100 - Forecasting Project Completion Using Limited Data with SmartPM's Michael Pink

Welcome to Listening with Leaders. I'm Doug Noll, lawyer turned peacemaker. I teach executive leaders how to listen to emotions rather than words so that they can become the leaders everyone wants to follow. And I teach those same leaders how to be authentically present, available, and connected to their families despite being insanely busy. I have learned that we are 98% emotional and only 2% rational. Learning how to listen to emotions is, in my experience, the foundational skill of life. Stick around to the end of the show, and I'll reveal how you can be on our next guest in 15 to 20 minutes. So let's get started.

Michael Pink, welcome to Listening with Leaders. You are the CEO and co-founder of Smart PM. Which can be found at smartpmtech.com. Welcome to the show.

Well, thank you so much for having me today.

Well, we were talking a little bit before we started recording, and we both come from a construction background. I, from the litigation area when I was a trial lawyer, I did a lot of construction litigation, and you were a consultant in disputes and claims. So it was pretty interesting to hear that we shared some similar stories.

Absolutely.

Tell us a little bit about your backstory. And how you got—

Sure.

How what? And how you got to SmartPM, how you started.

Oh, absolutely. Yeah, I will. I'll start with getting out of college. I was what's called an industrial engineer. I went to Georgia Tech and industrial engineers are people who help add efficiencies to processes, right? So somebody who maybe helps an airport be more efficient with processing people or maybe helps the manufacturing company become more lean. And optimize and make more profits as a result. So it could be anything, helping, you know, processes improve through added efficiencies and minimizing waste. I had worked for a contractor in college to make some money because it was a good opportunity to just make $15, $20 an hour. And they had very good hours that I can choose from to make, you know, to work a bunch and make some money. And that was put on my resume. So when I graduated, my— one of my offers that I received, which was in New York City where I wanted to move, was with KPMG in their construction consulting group. And what we were doing there for the most part was dispute resolution or claims management or claims analysis for projects that had gone over budget and/or were late. As well as fraud analysis, actually. We did an investigative and integrity advisory services. So projects that were getting people stealing money and whatnot up in the Northeast, you know, those were other interesting things. But really what I was able to figure out was how do you take data in construction and, and learn about a project better than anybody who lived it such that you could testify to it. As an expert witness and/or, you know, prove that somebody was, you know, prove where all the money went and why it happened, even though the project was, you know, basically done. So I didn't live it. I could go to the data. I could understand it. But the story had to be so accurate that, you know, you could testify to it and write an expert report about it and it would be right. So really what I had to learn how to do is understand data because it was over. You know, the project was over and That went on for a long time, but I did learn a lot about what data is important in construction. But I also, as I mentioned to you before, you know, I started to see patterns of mismanagement, right? Started to see, you know, areas where I'm sitting there looking at the data going, how did you not know about this at the time? And how did you let it continue on? And how did you not talk about this to fix that problem? To now be, you know, months if not years late and tens if not $20 million over budget. And who's going to pay for that, right? And why did— and we'd have to not only decide what happened, but who, who was asleep at the wheel while it was happening. And, you know, you just sort of pick up a lot in that process of a lot of breakdowns. You know, again, going back to industrial engineering, I'm a guy who studied added efficiencies and waste, and I'm sitting there on the back end of a project saying, oh, here's what happened. Uh, so that was something that always perplexed me for years, is why am I not helping solve this problem. So that's really where I decided to move, is, is not sit there on the back end of a dispute to help somebody argue over money that was gone. But how do we help them look at the data, the good data that I know about now, and do it in a manner that doesn't require paying $300 an hour for a consultant and do it in a manner where they could look at the data because they had access to it, put it into a system that would enable them to understand you know, the risks and all the performance issues that are happening in real time so that they could manage outcomes better, so they could avoid that problem. And that's really what SmartPM was, was my— taking my experience and my understanding of information that was available on projects and coming up with, you know, technology that could analyze that and present it in a manner that people could use before the problems happened to ultimately get their projects done on time and on budget and stay out of court.

That sounds like a very complex undertaking.

Mm-hmm.

To build a platform that can absorb the data from the various planning programs that contractors and owners and people use, to take all that data and then reconstruct it into something that gives you analytical information that you can act on. How do you go about developing that?

Well, first of all, you have to, well, for me, I had to not think it was going to be that hard. So I had to believe that, oh, it's going to be this easy, you know, like, I'll just quit this job and I'll just go, you know, build that thing I can't stop thinking about and then it'll sell like hotcakes. That's sort of the mindset I went into. I had started a business to get away from the dispute side, and I decided that after a few situations where I was put into a position where my integrity was being questioned, not me personally, but people were asking me to do things that I didn't want to do on behalf of customers or clients, and I felt like I couldn't I couldn't spin the data enough to make my company happy. So maybe I was in the wrong business. So I wanted to be more proactive anyway, and I had some ideas on technology, but I also knew that there was ways to get involved earlier in a project as a consultant. So luckily for me, I started a business where I was able to make money and doing something that was more proactive instead of reactive. And all the while, you know, people were looking for a reasonably, reasonably rated consultant to help them be more proactive. And I was the guy which gave me some runway to explore the idea of building this technology, um, you know, by making some good, you know, some extra money, uh, than I was as a salaried employee. So I landed a couple projects and I was able to, you know, make money and then put some of that money into the building of technology and sort of build a business while building a technology And while I'm building that technology and offering a service, I can sort of move into a tech-enabled service and then ultimately do that long enough to bring it to a, a full platform on its own. And that was really the process that we followed, was able to bootstrap easier than most because we had a revenue stream and we did provide a service. And then as we built out that technology, we used the technology to be more efficient than the competition and eventually We're able to create a hands-free platform, as I call it, that doesn't require me anymore.

You, in our Authority Magazine interview, you told a story about that I thought was fascinating where you were giving a demo to a potential client and they gave you half of the job data. Tell us what happened there.

They gave me half of the job data for what?

I think, I think they wanted you to demo out the platform, and they gave you half the job data. You didn't even have the full job data, and you input all the data. And if I recall the story correctly, you predicted within, within one day when the, when the job—

Oh yes, yes, this was an interesting one. And this was actually more when I was doing the manual side of things. Um, we, uh, we worked on a project down in Brazil. Uh, it was a massive project where we were asked to study delays and impacts. There was all sorts of claims, like this was a big $6 billion or $3 billion project that went to $6 billion steel plant. And, you know, they had 10,000 people on site, some people from China, some people from Germany, some people from Brazil. All the contracts were in English, consultants all over the place. And You know, there was— as soon as these people got working on the job, they secured the contract, they were submitting like claims for hundreds of millions of dollars. And, you know, you've got all these people from all over the world are building this plant for one of the biggest companies in the world. And all of a sudden the budget's getting just absolutely destroyed. And it's, you know, we're about 50% done on the job. And, you know, we dealt with all the claims. But then the question was, when is this— when is this going to get done? And we were asked to take all the schedule data, which was garbage schedule data, by the way. I mean, it was just, they were using like Microsoft Project on this massive, you know, massive billion-dollar project. And, you know, usually I see, you know, 50 pages of schedule data and this had like 4. And I'm like, this is not a schedule, but nonetheless, let's take what we can to understand productivity. Historically and all of that stuff, all the stuff that needs to get done. We'll use your schedule as a reference point. We'll fix the logic. We'll start to predict out, you know, based on performance history to date, how long things should take, how many people are required, and then we'll forecast out when you're going to get done. And we did. We did. We— it was piecemeal data on a half-done project, but we were able to figure out productivity rates because it was a steel plant and there was a lot of, you know, installation of steel, and then we had to get into the, you know, electricals and commissioning and all that kind of stuff. But we had enough data to do a decent job of understanding performance to date, and it was 50% complete. So that's usually a good indicator, you know, it's a good line to draw to, you know, take performance history and extrapolate. And then we had to, you know, come up with a plan to accelerate through that. But at the end of the day, we told them, you know, you're They said they're going to get done on like December 15th of whatever year it was. I think it was like 2009. And I said, no, you're going to get done around Thanksgiving on 2010. But if you do these 5 things, you know, you get this many resources in this area and you get this many crews in this area and you work weekends, you can get it done by September 8th. And they're like, get out of here.

We can't—

do not issue that report in anything other than draft. Like, I— we cannot report that. Like, we've already told them it's getting done on December 15th.

Uh, we—

if, if we do that, we're gonna, uh, cause problems with our shareholders, and it could cause problems to our stock price. And we're like, well, that's what's gonna happen. I mean, that's what the data says. And they're like, nope, we're gonna tell everybody it's December 15th. You guys are fired. Go home, go back to America, get the hell out of my office. And that's what I did. And I forgot about it. September 8th, 2010, an email comes across my, you know, desk of a picture of steel being made for the first time ever at that plant. And I'm like, boom. So anyway, analytics work.

Analytics works. That's a great story.

Is that the story? That's, I think, the story.

Yeah. So, what is it? I think I can tell, but what is it that gets you really excited in the morning? You get out of bed and go to work.

What gets me excited? Well, I can tell you what these days, I get really excited when customers, you know, first of all, decide to buy our product. But more importantly, when they expand. You know, we don't walk into the industry saying to anybody, you should buy our product and buy it enterprise. We don't want— we know that the industry is not going to do anything before trying it out on a few projects. But when they decide to expand and go enterprise is really, you know, for me the best because you've proven the value. They feel the value, the problem that you promised you would solve or the problems that you promised you would solve for them are seen and understood and they are willing to put in, you know, put it on every job. And to me, that's great. And it's, you know, it means that they see that we're helping them get their projects done on time and on budget and keeping them out of court to a point where, you know, they rely on the information and what we, you know, all the work that we've done to get this product to solve that problem is working.

I love that.

I'm just curious. That's great. I'm just curious, when I went to your website and I looked at the different displays and information you can get, does it— I presume that it gives people alerts if the software, the platform detects a problem. It says, look at this, what we're seeing here is a problem and here's why.

Yeah, we do our best. It depends on the situation. A lot of our customers, the data gets ingested as part of the process. Yes, they'll receive a notification. And we just did actually roll out our, our, our subscription notification system that will— you can set up and anytime a new schedule is loaded, as soon as the analysis is done, certain reports can be sent to different people right to their email. The way that it's structured is, you know, you look at the data and based on the coloring or some of the analytics, It's telling you where all the little problems are through, you know, green, yellow, red type indicators, you know, little, you know, triangles with exclamation points will show you where the issues are. But yeah, we do our best to, to bring their eyeballs to the areas of risk that they need to know about. And as a matter of fact, our Perform— our executive dashboard actually in multiple categories allows you to— it brings up your most troubled projects in each category. So, you know, in your business where to focus, because without that information in construction, think of a business that has like 100 projects. You know, you don't always know what you're being told from the people at the site is true because, you know, they're very optimistic and, you know, never say die type attitude. So most people say things are great. Even though they're not. And that require— and everybody knows that, but the solution without a technology is to question everything. What we want to do is really hone in on, you know, where are your low-hanging fruit areas. Once you get those solved, what's the next bunch of low-hanging fruit? And do that over and over and over. So that's how we operate.

I, I just sounds like your clients would find this extremely efficient and cost-effective.

Yes, yes, we get told we don't bill too much. We also get told, but don't bill us more in the same sentence.

Sounds like the construction industry.

Yeah.

Well, what is it that you think is unique that you bring to the table that's made all this successful?

Um, gosh, well, I think what number one thing that's unique is that, you know, I think everybody who does what I do or did is always trying to think of, you know, how to make this better. But it's really hard to leave that world of, you know, people being— calling you up and paying a lot of money for your time and walking away from that. That was the thing when I was talking to the companies I used to work for, I was like, why don't we build this idea I have? And they're like, no, we build ours. And I'm like, but we could like bill like a 10th less, you know, like 90% less hours and just charge for software. They're like, yeah, I know, but that's gonna make us less money. And I'm like, but we're solving a problem. It was just my— the uniqueness of that was just being willing to walk away from a very— if you wanted it to be a very successful financial career, financially successful career, and doing something that sort of goes against that model was number one. Number two, I just know data. I just was able to see an industry that had issues with data and I don't know, math was always my thing, just numbers. I mean, I speak better in numbers than I do in words and just, I can get stuck in it. And I just want to know more and more about what can I do now with these numbers and how can I take it to another level? And I want to advance. Even when consulting, we didn't have enough time to do everything I wanted to do and take it to a level of accuracy that you couldn't do without a computer. That to me was just getting better and better and better. And now we're looking at all this data and studying things about the industry that you just would never see without all this data. So to me, that's another thing that gets me up in the morning is just being able to see numbers and take them to a whole new level.

Well, this is really cool. What you're doing is really— I'm fascinated by it, partly because I'm a lawyer, I'm not trained like you are, but I understand the importance of data having presented, done hundreds of trials. But also because of my knowledge of the construction industry. I mean, what you're doing strikes me as revolutionary.

Um, I hope so. That's, that's the goal.

One more question. What's one thing about yourself that we wouldn't know unless you revealed it to us?

I like soup. As a matter of fact, what kind of soup? All soup. Uh, I'm a big soup guy. Uh, I actually was considering right around the time I left my last job— I left my last job without a plan, and I had I had a baby on the way in 2 months.

I did too.

My wife was like, uh, what are you doing? And I was like, I don't know, I, I, I just can't take this job anymore. Um, I don't know what I want to do. Uh, I think there's a chance I want to move to Colorado and open up a soup store, uh, and, uh, and, and make really good soup and have it open like right after, like lunchtime to maybe like 6, 7 o'clock. And, you know, take all of my favorite soup recipes and just offer them. And, and then my wife was like, yeah, we could do really good high-end grilled cheeses. So that was a really cool idea to me at the time. But then I got, you know, through that, somebody called me up and asked if I could do some consulting work on a, a big project out in LA. And, uh, the rest is history. I mean, I took that job, and then I, you know, still had this idea about that software, and it just sort of went. So the soup business got put on hold. Well, maybe one day after this is all settled.

Hopefully it's only on the— well, Michael, it's been great talking with you.

Thank you so much for your time today.

Absolutely, absolutely. Thank you.

Doug Noll here. Thank you so much for listening to Listening with Leaders. If you are a successful executive leader who would like to be on this program, please visit podcast.dougnull.com/podcast. If you got something out of this interview, would you please share this episode on social media? Just do a quick screenshot with your phone and text it to a friend or post it on the socials. If you know someone that would be a great guest, tag them on the social media to let them know about the show and include the hashtag #ListeningWithLeaders. I love seeing your posts and guest suggestions. We are regularly putting out new episodes and content. To make sure you don't miss any episodes, go ahead and subscribe. Your thumbs up ratings and reviews go a long way to help promote the show and mean a lot to me and my team.

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