Data in Construction

Data Governance in Real Estate & Construction: Ian Cameron

Episode Summary

As Real Estate and Construction generate more and more data, it is critical that we stand up the processes necessary to keep our data current, organized and useful. Ian Cameron has been a leading voice in promoting data governance in Real Estate and the entire building lifecycle, and shares his experience and perspectives on how data governance works and can be employed.

Episode Notes

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Episode Transcription

Ian Cameron

Hugh Seaton: Welcome to Data in Construction. I'm Hugh Seaton. Today, I'm here with Ian Cameron, chief innovation officer of OSCRE. Ian, welcome to the podcast. 

Ian Cameron: Thank you Hugh. I'm really looking forward to this. 

Hugh Seaton: Yeah. So I wanted to bring you on to talk about data governance, something I know that you've spoken and actually done some e-learning and generally had a lot of smart things to say about. Let's start, with the ground level, what does data governance mean to you? 

Ian Cameron: Okay. It has several flavors. And then in part, it depends on who you are as to which flavor you choose. But data governance goes in hand with the big movement towards being all things digital. And that includes things like data integration or systems integration.

Building the underpinnings for analytics, providing control mechanisms and managing risk around data. They're all tied to data governance. In the data world in general, not just in construction or real estate, but in the data world in general, data governance has been getting a tremendous amount of focus, as a means of reducing risk, of improving the way that data is managed, providing a foundation for connecting technical and data things to the business. And what's starting to happen out of this is that some new roles are emerging and it's also generally pulling folks with bit more of a business perspective on the construction world, into the data world.

And that brings a significant focus on skills. So the topic of data governance is actually pushing organizations to get better at the way they handle data. Define things, establish a data strategy, establishing an internal practices to be able to manage data correctly, but where it becomes especially important and very powerful is when there are collaborations involved or information has to be exchanged between parties and I'll just give you a quick illustration, the relationship between the design stage in a construction project and the bidding and the building and the operating that asked that lifecycle, going down that line between those various stakeholders and the stage of the process, that means that the data has to have the capacity to move between stakeholders, in between systems and from upstream to downstream. 

Data governance is a mechanism for putting some controls around that, some definitions, uh, and a better understanding of how to connect those systems to make that life cycle come alive. And the construction industry has been needing and wanting that for the longest time and data governance while on the surface of things can sound a bit like a policy or something that somebody else does. Data governance is actually everybody's job including those that don't think they have a data role, because they do. 

So at least I could start there just to get a general sense of it. Then maybe we can unpick it as we go.

Hugh Seaton: Well, let's do that actually. So when we think about the word governance implies that you are managing or governing something. What is often the beginning of that? Like, let's assume that you have an entity, whether it's a contractor or it's a building owner, or it's a collection of the above that have not been governing their data for lack of a better way of saying it, or what do they do? What are they doing to, to enact data governance? 

Ian Cameron: All right. I'm going to start from the perspective of the owner of the property that's being built. And that could be, let's say an investment company that is going to put a new building on the market and to lease it out, or it could be an occupier that's having a building built to house its employees. Both of those are common situations where this is going to come up. So if we start from that perspective, what it means is that when a building is being designed and built, and then finally handed off to me as an owner operator or an occupier, there's going to be a handover moment when information is being passed off.

And I don't just mean drawings. I mean, let's say as-built costs. And what that cost break down is. So for example, I'm going to want to know how much money I spent on let's say building equipment or interior. Or, um, base building costs because the are depreciated differently in my financial systems. So I need the cost data coming from the contractor to me and therefore the contract or system has to be able to find a way to export that to me.

And I need to be able to pick it up at my end. There's a very simple one-to-one data flow. That's very, very common in the industry, but extremely difficult to pull. Simply because most construction management software platforms do an incredible job at scoping and managing the construction process, but not necessarily thinking about other dependencies.

For a client or other service providers on that same information. And that's data governance is a mechanism by which it shows the way to common understanding of what the different types of data are, how it's going to be handled. What level of data quality is associated with that. And, and here's how the, the, you take that whole end user or customer perspective and turn it on the.

The other way around and just focus on, let's say the contractors, I think contractors are probably finding that there's a greater demand for more data to be given to their customers. And therefore they have to think about their own data strategy, their own internal practices to make sure that data is accurate and available and transmissible. And what that's causing in many cases is that the contractors are having to figure out what their data strategy is and what their approach to data governance will be. And that's a whole new thing. In part, because historically the whole construction industry, while very focused on specifications and delivery and contracts have not been as diligent, thinking about a forward looking view of what their data strategy ought to be.

Data governance is one of those principles that I think the contractors are going to find that the customers are much more driven towards. Better management of data, lower risk, better quality and easier connections than ever before. So it's causing the construction industry to rethink the way that data is being used in individual organizations and also between them.

Hugh Seaton: And how does data governance or a data governance perspective change how data is produced? 

Ian Cameron: Two or three things and we'll just make this really pragmatic. One of the biggest stumbling blocks in being able to share information is that there's a lack of standards as to what things mean. And one of the reasons that OSCRE is thrilled about our collaboration with CSI is the fact that you're a standards organization too.

And so, one of the first things to do is to look at your current systems, your current data, data models, I'm putting a new term onto the table. A data model, even a master data model, a master data model is a set of data definitions, that are common across the organization that also potentially can be inserted by reference into contracts for data management services that come with other services. So for example, a construction contract or construction contracts may begin to move to the side or the direction that calls for data to be transmitted along with, as builts and other kind of final deliverables in the project.

And that's fairly new. So data governance, the early stages to get data governance allows you to put more rigor around how the data is defined, structured, managed, curated. If you want to use a current term. To ensure that that quality is there and the accuracy. 

So the early stages of data governance are all about better controls, better use of standards. Interoperability is another term that you may start to hear more often, and that relates to the degree to which your data and your systems can inter operate, then integrate with other systems with other business partners. 

So the first stages in data governance is to focus on two things. One is what's the current state of your data management practices. And then, where are the places where you might be able to improve those things, and then start to put a plan for improvement in downstream. 

And I'll finish with the comment here with there's some really good frameworks for assessing where you are in terms of data governance maturity, and I'd strongly recommend a couple of templates that are frameworks that are really good for assessing where you are and figuring out where you want to go. One of them is called the DM Book, the data management body of knowledge. 

Another is a tool that comes out of Stanford university around data governance maturity. And if any of your listeners are inclined, I'd definitely a recommend going to have a look at both of those for some guidance as to what kinds of things to think about if you're just getting started with this journey.

Hugh Seaton: That's great. And I'll actually link those in the, show notes. 

Ian Cameron: Good. 

Hugh Seaton: So, something you said is really interesting and that is that that owners are beginning to put some of this or specify some of this in contracts. How much are you seeing that? And are you really seeing a big change or is it a lot of very sophisticated owners have been doing stuff like this for a while? And this is just another flavor of them being good at what they do. 

Ian Cameron: Yeah. The more sophisticated ones have been doing this for a while and it is new and it's slowly building momentum because for our industry, it's a bit of a leap. And it takes a mindset shift. And I would say that we're not at the stage where construction contracts have gone as deep as they will in defining data management requirements.

But it's definitely going in that direction. One of the reasons for that is that the customer is becoming much more savvy about this because they are under pressure to ensure that they've got data quality, as part of their system for making decisions or running analytics.

But they're dependent on data coming from a whole slew of other sources, including the contractors. So the customer has to have confidence that the data coming out of a contractor is the right stuff. And ultimately that's probably going to end up in contracts much more often than it is today. 

Hugh Seaton: Yeah. That makes sense. And we didn't define OSCRE as well as I might have, OSCRE's a multinational organization focused on real estate. So your perspective is one of the reasons we're talking about from the owner's perspective. Are you seeing that from the owner, from the tenant perspective that ESG and specifically kind of environmental impact is one of the reasons why people are thinking about data more than maybe they were before. 

Ian Cameron: There are other reasons that the interest in data has escalated, but that's definitely one of them. And I'll just touch on that then a couple of others.

So ESG is a, it's a high priority item for OSCRE in part, because over the last 20 years, we've developed data standards that include the environmental side, but coming from other sources, such as, just leasing or property management purposes, but in the end, it's the same data. So we're looking into more specifically how to standardize data for ESG, not just reporting, but ESG use or certainly the environmental side, but the S and the G are also becoming much, much more important.

I know you didn't necessarily ask me the question, but this is where the data governance piece does actually come back in. If you were to have a look at, for example, the GRESB reporting that many organizations have gone to that, including on the environmental stuff. That's actually part of the history of the source of, of GRESB, for example, the green building realm.

But the long-term answer to trying to improve your ability to manage the environmental comes from the G the governance, in that, that's where the practices sit to ensure that the data being used to assess where you are on the E comes from data governance practices. Ultimately that's also where if there are needs to establish goals for improvement in the way that the environmental or sustainability is handled, that's also going to come from the governance side, because that's all about how you improve things.

So our belief is that the governance side is going to become extraordinarily important in the next few years, to help organizations not only understand ESG and how to implement the reporting and so on, but also how to improve over time since that's all about improving business practices and the like, and managing that data more effectively.

We are very interested in ESG. We are definitely a long way down the road already on the environmental, but we are very specifically focusing on the G part of ESG. 

Hugh Seaton: That makes a lot of sense. And obviously having data makes governance of other things, possible in some cases.

Ian Cameron: Right.

Hugh Seaton: Ian you'd hinted at some other reasons why governance is, is increasingly being looked at... what are some other reasons. 

Ian Cameron: One of the things about, those sources that I described to you is that the first time anybody goes to have a look at them, they can be, they can seem pretty daunting. But in reality they're good guides to be thinking about what kinds of skills do I actually need inside my organization to be able to not only help ourselves, but help our business partners and our customers. So for me, one of the main reasons to focus on data governance practices is to help build the skills in these organizations to deal with the tidal wave of demand that's coming around better data.

And one of the risks in being able to get that better data is not having the people with the understanding and the skills in the organization. Additionally, The question becomes well, how do I build those skills? Do I go find them somewhere, do I hire somebody, do I upskill? And the interesting thing is that the real estate industry is no different than any other industry on this topic.

The demand for people with data and data governance skills is skyrocketing. And in the end it may actually turn out that even once you get started on a journey, you're going to find it difficult to find the people. So training and education and up-skilling is definitely one of the roles needed to build more effective data governance.

And, this was not intended to promote OSCRE, but that's one of the reasons that we've gone down the education lines and training lines to be able to help people understand what skills are needed, to be more effective around data governance and how to build them and set a path for improving those over time.

That's also why that ties back into the G and the S, the ESG. The other big payoff here is to establish some new roles. So yes, building skills, but also establishing new roles in an organization and one term that kind of covers all of that is a data stewardship. So there's another term that's popped up in this conversation Hugh.

What's starting to happen is that the lines between, let's say a business view of this topic and a technology or data view of this topic is that data stewards being a new role that comes out of the data governance field, calls for an organization to be on top of, of its business practices its business processes and how data plays a role in those processes and therefore data ownership and process ownership becomes important.

And that's where the business, IT kind of interface kind of is built. So I'm talking about the third reason then that data governance has taken on a bigger role then. It's around defining what that data stewardship looks like and, and helping evolve those new capabilities in an organization specifically around this one role data stewardship.

Hugh Seaton: That's a pretty good term to add. So data stewardship... you hear it. And it's nice to define it a little and to make some of this concrete as well as really you're talking about ensuring that the origination of data, whether it's a daily report or it's a maintenance log or whatever it is, is done in a way that is, is standard and uniform. So you can aggregate it all together, but then keeping an eye on what happens to that data over the course of its life cycle. Has it been aggregated? Has it been added? Has it been transformed in any way? So that when people are looking at end data, someone has paid attention to what's happened to that data all the way to the point where it's being displayed or it's put into a model or whatever.

So I think it's really, really exciting and important to talk about the fact that ultimately someone has to be responsible for not just making data and not just storing data and not just auditing data, but paying attention to it, you know, as their job, which is really what you're describing as a data steward. Right? 

Ian Cameron: That's right. Sometimes it's a piece of a job. Or it's a whole job. Yeah. But it's definitely on the increase.

Hugh Seaton: I had some other folks on earlier, and they used the word hats, and I like that ideas that it becomes a hat that somebody puts on because not every, not every organization can hire a full-time data steward, at least not yet.

So it becomes somebody a hat they wear one day a week, or whatever it needs to be. But even so they're the responsible party, which I think is the point 

Ian Cameron: Hugh I'm actually going to try something with you. I'm actually going to take on the moderator hat for a minute and ask you this question, but it's kind of a leading question.

One of the big gaps in the industry that data governance and data strategy is trying to solve is the interface let's say between the design community and the construction community, and then between construction and let's say management and operations and maintenance or facilities management.

So there are three big baskets right there. My sense is that each one of those types of stakeholder have their own issues to deal with. "Thank you very much. Why should I be thinking about solving somebody else's problem? But in the end there's huge benefit from being able to pull that data from one to another.

What's your, what, what are you seeing, let's say in the design community relative to data versus contractors or construction companies versus let's see F & M and OM. 

Hugh Seaton: Yeah. I think that you put your finger on what is happening. And that is, I think that there is a within silo maturing and sophistication happening before people go across silos.

That isn't always true, and sometimes there are software vendors, for example, that make a point of going from one to the other. And they'll kind of take on some of the data governance role because it's all within their system and it's easier that way. Across silos I don't see happening design into construction quite as much as I see construction into operations, partly because, there is something already in the RFI change order process that is a, an established way of communicating back and forth across the design to construction silos. Right. 

And it may not be perfect, no one would argue that it is, but it exists. Whereas a two way communication between contractors and owners after commissioning is, you know, it attenuates to say the least. So I think that the need to make that moment of handover as complete and well done as possible is driving a different kind of governance or different kinds of standards and, or processes that make up for a lack of governance, if that makes sense. So there are handover software companies that really do honestly as much services at certain points as they do provide software, because they're making up for the fact that there wasn't governance and you're calling this a tomato, I'm calling that a tomato, and that happens all over the everything you talked about before.

Right? So I think, I think that, that in the last few years though, there's really been a lot of investment and push to make the handover process increasingly well-run, it is still a long way to go, but it's recognized in a way that maybe five years ago it wasn't. so I think that each of the silos are themselves becoming internally better and better so that they have the opportunity and the frameworks in place to, to cross the silos more effectively.

But I I'd be honest. I think it's early in that process. 

Ian Cameron: That seems to make sense, but what's interesting, at OSCRE, we have a couple of standards projects, one completed and one in the works at the moment. And what I mean by standards projects is that much, like, I think CSI may have done over the years that we convene stakeholders in the industry that have a common problem who are interested in solving it through developing a standard for a particular role, let's say, the term in the data world is a use case. So if you're building like glossary out of this conversation, Hugh, that's another one is a use case and a use case... you've already mentioned one, is handing over data at the end of a construction about being complete. And we've just completed one in the housing sector in the UK called development hand, handover, and it is specifically about the data that a construction company or contractor would hand off to a client at the time that the project is being handed over.

So we have developed a development hand over data standard. And what comes with that is a business case and a process of how it works and when it happens. And I'm mentioning that simply because, as you called it out, that handover point is a huge risk problem, uh, and having a standard for development handover is extraordinarily important. So I'm glad you mentioned it because it's very current for us. 

Hugh Seaton: The good side of developing a standard is people have somewhere to go. They have something to start the hard part about the kind of modern software enabled world is it's harder to make a standard stick when there's enough players running around that they're not so much a competing standard as a competing way to do some of what a standard does just less effectively.

So it's great to see OSCRE pushing something with your kind of weight, which is, you know helpful. 

Ian Cameron: Yeah, good. And actually I have a second one that I wanted to point out and you mentioned earlier between the design and the construction stages, and those of your listeners are familiar with or steeped in the BIM world.

There's a lot of action that we're seeing in BIM in, certainly in the UK we're monitoring what's happening in north America. Canada has tons of activity going on in this arena. But the reason I'm mentioning this is that building information modeling directly gives you the ability to do that handover if it's structured right at the beginning.

So the other thing that we're working on at the moment, are data exchange standards around bIM, that means collaboration with other organizations. And that's where our working relationship with you came, Hugh, is through CSI and OSCRE collaborating to make sure that at least we're talking from a data standpoint.

Well, the same things coming in the BIM world that it's been out there for a good long time with various degrees of adoption, if you will. But the game has changed in the last 18 to 24 months for two or three reasons. One is that there's better understanding of the whole data challenge and how to solve it in general.

But, if you take an another example coming out of the UK, The housing industry was dramatically shaken up recently because of a major fire that took place at a place called Grenfell in London. And it was tragic. And what it has caused to happen is catching a potential problem with a defect further upstream, or to at least understand what the current risk is based on data that would be available during the design process and where this is going is around what's referred to as the golden thread, which is pulling that thread of data all the way from up in the design realm, down through construction, to operations. 

And an example of where that would be beneficial is if any major property owner was trying to figure out what the risk is, they need to know where some of those riskier building materials are.

The only way we're going to do that is if they go on asset register that identifies the specs for a particular... in this particular case, it was to do with the cladding on the building. The only way they're going to know about that information is if they've got the information initially, or the data from the construction side to know that they are actually at risk.

So that's caused a significant... sent a ripple through the construction industry in the UK. And so what's starting to happen there is that the BIM world are talking to their partners downstream and to the government, and to the investors in housing about how to create this golden thread of data, which is in its simplest terms is a de facto implementation of an asset life cycle view.

And that's something that we've talked a lot about before Hugh is, and that's where this is going. 

Hugh Seaton: And this is a great way to kind of bring it all home, if you're thinking about the incredible complexity of building a building of any size, if you don't have data governance policies and practices in place, You're not going to be able to keep track of the changes and reality of, of what happens between, you know, a bright spark of an idea in a developer's eye through to commissioning through, to operations.

There's just so many things change and get tweaked or get replaced or whatever it might be. And I think that's the point of this, this golden thread is the idea that you're going to be able to have the data not only retained from the beginning, but as it changes, it gets augmented gets worked with, gets replaced.

You have a record of it all the way through, that isn't overwhelming, point one, and point two is you can trust what you're looking at. I mean I think that's the core here, right. Is being able to trust that there's a process that produced the data you're looking at, that you can believe in as opposed to being a starting point, but we got to go spend two weeks investigating to make sure, you know, find the parts that aren't wrong.

Ian Cameron: Right. There's one feature of this conversation I just want to shine the light on more specifically, and that is how you get data from one system to another. That can also be, how can I get data from an architect to a contractor, let's say. Especially when each of those organizations have probably invested tons of money in the software system they're using today.

And the last thing they want to hear as well, you've got to make changes to that. Well, the cool thing about data exchange standards is you don't actually need to change the underlying system. All you really need to do is to make sure it can go from one to the other. And it may seem overly simplistic, but the kinds of data standards that OSCRE's developing are more focused on moving it from A to B, than ensuring that A is internally consistent with the standard, and B is also internally consistent with a standard. It just needs to be able to share it from one to the other. And the standards are set up in such a way that it allows for that connection between the systems, without causing the software vendors, a heartache or a customer to think, well, you know, I spent all this money do I need to go change things? 

Well, no. What you really need to do is to focus on the connections, which completely simplifies the integration problem or the source.

Hugh Seaton: It really does. Cause you're, you're saying to people, you don't have to change what you do. You just have to change the way you transmit it to someone else.

Ian Cameron: That's right. And the interesting thing about that is that is a huge, you could hear the huge sigh of relief coming from the software side of the industry to say, look, we've invested in tremendous functionality and we've got our own data model. We just can't change that. We'll actually in the end there's no need to. The real need is to find a way to develop let's say a transmission mechanism and an API, some of your listeners may have heard of an API is basically a connector. But what we're starting to see more and more is that these APIs are being built on OSCRE standards. And the cool thing about it is if you're shipping data to two different systems, you don't need to build two connections. You only need to build one. And then all of those systems tap into it. And so I'm justifiably trying to make a complex topic, much simpler because that's what it boils down to. 

Hugh Seaton: Well, Ian, this has been fantastic. I want to end with where people can find out more. So you've been cautious about talking up OSCRE too much, but I'll say there's some fantastic resources on, on OSCRE. One of which is, a course, I believe a certification on data governance. That's right. It's done real estate, but nevertheless, a lot of the topics in the same.

But you got a lot more going on there. You want to just talk a little bit about that and where people can find out more? 

Ian Cameron: Sure. Thanks. is our website. And, there's a couple of things that you can find out more about there. One are the education programs, which includes data governance, as you said, in a variety of formats, there's an online... And the reason that we're providing a variety of formats is that people learn differently or they have different objectives. So for example, This conversation that you and I are having from the standpoint of learning this stuff, it's not just an individual taking a course, which we've set up. In my mind, the best formats to take on a training education is in a team environment.

So if you go to do data governance, why don't you do it with the whole team at the same time? And we've had a good number of organizations have sent teams of, I don't know, a dozen to 20, through the same program early on so that gets them all to the starting line at the same time.

So we've got some programs for that. The other thing that you can pick up from that website is a bit of an understanding of what the data modeling and data standards are all about because ultimately that does play a role. So that's available. 

And I suppose finally, we have a monthly events called innovation forums. We're talking about data governance and other things, and I know you have to got some excellent programs yourself. Hugh. But where it comes down is we want to, we're trying to keep the dialogue as high and as consistent as we can. So that's where we have the webinars kinds of stuff, but we're very much committed to figuring out how best to help an organization learn how to do this.

A learning organization is our banner term for focusing on that. How does an organization actually learn to improve how it does so that the changes stick. So you'll be hearing more from us about learning organizations, tied to this whole data conundrum, in the months ahead. 

Hugh Seaton: Fantastic. Well, Ian, thank you for being on the podcast and talking through data governance and other topics.

Ian Cameron: Good. You're very welcome. It's always a pleasure, Hugh.