Contents
Based out of New York, Dr. Davis is a senior researcher at Hassell, focusing on the relationship between people, space, and design technology. Prior to joining Hassell, Dr. Davis was the Director of Research at WeWork, and a research assistant for Antoni Gaudí’s Sagrada Família. He originally studied architecture in New Zealand and later did a PhD in computational design at RMIT University in Australia. Daniel is a regular columnist for Architect Magazine and his research has appeared in a variety of publications including Wired, Fast Company, and the Harvard Business Review.
In this interview, we discuss a wide range of topics include the role of data in company culture, what can firms do to embrace a data-driven mindset early on, how the team is structured at Hassell, and lessons learned throughout his career.
George Valdes: So I kind of want to start off by talking about your current role. I should have prefaced that, but basically it would be helpful to kind of walk us through a little bit of your career trajectory, and maybe talk a little bit about your current work.
Daniel Davis: Yeah. Yeah. See, I guess the trajectory is that I studied architecture in New Zealand and, went on to do a PhD in Australia, worked on La Sagrada Familia with Mark Burry there, and then, after that I moved to America and I worked for CASE, which was a consultancy ran by Dave Fano, Steve Sanderson, and Fed Negro and kind of two years into being there CASE got acquired by WeWork and I joined WeWork. Worked with you and whole bunch of other like, really interesting people for about four years, kind of rethinking the way that spaces constructed and designed at WeWork. Wheels kind of fell off that a little bit and about a year ago, I left and joined Hassell, and Hassell's an architecture firm that's whole around the world I'm doing a lot of. I was really attracted to them for the workplace projects they do. Really advanced, sophisticated kind of projects but they also do a lot of kind of urban design work and airports and all that kind of stuff. And so at Hassell, I joined them as a senior researcher and, we're working to kind of better understand the performance of projects and think through how to kind of get more performance out of the things that we're designing.
Research Team's Organization Structure
George Valdes: That's great. And how, how big is the research team right now?
Daniel Davis: The team is pretty small. So it's about two people on the research team. And then we have a strategy team, that's probably about a dozen people and we work with external partners for the rest of the research.
George Valdes: Oh, that's cool, and so the way that your org is structured, is it that you're working much more closely with the strategy team or do you work on the, on per project basis?
Daniel Davis: So the strategy team tends to work on individual projects and the research team tends to look more broadly across collections of projects, what kind of themes or topics that may be of interest to the practice.
A Culture of Data
GV: Very cool. One of the things that I'm very much interested in chatting with you is this, but before we turned the cameras on, we were talking a little bit about the culture of data and, for context, you know, a lot of our, you know, at Monograph, we serve a lot of businesses that are mostly, you know, between a sole practitioner, all the way to a 75 person firm and within that, right, there's actually, you could look at it as like, those businesses look very different at even just a very minor step change.
So, a five person firm looks very different from a six person firm, just because even just adding one person changes the dynamic and that we've been just been noticing that that kind of breaks down as you scale up.
So even within that, there's like five different types of size firms and I'm very curious about how, you know, a lot of your work has been focused on working with larger companies, that might already be looking at data from a very specific lens, like maybe namely project-based.
I'm curious, what are your thoughts about how firms at all scales can maybe start to think about data, both from like actually how it could help the business, to also how do you instill, like maybe even a culture of data.
DD: Yeah. So, yeah, I think you're right in that, like there's a difference in scale there, between, say how small firms approach it and how large firms approach it.
So for large firms, there's almost no question that you gotta be going up against other companies that invested a lot in that kind of technology and that a really sophisticated in their approach and that you're going to have to toe the line with them and make them where they are.
The smaller companies, that I think, it's a more kind of leery pitcher, you know, like if you're a sole practitioner or your firm has five people and you went a lot of your work through kind of personal relationships and doing good work in your community, like, maybe some of the stuff doesn't actually matter that much to you, that, there's other ways to kind of improve your firm and I think there is a danger with a lot of this that, people kind of save the shiny, exciting new piece of technology, over invest in it and don't get the value out of it because realistically, they were just like other more interesting and more impactful things that they could do.
That said, though, I think there's, quite a few examples of small firms and the industry that have been really successful in their approach to data. So I think if firms like, The Living in New York, probably best known for winning the MoMA PS1 competition, but, they later got acquired by Autodesk, but still kind of do their own kind of independent work. And they've done a number of projects that are really like leading edge and how they approach data.
So they did a project, Princeton University, they made kind of like a house for a robot and they used machine learning and computer vision to understand that grain and wood and then kind of sandblasted the wood based on the material. But I think like those are two kinds of like, extremes, right, like going all the way in and everyone working there is like an absolute killer at that kind of stuff and I think for firms that are maybe in between, it's a more kind of tricky thing to work out, but I think for those firms that, in that kind of in between state, I think there are kind of ways, kind of entry points in that.
They don't necessarily need to be like complex machine learning techniques. It could be, how they approach marketing, maybe they use more analytics in that process, or it could be, how they manage the firm or how they manage HR, that has more kind of data applied to it, yeah we can go into that, but
George Valdes: Yeah, that's interesting, you bring up the living and it's like for them, it is their practice. Like you cannot divorce the two, they just don't work without thinking about how data informs their project. I mean, it's probably safe to say that almost everything they do starts with like a point in space, right, and you build up from that right there.
All they're doing is managing data to construct really interesting spaces, versus maybe a firm that's really much more interested in, you know, developing residential projects, right, where their client base is just their own, how their personal interest maps over to their work is just very, very different.
And, I think it's an interesting contrast, but, and I definitely agree with you that even though it's a smaller firm or a firm that doesn't look at data the way that like The Living does, can still even use a spreadsheet, right, or at a very basic level to track market or whether that's like, how many people did we reach out to this week, how many meetings were we able to book.
It seems very reductive, but even that is, that level of visibility can help improve a business moving forward. I think we talked a little bit also about this idea, like potentially there's maybe three different legs to the stool of data within a firm. I'm sure there might be more, but, you know, be curious about your reaction to this idea that like, there there's like pipeline data, how are we managing the work that comes in, cause you know, if you unpack a business, it's ultimately an equation. And so it's like inputs and outputs. How many come in, how many projects are able to be worked on, how many of them close, right.
So all that pipeline data would capture that, then it would go into like project level data, which is more to say it could be either performance based on like, how are we performing as a team, or it could even be like some of the work that, a lot of firms are doing, which is like looking at how data could impact design and then potentially even like talent, like how do you actually design careers for your team members, and like, how does data inform their career growth is another kind of like, I'm curious like how, what have you seen across your career and what are some of the, maybe pitfalls, that people should look out for when they think about that framework?
Daniel Davis: No, I think that's a really useful way of thinking about it, cause I think it is designers and architects, we often think about these technologies as applying just to the design process and it's true of like daters trip, like computation design, whole bunch of other things that we put so much love and emphasis, and what we're doing in the design process. We often don't put the same amount of attention into the kind of overall process of running a business, and in many cases, the low hanging fruit exists outside of the design process and those places. So in areas like marketing or an egg shell, like this products that you can buy off the shelf, like culture amp and stuff like that, that have pretty sophisticated data analysis tools and pipelines. You don't really need to know that much about what's going on to use them and benefit from them and many cases, I think, those are probably easier ways into this, then necessarily going onto a project and doing a whole bunch of kind of analysis and GIS work and whatever to analyze it. Yeah.
George Valdes: Yeah. Is there, at the kind of scale that you operate in, what are the biggest challenges you face when it comes to actually just even either collecting data or what are the actual questions that people should even be asking themselves before they start even thinking about data?
Daniel Davis: Yeah. I think one of the questions that I always ask is like, realistically what's going to change if you invest in this collection of data and you do that project, and this happens time and time again, when you're a researcher, someone will ask you to go and do research on whatever it is. And they're not really, they're asking you to do the research, they just want you to come up with the right answer that supports their view and validates what they were going to do anyway, in that case, it's like, why are you even like fathering, doing this research and gathering this data or doing the analysis because your come was kind of preordained and you're just like post rationalizing it basically. So I think, one of the questions that I ask is like, if you were to do this research, if you were to gather this data, like realistically, what would you do as a firm with that, that you wouldn't be doing already, and like, how would things change for the better or for the worst because of that and then I think once you have that kind of in place, some of the major challenges, I think, the technical side of it actually isn't that hard. Like, I mean, all these tools have been kind of established, It has been people that have kind of worked through all the kind of difficult parts of doing the technical stuff. I think the main challenge is really cultural, that, even if you have buy in and support to do something, it's for many architects are really unfamiliar kind of process and something that they're not necessarily comfortable with and there's a lot of kind of educating and, championing and kind of encouraging to get that culture's developed where people feel more comfortable, engage with it and, being a part of it.
George Valdes: Hmm. What have you seen that as helped, in basically with that internal educational process, is it, you know, identifying the people that, like I instinctually, I just think it might be involved in identifying people that are more naturally inclined to care about that. And so you kind of build rapport with those types of champions within the company that can help, maybe either lead initiatives or help other people also come to see the light in some way. What have you seen has been very helpful?
Daniel Davis: Yeah, I think that's a really successful tactic that within an organization, you can kind of place people on a spectrum. And there's some people that are just going to be so anti what you're doing that has maybe been like with really kind of working with them and there's some people that are going to be real champions of what you're doing and you should be kind of identifying those groups of people and cultivating that relationship with them and then I think beyond that, I think for a lot of people, it's hard to understand some of these things in the abstract. Like, I think I've seen a lot of these initiatives that I've seen sort of full over or fail have been when people have gone and kind of guns blazing, hire a team of like 10 people to go and do this radical transformation and it kinda don't get anywhere because they've invested so much capital in doing this one thing and It doesn't quite find the traction or the audience that it needs and a lot more of the kind of successful efforts that have seen in that have been more kind of gorilla and grassroots with teams. We'll do like one or two things that are like small scale and interesting, and gets the attention of a couple of people and builds kind of interest and then kind of snowballs from that and I think, my experience, that's a much more successful technique than trying to just boil the ocean with some of this stuff.
George Valdes: Yeah, yeah, to use your, your water metaphor, ocean metaphor. I think of it as like trying to steer a large ship, on a dime and the amount of effort that it takes to do that, it has to almost come from the very very top of an organization in some ways to kind of really, like go all in on that, right. It's like, in the tech world, it would be similar to like, even though Facebook's not so popular today, but it would be like equivalent of Mark Zuckerberg telling the entire company, like we're going to drop everything on desktop and just focus on mobile and all the engineers will not have to learn how to like, build for mobile apps. And that's like a company wide shift that takes a lot of courage to do it in some way, but also a lot of beliefs to do that. Yeah
Daniel Davis: Yeah.
George Valdes: Yeah, at the scale that you're at, that, it's, you know, you kind of do that or you have to do it in this way where it's a girl.
Daniel Davis: Yeah. I feel like even with like support from the top, there's always going to people in the middle that you'll send it to kind of win over and convince, because they're facing their own kind of precious day to day, right, that, different than kind of the priorities that you are dealing with and even if they're getting pressure from the top to kind of, fall in line with something, often they won't, because they're not getting judged on it, or it's not kind of what that prioritizing. So I think you need both of those things at once to really be successful in implementing some of these strategies.
George Valdes: What would you say is like, if someone wanted to bring on a team, like, let's say it's a company that doesn't have any researchers on board, and they are of the scale enough where it makes sense to do so, what would you say is the kind of maybe low hanging fruit initiative that they could think about tackling or the kind of maybe lying questions instead of just like a, it's not like "Hey do this project.", but more like how, you know, what could be a way in which they can actually start to introduce that into their culture?
Daniel Davis: Yeah. I think a little bit about like what data is already there, at the company, cause gathering new data and creating new data is always problematic and kind of time consuming and it's always going to kind of slow down a project. So I first like kind of do a stocktake of like what exists currently at the company, what's available to be kind of analyzed and understood and based on that, kind of finding some of those kind of low hanging fruit and my intuition is that most of that data probably won't reside in projects, but will be kind of adjacent to projects, whether it's like costing or whether it's, HR and resourcing. Yeah, and I feel like those are also kind of fields where, there are these kinds of existing tools that, people are probably more likely to easily kind of implement and take out.
George Valdes: Hmm. Have you seen it where, well, I mean, at WeWork, cause you and I overlap there and it was very interesting to see how transparent the company was to some degree about if data mean, I think many people had access to Tableau, or Looker, right to be able to parse whether it was like sales data or construction costs and that visibility, it feels like that actually can empower. I mean, I felt that kind of empowerment of being able to use that data to inform whatever initiative I was working on, without having to go and ask somebody to like, do that for me, or like pull a report from me or, or whatnot. So I'm curious, what are, the maybe pitfalls of doing that within an architecture practice, a place where that kind of can also happen, right, like a more traditional office and whether the potential pitfalls of doing so or not.
Yeah, it's probably with just, emphasize and just like how well set up we were, it's kind of data, infrastructure and pipeline was, like, a lot of that was, they found out who kind of came in with their patient of how to use data in the design process. But this also just like incredible kind of data teams and BIM teams that we worked at, worked through a lot of the kind of tactics with that. And the end result was that like, every BIM model was inside a huge database to anyone at the company could access and, you could query that database and ask it like, what's the largest meeting room I've ever built and I mean, it'll come back and like one second, right, and most architecture firms, if you went to them and asked them, like, what's the largest meeting, right, I just have no capacity to even kind of answer that question, which in some ways is insane because they spend so long entering data into raber, raber is this huge database, but that data is kind of thrown out at the end of the project, once you produce the construction drawings.
Daniel Davis: Yeah, I think there's potential for companies to kind of adopt that process, of kind of warehousing data, like WeWork had, but I also think there was a kind of a culture that we work with, there's a lot of people really fluent and using data, there were, courses that employees could go to kind of spend a week learning how to be better at analyzing data and asking questions and data. And I think that all kind of contributed to, the success of those initiatives that we were and I think doing one without the other potentially isn't going to be quite as successful.
George Valdes: Yeah. Yeah. They're the role of operations of like sales ops, rev ops, is one that was very critical, to enable at least on the sales side, the growth team, visibility into pipeline or visibility into, you know, like forecasting and revenue projections that didn't really, I think, without those teams, you don't really have the institutional knowledge to be able to do that effectively. Like you need a team that's just focused on how do we connect the data across the company operationally to make it efficient and effective, which actually might look very different from a traditional BIM team in general, right, it's just like, there needs to be the introduction of a new layer of just focusing completely on practice operations throughout the business. .
Daniel Davis: Yeah. I remember some of the conversations that WeWork, which is like, some of them was hated compensations like how do you measure like a square, but, and like your room,right, and like, trying to define that, which was a really key metric for a lot of projects, you know, like there's a kind of rigor to that, has to kind of access for that stuff to that.
George Valdes: Yeah. Yeah. It's the definitions are like what a room met, which we won't dive into today, but it was, it's interesting how, like, it was almost at a philosophical level of what it, what is it room, how do you define a room, that was, I remember some of those conversations were pretty funny, but I think, I think this, this notion of introducing, data-driven culture, at least one that's looking at and I guess my own perspective is that I don't think that the data is everything, righ, I think you brought up a very good point earlier, like somebody will ask you a question, wanting like, prompting you with the right response, like what they want the data to say, because it is, you know, you can craft data to tell the story that you need to but at least having that additional sensibility to,so data helps the organization run a more effectively on things. It gives more alignments, like there's less ambiguity when it comes to discussions about certain things, obviously rooms is one that that might be more controversial. But if there wouldn't be this kind of new way of looking at a firm, organizing a firm , do you know of other examples of other firms that are kind of approaching this problem in a different way, similar to Hassle looking at research this way?
Daniel Davis: Yeah, I think maybe like another way of kind of framing that, a thank you about that, is just like hot clients, like what's the kind of environment that operating with it and how are they thinking about this because a lot of projects are laid by the client, right, and getting into a world where historically clients didn't necessarily know a lot about how they buildings were performing and we're getting to a place where that getting a lot of data back from their projects, whether it's from kind of census embedded within, building elements or kind of, objects placed within the space, whether it's through kind of sieving and cameras and stuff like that, like, clients are getting really sophisticated themselves and how the thinking about the performance of the real estate that creating and I think that that in itself has kind of create an environment where it's going to be an expectation tactics, to be able to kind of talk about their projects, not just in terms of the kind of creative and, mashing of aspects of the project, which I think still clients are going to want because if clients know what they want, they don't need an architect come in and challenge them and to, kind of shake things up. But they're also gonna want to be there, to see architects be able to kind of justify design decisions through data and three evidence and I think that kind of atmosphere where the client has that kind of understanding and that sophistication is gonna push more kind of the architecture firm itself to be good at doing that and it'll be a core competency, I think, for a number of kind of architecture patterns.
George Valdes: Yeah, and it's actually thinking a little bit about, it's like this, this idea of the relationship between data and space is not a very, necessarily a new idea either. I think quantifying spaces is part of the history of architecture in many ways, at least from like the postwar, right, like thinking about whether it's like, proxemics where you're trying to develop a way in which to look at the distances between people, then like some of it's sort of like fluffy pseudoscience, but there is a history of trying to understand how spaces function such to justify design decisions and what's interesting is that, it kind of has evolved to a certain point. But like you mentioned, the clients are just getting much more savvy about how it actually impacts, what they're most concerned about, which is the maintenance of the thing after it gets built, right, what happens after all of that, after the design work happens, the hand off happens, they're the ones that are left with having to unpack and understand the actual performance of the thing itself. So as architects, transition and start to develop more intelligence around how to encroaching that, I guess the hope is that, you know, they can become better risk managers in some regards with their clients.
Daniel Davis: And probably like, the part of the story that we're not telling at the moment as well, is that like there's groups outside of the traditional kind of occupation practice that are entering into that territory and that think about that, so, a really kind of prominent example would be Sidewalk Labs, which is a subsidiary of Alphabet, which is the parent company of Google, and they were doing that kind of, waterfront project in Toronto, which recently kind of, didn't go ahead, but you can see in the way that kind of Google is thinking about that, what Sidewalk Labs were thinking about that, a lot of real sophistication and, how they were going to gather data out of that project and feed that data back, both into the design process and also into the way that kind of people live within those projects and there's obviously a lot of, kind of, political tension there about whether that kind of gone too far and some of their ambitions around that project. But, I think that's also kind of some of the backdrop here is that like, if firms aren't going to be the ones that do it, then companies like Google are coming into this space and I kind of be the ones that really get there.
George Valdes: Yeah. I remember, shortly after I grew up, around the same time that, I look my last year in grad school, just hearing things like, Oh, McKinsey's deciding, it was like moving to designing urban plans for towns in Africa and whatnot, and just the ways in which other adjacent industries, right that just start to see the opportunity in this industry of like the things that either architecture firms are not necessarily tackling or that they might be more risk averse to tackle, these other entrance are just coming in saying, well, actually, like that can be part of our like wheelhouse and that can be part of our core competency because, you know, we already have the relationship with the buyer, you know, the executive team at a company, why couldn't we go and pitch urban design, or why can't we go pitch something else, which is also, you know, I think, this is going back to the culture because I think that part's so important, it's like, it's either the culture of firms starts to change and such that they look at data very intently, or, which could happen, right, I mean, as younger generations of people start to go into the, that grew up with data, meaning like Instagram, if you have an account as a, let's say you were an influencer in undergrad, selling design objects through your Instagram account, while it's being an architecture student, you probably got to see a lot of dashboards it's along the way and like, started to look at your world through the lens of analytics and causing effect and doing experiments , so that will naturally mean that once that generation comes up and graduates, they are much more data savvy, right, and they're going to either ask of that from the companies that they want to work with, or just start fresh and rethink like entire new business models, just based on the kind of culture that they've grown up with. But I guess the big, the big challenges today, how do you do that today? How can you impact that change today?
Daniel Davis: Yeah, no, I think, it's definitely gonna be a challenge for firms and certainly I think like large firms kind of have an advantage here, where this kind of a scale to them, that a lot of this makes sense, where you can kind of put resources aside to look at some of these things. We have a lot of the data on hand to do this and I think, you're already saying a number of the kind of large firms. I actually do some pretty cool and interesting things in the space, and yeah, I think that kind of question for you smaller or medium sized spends, is whether you go along with that or do you kind of say against that and kind of positioning yourself as something outside of that as a point of differentiation.
George Valdes: Hmm. That's a good point about like how you could position yourself almost, but are you saying like positioning yourself as an anti data firm or do you mean like, yeah, maybe kind of, how would you to play along with it, how would you position against that grain?
Daniel Davis: No, I'm not like, I think a pretty much any other industry has gone through this process already. So you can kind of look at it, what's happened there. So if you look at something like advertising, like Google is the dominant company in advertising because incredibly sophisticated in how they predict, what people are gonna click on webpages, there's a whole bunch of like small creative firms that are like, we don't give them pocket back any of that data, we're gonna like make an ad or make a brand for you, if that is authentically who you are and not driven by some kind of data. And the same is true in the passion load, right, like is, the dominant companies and passionate, like fast fashion companies that use a lot of data and forecasting to understand what's coming but then there's a whole kind of industry people that are like, who I am and this kind of authentic thing that I'm producing is the thing that's valuable and, kind of going against that grain, that analysis.
George Valdes: Yeah, that's a really good point , I mean, those are really good examples in the world of architecture. It would be just firms that resonate with a lifestyle. And so it's like, it's, it's almost harder to come across that in like commercial, like by typology, right. It's not like you can hire, the, I don't know, the Virgil Abloh, architecture to work on a hospital necessarily, just because there's a sort of misalignment in terms of what the, you know, it's a larger organization, much more stakeholders and so it's harder to sell this idea of like someone that's really about a lifestyle into, you know, designing a hospital, though I really would love to see if that happen. It's probably really bad for patient outcomes, but I'm sure it will be pretty well to reside there. But, I think it does make sense within the realm of residential, right, like you, if you build a strong enough brand, really that means that you have to think about marketing. You know, very distinctly and I think that is still, you know, that's a whole another can of worms about how architects market themselves and how can they put themselves in front of people. That is still not to say that they can use data to inform that, it just means that, yeah, it's like one avenue in which they can approach it, where it's like, it's not about the projects. We don't really care about data driven projects but we will look more at like, how are we reaching the audience that we want to reach with the kind of lifestyle that we're trying to sort of create environments for.
Daniel Davis: Yeah, yeah.
George Valdes: Yeah. The, was the other thing I was thinking about this when it came to like the cultural piece, that escapes me, but I think it would be really interesting to talk a little bit about the data pipeline. You mentioned a little bit about how it might be much more accessible for larger firms, like looking at like historical data. What have you seen as the kind of like the quick wins that someone could implement today to help understand like what should every firm be looking at if they have the resources to do so?
Daniel Davis: Yeah. I feel like the Holy grail, well, every family has post-occupancy data and I mean, we just, as an industry on great at doing that. For the most part, we construct projects, see them opens. We may talk to the clients, kind of, one off about how things going down the track, but you don't get a lot of good feedback about whether or not the things that we design group formed the way that we say or think they are. So I think, I mean, that's where I think a lot of the opportunity lies, these projects and these companies. But I also think it's a really hard nut to crack because there's a whole bunch of kind of different reasons why that doesn't happen currently. and each one of those is really difficult and challenging to sort of.
George Valdes: Yeah. Like one that comes to mind is contracts. ,How a lot of times what you're trying to do is get someone to agree to have data collected, to understand, like the potential value of what the design is offering. But even with that, I do wonder what kind of data is publicly available, that can help inform at least something. As an example, I remember just as a side project for myself, I was like looking at, developing, if this, then that using, if this then that to geo locate a range around a project so that if any picture was taken an Instagram geo located at a certain building, I would populate a spreadsheet with that information. It was very simple and the building I chose was VIA 57, by BIG, just to see, what are people even taking pictures of it. It's a very domestic stuff, just like friends, family, whatnot. But sometimes it was the view outside. Sometimes it's about like, Oh, I love this place. I love, look, check out my new apartment or whatnot, or like there's this kind of capturing or like the daily life, that's very fascinating, that can be helpful for a firm to understand, well, what is the day in the life of a project that we've actually done, what does that look like, do people even take pictures of the building itself, like, so I'm sure it's similar to that there's probably ways in which a firm could start to understand the impact, the design impact of what they've put out into the world.
Daniel Davis: Yeah, no, I think there is, some examples of kind of publicly available data like that and often not necessarily in the States, but definitely in Europe, like governments put together a really good datasets, that are really well organized, structured, related to kind of the built environment and, cities and some of that kind of gives a hint at how people are using space. But , I also think that a lot of what we want to know about projects isn't in there, and firms are gonna need to create and generate a lot of that data if they want to get to this place where they really understand the performance of what that designing.
George Valdes: Hmm. Have you come across any examples of where there have been successful implementations of a post occupancy, aside from like, you know, we work as a great example, but they're almost there because it's such a vertical business, soup to nuts, there's it can really kind of fall in line with this example, like they are the client but, are there any other examples of you've might've seen where there was a successful implementation of a post occupancy in a project and what that might, what outcomes that led to?
Daniel Davis: Yeah. I'd say like pretty much any vertically integrated company, like whether it's Disney or Starbucks, I mean, they have in house really sophisticated ways of kind of understanding and thinking about this and often that kind of the market leaders and doing a lot of this work, but they never talk about it because it's kind of a competitive advantage, to keep that wrapped up and I think, I mean, to be honest with you, there's not many examples that I can think of in the occupation industry that I look to as kind of North Stars and I think some of the more interesting and better examples of what's happening and the space exists kind of in the TIC WORLD where it's pretty common to, do usability studies, run analytics, AB test things and I think a lot of the techniques that they're using in that kind of realm, are applicable to what architects are thinking about as well.
George Valdes: Hmm. Have you thought about, or like has come across conversations about even just how, if a firm were to shift us or create a new line of revenue for the business, let's say, let's hypothesize that a firm really wanted to understand post-occupancy they could in theory, create a line of revenue that was about almost like a subscription service for a company where they basically are providing the core infrastructure, the software infrastructure, to be able to understand the project but then give value back, so whether that's to the, workplace experience teams that are probably part of a larger commercial, project, you know, a commercial client or, you know, it's likely that's where it would resonate the most, but have you even seen any instance of that where people experimenting there?
Daniel Davis: Yeah, there's some examples of them's trying that kind of model. And I, I mean, I think it's a really interesting model, because the way that architects traditionally operate is like the client comes to you with a problem when they decide that something's gone wrong enough to justify hiring an architect, to kind of deal with this and often the client isn't the best one to judge that because they're not an expert in that kind of situation and that, someone who has that kind of expertise is maybe better off to say where that kind of point or time has come. I think some of the challenges that other firms have faced when they've kind of gone into that model of like consulting after a project is that firms aren't really set up for, the way that they think about like revenue inside of business is often related to projects and so often that kind of service ends up becoming kind of business development for them and it's not necessarily a successful initiative that, is this kind of ongoing service offering and I think some of the more kind of interesting companies in that space aren't necessarily architecture firms, like a Comfy, it's like an app that people are using to. With the app, you can vote on the temperature in an office and it will kind of adjust the temperature and, to satisfy as many people as possible. I mean, it's a form of post occupancy evaluation, right, cause it's constantly polling people about whether or not their comfortable but then they're trying to sell you on occupational services after it. So I think their kind of business model is more aligned to doing that just because of the way they're structured, but it's not to say that I think, I mean, sometimes got to get to a place where they do that really well, but there aren't many examples that I'm aware of, of firms that have been really successful at that yet.
George Valdes: Yeah. It would seem like maybe one route would be in this, the institutional knowledge required to even run a business like that, which is also very different. Like, it goes back to the idea of steering the ship, where it's just such a directional change that you would have to really be all in and have to hire somebody that has experience running that type of business in order to be sort of be the general manager of it. Otherwise yeah, it's just like it, even the accounting structures inside of a firm wouldn't might not even know, might not be well suited to understand how to run that side. Yeah, I mean, I think this is, probably where there's going to just be continuous, I mean, there should be continuous innovation, but then the industry it's like figuring out what kind of new, either firms are anticipating sort of new lines of revenue that could emerge from their services or potentially investing in other companies that are doing this so that at least like there's collective upside. So if like, there was a company that was doing something transformative, you can get into the industry itself, could be supportive of that kind of change.
Daniel Davis: Yeah, I think it's like an interesting point, right? Cause I think a lot of grounds, I feel like the secret source is like, I don't know, like some script that Beth created or like the thing that creates them or makes them successful, isn't that thing that they think, and they waste a lot of time competing against one another, and building stuff in house that perhaps it'd be better shared through the industry and. the at time kind of focusing on the thing that actually matters, the most thing kind of differentiates them the most from other firms.
George Valdes: Yeah and that also brings to mind how often it is that, one thing that, almost like as a sort of advice in some ways about like building software in relation to, or just building these tools and whatnot is like, ultimately, the thing that's least thought about often is the maintenance of the thing that's been built and it might resonate with the industry in the sense that like architects in general deliberate thing, and then kind of the maintenance of it is more risk that they'd rather not think about but when it comes to actually building tools inside of a firm, like it does require, you know, things get outdated, new frameworks come in, a rhino gets updated and that breaks grasp opera or whatever, right, like whatever tools you're using, there's all these kind of the, the issue of maintenance is incredibly important for anything that's built. It does require an investment of perpetual investment in the thing that's built, especially for if you're being serious about it.
Daniel Davis: Yeah. They're curious for you guys, like how much do you have time, do you think you spend on like, creating new things, this is, supporting and maintaining, like the thing that you've already created.
George Valdes: For us, it's a constant series of trade offs, we have to, it is just constant prioritization, what things should we build today that is going to serve the most amount of value to the most number of users, both the ones that are here today and the ones that will be here in the future and you constantly have to recognize that ,you might not make everyone happy, on any given week, you know, there's always going to be someone that , you know, they might be missing a feature or there's, a, you know, something that they're coming across and like, we have to constantly build frameworks for ourselves. To say, well, how much of a priority is this thing in relation to other things that we could invest our time into? And I think that it is a very healthy model because I think, you know, it constantly forces us to keep top of mind of like, what is the thing, like, are we building the right thing that will add more value, which could be helpful inside of a firm to, out of all the things that we could be doing, is this the thing that's going to be, maybe the least amount of effort to build with the highest value, and constantly iterating on that process and checking our framework, to make it better and more inclusive of like, you know, all the various kinds of feedback that we get. right?
Daniel Davis: Yeah.
George Valdes: Its own thing, it's like, you will constantly be thinking about it.
Daniel Davis: Yeah, maybe to kind of bring it full circle, like, I think it also relates to like, what are they ask itself, right. Like, all that kind of agitation around revert and where that's going at the moment. Like, I mean, Autodesk are in a tough position. I kind of imagine what it's like being a product manager inside that company, where you have this product that's super successful, thousands of people are using it in production, the code base is old and you're trying to make these decisions about, like, people asking you to basically scrap everything and build something completely new. And at the same time, there's like a little feature that you need to kind of add in, and you're also trying to support everything else, like, I mean, it must be really hard to kind of navigate that, that kind of complexity there.
George Valdes: Yeah. I'm not as familiar with people at Autodesk, but I imagine that if the business is one that has been built over time through acquisitions to just buying other products, not necessarily creating its own parts internally, that is part of the internal struggle. It's like they know that they can invest it. They're actually very good at allocating capital to generate value, right, that's proven out to be the case, but it then presents opportunities for other companies to come in that are very customer focused customer centric, to come in and provide new solutions that the industry has been asking for for a very long time. I don't, you know, I'm sure they're aware of those things and, you know, I'm sure that a lot of very smart people that have, that are aware of that, but, you know, it kind of, is sort of the lane that you want to drive in and that's, that's kind of the lane they've chosen . So, I do want to open it up for questions for anyone out there, that wants to ask a question, I know we have a couple of people here. Let's see.
I think actually I can kind of jump in and ask you some questions that I have, part of a little lightning round. So what are your favorite tools to use right now?
Daniel Davis: Especially when really we spoke about this a little bit before the meeting, we're using teams internally as so, and I never thought I'd be saying this about a Microsoft product, but they absolutely fucking nailed it on that one. Like it is so well thought out the way that they kind of combined chat and, calendar and, video calling and Wikis. It's a really nice product and then in my own work I've been using a lot of, pandas and pie fin, for the kind of data analysis that we doing, yeah, a little bit kind of tooling around that, really well established and really nice to use.
George Valdes: Yeah. We talked a little bit about the data side .For those in attendance that haven't tried out Data Studio by Google, I highly recommend that, we use it a monograph, it's like a really powerful, free, business intelligence tool, basically create your own charts and graphs, sort of like data that you pipe in. And it could be just a simple spreadsheet, but it's a great way to make dashboards, if you are conscientious about spending too much money on something like Looker or Tableau or even Power BI. Oh, we have a question. Can you foresee large architecture firms seeking to commercialize their data and processes as digital products? What impact did this have on the industry and its business?
Daniel Davis: Yeah, I think, there are examples of practices that, let's say like some of the analysts cool tools, that kinda turning into, not just services, but products that's selling to other companies and one of the examples that we kind of talked about is proving ground, like that doing some really cool stuff around, their analysis and how they integrate, BIM analysis and to, Power BI dashboards and stuff like that . So I think there are kind of companies that are working to commercialize that. I think like, with firms where they get to a point where they can sell data or with the like the data itself is more valuable than the services they offer. I don't really see that happening just because the data's only really valuable and like a big kind of aggregated scale and most spends just don't have that much data and the data that they do have is so kind of idiosyncratic and unique to that particular fam and the way that they practice, the way that they decide that, it's not necessarily useful to other friends have the people to have it.
George Valdes: Yeah. There's also the challenge of the data is only as, like, basically once the product has been delivered, it's somewhat out of date, which is another kind of challenge that WeWork also had, like from its pipeline, from the data pipeline perspective, what a great question. What's your level of confidence at large firms trying to innovate invest, internally will ever catch up to the high part, giraffes test fits, et cetera.
Daniel Davis: So I don't think they need to necessarily catch up to those firms like, that doing their own thing. And I think it's going to be more about kind of collaborating with those organizations and I think with all of these kind of things, it's like, you can have these really sophisticated algorithms, say in the case of testa or hypa, like doing possible design process, but you're also gonna need the kind of creative and strategic intelligence, so that a designer that understands the context within those, in which those operating and by bringing those two things together and kind of successfully operating them, I think there's a lot of kind of opportunity there. That said, I do think there's probably gonna be sectors of work that, just aren't going to be viable for academics to compete with them. So if you were doing a lot of 80 years at the moment, I'm probably getting out of that market because there's just so many people trying to productize that space and that doing like really interesting things, so that I think it would be kind of hard maybe to go toe to toe with a company like that.
George Valdes: Yeah. it's definitely interesting that as how the space is evolving by sector, where a lot of this, the focus of new companies. It's either you have the horizontal platform of like HYPR, that can, in some ways, meet any use case or it's more infrastructural versus like a test fit, which right now is very, hyper-specific to a couple of topologies and you know, from a strategic perspective, it's not as likely that a test fit might meet the needs of a large institution, that has different objectives from what it's looking to do, whether that's cultural or even, like universities or hospitals, they just might be looking for a different set of requirements that are also ever evolving then where like, something like test fits, it's great for a very specific use case, assuming that use case doesn't evolve quickly or that there's not a lot of updates that happen to that use case. What would be a collaborative open source project that you would like to see in the AEC industry?
Daniel Davis: Oh my God. So many. Yeah, that's a really good question. I think, kinda as we spoke about earlier like, this always spends like competing against one another on things that don't add that much. So maybe going back to the earlier question about like how you compete against hi-fi, like, I don't think you did, like, trying to open source and democratize, a lot of that kind of institutional knowledge that's wrapped up in scripts that individual companies kind of hold onto, and make them available. For me personally the thing that I would just love to see in the industry, would be like some form of data sharing agreement, where organizations or companies got together and agreed to somehow like anonymize and share project data and project performance data, because I think, but any one company or anyone from them, the number of projects they have is inherently limited, but if you can open that poll up to say 10 from sharing the data between one another, I think the kind of insight and performance I'll be able to get, it's kind of be a lot greater, but, obviously recognize that it's kind of pretty fantasy fault because yeah, firm's just not going to get there. I don't think I'm doing something like that.
George Valdes: Very good points. For me, it would probably be, although it happens to some degree, I don't think you see it as you do necessarily in the tech industry when it comes to things like business development and marketing, the kind of continuous sharing of tactics, strategies, and techniques that people are doing there, that are really talking about how they won certain projects, even if they're competitive with each other, is very fascinating because what it ends up doing is creating an ecosystem that is constantly looking for better tools and better techniques and better strategies, right, to grow businesses and I think that personally is something that the building environment industry should be really be looking at, in general. It's like some of the project information stuff is probably not where you can get your biggest upside, in my mind I actually think that, top of funnel looking at how you're actually bringing in business and really trying to innovate on that, is critical. It seems that the vertical business will be better suited to innovate on AEC data because they own the data and have a longer time horizon. Do you see a smaller sector emerging that does this specifically, PropTech maybe, and take portion of the work out of traditional architecture design firms? .
Daniel Davis: That's an interesting, I haven't really kind of thought about that. I think, you're right and that like the vertically integrated companies have an advantage in that they own the entire process and so they have the data from the very start of a project, right through to kind of it's occupation and look at that kind of tools by cycle of the project and they also have the kind of financial incentive where, if you're a company, like WeWork, you know, like, you designed something that doesn't perform, you own the kind of cost of that financial aid, whereas that's not necessarily the case, for people operating kind of more traditional methods. Yeah and I'm interested in what this may look like, I guess, you kind of suggested that maybe it could be like his own kind of area of specialization and kind of practice, yeah, I'd love to say something like that kind of image in the industry, would be really interesting, right, like a firm that kind of specialize in like, taking all of your project data, analyzing it longetudinally and giving you advice on ways you should be investing and how you should be kind of designing your space or like maybe even the brief that you're giving to you architects, yeah, I think that could be like really cool, but, maybe some property management companies are doing stuff like that already, but I personally aren't really aware of across any of that. Yeah.
George Valdes: Yeah. I think what I've seen is, some companies that are really focused on things like capturing the physical space that commercial developers might have.
So they 3D scan everything and then offer the additional value back to those firms based off of those 3D scans, whether it's as built or things like that but that's the core focus of the business. So the whole business is structured to support those inputs and outputs and I think, in any other kind of small sector emerging, again I think it's not even just the only the data on what is built, the other piece of level that these types of businesses have is the marketing side.
They become actually the investment on the marketing and sales side, is probably about equal or disproportionately, maybe even more higher than investment on the actual things being produced at times.
And so there's just how you look at, like, you actually have to become a very good brand company, a very good marketing company to be able to sell a verticalized solution and I think WeWork was a very good example of this, in terms of what they were able to do with their marketing and sales teams.
Otherwise, you know, anything, all the investment that you're putting into optimizing the product, you just can't sustain it. You can't make the product better if you're not very very good at something likethat.
Thank you Mitchell for that question. So I think we're a bit over time. So I just want to, basically thank you Daniel and then kind of roll up the carpet for you and would love, you know, if you could share any insights like the next article that you're writing or anything else that you're doing these days.
Daniel Davis: Yeah, we're actually working on a really cool project, at Hassle at the moment. Looking at how people in Australia kind of going back to work, because Australia is like this really interesting case study because they've gone through kind of all the lockdowns and stuff. There's still some places in Australia like Melbourne that are kind of like lock down but other cities like Perth have been kind of free of coronavirus for a long time and yeah. So we're studying at the moment kind of what that's like for the people that are returning back to work and probably around November, we'll have something to kind of release and talk about, related to that. But yeah, I'm really excited about.
George Valdes: Very, very cool. I'm looking forward to seeing that. So just love to let everyone know, I've started my sign up, if you're a firm owner, and you'd love to see more visibility into how project budgets are being managed, how your projected pipeline looks like Superman, like an organizational level and see it all in real time, then I encourage you to sign up for, for monographs and, and check us out. Thank you so much Daniel, really I'd love to have you come back on this, especially after that report is up, to talk a little bit about that as well. Hopefully, you know, things have settled a bit by then as well, when it comes to COVID, but I'm really looking forward to it.
Thanks everyone and see you later. Cheers.
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