apps, your Proptech facilitates, sanitises data flows between business applications. What examples can you share today where these data flows have lead to improved outcomes?

Liam Murray: (07:14)
Yeah, so I think the big focus is around the data democracy, not just being everybody having access to everything, but there’s also a level of security around it. And what we’re trying to get is clients to own their own data, and once they do that, they can then decide which departments within a big commercial real estate company can access which datasets. So obviously some of it is secure, some of it isn’t, some of it can be crushed up. So we’ve seen some great examples from where traditionally the development team wouldn’t normally talk to the operations procurement team and from cross layering data sets, they managed to identify about $12 million worth of assets all from one manufacturer. And suddenly that meant the development arm could talk to that manufacturer and go, “Well, rather than us going around in circles.”

Liam Murray: (08:09)
Other examples, the leasing team don’t normally interact too much with the facilities maintenance teams in a traditional model, whereas we were able to see that certain lease types, so certain tenant types created a lot more issues, and that was actually from statistical information that was captured. And so the tenants that had long hours or particularly lawyers in large buildings would tend to have more complaints because they were working in the evening when it was harder to get reliable, and that might affect the system choices when you design. So cross layering is quite important.

Scott Willson: (08:49)
Yeah, right. Some interesting points there. Stephen from CSIRO, where does CSIRO see the greatest potential for data collaboration in commercial real estate?

Stephen White: (09:04)
Thanks, Scott. Yeah, so just in terms of my interests, so I’m not Data61, I’m in the energy business unit, but we do collaborate really strongly with Data61 and particularly their synapse data streaming platform there. So my interest is in energy efficiency and also in integration of buildings into the electricity grid. The air conditioning system in buildings is responsible for almost a quarter of all electricity consumed, and as much as 50% of the peak demand days and the security of the system is certainly influenced there. So opportunities in the energy space, we have data sets in the residential building space, so we’ve got almost a million dwellings that got rated through the national construction code, and so we’re custodians of data there through the regulatory process and the national construction code. And then we’re developing the building automation technology and how do we actually create the ecosystem of innovation there.

Stephen White: (10:16)
And I guess the opportunities that I’m really interested in is where does government play a role in data infrastructure to enable that ecosystem of innovators and to underpin markets. And so in the case of the Natters data set that we’ve got, to what extent, or it’s been an ongoing conversation and presumably we’ll come out the end of the sausage factory in due course, is a disclosure of energy efficiency ratings in the market. And suddenly that then creates a bunch of secondary markets and potential for low interest loans. We’ve got at least one banking institution that is using the Natters data set to underpin low interest loans and stuff.

Stephen White: (11:05)
And so what’s the role of a trusted institution to manage data, and the Open Data Institute talks about this concept of data in institutions to be stewards of data. What’s the role of those kind of institutions and how do they play in a way that encourages competition and innovation, but doesn’t come in with heavy handed government bureaucracy and stuff. So those are the kinds of things that we’re tossing around as we have a whole bunch of data sets, unique data sets that come into us.

Scott Willson: (11:46)
Yeah. That’s a really interesting point there, Stephen. Thank you. Simon, you touched on this as well, so I’m going to jump straight to a question on this to you. What do you think government and regulators could do to facilitate further greater and greater sharing and greater transparency in the marketplace for commercial real estate data? Sorry Simon, you’re on mute. There we go.

Simon Fonteyn: (12:14)
So can you hear me? Yeah. In 2008, the Productivity Commission actually looked at the whole sector of commercial real estate in a retail space, and they recommended that information in each state, at least enough to be able to form a view around the key details of a lease be registered. Unfortunately, governments have actually not done anything about it since 2008. And it’s really miles behind where it should be in this day and age, where you can think that you can go to, or you can get an RP Data and get information about everything in a residential setting, but yet you can’t find what other leases in Highpoint Shopping Centre or any other major shopping centre in Victoria, it’s a really archaic situation. Mind you, globally we know we’re actually probably more advanced than a lot of countries because a lot of countries, you can’t get anything.

Simon Fonteyn: (13:24)
So here there is a registration process, but it’s not really providing that national footprint to be able to really do the type of work that say Chris, who’s looking at things nationally, need to be able to do, to be able to look at a whole of country situation. And without talking out of school, the main reason why governments and the whole industry as a general rule have not progressed this, is because the commercial imperative is not there. So it’s not in landlord’s interest to really provide this information because it’s commercial in confidence. And until such time as that information has been taken into the public domain, I don’t see that actually changing. So it’s really up to governments and regulators to be the custodians as Stephen said, to make this available to create further transparency. And if that is available, then obviously there’s a lot of economic benefits, not only in terms of better decision-making, but also being able to provide transparency to a market that’s often shrouded in mystery.

Scott Willson: (15:00)
That’s an interesting point, Simon. I think the commercial imperatives are a really interesting point. Just to tease that out a bit further, a question for you Chris, what would create a collaboration on these sorts of things, if there was a national registry where leases were registered, what would that mean for how you do your job and what would this mean for the tenants that you represent?

Chris Hanley: (15:21)
Yeah. Just speaking to the retail context that Simon alluded to before, I mean, I know from my dealings with retail tenants in New South Wales, it’s of great benefit having access to the volume of lease information that you can get because of the registration process here. So applying that same process in other states would give national retailers or any tenants operating outside of New South Wales effectively, greater control or greater understanding of what the context is that they operate within and give them a greater ability to make decisions around lease renewals and that sort of thing, with that greater information to hand. And then similarly in the commercial context, in all property classes, that additional information would be to the benefit of the tenants, I think it’d also be to the benefit of smaller landlords as well. And in a retail environment where you’ve got a dominant landlord or a sole landlord in control of 400 or so retail tenancies, it’s effectively its own market.

Chris Hanley: (16:28)
And so a situation where you’ve got a landlord having 100% of the information about all of the tenants, what they’re paying, how much, what turnover they’re doing, and the tenant potentially having zero information outside of their own lease, which is expiring anyway, I think there’s a big imbalance that could be tipped more towards a tenant’s favour, without significantly impacting the landlord. So I think there’s certainly potential for that to happen, and it hasn’t blown up the market in New South Wales, so applying it in other states, I think, would be a good thing. And in terms of other information, I think about the US where the registration doesn’t necessarily apply, but there is a greater level of sharing between the agent and broker community around availability information and deal information as well.

Chris Hanley: (17:21)
And that certainly hasn’t blown up the agent community over there either, I think it just takes what is essentially a very inefficient process at the start of the lease, where you’re looking for buildings to put your tenants into, and it just condenses that because you know you can go to one location and find all of the availability information you need, rather than having to run a process whereby you’re effectively contacting every agent that is active in the market you’re searching in, to try and understand whether or not there is any availabilities that suit your client’s requirements. So more collaboration, I think, is better for the industry. I think it’s going to lead to a more efficient industry and probably one that’s a little bit more balanced between landlords and tenants. But certainly I think our view is that this greater collaboration is certainly coming, so we just need to prepare ourselves for how we participate in that.

Scott Willson: (18:18)
Yeah, that’s great. That’s an interesting point around the New South Wales, maybe we can return to that subject soon, around those state-based disparities based on practises that take place. Question for you Liam, we’re hearing here the industry approaches the position around data collaboration from a position of fear, and this is based on those asymmetry positions that exist, and those markets can exist where you’ve got those disparate information flows. What do you think can be done to switch that perspective around from position of fear and protection, to one of openness and collaboration?

Liam Murray: (18:58)
Yeah, I think it’s feeding the information back to the property owners at times, what tends to happen is quite often, it’d be done with one platform or an external consultant, and that never gets centralised back to the property owner who can then share that with who they want to share with. So it’s not necessarily somebody being the custodian of it, and there will be times when they don’t want to share it because it’s commercially sensitive or their offering lease is very intricate. And so it can’t be compared apples with apples, but at least if they’re storing in a common schema and then they can pass that out to somebody else and they can understand that schema, they can choose to share. Whereas at the minute when they do share it, it’s a PDF of an offering to another PDF of an offering. Whereas if the owner of the building becomes the owner of the information and treats it the same as their bricks and mortar, and then passes it out in a nice structured way, there’d be efficiencies for everyone.

Scott Willson: (20:02)
Yeah. Just a follow on question for this and it begs the question about skillsets, I guess, that would need to exist in the industry. Now it’s something I see a little bit of, where traditionally professionalisation of commercial real estate hasn’t necessarily always led to real estate owners having a lot of competency and skill sets in the business around this. So what do you think a greater collaboration environment would look like around how landlords, how owners and how other service providers in industry would need to recruit and attract talent and what sort of roles they would need to be looking for?

Liam Murray: (20:42)
So yeah, it’s probably having a common schema that everybody knows they can work to, and then those skillsets can start to emerge around that and that where that schema crosses everything, so covers leases, covers asset management, covers sustainable and efficiency, covers facilities management. If everybody’s storing their information in a similar way, then people can start to really specialise. Whereas at the minute we’ve got software as a service vendors doing one thing and in one direction, and then we’ve also got some of the big REITs trying to do in-house software development, which no one can then tap into because they can’t see how it’s built. So trying to meet in the middle so that everyone can share information because the last thing people want to do is spend endless amount of time trying to digest, like building custom APIs every single time for information, cost time and money.

Scott Willson: (21:41)
Yeah. Okay. So common schema, a common way or a common language to work with these information flows. Interesting point. So I guess related to that is probably a question for you, Stephen, what examples can you identify in your work, where collaboration has led to joint benefits for its participants? You mentioned some of those open data projects, I’d be really interested in your take on where you’ve seen some wins here.

Stephen White: (22:06)
Yeah, well, a lot of the projects that I get involved in, in the environmental space, have got some sort of underpinning government scheme that creates value. So something like neighbours, for example, for energy ratings there, by actually having an ecosystem around that, the building owners get their rating, asset values go up for the higher rated buildings and then there’s a value proposition for upgrading the performance of buildings that then get contracted out through players.

Stephen White: (22:45)
So the Natters scheme, that’s in the residential space that I talked about before, that’s all based off national construction code that then triggers a bunch of things. Neighbours, or the Green Building Council, with their green star rating schemes and things, they drive an ecosystem of collaboration there, but it’s all centred around someone who’s the custodian of the scheme and custodian of the scheme being custodian of data.

Scott Willson: (23:13)
Yeah, interesting point. So we’re talking around the constraints and also some of the opportunities. Where do, I guess, CSIRO and some of the work you are doing at the moment, help to, I guess, add to this common language of the data that’s available? Have you got any projects that you’re working on at the moment that work on this?

Stephen White: (23:35)
So in our building automation space we’re certainly trying to champion structuring of data. And so with HVAC equipment, that’s the stuff that’s the chillers and the valves and all that sort of stuff, using the brick schema as an ontology that structures things up. And our aspiration, I guess, is to head towards something that looks like a no customization tool and to make it easy. How do we get scalability through our mobile phone, and the apps that run off that, is you’ve got one app, you download it, you use it, kind of thing, and there is no human intervention.

Stephen White: (24:19)
And we’ve got this mindset in the industry that every building’s a prototype. And I’ve heard that said a number of times. And somehow or other to get scalability in this industry, we actually have to structure up the data so that you can almost have that mindset of click instal then use, and you don’t actually have to go back and bring in the experts because every time you put someone on premises, you’re chewing up a lot of transaction costs. And ultimately in my game, energy is a commodity product, there’s not a lot of fat to be had there.

Scott Willson: (24:58)
Fascinating. Simon, returning to you, can you think of some examples you’ve seen perhaps, in your endeavours outside of Australia as well, where some of the tools that are used in your suite of products, are in use and what that’s meant for the industries offshore and how they’ve developed?

Simon Fonteyn: (25:19)
Yeah. So Chris made a good point about the US, so in the US, they have a company called Co-Star, which bought LoopNet, even though they don’t register leases in the US, or some states I believe they might do, but the broker network, they have a sharing mindset. So the way it works over there is that the brokers are incentivized to put data in because they’re the ones doing the deals, and they get an incentive in terms of getting data back, through either a reduction in subscriptions or that they get benefits. And so that’s how it’s done in the US. In the UK, they have different laws around in the UK, but automatic right of renewal on a lease, and they do have a data collaboration tool there. The main differences between the US and us, is that in Australia, the majority of leases have a commercial in confidence provision, and those things tend to be enforced.

Simon Fonteyn: (26:51)
The other thing is, in Australia, particularly in retail, which is my sector, the majority of the agents don’t operate in the largest shopping centres, they tend to be owner managed. And the REITs are not really incentivized to provide that information because they use that for their commercial leverage, so I don’t see that as something that’s directly comparable. However, where I do see there are opportunities to work, is more around de-identified data. So what Urbis, Urbis is a benchmarking tool, I’m sure you’ve all heard of it, they take de-identified data from the landlords mainly, and then they provide benchmarks. We have a product project on at the moment, which we’re working with a few groups about doing something similar. So providing data, using collaboration tools to be able to provide benchmarks which don’t breach anybody’s confidentiality, but yet provide information around what are some of the key benchmarks in data, in places that are hitherto unavailable in terms of information.

Simon Fonteyn: (28:24)
So I see that continuing to progress, I see that benchmarking piece continuing to gather pace until such time as where all this information becomes available. And I think it’s almost inevitable that it will because we’re moving to electronic data interchange. So for example, in New South Wales from one August, there’s new legislation that requires leases to be automatically digitally registered and signed. So that’s going to create opportunities to digitally read that information and make that more available. And I just see that happening more and more in other registries around the country. So I think it’s only a matter of time, it might take a decade or so, it might be quicker, but it’s inevitable that this information will become available, whether people like it or not, it just will, because there’s too many ways now which that information can be shared.

Simon Fonteyn: (29:37)
And to be honest with you, as Chris said, New South Wales has had registration for years, it hasn’t collapsed the market. In actual fact, New South Wales has the strongest commercial real estate market in the country. It just provides more transparency, there’s significant economic benefits. So it’s really just a matter of time before other places follows suit, but it may not be in the same format as New South Wales, there may be other ways in which it’s done, but inevitably it will happen.

Scott Willson: (30:12)
Yeah, interesting point. Returning to you Liam, how do you think, from an owners perspective, that real estate owners can position themselves to take advantage of improvement in data availability, as Simon is describing, it’s just a matter of time. What actions do you think big owners, landlords can take now to begin preparing for that future?

Liam Murray: (30:36)
I think with the boom of Proptech, and it’s having a clear onboarding strategy, we’re seeing lots of these big companies doing lots of Proptech in different directions, and it’s not creating a common data model, it’s scattering the information even further away from where it needs to be. So having that process and we talk to everyone about, no matter what it is, what you signed up to, you need to make sure you know the what, the when, the who, and the how the data’s being accessed. So that they can understand, is this being on sold, is the data that I’m giving to you, being on sold. There’s lots of metering companies who are SaaS based, their revenue is based on selling that meta data to third-party [inaudible 00:31:27] but the owners of the property who bought the meta and run the meta, they haven’t given anyone permission to do that, they’re just deeming it’s their data and they can sell it.

Liam Murray: (31:38)
Whereas having those declarations upfront, and quite often, we’ve seen some fantastic stuff with manufacturers putting IOT devices inside their units, so that they can get telemetry on how their units are performing. And some of our big clients have been like, “Fantastic. You have the beta, because if you improve your product, we get a better outcome as a client, but you have to tell us you’re doing it, you can’t just, it’s my data, I’m going to do something else with it and not let you know.” The owner of the data is the owner of the building, is my take on it.

Scott Willson: (32:12)
Yeah. Interesting point. I guess it’s a really interesting one, and perhaps in for those Proptech listeners out there, a relevant question because the SaaS business model is a pretty popular one, it’s quite an effective one as well, and certainly encourages, in the right setting, the right incentives and alignment behind it. But how do you think the Proptechs can really aim to achieve a balance between suiting and designing their onboarding for landlord customers, with the appetite that’s needed for actually moving fast and breaking things? We’ve seen a lot of adoption, we’ll see a lot more in the years to come. How do you think a Proptech should position themselves to really balance what can probably feel like competing requirements between groups at times?

Liam Murray: (32:58)
Yeah. I think being API centric, so the days of you having a nice dashboard and people buying a product, because you’ve got a nice dashboard, are long gone. All of our clients have got data analysts in-house, they’ve got Power BI, they’ve got Tableau, they can make any dashboard they want, they want API to consume your data. And the Proptech companies needed to have faith in what they do with the data and their unique IP of how they manipulate it, whatever their model is, they ingest, do something smart, send it back. They need to have faith in what they actually do is the value, not hoarding the data. Have faith in what you’re doing with the information, is the value.

Scott Willson: (33:43)
Yeah, right. So the special sauce, being clear about what your special sauce is, right?

Liam Murray: (33:46)
Exactly, exactly.

Scott Willson: (33:48)
Yeah, okay. Interesting point. Returning to you Chris, are there data sets that don’t exist yet, which would transform what you do?

Chris Hanley: (33:57)
So I’ve just been thinking about that a little bit more and trying to compare the different industries in commercial real estate and in retail, you’ve got turnover of data that is a really good indicator of the suitability of a particular site to the product that you’re trying to retail out of it. And in the commercial space, it’s not as clear what the impact of the location is on the performance of the business. And so if there was a really well-defined metric that we could point to, that identified the overall commercial impact of a location in the commercial office context, that would be really helpful, but it’s hard, that’s Nirvana. Other sorts of information that I think would be amazing would be utilisation information for commercial office buildings. So particularly in this post COVID landscape, people are really trying to understand how their buildings are being used. And there’s a range of different ways that you can determine how your building is being used, but that lack of standardisation makes it very difficult to compare one building to another, and what that information really means when you’re looking at two different data sets.

Chris Hanley: (35:19)
So one might be race gate swipe ins, whereas another might be a richer data set to do with how long people are sitting in individual chairs. And so some sort of standardisation or a standard data set around building utilisation, I think would be extremely handy. And it gives you an ability to compare one building to another, in terms of their carrying capacity, what’s the impact in terms of tenant experience with a high volume building versus a low volume building or a low population building, I should say. That would be really good because ultimately we’re trying to find what is the best place for our client to locate themselves within.

Chris Hanley: (35:57)
The commercials, the rent, the incentives, those sorts of things, they’re good to know in terms of buying the product at the start, but then there’s a commitment for five, seven, 10, or even longer, that you really need to understand before you go in. And those sort of metrics would be very helpful in terms of determining what’s the right spot for the client. So I think that would be very handy, how we get there, I’m not sure, I’ll leave that to the big brains out there, I suppose.

Scott Willson: (36:28)
Yeah. And I guess just returning to some points Simon was making before about the benchmark data he’s working on, he used the Urbis example and then some work that he’s involved in at the moment around furthering some of that benchmark analysis that could be available. If that sort of information were available out there, how would that help you? Would that start to fill some of that void around utilisation potentially, would it potentially make it easier and get better outcomes for how those lease renewals or new leases take up and maybe even shorten the cycle for renewal, would it make a difference?

Chris Hanley: (37:04)
Potentially. I think the benchmarks that Simon’s referring to, are looking at different categories of retail shopping centres, and then looking at different rental profiles for different industries that operate within those types of shopping centres. I haven’t poured through the data set in great detail recently, but from what I recall, I’m not sure how transferable that analysis could be into the commercial office context because of the different things that you’re considering when you’re looking at a retail shop versus a commercial office. But yeah, look, at any sort of market-wide or industry-wide benchmarking is always going to be relevant and give you an ability to benchmark your own occupancy costs, from the client’s perspective, their occupancy costs versus their peers.

Chris Hanley: (37:53)
And we certainly try to provide analysis to that effect as part of our recommendations to our clients. But again, if that analysis was available at a market level and for purchase, then that would give us more time to spend analysing other things for our clients. So again, yeah, that would save us time. A lot of these emerging data sets and subscriptions that you can get access to, really just take time away from work that we’re already doing and allow us to focus on stuff that is a lot more customised to the individual tenant. And so, yeah, look, it will all be great, more data is more helpful for all of our clients and ourselves, it just takes time out of it.

Scott Willson: (38:40)
Yeah. Thanks, Chris. Question for you Stephen, and I told you I’ll be asking you this question. If you had a magic wand, what single change would you make and why?

Stephen White: (38:53)
Well, obviously I’m going to pitch what I’m doing in the space when you ask me a question like that, so just to build up the pitch, should we say. Ultimately this data democratisation is indeed what we’re searching for. And ultimately that comes down to data platforms that actually enable the data democratisation. And so what would a data platform do? We talked about semantic web technologies and structuring up data, so creating context to data is really important, federating multiple data sets, and when you’ve got context and you’ve got federation of data, then you can start to apply artificial intelligence and do the smart things.

Stephen White: (39:39)
And obviously in the my CSIRO world, I would get off on doing the smarts over the top, but unless the data has got context, unless it’s federated with a whole bunch of other data sets, I can’t really do that. So in my world, I would pitch to the data hoarders, people holding on tightly to their data sets, I’d say, “If we collaborate around some sort of data platform, then we can do a whole lot more interesting things than we otherwise would of.” But at the same time, having to deal with the data fearers in this world, who quite rightly are worried about access controls, and we’ve had a good discussion around that. And so a lot of the business model stuff that needs to actually think really hard about access controls and data governance issues.

Stephen White: (40:31)
So from a pitching point of view, at least in the HVAC air conditioning space, we’re building up what we call, the data clearing house, and we see it as a bit of a data institution that is stewarding data on behalf of the industry for the industry and that kind of intervention there, where a trusted not-for-profit type of arrangement to actually liberate data and enable the smarts to be used and competition around who can provide really good value added services. So that’s my wishlist, long journey to get there, of course.

Scott Willson: (41:10)
Yeah. So that federation, establishing the context, the federation, the commonality, creating a platform that spans beyond, I guess, HVAC into the broader sphere of what is commercial property.

Stephen White: (41:24)
And the ability to have a rich discussion. In my energy world, we have fault detection and diagnosis and tools like that. And purely from an energy efficiency point of view, they have payback times less than two years, and yet it’s not a widespread practise. Probably starting to gain a bit of traction now, but it hasn’t been a widespread practise. And a lot of that is to do with trust around the data, about information asymmetry, the fact that if I engage in this industry, I don’t understand it properly, where can I go to have someone to navigate the complexity of this with me, and how do I avoid getting locked into someone’s commercial weaker system? All those kind of things have prevented, what is otherwise greenhouse gas emissions saving, low-hanging fruit from high financial returns. So it’s really important stuff, this data democracy, to enabling these important environmental and economic benefits.

Scott Willson: (42:33)
Stephen, are you suggesting that could be a role for a data utility that can enforce this?

Stephen White: (42:39)
Well, so that’s the interesting thing to me. When we built up the electricity industry, we realised that the poles and wires, you don’t build poles and wires multiple times down your road, you actually have to share a resource there before you can actually provide any electricity. And so I, in my philosophical world anyway, say, “Well, what is the role for common good data infrastructure?” And government understands that we build roads so that cars can drive down them, do we need to actually build up data infrastructure? I don’t think it’s the solution for everything, but I certainly see a role in some instances where there’s demonstrated market failure.

Scott Willson: (43:30)
Thanks, Stephen. I’ve got some other questions, but we’ve had some excellent questions from the audience, that I might just jump over to it so that I can cover them all in the time we have remaining. First ones for you, Liam, if the building owner owns the data, in your opinion, how is this handled when executing transfer of ownership?

Liam Murray: (43:48)
So one of our big ROIs that we talk about our platform or our ecosystem as such, is that we’ve directly seen it firsthand when a client bought a building, there was only seven people who bid on it. When they come to sell it, and they put into the data room, so much information because they had so much information and were very transparent, and they had 30 plus bids and it was only an 18 month period later. So the market had changed, but when you sell a building, the more information you provide, the more judgement on the risk that the purchasers are going to do. So it’s not just that matter of, you’re not going to sell a building with none of that data, if you’ve got it, you put it on show and you get a higher value for your building when you come to transact.

Scott Willson: (44:43)
Okay. A follow on question for that, and I know this is an area potentially you’ve looked at before, how has BIM contributed to making progress to solving the common schema that you talk about?

Liam Murray: (44:57)
Yeah. So BIM traditionally has sat at the front end, as being new build designer led and given, I can’t remember the stat, but I think it’s 80% of all buildings currently built are still going to be here in 30 years time, so there’s not going to be magic BIM models of all the stuff that’s already built. So the focus not on the geospatial aspect of BIM, but the actual. I always say, in BIM, the I becomes before the M, so the information’s more important than the model. So getting the information to move through, whereas I’ve been involved in so many projects where they’ve had a BIM model for coordination, and then the information from it has never even created an asset register, which is just criminal, but it’s not seen as a whole of lifecycle thing, it’s seen as the coordination and trying to change that to help.

Liam Murray: (45:53)
It does help massively having IFCs and the role of Coby and, Building Smart do globally, really powerful too. But then there’s still, yes, Stephen mentioned haystack, being able to translate from IFC to haystack and then across to … there’s endless amounts of different schemas, being able to translate quickly between those is what we’re trying to help people do, so that there is a commonality you’ve not got. [inaudible 00:46:21] in there and then called a phone call unit in the other system, and they can’t understand we’re talking about the same thing.

Scott Willson: (46:29)
Yeah, sure. Did you feel it’s like water, the data is like water, it’s inevitably going to find the lowest point and find a way through? Do you think that it’s just a matter of time before a lot of initiatives around better use of data, better collection storage, transferability of it is going to happen, or do you feel like the impediments in the way right now are going to make that slower than we think?

Liam Murray: (46:52)
I think it’s getting slower and slower. I think there’s more people introducing, to use your water, there’s people putting oil in here, there’s people putting alcohol in here. So they’re all making it harder to [inaudible 00:47:07] that’s the what’s it called, and people have got slightly different vested interests, if that makes sense. Certain people want a data set for what they want, certain people want a data set for what they want, and that’s the only commonality in our view, is the owner of the building. And that’s why bring it back to the owner and then he can pass the leases that he wants to share that piece, he can pass the BMS data to somebody who wants to do something smart [inaudible 00:47:34] flows.

Scott Willson: (47:39)
Thanks, Liam. Next question, I’ll throw this one to you, Simon, has anyone quantified the economic benefits and opening the lease data through a registry?

Simon Fonteyn: (47:54)
Yeah, well that was actually quantified in the Productivity Commission report, you can look at it, in 2008. So we did a whole lot of analysis of the benefits of having information, including things like information asymmetry, better economic outcomes from both landlords and retailers. So that’s all there, just look at the Productivity Commission report. I would say just as a corollary to the benefits, I think one of the things that we as a group have to realise, is that we’re really only at the infancy of what data can be used for. And having the CSIRO Data61 in our offices, we started on a project to use AI, not just to releases, but to make better intelligent decisions. And what’s actually available and what can be sourced and gleaned from correlations that the average professional, and I’ve been in this industry for most of my career, I would not have thought or even realised that these correlations exist. It’s actually mind blowing.

Simon Fonteyn: (49:16)
So the imperatives are not only from a transparency point of view, but it’s going to become a situation where probably in, I can’t put a timeframe on it, but investment decisions, relocation decisions, are going to need this sort of data to actually work. So it’s becoming like that where other industries, like for example, medical, finance, engineering, that this data is available already. And so it’s only a matter of time before the commercial real estate either catches up or is forced to catch up. And even though Chris, who works for a number of banks, the banks may refuse at some point in time to actually sign off on things if they don’t have this data. I mean, I can see that coming, they won’t get their approvals.

Simon Fonteyn: (50:19)
So it’s almost becoming a necessity where there’s going to need to be more information, and unfortunately the governments, they haven’t wanted to step in. And by the way, governments hold a huge amount of their own data in this space, and they haven’t released it either, so they’re just as bad as not facilitating this. So it will happen, it’s just a matter of time, but I can’t put a timeframe on it.

Scott Willson: (50:55)
Yeah. It’s an interesting point. I think you mentioned the banks and increasingly they’re going to require it. I’m interested in your view around what you think would be the effects of banks using more data for decision making purposes, and what it could look like for their work practises outside of direct property, work practises?

Simon Fonteyn: (51:15)
Well, I mean, Chris would probably be able to talk more, but for example, you have AVMs, which stands for automated valuation models. I can see the time where a bank who’s particularly a big facilitator of real estate, won’t make a decision unless they’ve got 50 or 60 data points spanning across my set, Liam’s set, and Stephen’s set. They need a big dataset to work out, okay, if I’m going to invest $20 million in opening a branch or not a branch, but say a major a retail/commercial facility, I need all this data to be able to make a decision. And if I don’t have it, I can’t make it. So you provide it or we we’ll go somewhere else where they can provide. So it’s becoming like that, that the big data sets are becoming ubiquitous.

Simon Fonteyn: (52:11)
You just have to look at a company like Quantium, which is mining very, very large data sets, not necessarily yet in the commercial office space, but it’s only a matter of time where these things will be required to make decisions. Because professional, and we talked about the professionalisation of the real estate sector, the majority of people who work traditional real estate sector, are trained either in land economics, accounting, finance, they’re not trained in data science. So they need support from data scientists who normally sit under the professionals, like Chris or myself, but they will be increasingly saying, “Well, I can’t give you a sign off unless I have this data.” So that’s where I say this going. And it’s been only recent where I’ve had the CSIRO in my own office and I can see what they can do, but it’s really opened my eyes to say, “Wow, this is what’s coming. And it’s not a matter of if, it’s a matter of when.”

Scott Willson: (53:22)
Yeah. Chris, would you have anything further to add to that?

Chris Hanley: (53:26)
Yeah, I think Simon’s right. It’s really hard to ascertain whether or not a relocation from one space to another has been a good move, or is likely to be a good move, when you’re only working with limited data sets. So if all of a sudden there’s this ability to tie together different data sets to demonstrate the validity of a move from one spot to another, I think if that starts to emerge, then you’re right, it’s going to become a requirement in order to support the deal, to demonstrate that it is going to have a positive benefit to the business. So that data sets not available at the moment, and often our recommendations will include some reference to whether or not the deal looks like a good deal in the context of the market, so the commercial stacker.

Chris Hanley: (54:22)
There might be questions around, have we investigated what the impact is on the staff in terms of travel time or employee experience or those sorts of things. But certainly if there was a broader data set that was able to demonstrate whether or not previous decisions were successful or not, that would also be great for identifying whether or not relocations or renewals in current offices were the right decision. And yeah, I mean, if that data set was available, it would be compulsory, which it ought to be.

Scott Willson: (54:58)
Brilliant. Thanks, Chris. We’ve probably got time for one more question each. I’ll start with you, Stephen. What would it mean, you’re leading some of the work that Simon was introducing around AI and when you’re working with big data sets you’re privy to, are you excited by the opportunities that AI presents for commercial real estate?

Stephen White: (55:21)
Yeah, totally. And I think from my point of view, there are so many different application domains and I’m really passionate about occupant centric utilisation of AI. And the success of doing AI and things like that to me, is around the richness of the dialogue of what we can do. If it was purely about energy, energy obviously is my passion, there’s a certain number of things we can do with AI, but when we get to comfort and productivity and asset utilisation and all these things that we’ve talked about today, then you’re starting to bundle lots of value propositions together, and that’s when, I think that we’ll see it happening.

Stephen White: (56:09)
And the difficulty of course, is individual siloed providers, just with one little application that they do, it’s not a very rich conversation, difficult to get value out of the AI there. So that collaboration, partnership around data is important for the future of AI, I think, in the commercial building sector.

Scott Willson: (56:32)
Fantastic. Last one for you, Liam. Magic wand question I asked Stephen before, you’re a magician, you’ve got a magic wand, you’re waving it around, what’s your single wish around one thing you could change?

Liam Murray: (56:46)
Probably if everyone adopted a common data model and there are various parties around the world we’ve been working with, Microsoft and Rick’s in the UK and different parties, but everyone coming together so that we go, “Right, here’s 500 tables and 20,000 fields, and they’ll all be called this.” And whether that’s making an offer for release, with all the different terms in it, whether it’s an energy data set that needs to go to the Stephens group, whether it’s there, that everyone just agrees on a common schema for all commercial real estate. And it is possible, we’re covering lots of sectors and you just don’t use some of it when it’s healthcare and you don’t use some of it when it’s retail, we don’t use some of it when it’s office, but it can all live in the same common data model schema.

Scott Willson: (57:39)
Brilliant. Thanks, Liam. Simon, magic wand, what’s your answer?

Simon Fonteyn: (57:46)
Well, if I had a magic wand, I’d love to be able to get registration in every state. That would be my number one. If I could achieve that before the end of my career, I think it would be great for the industry. So that would be my number one thing. In terms of the magic wand though, sometimes there is a lot of things that can become redundant. So my concern is, and Chris touched on this, is the sector is actually quite inefficient in the way that things have managed. So AI has the power to actually make things much, much more efficient, but it also has the power to actually make a lot of processes redundant. So there has to be thought around how to use AI and data democracy, to basically benefit not only the whole sector, but those people who work in it as well.

Scott Willson: (59:00)
Awesome. Yep. And Chris, magic wand?

Chris Hanley: (59:08)
Yeah, I think for me, ultimately I’d love to be able to get access to a data set that helped demonstrate whether or not a relocation from one site to another would be to the benefit of the business that I’m working with. So some sort of aggregation of different data points that gave me, ticking a box or not, that would be ideal. It would probably do me out of a job, but it would be very handy. Because often we get caught up trying to make recommendations to clients and it could be that there’s a couple of different options that could work for them, but I’d love to be able to have a really concrete indicator that I could point to, that said, “Look, there’s an AI platform, let’s analyse these 20 different data points, that it’s recommending that you proceed with this transaction, and it’s right more often than it’s not.” So if that existed, that would make my job a lot easier, but I’d probably have a bit too much time on my hands if that existed.

Scott Willson: (01:00:16)
Thank you, Chris. That’s all we have time for today. Special thank you to Stone & Chalk, who’ve made today possible. Stone & Chalk are Australia’s leader in connecting founders, investors, and industry stakeholders and they’re home to more than 20 of Australia’s pioneer in Proptech. So a special thank you to Samantha Anderson, Stone & Chalk, for making today happen. Thank you as well to the Proptech Association of Australia, and thank you to all our panellists, Simon Fonteyn, Liam Murray, Chris Hanley, and Stephen White.