EP 114

Paul Heming: Hello and welcome to episode 114 of the Own the build Podcast with me, Paul Heming. Following on from last week’s eBook share, you can again find in the podcast description a free copy of my eBook, the ultimate Guide to subcontract tendering. Simple Guide to Creating masterful tenders. It is the thing to be doing guys, and thanks to everyone who’s given me feedback. I’m on Paul@c-link.com. So give me a shout if you want to ask me any questions or give me any feedback. In the studio today, we have an illustrious guest. We have got Andrew Knight, who is the global data and tech lead at the Royal Institute of Chartered Surveyors, the RICS, who I think everyone will have heard of. Andrew is a highly experienced technology specialist and is currently leading the program to develop, enhance, and gain adoption of RRCS’s data standards. I’m interested to learn more about all of those things. Andrew, it’s great to have you on the show. How are you today?

Andrew Knight: I’m great. A pleasure to be talking today.

Paul Heming: Pleasure is all mine. You know, talking to the RICS talking about new data standards, it might sound sad, Andrew, but I’m looking forward to this quite a bit. So, at the top of the show, I always like to ask the question about your journey. You are in construction, you’re at the RCS. Talk to us about your journey into construction, your experience and what exactly you do today.

Andrew Knight: Yeah, surely. Well, I mean, it’s a very long journey. We’ve only got an hour, so I will have to bridge it and take out the bits that aren’t – 

Paul Heming: We’ll edit it.

Andrew Knight: Yeah, that aren’t suitable super for public consumption. But joking aside, I mean, my data and technology experience goes back an awful long way. I asked this question of the audience at the future build a couple of days ago and got people to put their hands up if they’d ever heard of a punch card and not many had. So I’ve been in the data and tech space for a very long time. In terms of construction and indeed the built in a natural environment more broadly, I’ve been with RICS, it’ll be 12 years in April. And one of the great things about working for a professional body like RICS is, (a) it covers such a wide range of practice areas across the built environment, not only in the UK but globally as well. And you get the opportunity to move around the organization, do a number of different roles. So my kind of learning curve, not just about construction as a practice area, but also building surveying and valuation and planning development and infrastructure and all the different ranges. I mean, we have over 20 different practice areas that surveyors can become qualified in, has been over that 12 years doing a variety of roles and they’ve ranged from working with our member firms of every size around helping them understand the membership process, the kind of competencies they’re involved, working with construction firms and others to identify the kind of training they need around things like any C3 or four, or procurement and the whole range of issues or you know, things that they need to think about in terms of their skills and competencies. And also increasingly now the technology side of actually how do our standards relate to the real world and the real world of technology now. So it’s been a really kind of interesting journey for me to move across from our standards team to work in public affairs, working with our external stakeholders in the city, for example, looking at issues around valuation and cost benchmarking and all those kind of things. So it’s been a real kind of university education within RICS around not only construction as a practice area, but that broad canvas of all the different areas that surveyors get involved in. Cause I made the stupid question when I joined RICS and said what does a typical surveyor do? And they just fell around laughing like the aliens in the cabri smash –

Paul Heming: Oh, I guess the big question though, Andrew, and I think I know your answer because it’s obvious given current company, what is your favorite type of surveyor?

Andrew Knight: Well, I think I will take the diplomatic –

Paul Heming: Stop thinking about it. 

Andrew Knight: No, I’m going to take the diploma route and say that they all have wonderful things about what they do. Yeah, big sigh. But I think they’re all fascinating because I think they mix the kind of intellectual rigor of the kind of things you are doing with the fact you’re also working with the real world. So whatever you are doing as a surveyor, there’ll be this intellectual judgment, skepticism, analytics considered judgment, but that actually you are dealing with real world objects that have such an implication for human beings. So whether you are QS or whether you’re a program manager or whether you are commercial manager or whether you are a building surveyor, you’re dealing with real world assets, things that really impact people and have a really profound and hopefully positive effect, but also there’s some really intellectually challenging elements as well.

Paul Heming: Yeah, no, I think you’re absolutely right. I mean, we’re going to talk, actually, you’ve already touched on something that when we originally spoke, I wanted to bring back out in this conversation that intellectual or professional skepticism that all surveyors have. Want to drill into that a bit later because we’ve talked about the evolution of the role of the quantity quite a bit on this show. So we’ll come back to that. And the answer was actually quantity surveys were the best affairs. Just so it’s clear.  So, all of this is in the context that a lot of quantities affairs are listening, lots of other people listening as well. But talk to me then, so your global data and tech lead, what does being the RICS’s global data and tech lead actually involve other than sounding truly fantastic?

Andrew Knight: Well, it sounds truly fantastic and I guess I always feel privileged when I wake up each morning and think, well, I’m going to do that day because A, I get to talk to an incredibly interesting spectrum of people, not only within the profession, but within the data and tech sort of ecosphere as well. You know, all those various people who are innovating and bringing new products to the sector. But also because I have the ability to roam at will, if that doesn’t sound a bit too strange way of putting it to think, well actually, what are the effects of data and tech on the profession? How does that impact our standards? How does that impact the competencies that our members need, both in terms of CPD, if they’re in the professional already, or what does it mean in terms of competencies when they come on board as the new generation? And indeed, how do we use data and technology to attract the next generation and broaden the demographic of the profession? And I say, how do our standards now work in the world of data and technology? How do we make sure that these real world standards still have relevance and still can be applied in this increasingly digital world? So, it’s a wonderful role to have, as I say, I get to speak to lots of people. I get to sort of arguably stick my fingers in lots of elements of what we should be doing as a professional body to make sure that we continue to be relevant because the sector one can argue is a little bit of a laggard compared to other parts of the economy in terms of the way we’ve digitized. 

Paul Heming: It’s a little bit of a laggard.

Andrew Knight: For me that’s a kind of a double edged sword in the sense, yes, we’re behind the curve, but then think of the opportunities, think of what we can do in terms of improving the way we deliver the built environment by digitizing in a responsible, sensible way and taking the learnings from perhaps where things didn’t work so well for other sectors.

Paul Heming: You are completely speaking my language. I think that therein lies the opportunity. Yes, we haven’t digitized, we’re 21 out of 22, I think, for digitization of all sectors of industry. So there’s a long way to go, but I agree, that should wet the appetite of people listening like, imagine what we could do in a world where we would digitize. It’s absolutely amazing. You said one thing there, which I didn’t know if I wanted to ask you, but seeing as you kind of touched on it, the relevance of the RICS. So the RICS is an old and very traditional establishment and organization, been around for decades, years, centuries, right. Talk to me about that word there, relevance, because is data in tech part of how the RICS sees its vision of retaining its relevance? Like how does it hold onto that?

Andrew Knight: I think very much so. I mean, we have three kind of really broad, important kind of objectives as an institution at the moment around diversity and inclusion, which I think is clearly a huge issue for the profession to make sure that we reflect the citizens that we serve, and that we get the broader set of demographics in as the next generation to, I know it’s a cliché to talk about the global war for talent, but we need the best people coming into this profession. And so we need to fish in the biggest pool and get that wider demographic. We’ve also, as you well know, across the many dimensions of sustainability, not just emissions, but more broadly thinking about sustainability, the built environment and it’s an off quoted figure, 40% of emissions from the built environment. We have a huge responsibility as a profession to dry that change.

Paul Heming: Again, huge opportunity. 

Andrew Knight: Yeah, it’s an opportunity, but it’s playing catch up because we’ve clearly had a huge impact in a negative way upon the environment, and we’ve got to negate that in a positive sense of the word negate. And then finally, data and technology will radically, in a good way change the ability of the sector to respond to those challenges, make it an attractive professional, contemporary one. But that does mean that for us to be relevant in a digitized sector, our skills, our regulatory approach, our standards, our competencies should reflect that relevance is about keeping up to date in the same way that we’ve taken on board the concept of a disto or what could now be considered to be fairly low tech approaches. Every sector will evolve. As you say, we’ve been around for over hundred 50 years now, we’ve already seen waves of technology come in. This is perhaps one of the most significant waves, but it’s yet another wave that we need to make sure that what we do is relevant in a digitized world, but at the same time, not losing sight of the fact that it’s still a people profession and always will be. I love the phrase that somebody used on BBC saying that you’re not going to lose your job to artificial intelligence, but you might lose your job to somebody who uses it if you don’t. So it’s about making sure we use the tools that are out there, but still understand this is about people and professional conduct and things like conflicts of interest and terms of conditions and the relationship between us and our clients. It’s still a people business and we still need those conduct standards as well as the technical ones.

Paul Heming: I think you’re absolutely right. Again, we’re agreeing on a lot of things here because we’ve done quite a few shows on AI data, how it could impact quantity surveyors and facetiously titled one of the episodes of the extinction of the Quantity survey, which was met with rapturous anxiety and dismay and sometimes anger. And if you’d actually listen to the show, it was pretty much saying that actually if you wrap up what tech and data is going to bring to the sector, it’s not going to wipe the need for quantity surveyors off the face of the earth. But those who don’t adapt and upskill and learn about it, eventually they will probably be wiped off the festival. It’s in the same way that if you hadn’t bothered to learn Excel 25 years ago or in the 1980s or whenever, and you were now refusing to use it, life would’ve moved on beyond you. So I completely hear everything you’re saying and in many ways you’ve answered this question, but I just want to ask it again, or for clarity, why is data important to the RICS now?

Andrew Knight: Well, I mean, I don’t know how good your Latin is, but modus is some Latin expression for measurement as I understand. So fundamentally a surveyor is there to measure. And it might not just be a dimension, it might be a cost. You know better than I do and it could be a quantity takeoff, a build of quants, but you know, the survey’s job is –

Paul Heming: Don’t get me started.

Andrew Knight: Yeah, the job is to measure. So ultimately data really is everything because that’s what we’re reporting to clients, that’s what we’re basing our reasoned advice on whether it’s evaluation or say, a quantity takeoff, a benchmark. It’s all about measurement. It’s all about data, and it’s all about the quality, the provenance and the professional skepticism of looking at a piece of data and thinking, do you know, that doesn’t look quite right. And also being kind of using a bit of common sense. I mean, a colleague of mine in our standards team, actually in the construction part as a QS taught me a story years ago when I first joined. And he said, I said, I remember as a young QS going and presenting this early cost advice and you know, I reeled off the numbers for this building and it was like 15,658,755 pounds and 14 pence. And he thought, what have I just done? Why have I said 14 pence in so many, you know, I should have just said, it’s going to be 14 million pounds. You know, which fool goes out there and talks about data at that level of granularity knowing that it’s an estimate. And therefore there’s that illusion that just because a spreadsheet or a program produces something to that level of decimal points, you’ve got to be interpreting the data and understanding and adding that human overlay experience. And, and as I say, judgment.

Paul Heming: Yeah, I think my feeling on this is professional skepticism, human analysis and use of that data is what makes some people think it won’t wipe the need for QS’s off the face of the earth. And obviously I don’t personally think that, but what my belief is that the data sets currently in construction are so weak, and that’s whether you’re at a huge company or at a small company, obviously there is a sliding scale, but the data sets that we have as quantity surveyors, even project managers, site managers to be professional skeptics, which is our job, the data set is rubbish. So that leads me on to, I was reading about your role and the fact that you are trying to gain adoption of RICS’s data standards, and that got me to thinking about how important a role that potentially is because the data at the moment is very sparse. It’s pretty weak business to business. So what are RICS’s data standards and why do they matter?

Andrew Knight: Perhaps, I’ll answer the question in the opposite way you phrased it. I mean, data is key and as you say the sector’s not been great at using the pretentious phrase curate. You know, we haven’t been good at it. It hasn’t been kind of part of our DNA. And you mentioned if you hadn’t learned Excel in the last few years, you wouldn’t be particularly employable. I’m probably going to be off build Gates’s Christmas card list, but if you could ban Excel, that would be a good start. Because what you have is a lot of sort of well spirited –

Paul Heming: I agree. You want my Christmas card, let’s forget build Gates. I’ll give you a card.

Andrew Knight: I always say, look, if I asked a group of 20 people to give me their annual kind of budget on household expenses using an Excel spreadsheet, I’d get 20 different versions. And probably someone wouldn’t even tell me pedantically which currency they were talking about. 

Paul Heming: You’re talking my language so much here, Andrew. Actually, in the footnote of the description of this podcast, I talk about 80% of QS’s are still using Excel and why that’s a problem. But sorry, go on.

Andrew Knight: Everybody do it with the best of intentions. It’s an incredibly flexible, powerful tool. But you then end up with as many versions of the truth as there are QS’s. It’s like monkeys writing Hamlet or something. You know, you get this.

Paul Heming: Alright, be nice.

Andrew Knight: No, on a serious note, the trouble is we then get lots of data that, you know, it’s the same objects with a different name. It’s like the more common wise, I’m playing the right, I’m bringing the right quantities, but just in the different orders. So we end up with that lack of consistency. And in some respects it’s not rocket science, it’s just as a sector, can we agree what we call things? Can we call the same things the same things? Can we be clear with the unit of measures we’ve used? It’s that metric. Is that imperial? Is that GBP, is that US dollars? What was the date of that particular estimate? Can we just structure the data with a little bit more discipline and more consistency? And so what the data standards are trying to do in a situation that sometimes doesn’t feel a bit like herding cats if I’m honest, is to try and just get some consistency on a machine to machine level and say, look, if we’re going to exchange data between participants, can we just agree what we call things? Can we agree that we label it and say where did that data come from? Back to that kind of professional skepticism. How old is this data? How is it collected? Where’s it from? Is there some assurance from it? Is this from some part of the tier of construction or the architect? Where did it come from? Are they prepared to assure this data in some way and can we just have it in a structure that’s machine readable so we can actually just pass it from system to system? Because everybody will have their different systems. It’s more of a kind of a babel fish, if you get the reference of that concept of saying, look, let’s have a common format for data interchange that says, tell me about the asset, tell me about the property rights cause there may be some title issues on the site, for example, there may be some planning constraints. Tell me all that information as well as things like the ICMS standard we have for reporting as well as perhaps the NRM type that level of cost coding. Just give us the information in a standard format so we can all agree we’re looking at the same thing, but critically have that metadata as the jargon is, where did it come from? Who signed this data off? How old is it? You know, which particular early cost advice report is it, what’s the data bit? Where did it come from? Just a bit of bit of labeling.

Paul Heming: And how’s it going? How is uptake?

Andrew Knight: I would say it’s going to be a long journey and it mirrors the sector as a whole. And I think for me, the frustration, if I can use that phrase is that I think we have a lot of the technical tools that the sector needs. What we do need, I think is a change in mindset and behaviors. And some of that, dare I say, is in built to the nature of contracts, the sort of the nature of the, dare I say, combative part of contracts are around the construction sector particularly, and some of the perhaps onerous rules around commercial sensitivity, which sometimes block data being shared. And I think also perhaps a general, perhaps misunderstanding. And in a previous life, I worked in the kind of the consumer kind of data area where there was already, I hesitate to use the word maturity, but already a sense that it was better to pull data than to hoard it. Because actually if you had a shared view of the market, whether it’s for benchmarking or behaviors or whatever it was, if you had that whole view and you’d pulled your data, it was much more powerful to have that than to hoard your kind of 5% and run all your benchmarking and run all your profiling on that limited view. And I think it’s not just construction, you think of commercial real estate and valuations and attributes of properties. The more we can encourage the whole built environment to realize the importance of sharing data, both technically and from a kind of a behavioral point of view, we’ll get a much better set of data. And a lot of it also just comes back to the fact that we’re still in this document world where one of the other things I try and talk about is we’ve got to move away from documents to data, structured data that computers can read rather than saying, well, yeah, I’ve got all the information and here’s the pdf.

Paul Heming: Now you sound a lot like the CTO at my business, who is a non-construction minded, well non-construction experienced individual who’s trying to shake up the way we gather data and do it in a way that perhaps someone from a different sector would do it, look at it in a different way. And for me, that’s really exciting for us as a business and what we’re doing with our data. But yeah, completely resonates that AI data is only as good as the actual structure that the data set is coming in. The more data we have, the better. And we’re in a position where data sharing and the combative nature of our sector means that people are a bit more closed, a bit more fragmented. I know that there’s a lot of interesting stuff going on, like the project data analytics communities. There’s a lot of interesting things going on where people are trying to tear down those walls, so to speak. But really interesting start to the show, Andrew. Let’s talk more after the break.

So Andrew, data and data monetization. So in our business, we are strategically focused, long-term focused on how we can use the data that we gather from all of our construction projects through our technology for the long run. It’s not easy doing that, but that’s what we’re trying to do. You’ve talked about how important that is for the industry. You’ve also talked to me and talked online about data monetization. What do the ROCS mean and what do you mean by data monetization?

Andrew Knight: Well, I suppose, if I’m honest, this is probably my personal definition. I’m not sure whether I probably articulated to RICS to have theirs. I, in a funny way would reframe it totally. And perhaps, I’m being too future thinking here in the sense that actually what I think the sector needs to do is think beyond the monetization of the data, but think of monetization of the analytics of the data. Because I think, and we touched earlier I think on the whole issues around sharing data and the barriers to those, some of which are technical and some of which are arguably more behavioral. What I think for me the key is for people to kind of let go of the idea that merely holding some data set has value to think, well actually the value I bring is actually turning that data into information and analytics and useful.

Paul Heming: QS job.

Andrew Knight: Yeah, I was talking to somebody in the states a few weeks ago and they were talking about the concept of, they called it dark dataware and they were talking specifically about construction, where effectively we were almost recording too much data that actually wasn’t of any use and wasn’t being turned into any actionable information. And that we shouldn’t be storing data for the sake of it. We should be thinking, well what data is important? What business decisions do we want to make? Then let’s store that data and do the appropriate analytics on top. And the value, the monetization is in that analytical there, not the data itself.

Paul Heming: Yeah, absolutely. And that’s where I think the QS comes in as someone who is already very data analytical, just looking at poor data sets, I think as I was talking about earlier. So if you were to, I completely understand that you’re now saying you want to get data, you want to be strong with data analytics. What advice are the RICS currently giving to contractors on the data that they should be gathering so that they can then analyze it? What should we be doing?

Andrew Knight: I guess I would take that as a standard led approach. Now if I think of something like things like ICMS and NRM we’re saying, think about the structure, think about what you report. And if I think about things like ICMS, which is international construction measurement standard, which is looking at now both costs and emissions right across the project cycle, it’s taking that kind of cycle view of saying, actually, can we be taking these snapshots of costs and emissions and projections thereof all the way through from early stage to turn out to hand over right through the operational cycle and be thinking actually, let’s have that structured high level reporting that we can use to benchmark. And basically, it’s about getting back into these consistent data structures. Because once you have the data with that metadata that sense of providence, where’s it come from, it’s properly kind of annotated, you can then begin to answer business questions. And I guess the challenge and what we would be recommending is what questions are you going to ask because you can store data for the sake of it, but actually what are the business decisions you want to be able to ask this data? What are the kind of things you want to use? And there’ll be certainly things that will come out of the data analytics that you didn’t know about and perhaps things you can use it for. But you do need to start with an idea of, well, what do we want to do to decide to decisions make, advice to give to clients? You know, what are we going to use the data for some sense of an end game at least to say, well look, there must be some usability, some purpose to this rather than analytics for the sake of it that gives us information that’s not actionable or really doesn’t matter or drive any value for client or for contractor or for top tier or whatever.

Paul Heming: For anyone. Yeah, I think a lot of the data for quantity surveyors that would be really useful would be around cost, would be around an understanding and ascertaining whether what you are paying for is right, like your cost estimates, etc. So if that is, you’ve talked about your plugging the RICS data standards, which makes perfect sense, right? But so say I’m a contractor and I’m commercially minded and I want to start standardizing the data that I’ve had, that I have or that I want to gather. I’ve answered those questions. It’s about cost, for example. All of this still feels quite abstract the way we are talking about it. I want to try and help someone picture it. If I want to do that, how do I do it with the data standards?

Andrew Knight: I think you kind of start simply and think, well actually let’s think about some structured data that says, on the one hand let’s have some basic attributes of what are we building? And I know it seems obvious to say, but what is it? Where is it? How big is it? What’s the size of the floor plate, you know, information on really the kind of asset itself? Because if we think of the kind of benchmarking use case where you want to say, well actually how can we cost jobs better in the future? How can we work out based on what we’ve built in the past, what are the kind of issues, what are the kind of costs that we should be looking at? And if we think of kind of life cycle and emissions, can we begin to build a library of the implications of certain design and material that decisions on embedded in operational carbon? So on the one hand, let’s think about storing a reasonable data set about actually what is it we’re building, not necessarily a detailed BIM model if that isn’t part of the project, but basic attributes about the size, the function, location, height, etc. of the building so we understand what we’re actually building here. And if it’s in an infrastructure space, the various attributes for bridges, tunnels, etc. Not at the necessarily hugely granular level, but enough to start that kind of benchmarking conversation.

Paul Heming: Start simple and iterate effectively.

Andrew Knight: Yeah, exactly. Start simple. And then when it comes to the cost side, and once again I’m plugging the ICMS standard, but the beauty of that is it’s quite a high level reporting standard. So yes, you might have somewhere squared away how many aluminum bolts you used and how many square feet of carpet or whatever. But I’m being slightly sort of flippant there, but my point is, it’s about thinking at those higher levels of granularity, can we begin to benchmark sensible levels of yes, how much do the groundworks cost as opposed to the electrics and the sanitary wear and the windows and getting that level of granularity that makes sense, that’s practical to record and analyze and keep and then means you can begin to make some meaningful business decisions because you can be swamped by data and that could be a danger particularly for the smaller firms where you just haven’t got the resource to do it. So it’s about having sensible levels of granularity on the data you record.

Paul Heming: Totally. And touching on the small, I swear you keep on giving me the most fantastic segues. I wanted to ask you about small businesses. So talking about small businesses, the langor, bees, whoever, they might be able to say, look, we’re going to allocate a data team, we’re going to create a data team. 99% of construction businesses are SMEs. How can we help through this conversation? SMEs build a data capability.

Andrew Knight: Realistically that they will need some outside help. But you know, there’s a very vibrant kind of contact PropTech sector out there where there’s much more accessible technology, it shouldn’t cost the earth to get some help in and think, well actually can we build some simple systems here? And you know, having perhaps just Excel, you know, power Bi is a relatively simple to use product in terms of getting analytics on top of quite a disparate set of data sets, some of which could be there are said Excel. You don’t necessarily need to move away from that in the short term and it’s probably worth thinking, can you get some kind of consultancy support? Can you get somebody comes, perhaps comes in from the outside and just helps you build some simple dashboard. Just some start. It’s the cliché of the longest journey starts with the single step, but look at the data you’ve got. Can it be curated and tied it up in such a way that actually somebody could come in, build some dashboards for you, build some of that initial feedback loop of some value here by looking at the data you’ve got, maybe doing a bit of tidying up, putting something like Power BI or Tableau on top of it and giving you some useful dashboard that you can start comparing your projects and looking at exceptions.

Paul Heming: It’s small chunks as well, right? You don’t need to create this massive thing. It’s do one thing to improve your business.

Andrew Knight: Exactly. You know, the thing about it’s agility, it’s small little sprints to use the IT term take one issue and say, look, maybe we got an issue around benchmarking. You know, we want to get our previous data in such a state that we can do a bit of a better benchmarking when it comes to doing tenders. Let’s just look at one issue, get some help on that, fix that, get a return on investment and then grab another problem. Say, okay, we want to measure labor rates over time, we get a better understanding of how we’re using subies or whatever. You know, it’s about taking a problem at a time, a little chunk, tidying up the data, working out how you can make that work, get a return investment, do the next thing. What I wouldn’t recommend is trying to sort of digitize your whole place overnight because you’ll just get sucked into time and resource and money and you’ve got a day job, you’ve got projects to run.

Paul Heming: Definitely. No, 100%. And we’ve talked already on the show about professional skepticism, which is your phrase, but I’m running with it and I’m going to steal it.  What do you mean by professional skepticism?

Andrew Knight: Well, I think people always kind of slightly have a pejorative view when you talk about somebody being a skeptic. But for me, it’s somebody just using their experience and judgment to look at in this context of data, input a piece of data and say, does that look right? Am I comfortable with where that’s come from, how it’s been collected? Do I think it’s fit for purpose? And this is a term I use equally in a valued statement. Whether I’m talking around the valuation process or whether I’m talking about looking at a construction data set. It’s saying actually as a professional, I should reserve the right to say, tell me about the data. Where does it come from? How recent is it? Who’s given it to us? What was the methodology? You know, has it been updated? Has it been manipulated in some way? And we can slightly open the can of worms or the tin of worms here with kind of AI and big data because there is a danger that you lose a level of abstraction once something’s gone through some kind of AI program where you just really can’t trace where it’s come from or what’s happened and how the algorithm has decided about the number it has spat out at the other end. And that is a big challenge and maybe a topic for another day. But there’s still that, I think that responsibility in the same way that you were looking at set of drawings and doing a quantity takeoff from that you’d say, well who did these drawings? Is it for the correct architect? Have I got the right drawings or the right building because this doesn’t look right and these are the most Up-to-date ones? Have these got all the changes that the client asked for? It’s that sort of basic quality control of saying data, whether it’s digital, whether it’s a 2D drawing, is this the right piece of material for me to base my decisions on? And I have the right to be skeptical until I’ve asked some questions to assure myself that I can now give you, Mr. Client, the right advice. Because I’ve been skeptical, but I’m now positive I’ve got the right data.

Paul Heming: Yeah, I mean I think professional skepticism is probably higher in construction than it is in many sectors as well. I think it’s almost innate to the skepticism side of almost all of us because of the nature of the industry that we work in. I think you’ve answered this in many ways, but we’ve talked about the evolution of the role of the quantity surveyor. The RICS very much wants the quantity surveying role to continue into the future, I would imagine, given the nature of the organization. How do you see you being the RICS, but also yourself, the future role of the quantity surveyor? What are you preparing for?

Andrew Knight: I think what we’re preparing for is for quantity surveyors, and I would broaden this and talk about a lot of kind of surveying practice areas, and this hopefully doesn’t sound overly optimistic. What I mean to get across here is that I see technology in so many ways removing a lot of the drudgery tasks, if I can use that phrase, the kind of basic data aggregation, data capture. I mean, there’s an interesting statistic from data science actually where a huge percentage of the average data scientist’s time is spent tidying up data, curating data, then they don’t actually spend most of their day job doing the data science bit. And I think the opportunity not only for QS is, but more broadly is that whilst they retain their skepticism, a lot of that basic legwork will be done for them and that will free them up for what they do best, which is giving clients great advice on options on what to do on managing the stuff that happens. And actually, maybe I’m being over optimistic, but I genuinely feel for the profession as a whole, technology can automate workflows. It can make data better. We’ve talked about skepticism and not believing things that just appear on a spreadsheet, but it’s about making data better. It’s about joining data sources together. It’s improving the quality of data and it’s freeing up actually for more human interaction. For more quantity surveyors value is spending more time with their clients providing advice. So I think we should be genuinely very optimistic that actually it’s about, and it’s a cliché to talk about going up the value chain, but a QS should be not sweating over a copy of Excel. They should be working with clients and architects and other parts of the value chain to add the value they bring. And increasingly with the challenge of whole life view of assets and design decisions and thinking about emissions and that bigger ESG part, QS’s have a huge role to play in those early design decisions, not pouring over a copy of Excel. They should be saying, look, these are the options. We’ve crunched the data, these are the options. These are the trade-offs between embodied operational carbon, between maintenance cycles of the HVAC, depending what you’re going to put in here, working around those scenarios and looking at the tradeoffs with  client. 

Paul Heming: I mean the reason why I like your terminology professional skepticism is I feel like at the heart of what a quantity surveyor does, they are professional skeptic and businesses, whether they’re contractors, clients, whoever that employ quantity surveyors want the quantity surveyor to be a professional skeptic. But sadly, the quantity surveyor spends endless hours doing what you’ve just described, the data scientists does, doing manual tasks that could be automated or trying to get hold of data that could make them a better skeptic. Our business, we think we automate out 600 hours of lost time for quantity surveyors during a project, but just the ability to be able to focus on being a professional skeptic would massively radicalize the success of many projects, I think, and the enjoyment that many QS’s would get out of work, right? Take away the nonsense, take away the drudgery as you put it, and focus on the data and actually getting into it and being that professional skeptic. I think that’s the future. My only concern is how quickly we can get there because I look at the experience of BIM in the sector and how long that’s been here and how absent it still is on many projects, particularly down the chain. But yeah, it’s fascinating stuff, isn’t it? 

Andrew Knight: It is. I mean, it is interesting. I mean, I suppose we’re into kind of the drivers and barriers part of the discussion and I guess, given the importance of the whole kind of sustainability and ESG agenda and how that will, dare I say, trickle down from project sponsors and from the capital markets in terms of investment and reporting requirements, that there will be, I think in a good way, a real drive here about driving more openness about data in terms of the kind of emissions and costs involved. And I think that will force in a good sense of the word, more of this digitization. So I think there will be positive pressures that will drive this. It will take time and you know, it’s about, and as ever, it’s not so much about technology, it’s about change management and leadership, isn’t it? You know, it comes back to the fact that we have the technology, but I think it’s about leadership and investment and change management and taking people on the journey. Sounds a bit cliché to say that, but you know, it is a journey to get people to think and act differently and use this technology.

Paul Heming: Yeah. And don’t rally against it because as we said at the top of the show, such is the lack of development or digitization means that there is a huge opportunity for your business to transform itself. And I wholeheartedly very biasly running a tech company in Cozi, Spain, technology now believe in that. But I see businesses getting transformed and I really believe that the opportunity is there and we’re so undigitized that we can become more and more digitized. So we’re at the end of the show, Andrew. We’ve rushed through that. There’s much more to talk about. But perhaps there is room for another show. I’m sure that there is. Thank you so much for coming on the show. I’m going to share your details, I’ll share your LinkedIn, often doing great posts there, hosting webinars and really insightful things at the forefront of where the industry’s at. So I recommend that everyone does take a look at that. And yeah, like I said, thank you so much for coming in, sharing everything that you have. 

Andrew Knight: Absolute pleasure.

Paul Heming: And everybody, as always, I will be back next week. Have a great week ahead and I will speak to you soon. Take care.