Digital Builder
Digital Builder

Episode 21 · 3 months ago

Data Strategy in Construction: Finding a Competitive Edge

ABOUT THIS EPISODE

Incredible opportunities exist for those who build a strong strategy for managing their data.

As the speed of decision-making in our industry continues to increase, data can help make not only faster decisions, but better decisions too.

Plus, if you build a strong data strategy, you’ll be setting yourself up to leverage more advanced technologies further down the line.

Jay Bowman, Managing Director of Research & Analytics at FMI, and Andy Leek, Vice President - Technology & Innovation at PARIC Corporation, join the show to discuss the many benefits of having a strong data strategy in construction.

We discuss:

  • The state of construction data today
  • How to make sure you’re capturing useful data
  • How a baseline of data strategy leads to more advanced technologies
  • Improving data literacy in construction
  • The future of data in construction

Check out these resources we mentioned during the podcast:

Digital Builder is hosted by Eric Thomas of Autodesk.

Hear more episodes like this one by subscribing to Digital Builder on Apple Podcasts, Spotify, Google Play, or wherever you listen to podcasts.

Can’t see the links? Just search for Digital Builder in your favorite podcast player.

Hello everyone you're listening todigital builder. A podcast brought to you by autodesk. Made for constructionprofessionals who want to hear from those on the forefront of constructiontechnology. If you're looking for conversation centered around where theindustry is going this podcast is for you. Each episode will feature aconversation with a construction industry leader. Together we'll dig inon themes related to connected construction and discuss where thefuture of the construction industry is headed. Now let's get started. Helloeveryone and welcome to episode 21 of digital builder. I'm your host ERICthomas. This week our focus turns to data strategies and constructionincluding a look at a recent global industry report we released inpartnership with F. M. I. Titled harnessing the data advantage andconstruction. We'll use that study is a starting point to discuss commonindustry challenges with data and how to take advantage of this opportunityto drive improvements with construction data. To help tell the story. I'mjoined by jay Bowman partner and managing director of research andanalytics. With FMI and Andy leak, vice president of technology and Innovationwith Perich and is responsible for strategic planning implementation ofenterprise technology and innovation at Peric. His focus is on developing aproactive data centric strategy to integrate cloud based technologyranging from VDC to AI with processes that enable extended project teams tobe more collaborative and efficient while leveraging critical data insightsand dashboards from his connected data strategy and j advises epitomizedclients on a range of strategic decisions including businessdiversification, market entry and competitive positioning. He also coauthors. F Ami's annual U. S. And Canada markets construction overview,the most widely read industry overviews in North America and I've beencollaborating with J for over four years now on research projects andwe've released three industry reports together. So thanks for joining me onthe show gents and uh thank you for bearing with me on the lengthyintroduction. I appreciate it. No problem at all. Thank you. Eric it is apleasure to be on the show again. And also just the opportunity that we'vehad collaborating just on a range of topics like you mentioned over the lastfour years or so. Whether it was you know, understanding how time is spentprojects, both, you know how it's been efficiently and maybe how it's spentinefficiently the impacts of collaboration and how that really candetermine the success or failure of projects. And then really the mostrecent one other than this one we're talking about today, the role of trustnot only in organizations but between organizations and you know, it's notonly been rewarding for me having spent that time with you on these individualstudies but also just seeing how these past studies really contribute to andinfluence the approach to data and you know how people put value on data intheir own organizations. I appreciate that jay and you're absolutely right.It's so rewarding to have an opportunity to dive into thesedifferent topics and really find out the what and why behind them so we canoffer actionable guidance and insights for people out in the industry. It'sbeen a real pleasure. And Andy I know we haven't had an opportunity tocollaborate together very much but I'm super thankful that you're here sharingsome of your wisdom about data strategies and all the great workyou're doing over at Barrick. Yeah, I appreciate you having me on the show.It's gonna be a lot of fun to talk about this. We've spent a lot of timeand energy developing a data strategy and helping to bring our organizationalong and it's quite the journey just for our company but for the industry ingeneral. So I think it's a really important topic and excited to talk.Yeah, there's a lot of people talking about this specifically right now andI'm excited to pull out some more concrete like what do we do? Like howdo we do better? Because there's there's such an opportunity. But as Imentioned a moment ago, we'll start with a brief overview of the findingsfrom that research report that jay and I worked on, followed by a discussionwith both guests about the state of the industry's data practices and I thinkmost listeners out there have seen that old chart that says Constructiondoesn't embrace technology and we struggle with productivity improvements.But I really think that that story has changed in the last 3-5 yearsspecifically. We've had so much innovation and so many new things havecome out, but also it's a large contributor to the massive amount ofdata that we have. That we didn't necessarily have to think about how wewere going to leverage and store and manage and you know, completelydifferent ways. So with that said jay, I want to kick this off with you today.Can you share some of your highlights in any surprises that came out as weanalyze the data for this big report? Absolutely. And I think first of all, Iwould absolutely agree with you on the side of you know, where innovation hasbeen across the construction industry and even more broadly speaking, a cindustry. I mean when you just look at venture capital investment, I mean it'sgrown tenfold in the construction industry over the last decade. I don'tknow if there's another industry where there's really that much innovationgoing on. So it's actually a pretty...

...exciting time for us in our industry.And you kind of mentioned, you know, the rise in data and you're right, Imean there's just been an exponential rise in the data capture amongorganizations in our industry. And I think it really kind of start withthere is that, you know how a data strategy is really, you know, may seemoptional today, but it's really going to be a requirement tomorrow. And Ithink that is because of what we've seen from the amount of data capturewe've seen. But there's really three things I think from the study thatstood out to me and you know, the first one just being again, it's thatquestion of this option or is this a requirement? Because the speed by whichdecisions are having to be made. Now with the pressure on project schedules,budgets and everything. The speed by which those decisions have to be madeis just getting increasingly faster and faster and frankly pushed out more andmore to those frontline individuals that don't really have the luxury ofgoing back to somebody. In fact in the study, one of the things that stood outwas what was the greatest risk they saw to project success going forward and itwas the urgency by which decisions are having to be made. So that was clearlynumber one and data has a strong role in helping making those decisions notonly better but faster. The second one was just the recognition. I thinkacross the board Of the importance that data is going to really play in thesuccess of their organizations and how things get done. I think it was over50%,, 55%, probably that actually said, yeah, we recognize that this is thedirection of the industry. So we're not really fighting any kind of old stigmaof hey, you know, we're not going to embrace change. They recognize it. Andthen the third piece, I think along those lines, not only from the speed bywhich decisions after you made, but that recognition, but just therealization of what kind of skills that means for people in our industry. Uh,one of the people I actually spoke with as part of the research that we weredoing noted that you know, something like 20 Of employees or only 20% ofemployees might actually be data literate. So there's a huge sort ofneed from a new skill development. But those are sort of three big things thatstood out to me and combined what they spell is competitive advantage. Yeah, Ithink it really highlighted a lot of things that we were talking about orpeople in the industry speak about what we didn't have any real data pointsbehind and we surveyed nearly 4000 people for this project. And throughsome of the calculations that you know, Jay you so graciously helped us outwith we figured out that there's nearly a $1.84 trillion cost to constructionin 2020 tied to either bad data, inaccurate data or poor data. And wefigured out that this could potentially be 100 and 65 million in revenue impactfor GCS with 88 billion globally in rework costs tied to bad data, whichwould shape up to about 7.1 million for that 100 million or $1 billion generalcontractor. So like when we start getting more granular about those,those big cost numbers, I think it really does combine the, here's anopportunity to really improve how your organization works and the margins thatyou have and then also just makes it really clear that this is just a veryimportant thing to focus on is we build, how are industry consumes technologyand Andy I know you weren't in the report with us. So I would still beinterested to see your thoughts and hearing some of the things that jay andI just shared and then also just your insights tied to our industry'srelationship with data at large. Yeah, well, you know, it's it's awesome tokind of be listening from that outside of the report piece. Just there are somany parallels and what we're experiencing in the day to day and youknow, this is obviously a journey that's you know, it takes a while forthe industry to a ball. I agree with jay's sentiment around there is acertain perception that the construction industry has been one ofthe last to kind of really adopt technology. I think it's been more thecadence or the fidelity of the data or the use of technology that has beenslow to kind of really evolve. I mean the design world kind of picked upafter accounting and I think it just took a little bit for that to find itsway through the construction industry. But I think today really what it'scoming down to you now is now that we have the technology, we're we'redeveloping the data now. It's coming to a point where people need to knowwhether or not they can trust. It has the cadence high enough that they canget information in a reasonable amount of time. As jay said, people need to beable to make decisions quickly. Job sites are highly dynamic. Design teamsare moving at a rapid pace, deadlines are ever evolving and never gettinglonger, a way shorter and so to maintain budget, maintain schedule.People need to make decisions immediately and job sites or dynamicweather can impact them. Covid...

...deliveries where somebody said park thetruck for the day or there's all kinds of things that can impact the job siteand that knowing that context in the steam of the project, the people thatare on the ground on the job site no more about that job or they should thananyone, but there are obviously going to have blind spots, they can't consumeall the information is available to them all the time. And so that's wherethey're trying to find Okay, what tools do I have at my disposal today that Ididn't have just a few years ago. Is that data reliable? Am I going to getit in time to make this really important decision or am I going to putoff a part of the work or reschedule some something on that project that isgoing to have a spiraling effect into the rest of the project. So yeah, I seea lot of parallels and what the study was showing at the end of the day, itstill comes down to the age old issue with our industry is it's time andmoney. All the things we're doing have an effect. Our goal is to make surethat our clients have a good experience with us so that we can do repeatbusiness. So understanding this industry, understanding our craft andmaking sure that we're leveraging the latest technology as they said, it'sabsolutely going to be the new competitive advantage. I'm glad to hearthat your experience lines with some of the findings that we had and I want tocome back to one thing you said, that is incredibly important for me and jayand I have talked about this at length is the trust peace and jay and I, wedid another research project to see, You mentioned a few moments ago aboutorganizational trust, which you should absolutely check out if you'reinterested in this topic and listening to this podcast. But the relationshipbetween trust and data is incredibly important and jay, I was hoping youcould share more about the challenges tied specifically to data inaccuracyand how it did impact the way people trust the data to inform theirdecisions. It's a great question, you know, when you ask that questionactually makes me think of a mentor of mine who often when he talked abouttrust he really kind of broke down into components. He would say it's aboutcompetency and it's about consistency you know compensate me that okay I cantrust that you you know you can do the job that you're going to be accurateall those types of things and consistency that you're going to dothat over and over and over again. Yeah. I don't think it's too much of astretch to kind of take those two sort of descriptors if you will orcharacteristics of how trust is built and now put in this sort of dataenvironment. So if you kind of start with the sort of I'll say theconsistency piece of it right? Maybe this gets back to a little bit whatAndy was talking I mean there is a large percent of the data. It's justnot usable and I want to distinguish from women by not being usable and notnecessarily bad. Let's put the you know the bad off to the side for now. I meanthere is bad data as you mentioned it and it costs the industry a tremendousamount of dollars every year. But if we just talk about just the usablecomponent again from the survey results about half the respondents Or excuse me,a large percentage of the respondents said that you know maybe about 50% orso. It's not even usually can't access it right away. It's not really in aconsumable or understandable format or I can't really do anything but itdoesn't really have any, it's not actual in that regard. And so with thatthat kind of undermines that consistency meaning that I don't knowif the information I'm gonna get this time is going to work or if it's goingto be the right information this time and that undermines that trust and thedata is just that inconsistency and then the competences cps Now that'swhere I think the bad data comes in And about half of the respondents said thatanywhere from 20 to 50% of their data is bad. I mean meaning that there is aninherent sort of error in the data, you know, the wrong information, it was putin wrong, whatever it may be. And so I think that you know those thingsabsolutely have to be sort of addressed if you will from a trust perspectivethat the data is going to be accurate and that it's going to be consistentbeing no matter when and how I access it, it's right every time absolutelynecessary. Because you go back to that trust study we had, you'll recall twoof the hallmarks of really high trust organizations where they emphasizecollaboration and they shared information openly and easily in data,in my opinion, that's why I say all these studies that we've done, you cansee where they all interconnect here is a key component to that. Yeah, I thinkdata is the driver of the conversation now and Andy I feel like you may havebeen burned in the past on some bad data because your you're nodding yourhead as jay was sharing some of his opinions on this one and I think we allhave and it's a hard thing to sidestep sometimes because if if you get burnedreally, really badly when you were confidently using data that turned outto be inaccurate, it really increases your hesitancy to leverage data and anactual and quick way in the future and...

...to build that trust back uporganizationally and that you've built your data standards and your structurein a way that makes it so your project teams can go heck Yeah, I looked atthis dashboard, it said X and it means that it's X. Like that's it's the idealstate but we're not all always there unfortunately. Absolutely. You know,it's kind of, it's as I said earlier, it's a bit of a journey part of the useof technology as we're as we're evolving today and where we're headedis one missing data is as bad as it is almost as bad as missing from MS enterdata or what have you and so having gaps is always a thing that you've gotto overcome and so it's a matter of how can I trust the data, what you cantrust the data that's there but data that's not there? Well, I don't knowthat you can or can't. So that's part of the journey is understanding thatand you know, one of the things that we've, we've had to work through overthe last, You know, 10 some ideas has been 1st. What are the questions youwant answers to? Do we even have the data to back it up and if we don't, weneed to figure out a way to start collecting it. That's, that may help behelpful in three months or six months. It's probably not helpful today. Butthen once we had the data, make sure that you have a way to test the dataand make sure that what you're curating for the user base is actually usableinformation And it's timely. Like I said earlier, like the cadence of theupdates and things like that have to be at a pace where the team is gettingsome value out of it and it's not after the fact because at that point you'rejust writing parking tickets and nobody really cares about the data where Ithink that's important to understand too is there's different data fordifferent parts of the project, different phases of the project. Somedata is really critical in that critical decision making moment of dowe, do we order the guys to come on site to pour concrete or not versus dowe have the photo that back up a, you know, some sort of litigation thing orwe're modifying schedule, what's telling us to change that schedule,that weather or is it shipping and logistics? What's driving that decision?And so that's, that's where the trust part becomes. The most important likejay said is one is making sure that the data that's there is reliable and thatis actually all there. The other aspect is when it doesn't work and I'll tellyou there's two aspects of that. One is the data strategy is constantlyevolving. So I'll tell anybody today your data strategy today will bedifferent 12 months from now. It probably will be different 90 minutesfrom now. But ideally not you want what you're reporting on so that you canlook back over a longer period of time. But it's going to evolve. And sodeveloping a data strategy that is nimble enough to allow you to make sometweaks and add some additional data points without losing everything thatyou've built up to this point because you don't want to lose all thathistorical data. It's a really critical part what we're doing. But on the rareoccasion that something may go go sideways and that never happens inconstruction, but you are going to have some rebuilding to do you have a userand they're looking at a particular dataset for quality or safety or, orcost or what have you and something went wrong? You may spend the next sixweeks building back there. Trust that Yes, I double checked the numbers, wetriple check them and it's gonna take a while and as we're setting expectationswith your team, I think is one of the most important aspects of this is it isa bidirectional relationship. They're looking for information and answersfrom whoever is creating the data are presenting the data and you're lookingfor guidance from them on what's going to help them make important job projectdecisions. So letting them know, hey, we don't have everything perfect. It'sgoing to be a little bit of a bumpy road. Please bear with us that onlybuilds you a little cushion but you should take what you can get. Iappreciate that insight and I will get into some of the how do we do thisbetter in a few minutes. So for those out there listening like we'll havesome actionable guidance coming soon. So police stay tuned because I thinkit's the important half of this conversation. But the thing that comesup on this show a lot and just something I think about prettyfrequently when it comes to construction technology and data is thebalance between the quantity of the data captured versus the quality of thedata captured and the increased innovation I think is actuallycontributing to this noise a little bit because it's harder to figure out howto make sure everything is seamlessly moving from place to place unlessyou've really built yourself on some sort of, you know, real holisticplatform solution but Andy I'm curious how have you found the balance whenimplementing technology at paris between the quantity and qualitydiscussion. So two very important aspects of this entirely different ways.Right? So the quantity of it is the first part you gotta tackle. I thinkthe quality part kind of comes with this part, but the quantity is thefirst thing because a human being can only consume so much information at atime and they've got other things going on besides just looking at a report ora matrix or a bar graph. So how you...

...conserve that information up in a waythat's helpful but doesn't take away from their focus on the day to day, youknow the way we approach this was to create curated dashboards for a projectteam and we try to curate them based on their role in the phase of the job sothat there's not endless bar graphs and pie graphs for them to try and noodleall the way through all the information. They're looking for key insights, whatare some indicators of, hey, this could be good or bad. So simple things likestop like coloring red, bad, green, good, yellow or I'll be honest, way toobad, you know, simple things, but they become muscle memory and once peopleget used to that is something they can rely on, then you can start to focus inon the quality. I think quality is more perception of really noodling throughwhat are the questions they need answers to. Okay, so it's it's onething to understand that a cost book item might be a little higher, a littlelow, but why, Why is it off and what contextual data needs to go along withthat to help them understand? Yeah, it's off, but it's off because shippingwas delayed but they're going to give us a 50% discount down the road. Sowhatever, whatever is going to be that's going to help us out long term,these are long term relationships generally speaking. So the quantity ofit, I think we try to manage that by just how we curate it in a way thatthey don't have to go run reports or search for it or go big into the weedsand try and get it. It's simplistic dashboards in the most simplistic way,I've already spent more time describing it than what we thought. We try to puton a dashboard. Honestly, the quality I think comes back to driving into whatare the questions that need answers your super on point here. Andy and Ithink it's so important to be asking those big picture questions about likewhat do we actually want to achieve here because with this influx of newtechnology, if you're consuming, consuming, consuming, without thinkingabout that end goal. It really contributes to what jay and Idiscovered during this research is there's a common held feeling betweenstakeholders, whether they're at a big company or a small company or somebodywho's further along in their data maturity as far as just experiencingdecision paralysis on deciding what the heck do we do? Because there's so muchstuff and it seems really overwhelming and so like we'll get into some of thenuance there but you know, narrow narrowing your focus a bit, alwayshelps in making those improvements. But making sure you do that under the theumbrella of intentionality and then also I think just standardization andhow you capture and consume your data is is so terribly important because itmakes it so it's difficult to look organizationally to, especially if yourprojects are doing everything in a really different fashions. So that'swhen you back up into your organizational data strategy and you'vegot everything spelled out very clearly, it leaves less room for interpretation,ensures that you've got something that's easier to work with and givesyou what you need at the end of the day. So I think we've covered a really nicefoundation of what the state of construction data looks like right now.Plus we learned a little bit about the report which if you're listening, youshould absolutely go download it because there's so much insight thereand regurgitating statistics and data points that she was not an interestingway to kick off a podcast. So I definitely encourage you to take a peekat the final report. It's a lot of fun and there'll be links to that in theshow notes as well. So it'll be easy to find. And if you're a podcast fan,there's an audiobook version, not read by myself, somebody more professionalthan me. So if you want to, you know, work out and listen to a constructiondata, that's a great way to get going. But we we highlighted earlier thatacross nearly 4000 people we surveyed, they identified that one out of threedecisions that resulted in poor outcomes were caused by using bad data,which is really alarming statistic to see. So j I was hoping you could tellus a little bit more about how our listeners can ensure that the data thatthey're capturing is not bad. Like where do they start? Well, I think thisgoes back to something I want to piggyback on the anti mention the dataintegrity. Right? I mean that's that's number one and I think one of thecommon things that we heard, whether it was through the interviews or throughthe survey was that some of there's probably three really common challengesthat impacted that data integrity. And one was I'll call it for lack of betterwhere multiple project inputs. So here I'm talking about things like spelling.I mean we have people who tell us that you would not realize that there are 30different ways that you can spell the name of one supplier because sometimesyou can use all capital letters and sometimes you use, you know, just theregular, you know capital. The beginning of the sentence sometimes itscorpse sometimes it's you know, corporation. But those things althoughthey see minor actually added up from just a, you know, there's multipleproject inputs that gets back to one of the challenges. I said whether it is itusable information, I'm looking for a company. I think it only shows up onceand it shows up multiple times. The...

...other one was just multiple processes.People mentioned, Hey, we found out we had 20 different QA processes. How arewe capturing data? We had a different process on this every single time andthe last one being multiple platforms. You know where we're letting differentpeople choose different software, different hardware, differentapproaches. Some people using spreadsheets and that gets back to thatjust disconnected component of it. Which can contribute to bad data. Justin terms of how we start to share data across. But I think one of the otherthings that really stood out to me and it also kind of gets back to what youwere talking about with the data paralysis was that almost everybody toa man or a woman said that really have to start small and I only start smallbut start in one place. You can't really go solve all this at one timebecause I think it's just too much. But thinking that one area where you cankind of crawl walk run but really just standardizing how that data is captured,creating a common data environment. Those things in my opinion stood outmore than anything is what could really start to addressing the data integrityissues and trying to limit that amount of bad data. Yeah, I think you'reabsolutely right jay is that narrowing of the focus? Not necessarily to bedismissive of all the parts of your business that could benefit fromimprovements but picking something that's easier to tackle, especiallysomething you know, you have a considerable quantity of data thathopefully is good for that starting point to make refinements and you provethat test case to your team and your organization and then suddenly you'vegot more of a green light to start making those changes elsewhere andbuilding into that data strategy incrementally instead of going boom,like we're doing everything today because that's just a little bit toomuch to bite off. Especially if you're a very large organization. Andy do youhave any additional thoughts there? You might have captured some of thisearlier but getting getting to the root of that bad data I think is somethingthat everybody should aspire to that's listening to this. Yeah, I think tojay's point a second, you've got to start if you haven't started by now,you're already behind you got to start start small. To me it's it's focusingon some, some area that you have some data. That's that's measurable valuabledata. I'll tell you for us we started in two basic areas almost financial andthe other was safety and those are the two simplest places. Now Financial ismore complicated but we tried to focus in on a very particular area and kindof grow from there, but on safety it was again, it's not just the data, it'sas jane mentioned multiple platforms, you have multiple people that arecurating that information or collecting it or hopefully collecting it andmanaging the data standards. And there's just a lot that goes into itand then how you're going to get it out to people. Yes, there is much alogistical challenge of this is there is a data problem to this. So it's notnecessarily bad data. It's just it's managing the whole thing and it's it'sa much bigger effort than just rolling up a spreadsheet and turning it into agraph. It's, there's a lot more to it And that's too, I think uh you knowwhen Andy mentioned, you know, your data strategy is likely to change 12months. That's not a bad thing because you're at like if you start small, youstart that once one point and I think in the case studies that we did, thatwas the common thread through everybody. No one tried to solve everything at onetime. They chose one area of the organization where they could apply asolution. And so to to Andy's point That's it's not only okay that thatdata strategy might change 12 months from now. It should change 12 monthsfrom now because you're learning, you're adding to that body of knowledgeand you just kind of incrementally fine. Where's that next thing? What did Ilearn from here that's going to open up something else and it should be becausethe world is always changing anyway and we're just always kind of adjusting toit with those strategies. J I always tell people the more I learn, the lessI know because the more you dig into it, it's like peeling back layers of theonion and you're oh well they can do this well, can I do this? And if I hadthis one extra data point that all of a sudden I can start to tie these thingsout in a different way and and that's you know, it's amazing like the moreyou dig into data, the more you learn, that's when you you've just identifiedyourself as a technology nerd Andy, it's so easy to go down the rabbit holeon this stuff though because as soon as you you built that base layer then youstart going, oh I can do this now that this part of my, you know technologystack and my data is just dialed now. So it opens up new possibilities. Sothere's so much more. And you mentioned one other thing a moment ago that I'dlike to come back to as well is there's a human element in here that we reallyneed to remember as we think about how we work on this challengeorganizationally is in an industry as well because this data conversation isnot only I need dashboards, I need...

...something better than spreadsheets, Ineed information, the improvements to data strategies and the ability toconsume it better and make actionable insights quickly really just impactshow people get their work done. I mean we're all very familiar with long hoursin the construction industry. I work them myself many, many days when I wasstill working for a couple of GCS and I think anything we can do to improve thehuman aspect of getting their work done and then also building that foundationto leverage more advanced technologies to augment what the people are doing.It's such a win for this industry at large and it's it's a challenge. It'snot like you're going to go, I want to use machine learning and then I didn'tcapture any data, it's on spreadsheets, you're going to do that tomorrow. Butif you build that foundation correctly and you think about those incrementalchanges that are attainable to make, you can look at that future state andgo I can make this better And I can support my team better and it allreally does start with the data. So we said data about 10,000 times on thisconversation will keep it going but it's it's just so important but JI wantto come back to the interviews that you mentioned again and I think there wasso many strong nuggets that you got during those conversations that I washoping you could share some more of the success stories or just what really didwork for the people that you were speaking to. I know we've we've coveredsome of the challenges and the bad but it'd be great to just here a few moreexamples of we did X and it worked really well and this is fantasticbecause it's a challenge but it's an opportunity at the same time I guess isthe right phrasing from my perspective. I mean in the interviews because thesewere done you know across multiple geography is across the globe. It wasinteresting to get different perspectives from people in differentparts of the world even though I would say that there was still sort of acommonality to some of the issues and some of the solutions and as you posethat question to me, I would say maybe there's two or three that stand out butI could bucket these into one was a story about the what you know, what dida data strategy do for their organization and the other one or two Imight share with you is more along the how how did they actually make thiswork? And so if I start with the what and again, it's a continuation ofreally a lot of the same themes that we've been bringing up about. You knowthat you know, there is a time element to this that you learn from the dataand that's, that's part of the beauty of it in my opinion is that is onething occurs and you see what that does. It opens up an insight to somethingelse and next thing, you know, have a string of pearls, you know, to reallylook at in terms of all the things that are quite possible. But in one of theman individual I spoke with was talking about how one project is not enoughmeaning trying to collect that data. One part is when you start to combinethat project data across projects and even across other different aspects.That's that time element. It's not an overnight fix. But one of the areasthat they had sort of migrated to overtime was combining their projectcost data with some of the damages data they were collecting, you know, lookingfor correlations and saying, what do we find from this? And they were able toactually take some of the, I'll say the average number of damages or defectsthat they experienced, you know, per sort of a dollar sort of amount. If youwill in a sense, we were able to start to say, okay, we're not getting tonestle in the realm of predictive analytics here, but at least a red flagthat started saying, hey, when we start to see the number of damages or defectsper dollar you reached this amount or whatever that amount was, it's justsort of fluid kind of triggered something for kind of like what Andywas saying you're kind of red, green, yellow and it allowed them sort ofaddressed those things earlier because they knew when they got over a certainamount, you started to run over budget over schedule whatever. And so in a waythey were creating rules if you will, that served almost like pre decisionmaking, right? It takes some that cognitive sort of stress out becausethe rule is already looking for some of these things with all the other thingsI got to be thinking about. I'm a project manager on day to day basis.Having those rules in place that kind of takes them that cognitive load offand be looking for those things was super valuable to them because of thecost savings that they were able to realize as a result of that. And Ithink that also just gets back to one of these other things were alreadylooking at industry. Well we're working on such thin margins and we hear peopletalking all the time about looking for profit pockets, you know, from aconstruction contractor perspective, this is quite one of the best profitpockets out there, you know, because you're plugging holes basically in thebottom of the bucket to increase that...

...profit side on the other side that thehow you know, I mean the people mentioned, I talked about the oneperson I spoke with that brought up the whole issue of data literacy and againI'm sorry to keep going back to things and he said, but there really is acommon theme here was the realization that having the data being able to runsome of these calculations and these correlations and everything else wasfine but somebody has to consume it. And so that data literacy, the way theysort of address some of that was just how did they present it in regulargreen? How do you make it intuitive if it's if you're trying to make somereally fancy, you know, analytic type of report the likelihood of being usedwas really poor. They had to find ways that it was instantaneously understood.I can see what it means so I can avoid those bad decisions and you know, kindof maybe along that same line we found that some another organization usingthings like ipads and tablets, are they trying to push out some software on alaptop was a much better approach because people were more intuitivelyable to use the tablet or the laptop comparative. They were trying to chooseanother program. J I really appreciate you sharing the insight there with, youknow, just the people that we spoke to and the success that they've had and Iwant to come back to the first example that you've gone and I'm gonna kick thequestion to and because I I think he might have a good answer for us on thisone, but I think it's important to identify how we can start making apivot from only having our data support in the moment project level decisionsand using that data and moving it into an environment where you can leveragedata at that organizational level. Andy do you have any thoughts there on onsteps that you can make to start making that transition where you can take yourdata from project to project instead of it being captured once and then neverlooked at again. Absolutely. You know, absolutely. I think this goes back tothe data strategy and this is something that we were very planned full of outof the gate. I can tell you that it went perfect. And I can tell you thatthere were technology challenges along the way that prevented us from doingsome of the things we really wanted to do because jay mentioned it's not justone platform we're using we're using a couple dozen platforms that arecollecting data that we want to have fed to the project. Teams are fedacross the organization. And so the approach for us out of the gate was onewe want to make sure we had data collected, the easiest way to collectthat was hopefully in the cloud or in a centralized location. But beyond that,the data had to be cross project in nature. So whatever data we werecollecting at the project level, we ultimately wanted it to roll up to across project level so that we could really understand, okay, well we'rehaving quality issues or we're having safety issues, what kind are they? Andthen if we have a consistency that we're constantly having issues withpeople wearing hard hats or something like that, that we're able to identify,we have a training issue or opportunity, right. Or we're seeing issues in peoplegetting payment on projects or something like that, you know,understanding is it systematic or is it a systematic issue on a project levelor is it symptomatic of an organizational problem in the way thatwe're managing, reporting on data or the cadence of the reporting or howwe're following up. So there's a lot of, a lot of that that goes into the datastrategy itself and I want to make sure I touched on this a second ago that shewas talking, you know, the industry is all abuzz about data and analytics anddashboards and everything in reports or emails or however we communicate areall just vehicles for sharing the information. Right, and how we do thatreally kind of approach that away. How am I going to meet somebody wherethey're at and hopefully evolve them over time because it's not going to useit at the simplistic most simplistic level. They're not going to use it whenit gets more complicated and what we, what we learned in some world war hasbeen, we developed dashboards with some really simplistic KPs and then overtime there were more questions that were asked. So it wasn't so much a datastrategy that I had to evolve. It was okay. We've hit a certain level ofcomprehension of using the data. Now we want to do more. Now we want to knowmore. Now we want to know the why or we want to know how to prevent something.So there's one of the things you private santiago was understanding orkind of evolving people through the use of data helping people understand,there are different types of analytics and some of them are telling you whathappened there, the parking ticket or the police report. Some of them aretelling you kind of why it happened. Well they parked in front of a parkingmeter and then there's understanding more of, you know that predictive orprescriptive and understand what's likely to happen, what would happen ifwe did this and prevented it. Hopefully we could save money and fill some ofthose holes. So you work constantly looking for ways to avoid project fadeto go along with those profit pockets...

...because then you actually realize thefull value of your effort in the project that your customer, your clientis getting the full value of delivering a project on time and on budget. Andthen in return by working smart and communicating really well with yourteam, you're able to recognize the full profit on the project as well, whichhelps everybody. So I think it's really important to understand that the datapiece of it is really driving all these other aspects of the project. I reallyliked the phrase profit pockets. By the way, I'm gonna steal that. I hadn'theard that one before and I'm gonna, I'm gonna capture it and start using iton the show with some more regularity. So those that are listening for to meto stealing that one. But I'm gonna float this question out to both of you.Whoever wants to jump in on it first is completely OK because I'm not surewhich one of you is going to have a stronger opinion but how does thebaseline that we're building here with the data strategy and intentionallycleaning our data lead into some of this more advanced technology, likeartificial intelligence, machine learning, predictive analytics, virtualreality. I just love both of your gut check on like how this all inter playsand you know what the future or today brings because this is stuff that'sbeing used right now in the industry is some of our recent episodes wouldhighlight very clearly. I think it's how do you create a foundationaleducation, right, And that's probably a silly way to describe it, but if I'mtrying to teach someone to drive a car right, I'm not going to tell them howan internal combustion engine works and you know, how the metal comes togetherin its form, don't explain to them that, you know, the gas pedal and thesteering, and this is how you make sure you go, you know, in the break. And soI think in some ways, what we've been talking about so far today, that'swhere we want people to start, you know, artificial intelligence, machinelearning, that's understanding how the engine works, That's, you know, that'sgoing from Algebra 1 to calculus or whatever. So I think it's necessarythat I think that you're ever going to get to that stage or just jump in atthat stage. I think you're misguided, we have to start at sort of at groundlevel and I think that's what this represents. And and the only thing Iwould say is just so that people are clear, the data strategy is not the endgoal. The data strategy is the vehicle by which we're trying to accomplishsome other objective of the organization which is either betterdecisions and the reason we're trying to get better decisions, so thatprojects are successful, not only for our clients, but for our company aswell. We just have to keep those things, I think in my mind. Yeah, I agree. Youknow, I think an important aspect of this too, is as I kind of sit here andthink about this is we've been very purposeful about having an integratedapproach to technology. And what I mean by that is we have data coming from somany different places. You can get value out of one platform reporting onone thing I can say, you know, whether it's cost or safety or something likethat. But then what happens if you start to you mix them together, whatother insights can you start to get? And, you know, thinking beyond, youknow, right now, we're trying to get the H. I. To keep up with all the dataand the Ai and the ml aspect of this machine learning in and of itselfsounds like a big scary word. It's really just computers learning how to,you know, more efficiently processed data so that we can consume it moreeffectively. The same thing with artificial intelligence is, you know,we gotta teach the Ai to figure out what we want to know to some degree.And then at some point, that kind of flips to the other side where all of asudden, you know, in some utopian world, we're just inundated with so muchvaluable data, we're going to go buy lottery tickets every day. But until weget to that point, you know, let's let's learn together with some of that.Take some of the scariness of the black box away. I think J. J is perfect.Let's teach people have the fundamentals of how to drive the carright now we'll get to the other part because as soon as we have thatfoundation and they start to understand the basics, then they're gonna go, okaynow I want to add on some new chrome parts, I want to do some more excitingthings. I want more ways to slice and dice the data or drill down into it andthen they're nerds starts to show, right? And when we're all nerved outtogether, deacon out together, that's great. But at that point we all have akind of a level set together. We're using the same terminology, we'rereferencing the same data sets and saying, yeah, I know what we got thisdata, it came from here and I know when it's gonna get updated and I know howmuch I can trust of that data that is half the battle. And you know, once weget over that hill, then we're on to greater and greater things. So, youknow, as jay said a second ago is let's get let's make progress, let's movepeople forward, we're never going to be done. We might be substantiallycomplete, but we're never really done and it's going to involve. So I thinkthat's the great part about being a...

...human is that you learn some, you goapply it, you learn some more, you go apply that and it's a practice. So Ithink that's what's exciting about it to begin with. Yeah. And having thatsafe space to to actually go out and do that, you know where you catch peopleif there's a misstep, but you're all learning at the same time to improvethat overall street energy. But j I really like your analogy. I'm gonnasteal that one from you too because it's it's so important to ensure,especially early on when we're starting this process that people have theinformation they need and understanding is relevant without giving them the howdoes a combustion engine work? How do I change my tires? How do you do all thisstuff? Not that that information doesn't have value, but you'reproviding it at the moment that it's relevant for them and helpful and isn'toverwhelming. So it's that iterative process. And then once you do lay thatfoundation and then you get to qualify to everybody like these more advancedtechnologies that we can now start implementing like machine learning orartificial intelligence. They're not scary tools and they're notreplacements their augmentations to what humans are already do well. Andthey also capture the elements of things that humans do not do? Well.Like look at 25,000 site photos to identify site safety incidents. Like ifyou tell your, you know ahead of safety that that's their job tomorrow. They'renot going to be very happy with you. But you know, this advanced technologycan, can really augment in a way that makes us more efficient and then alsosafer at the end of the two, which is obviously paramount for our industry.I've got another question for both of you because I think it's allinterconnected to data literacy and understanding what to do with thistechnology and the information available. And then also how so Andy doyou have any guidance based on what you've been doing at Carrick or anyindustry best learnings on how we can make meaningful improvements in dataliteracy for those out in the construction space, you know. ErICthat's a really great question and and for a couple of reasons not to qualifyyour question, but I will tell you that, you know, it really, the audience isreally important understand. But you said earlier, it's all human for themost part, right? People are using this information or they're not and thatthere's a key distinction there and so what I think we've learned or what I'velearned at least, is you have to meet people where they're at, to a certaindegree so that you can get there by in, in the process, you got to get themcomfortable with the terminology. You start throwing acronyms that people andthey turn off immediately and it's like I've been done. It's like, no, it'sokay. It's okay. It's just one word, one acronym. I promised theseoverworked club with 50 of the whole room, just evacuates. Like there's noway. So we've got, I don't want to oversimplify it because it's importantthat people understand it is serious stuff, right? But at the same time yougot to meet people where they're at, you know, it's like I said earlier,it's a journey. We're all on it. It's all philosophical, I hear. I know, but,but once people start to have a feeling and you know, if you're leading thistype of effort within your organization, you have got to be consistent. You haveto constantly be beating the same drum week after week using the sameterminology, putting it in front of them speaking to it on whether it's ona presentation board or on a dashboard or on a piece of paper in front of them.Whatever means connects Is consistency. Once they get more comfortable. Thatbin is a thing. It's been around for 40 years. It's a thing. What does it mean?You know, I've heard jay said earlier, there's 30 different ways. This fellowcompany's name, there are 50 different ways to figure out what the acronymstands for the worst of which is the google it. So put a data dictionary or,or a basic list of, here's the things we're gonna be talking about and giveit to people ahead of a meeting, give it to him ahead of a presentation, letthem know what they're getting themselves into this, Just kinda helpsthat one side of surprise when they hear it for the first time and they'relike looking at the cheat sheet trying to find it. But then the more you cantalk about it, you know, as you're going through it the first time youwalk somebody through a dash border report, help them understand whatthey're looking at. You know why the things are here and make sure that youconstantly put yourself out there. I'll tell you like the vulnerability pieceis really important this, but you're never gonna get there by and if theydon't think that they can kind of like chip the edges a little bit and letthem know that it's you know, it's not like a lot concrete box. If they've gotquestions let him ask, let them let them challenge you. They don't believeyour data. Great. Now you want to hopefully have the right answers, butif you don't, that's okay and you may not, you likely will have all theanswers and being comfortable with that. That is really critical because onceyou know that then you start to understand what are the questions thatreally want answers to challenge them right back. You don't like this. Why?How can I make it better? And then make sure again you kind of manageexpectations, okay, I hear you. This isn't perfect. This is what we havetoday and this is kind of how it works,...

Give me three months built in somespace. It will take longer than you think, but let them know you are goingto make improvements on it. And jay said earlier, the consistency and thecompetency to actually come through is critical to the trust because it's notjust the data they're trying to trust, it's you, they're trying to trust andit takes a while to build both of us. I think you hit the nail on the headthere and you've got to take your people along with you on this journey.It's not a prescriptive action where you show up and go, hey everybody, wehave a data strategy now, so you're going to do this because regardless ofif it's the best data strategy that applies to every nuance of yourbusiness, you just brilliant. Like you show up with brilliance. But if you,you know, bring it to the table in the wrong way, you're still gonna havehesitancy, hesitancy and resistance. So it's it's a conversation and makingsure you're checking in along the way. So Andy I really like your approachthere. And the other cool thing that's kind of happening now is the differenttechnology that we're implementing either on projects or in the officelike 10 years ago. This was all the realm of the VDC team where it was likeadvanced tech of V. C guys do that. I don't, I don't mess with that, I don'tknow anything about that and that's a totally different conversation nowbecause the technology is accessible, it's easier to use and understandable.The U. S. Are better. The gadgets that we have are great. And if you have theright tool in the right superintendent's hand, I don't care ifhe's never sent an email in his entire life. If you can show him that it addsvalue and it's easy to use, you can get them to use it. It's just empoweringhim in the right way. Instead of showing up and going, here's an ipad,all this stuff is on there that you need your good now. It's like no nohe's not like you got to help him along the way. J do you have any thoughtsthere from any clients you've worked with in the past? As far as justensuring that data literacy pieces is so important because I think it's it'skind of the other crux like it's the other part of the data conversation, wecan have the best data in the world, but if you know those out there, don'tknow how to leverage it or use it. So what you know, you know, real simply itcomes down to two things. One is understanding the relationship andthere's no difference different than normal literacy, right meaning. Okay Iunderstand how these letters come together, these letters form a word.These words come together and they make a sentence and since come together makea paragraph and you know I understand the relationship and to me on the dayof literacy literacy side it's the exact same thing is understanding howthis set of data in this set of data tell me something of value. Therelationship and the connective tissue is where all the value resides in this.And to be understand that when this happens we get this result. You know,whether it's predictive or trying to understand all that's so important. Andthen the last thing is I think where people have been more successful asthey realize that all this is what they do with not to do too. And thedistinction between that is here's what I do with this to make my life easier,make my job's better versus something that's being pushed down. This is youshall do this without any explanation, explanation of that literacy side ofunderstand well why am I doing this? Why do I care about these settings andhow do I understand that relationship? I really like that. It's it's just areally deliberate process to bring all of this together in a way that impactsthe bottom line of the business but also impacts your people at the sametime. Like it's a very important relationship and balance to maintainand everybody's sick of talking about the labor shortage. But if you're nottaking care of your people in this particular moment, they're going to gosomewhere else and replacing them is going to be an absolute burden. And ifyou want to go back into the Trust Dance J and I did a lot of work tryingto figure out how much that actually costs you to replace those top tiertalent. Uh it's not a small number so go back and check out our trustedconstruction report from 2018 if you're interested, but I want to get thecrystal balls out now and so let's pretend that harnessing the dataadvantage and construction was the lever to pull in the industry and we'reall jumping on the data strategy train and we've got all these improvements ofcourse I I recognize that that is very aspirational but hopeful at the sametime like where would you guys say or feel like we're gonna be in say 10years time when it comes to our relationship with data in our abilityto effectively leverage it Andy could you kick this one off for us? Well I'lltell you, I wish that I had all the answers to this question. You know, I Ican't tell you exactly what's going to happen in 10 years. My my insight tellsme that if we're really if we're embracing all the technology that wehave today to its fullest capacity and realize, you know the bell curve, Imean everything is supposed to just be taken off vertical. We should be at apoint where not only is the data getting better and the inside isgetting better, but the use of it is...

...getting better. I would like to thinkwe get to a point at some point in the distant future where the people, youknow, so we're focused on the people in terms of helping them do a better jobto rest easier than making the right decisions, make sure they go home ontime and watch your kids play baseball, you know, have a life, you know, likepeople work to live, they don't live to work. So that's to me, my goal hasalways been, how do we get people home on times they go spend time with theirfamilies and do things like that. So to me, if we're really leveraging thetechnology, we might get to a point where, you know, this, what if Covidhas taught us nothing else, it's taught us that we can work remote. You can'tbuild remote, you can pre fab remote, you can't build on site remote. Sothere's, you know, there's not a one size fits all answer to all of this,but we may get to a point where the concept of remote project managementbecomes more of a reality. I mean, we're already doing aspects of it,having job site cameras and 3 60 cameras and drones, flying sites andscanning for not only, you know, earthwork, but progress and being ableto, you know, scan back and forth and look at what happened last week, Whathappened this week logistically what's on site, what's ready to go, where'sthe tower crane, all that kind of stuff. I think we're going to get to a pointin the future where the Ai is going to start to learn more about our creaturehabits like what do we constantly do on job sites? You know, when it's on theoutside of the building with us on the inside of the building, when it's a bigside project, when it's not, what are the common things like that's what I'mexpecting from the A I wanted to start seeing the things that are blind spotsto us. I think we get to that point, you know, we may be working from thebeach one day. I don't know that all of us will be, but we got to get to apoint where the technology for the longest time. I've told people, youknow, if you're expecting technology to make your life easier, you're lookingat it wrong, it should make your life better. It should make your decisionsmore. Sound easier, will come with better. But it's gonna take a while andso to me that's kind of where the opportunity lies right now is let's getbetter. Let's get adopted. Let's let's go proficiency in the tools that wehave because they're different. This is gonna sound super nerdy eric but youknow, you might, you might want to, you might want to pitch this on the trademarket for later. But Excel, you know of yesterday has always been the toolthat people leaned on. But I'll tell you whether it's power be I or one ofthese other B type solutions. I mean the I tools are becoming the new Excelbecause what you could do in an Excel file in a spreadsheet, you know, wasjust digitally what you were doing in a paper notebook that our field guys hadbefore our accountants had in the past. But B I tools are quickly becoming thethe Excel file or the Excel tool tomorrow because not only can you startto analyze specific data, but now you can start to think about it in a biggercontext across one project or multiple projects or one scope of work ormultiple scopes of work and that's where the deeper inside start to comefrom. So I know it's kind of probably a longer answer you were expecting, butthat's kind of how I see it. It's good, it's it's an evolution really. Likeyou're, you're absolutely right. Like Excel is still an important tool in theright circumstance, but we were behold into it because there weren't customtools that suited our industry for such a long time. Like fortunately that haschanged now and we can leverage new technology, be more effective andcollaborative and we don't have a, you know, a Myriad of Excel documentsliving on a Microsoft server somewhere that dies in the middle of a bid dayand you know, the drama continues. So we're past those days thankfully thedata is no longer locked up for an Excel cowboy to own it. You know, theircomputer goes down. You've lost all that information. That's the value of,of using tools that are more platform Miranda's. Yeah, you may have some baddata, but at least you don't lose it and you know where it came from and youcan go back and clean it up if you need to but you don't lose it and you don'twant it all. And a lot of that is not useful for long term. But what you havetoday, you definitely want to make sure that it's there and reliable. So yeah,you've got that that accurate and solid common data environment to build on.And I liked your point to about that working remotely. And obviouslyconstruction is always going to be a blended approach because we're buildingthings like, like you have to be there to build the thing to a degreeregardless of what's going on. But the one of the silver linings that's comeout of the pandemic is I think a new, an honest relationship with whereremote work fits into the different industries that exist in the world. Soit's going to be different for construction than it is going to be forinformation technology, etcetera, etcetera. But in addition to making ourtime more efficient, it also has opened up potential access for opportunitiesto a wider scope of people so you can have an absolute data nerd that livesin Idaho and is just gonna crush your, you know, dashboards and all of thisstuff and your projects in SAn Diego and that's okay and now they haveaccess to that job and they didn't have...

...it before. So that's I think one nicething that we can kind of build on and iterate and it's going to be a bit of afluid process for our industry specifically, but it's an important one.So j if you're getting your crystal ball out and looking at, you know 10years down the line, what what do you think is coming our direction? I thinkuh kind of piggyback on the conversation, I think tool is theoperative word here because I don't think it's 100% but I'd say 99.9% ofpeople in this industry are in it because we love what we do, we lovebuilding and you know, you think about con expo or in these other big eventswhere the latest, you know, kind of new tool is out there and everybody wantsto use it because not necessarily because of that tool itself is becausewhat it allows me to do, you know, like, well, you know, I really don't want ahand shovel because I really like digging with my fingers or you know,I'm just gonna stay with in shovel and you can have the pneumatic shovel overthere. I mean that we don't even think about that, we're automatically goingto adopt those tools because we immediately see how it impacts ourability to do what we love doing. And and and he said, I mean, to work so wecan live so we can really have a legacy of these great projects. But I thinkthe other side of it's true as well, and I think one thing that gets lost iswe often talk ourselves as builders, but construction is a professionalservices industry. I mean, that's really what it is, no different thanthe legal profession, accounting, you name it, we're professional servicesbusiness. And why wouldn't we use tools that include data to make that part ofour industry just as better as we would move from digging with our hands tousing hand shovels to be using pneumatic shovels as well. And sothat's really my hope and I actually right wrong or indifferent, veryoptimistic about our industry. I really think that we have some of the bestpeople in the world working in our industry And they will do this. It justtakes time. You know. But in 10 years, hopefully you know, we'll look back atthis conversation and I remember we were talking about that, that seems sosilly to talk about now because everybody is doing that. And so that'sthe way I look at it. I mean it's professional services business, it'sabout making good decisions is what a professional services business does andhaving that data and that information, you know, not to replace, you know,what kind of we know from our personal corporate experience from just that gutknowledge. But is that additional aspect to round out, make us the bestindustry and the best decisions possible before. That's my hope in you.I share your optimism. J I think there's a ton of potential and even aswe were alluding to earlier with the influx and innovation and venturecapital and like a very strong focus on construction like this industry impactsevery single human on the planet. And I think sometimes it's easy to forgetthat aspect because we're just in it in the built environment and we're, youknow, professionals working in this space but it's just so important toimprove and reduce waste and all these other things and technology I think isgoing to be one of those levers of change that we get to pull that's goingto really positively impact, you know, not just our industry, but the entireworld itself. So we're wrapping up to the end of the show and as you can see,we've got three data nerds on the call today. So we we went a little bitlonger than usual. But I think that's okay because there's so much greatinsight here to just jump in and say where do we get started? Like we'vereally highlighted, Okay, there's some challenges that our industry has. Thosechallenges are commonly shared across all the different stakeholders,regardless of project size or company type or location. But we have thisincredible opportunity to really start making meaningful improvements in bothon a revenue basis and just as a, you know, a way we get work done. But I'vegot one final question that I ask each guest and J you've been through thisone before, so I'm going to kick it to Andy first, but what is one tool thatyou will always carry in your toolbox, no matter what project you're workingon, I'll tell you for me it's going to be curiosity. It's as simple as thatcuriosity to ask the questions to challenge things that are there.There's all kinds of tools in this world that you can use to get to thoseanswers, but you have to start with the curiosity to at least care to know theanswers. So I think that's the most simplistic answer I can give you now, Ithink that's great and asking questions, it is a skill, it's not, it's not justsomething casual to go, gosh, you have so many questions retired of it, likehaving that onus to one care enough to ask the question and then also thecourage to ask the question because it's it's uncomfortable askingquestions sometimes, especially if...

...somebody is uncertain of how they maybe perceived by asking it, but being able to come to the table and you know,put that foot forward has an impact for you know, yourself as far as learningand bringing in new information and ultimately the projects we work on,because it forces everybody to have what might be a difficult conversation,but also a meaningful one at the same time. So thank you for sharing that jay.How about you? What is your one tool that you will always carry to anyproject you're working on? And I know we've already made you do this one time,so I'm interested to see what comes out on round two. Well, you know, it'scalled a toolbox for a reason, so it can hold multiple tools or mail that Iwill say, one that maybe don't say it's a new tool, but it's one I'm reallyworking to master and it's a complimentary sort of angle to whatAndy mentioned and that's that's listening. I've been really fascinatedwith a lot of the, I'll say the insights and thoughts of Juliantreasure if you're not familiar with him talking about listening. And thedifference that listening is not the same as hearing And one of things hetalks about is you know that we should be listening 60% of the time and onlyspeaking 40% and how is the easy trap to get into, you know, where I'm notreally listening, like I'm already thinking about what's the next thingI'm gonna say, how am I going to respond and everything that person issharing me that information and I have that curiosity that and he's talkingabout, it doesn't matter if I'm not listening to what the other person issaying, what other information coming at me is saying. And so really I'vejust been trying to really kind of see how I can put into practice reallymaster that listening aspect is Julian treasure has really kind ofdemonstrated more and more each day. I appreciate that context and you'reabsolutely right on. It's sometimes very easy to get into the position ofI'm waiting for my turn to say a thing now and there's value there and that'simportant sometimes. But being able to find that balance between I'm consuminginformation because this person is sharing something important with me andI also have something to add to. The conversation is key and jim lynchactually on the last episode said the same thing, J so you guys are in lineas far as which, which tool you bring to the table. But we talked a littlebit about how that changed in this world that we're in now with very heavyfocus on video calls. So it's very easy to fall into. I'm here and I'm present,but I'm not necessarily listening because I could be scrolling through,you know, whatever website I wanted to to check on the news or facebook orwhatever while you're sharing, you know, your insights, but I'm not reallyactually listening And so I think doubling down on the intentional andactive listening is, is probably a good skill for all of us to have in thispost, covid semi remote work life balance that we're experiencing here.So I know both of you are working on some really exciting stuff and have alot of external opportunities coming up. So I want to make sure I give you bothan opportunity to share what's coming up and talk about anything that you'reexcited about right now. So Andy is there anything you'd like to plug orshare with our listeners? I would say that not only working on things, we aregrowing at an amazing rate right now and trying to keep up with thatworkload and there certainly is always challenges with hiring people. So I'lltell you that we are absolutely hiring. So please, it's got to be on linkedinor on twitter either way, I'm on twitter at three D and the leak onlinkedin just got to google me. I think I'm pretty sure I'm the only guy herethat works at carrick in this role. So that aspect, I'll tell you the projectsare just getting ever more challenging. I've been very fortunate my role tospeak at a lot of different industry events and help help kind of hopefullymove the industry along and get buy in and we're really looking for peoplethat are just curious, excited about technology, excited about building moreabout building than anything. I mean the technology we can always teach butwe cannot teach people to be curious. We can't teach them to reach out andand want to go for that next challenging project. I mean the gritdetermination to be in construction or even in pre construction and I thinkit's important to point that out that we may spend 12 or 24 hours building,but we may have spent 12 or 24 months planning and there's a tremendousamount of work and technology that goes into that part of the project as wellworking with all of our design partners and all of all the folks that prefabthings and so on. So there's plenty more coming down the pipeline in termsof new technology, new opportunities. We are fortunate to be a builder thatis ready to move and go around the country and work on large and smallprojects. So by all means if you're excited to come and work with somebody,let me know because we got all kinds of great stuff going on. I love this Andyyour, this is a digital builder first, as far as a recruiting moment on theshow, but I really like it and for anybody is still out there listening ifyou're interested. I mean you've had an hour to listen to Andy speak abouttechnology at this point. So if you...

...like what he said, like shoot them alinkedin message, we may have an opportunity here. That's great jay. Howabout you? Do you have anything you'd like to share with our listeners beforethey head off into the distance? Sure. Well, I mean the first I've got to sayis just the excitement around being a part of the harnessing the dataadvantage and construction report. I mean, I really think this is just areally groundbreaking study that everybody in the industry should reallylook at. So it was really a it's an honor and a privilege to be a part ofthat. So really excited to see where this one goes and then just secondarily,you know, we have our next north America construction overview comingout towards the end of the year. It's not just, you know, where'sconstruction spending going, but it's, you know, how is it going, You know,what's changing from a composition standpoint and understanding, you know,where the markets maybe next year and the years after. And so you'll probablycatch me on the speaking circuit talking about that a couple of times atthe turn of the year. But other than that, this will be the big thing.That's great and I agree the project that we worked on on that report was anabsolute pleasure to bring to life. It was a beast. But there's so much greatinsight in there. So you have, if you're out there Absolutely worthchecking it out. We've got info graphics. Here's a recap blog. Uh jumpon the digital builder blog. There's obviously an audio book that Imentioned and jay and I are co presenting on a webinar on october 28thI believe, where we're going to get a little bit more into the data portionof this versus what we did today. It's a little easier when we've got visualsinstead of an all audio format. So that will be worth checking out and signingup for as well and we'll include a link to that in the show notes. So outsideof that for those out there, still listening. Thanks for taking the timeto join us on this episode of digital builder. If you've got any questionsfor me or want to appear on a future episode, you can find me on linkedinlike everybody else or via twitter at builder underscore digital and ifyou're enjoying the podcast, please do rate the show on Apple podcasts orwherever you do listen to podcasts. All you've got to do is open the app, finddigital builder and select the number of stars that you think we deserve.It's that easy and it makes a serious difference for my team and my bossspecifically would be very happy if those numbers go up. So please go outand like and rate the show. I would sincerely appreciate it and then ofcourse you did like this episode. Please share it with your friends. Andon that final note, goodbye. You've been listening to digital builder toensure that you never miss an episode. Subscribe to the show in your favoritepodcast player. If you're listening with Apple podcast, we'd love for youto give a quick rating of the show, simply tap the number of stars youthink the podcast deserves and then you're done. Thank you so much forlistening until next time. Mm hmm.

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