In this week's Industrial Talk Podcast we're talking to Lance Dofflemyer, Chief Data Scientist at MR Systems, Inc. about "The Power of Data and Unification of your Water Data Assets". Get the answers to your "Water Data Solution" questions along with Lance's unique insight on the “How” on this Industrial Talk interview!
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Lance Dofflemyer Interview
Thu, 4/29 10:10AM • 28:52
data, facilities, people, water, systems, lance, talk, important, process, utilities, plant, beverly, industry, insights, industrial, NOEM, ml, Rider, MR Systems
Welcome to the Industrial Talk podcast with Scott MacKenzie. Scott is a passionate industry professional dedicated to transferring cutting edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots, and let's go. Alright, welcome to the Industrial Talk podcast where we celebrate you industry heroes. That's right, because you are bold. I hear it all the time. You are brave. We talk about it all the time, you are just Daring Greatly each and every day, we are living through a great time and you're changing lives and you're changing the community as we speak, all around the world. take that to the bank, we are living through incredible times. It's exciting. And you know who's leading the way you you industrial professional, alright, in a hot seat in a hot seat, Lance Dofflemyer. He is the chief data scientist at Mr. systems. Now, Mr. systems, they are incredible when it comes to water. But you know, we were talking about data because there's gold in that data, the data that makes the product better, safer, asset runs more, let's get cracking data.
It's like we
just like your mining data that just makes everything better. And that's what Lance is all about. I mean, it's just an incredible that we take it for granted that water just comes out of our tap. And water is very important to our life. Absolutely, Doggone it, but it's more the fact that we just take it for granted that it's going to be safe. And that it's gonna I like it. I drink a lot of it. I got a lot in front of me. But before we get in that interview, okay. You know, I always talk about being bold, being brave, daring greatly. Those are not platitudes. Those are not just something that I just sort of, sort of, you know, stirred up and said, it was a great words, no. industry is all about bold, thinking bold, being bold, visions that are bold, that are brave, that are just like, okay, we're going to do it. Why not? Why not? and answer that question. And then Daring Greatly put it out there. Just, we're going to do it. We're gonna take action now bold, brave and daring greatly. And always talk about, hey, hang out with people who are bold and brave and daring greatly, and you're gonna just absolutely move mountains change, VA world. So you might have noticed a couple of times. She's been on the podcast a couple of times. Her name is Beverly Rider.
Beverly Rider is an inspiration. We got to our stack, our LinkedIn Beverly Rider. Yeah, just plug in Beverly Rider. And she looks at the world in a very unique way. She wants to change it. She is doing that. Right this very moment. She is an inspiration now. I met her as the Chief Commercial Officer at Hitachi America. And at that time, we had a great conversation and we were talking a lot about stuff. Find it out there on IndustrialTalk.com you will be inspired. And then she said, I'm going, I'm going to an organization called Neom. So you're going to get on your Google and you're going to type in Neom, and oh, you're going to say Saudi Arabia, and then euro are going to be dazzled by what is taking place at Neom. She has accepted a position as executive director with that organization. But
But talk about bold, brave and daring greatly. That's what Neom is all about. That's what she is doing her team, everybody in Neom. That's what they're doing. They're taking all of this great innovation that exists out there today, which it does. And they're applying it to a community, the community of the future. And I got this thing that's quoted from me, it preserves 95% of the name of nature within Neom, which is over in Saudi Arabia and its community of the future with zero cars, zero, straights, zero carbon emissions, bold, brave, daring, greatly, making it happen. How about that? You need to reach out you need to just go to that website, and you will be absolutely stunned. I remember. And I remember why my there's a lot more out there. So I'm not I'm not going too deep into it because you got to go out to that website. And I remember looking it up. And finally I said and I and at that point in time, I contacted a couple of people I said you've got to check this thing out. You've got to see what's going on there. It is spectacular. This is exactly right there. what the future looks like.
It's exciting. Beverly Rider boom.
Kudos, thank you for changing the world. That's what she's all about. All right, I want a paper, right? And pencil,
we got an A, we've got an event that I want you to at least consider going to. It's the digital summit brought to you by IoT solutions World Congress, I am running a side event when I say I am.
I have people that know what we're going to be talking about. And I just sort of sit there like eye candy and ask them questions. But I do have a utility background. And so we're going to be talking a little bit about the electric utility, right? The electric utilities, digital transformation journey.
And what makes this an interesting conversation, when you start talking about the utilities, we take that for granted, lights go on, everything works just fine. But when we start talking about bringing on alternative generation, which we've been doing for some time, but now it's really gaining a lot of traction, that puts a lot of stress on utilities. What do they do?
For me personally, it's a digital. It's an innovative solution. We're working with Intel, and a gentleman. His name is Mike Bates with Intel, and Phil carry. And he's got his consulting he, he was with Southern California Edison. And we're just, I mean, we're talking about this digital transformation, being applied to utilities, because because a Beverly Rider is is an inspiration to us. And those people that know him are an inspiration. We're going to transform doggone utilities. And that is what's going to be and it's may 11. To the 12th. You got joint sorry for the long intro. I just had to shout out to Beverly Rider and and this particular digital summit side. There's gonna be more it'll be out there on Industrial Talk. It's, it's exciting. As you can tell, I'm going to geek out on it big time. All right, let's get on with Lance.
You know, cool stuff. We live in a really exciting time, because of Lance, because of Beverly, because of Mike Bates, and Phil Carey all of these individuals that are saying, why not? Why not? Let's change the world. Why not? All right. Enjoy the conversation with Lance. Lance. Welcome to the Industrial Talk podcast, absolute honor that you have joined, and you're going to be sharing your insights and wisdom into water with the listeners of the Industrial Talk podcast. How are you doing? That? Scott? How are you? Thanks for having me. Well, it's a pleasure, because I love this topic. So for the listeners out there, let's get right to it. Give us a little 411 on who Lance is. Sure. I'm Lance dolphin, Meyer with Mr. systems. And we are a water and wastewater Integrator for the southeast United States. And all we do is water southeast, just southeast. Can you go northeast? Can you go? Northwest? As you see, I'm doing my little
thing I'm getting Can you go anywhere? We can go anywhere? Yep. I like that. I like that. All right. So what what are we talking about when we start talking about integration? What does that mean?
That's a good question. So we're in the field of process controls. And to kind of break down that that term, it doesn't really matter what manufacturing facility we're talking about. It could be a pulp and paper mill, you got trays on one side, and you got paper on the other. If you go to a you know, a cookie plant, you've got raw ingredients on one side, and you got cookies on the other world water, we have a lake on one side, and we have clean drinking water on the other. everything that goes on in between that is the process. Now, humans are really bad at, you know, controlling complex processes on their own. We're not very good at sub second decisions and staying awake 24 seven, so
I try. I try it doesn't work.
So we design industrial control systems to control those processes that manufacture whatever we want. And that's where the term process controls comes from. So what is the problem we're trying to solve here? what's what's that problem statement that we're trying to solve? Sure. So one of the issues that's come up in the water industry is really a siloed approach to water. And what I mean by that is that water utilities have historically evolved in an isolated manner. And to kind of give a background of the lifecycle of water, we have a lake on one side, and we pull water from that lake, we treat it, we send it out to a distribution system, which can range from a couple of sites to hundreds of sites that just manage moving water around the people. People businesses use that water and it goes to a collection system, and there can be a few to hundreds or even 1000s
Have collection systems, then that water is collected and sent to a wastewater plant where it's cleaned and put back into the river or lakes and the cycle repeats. So the nature of the water industry has largely evolved in a siloed fashion where each one of these facilities kind of operates on their own. And the challenge for water utilities is how do I know comprehensively what's going on in my entire watershed? Because I have all these data sources and mixed solutions that make up my water system.
So what we've been doing with utilities is, I'm gonna stop you real quick. Sure. So listeners, the process looks like this. And correct me if I'm wrong, lakes and rivers, that's where our water source, that's where our watershed where we're getting our water from there, we process it, we put it into the drinking cat category. And then there is at the other end of that drinking category or process is the collection, and then you put it back into the rivers and lakes. And then the process continues to go around and around and around. Got it, right, yep. Good.
So we've been working with utilities to really bring all these data sources into one application,
anything from a single application where they can navigate particular screens or dashboards or insights, so they can see what's going on at any facility at any given time.
And, more importantly, we've been standardizing these data sets so that they can be used for advanced analytics and data science and ml and things like that.
Why is that important?
It's important for a number of reasons. So anomaly detection is one of them.
If we can, you know, evaluate sometimes, you know, in some of our applications, there's, there's millions of data points coming in in real time,
it's quite difficult for a human to review that data in real time and make a decision off of it. And so, you know, anomaly detection is is pretty key on that.
By aggregating the data into one single pipeline, we can also introduce new KPIs or important pieces of information that are applicable to that municipality, you know, information that they would like to have had and know it's beneficial, but just had no way of getting it.
I have to, I have to ask what that example would be, I'm taking it for granted, I go to my sink, I pulled that water, it's all good. And and whatever is happening today, I'm okay. What what additional information can they glean, that makes it even better, I that's an interesting challenge that I share. So someone examples working with recently, as we had a large wastewater plant that
they, you know, they'll process, you know, anywhere from 40 to 60 million gallons a day. And they get sent a lot of water from a number of different sources.
Those sources are in other remote geographical locations. And I know the flow that they're sending, and I know the flow that the plant is receiving.
But what we what we don't know is if any flow is getting lost along the way, so by connecting all these facilities, I can ensure that the the flow that we're sending that facility is actually getting there. Or we can start to detect that, hey, maybe you have a pipe that's broken, or you have some loss along the way, I mean, just very simple. It doesn't have to be this complex, you know, ml algorithm, it could just be, you know, basic subtraction, that that can provide insights that they previously didn't. So I'm certainly 10 here, I want 10 at the other end, but if I'm sending 10 here, and I get nine here, that that's a flag that says, hey, we're losing something. And and it's important to be able to retain as much, you know, water as we possibly can. That's an important component to the whole process. Absolutely. So
let's talk a little bit about I hear what you're saying I have these siloed type of assets that I'm dealing with today, I get data from this one a data from this one, I've got multiple systems that I leverage. But I do I want to bring it under one umbrella, just want to bring it under? Where do we start? What are the actionable points? Where do we start? Yeah, I would start with the vision of what you're looking for. And the reason I bring this up,
it just kind of gives you a target and you can kind of start to make it more concrete from there. But now I would kind of ignore the the budgetary and resource constraints and really just start with what as a municipality do we want to see how do we want to connect our facilities and what type of information
and the reason that's important is because we can do quite a bit with quite a little with today's technology.
solutions are becoming much more cost effective and even even, you know, free or little to no cost.
So, you know, we start with
division, we'll go with them and say, you know, do you want to see all your facilities in one app? Do you want to control from a central location? I have to interrupt real quick, what's the pain I'm dealing with right now to push to, to push me forward to talk to labs? Like, I'm a municipal water? What What am I sitting here? I'm going, dang, we got to get a handle on this. What's that pain I'm dealing with right now. To talk to you.
Why do I want to talk to you?
Yeah, so I mean,
there is a huge need to understand what's going on at all the facilities in real time, because,
you know, we go in and work with a lot of these facilities, great people, great resources,
but they operate independently. In, that's just kind of the lifecycle of a water and wastewater plant. You know, as, as the population grows, these facilities, you know, will either build new ones, or these new disposable new ones, but often they just expand within the facility. And so you just have a mixed bag of control systems, you have a mixed bag of vendors that come in, and you just kind of have this conglomerate of systems. And it's, it's difficult to
streamline that and standardize that into one system that can operate and talk to one another. And that's really what we do is we go in and kind of evaluate, where are you at today? Where would you like to be? And how can we get you there in the most cost effective manner, which makes sense because I, me, if I was a municipal water, person professional, responsible for making sure that the water is good, making sure that I get it processed properly, the liability is probably pretty high. And if I don't have good insights into the data, I think that there's a possible risk there might be my off base here. No, that's absolutely right. I mean, it's, it's a pretty critical process, you know, we, it is, you know, we, it's not really a job, but we make the statement that, you know, we can't mess this up, or we're going to be on the six o'clock news. And that's, that's really the day to day that we live in. You know, you're right, people take it for granted that, you know, they turn on their their faucet and water comes out. And they don't really understand how many 1000s of people are behind that to make that happen. Again, amazing. That's true. That's a this truly celebration of people that I mean, again, there are things that we just take for granted as consumers of these products. Water is one.
So I sit there and I go, Okay, yeah, I approach Lance, I want to be able to get a clear picture of where I'm at and come up with here I am today, this is my future state. Let's talk a little bit about solutions.
Then when do you start pulling in the stakeholders.
So first we we engage and just see what they're currently working with, we'll do an evaluation of every single piece of technology that they're working with. And and process controls, it's, you know, we typically start even down at the center level, how we're monitoring that that process, you know, flows, pressures, temperatures, things like that, and the equipment, pumps, valves and so forth. And then we'll work our way up the topology, and just kind of get an idea of what we're working with. But we want to bring the stakeholders in very early in that discussion, because we're working with these plants. A lot of these, these great staff that are there have been there for decades, they grown up in these plants. And it's they really have, and
there's not much churn out there, thank God, I'm glad there's not that much churn out there. Yeah. So when we're talking about going in and updating their their plant, or you know, changing the way things are done, we're not just changing a plant, we're changing something that a lot of times these people have built themselves, they've developed these screens, they've developed these control systems, they were there when this, you put this system in. So you can't really go in and just say, Hey, we're gonna update this and it's going to be better, we have to understand that this is a part of who they are as individuals, this is a part of their identity. So we really need them to come on board and have their input early on discussion so that their voices heard. And we understand that we're trying to do this to help benefit them, not just the change something that they're passionate about, and they you know, they've they've created themselves.
Very wise, very insightful. Absolutely. I believe the reality is
the future, the innovation, and people like you, your company, and others are looking for ways of being able to make it better, safer, more reliable, all of the stuff that's important for a sustainable Do you find many of these water treatment facilities?
They've been around for many years?
Yeah, they've been around for, you know, in some cases, decades, and it's just a mixed bag of what's in there. And, you know, a lot of times it's it's more cost effective to expand the plant.
than it is to build a new one. And so you just have kind of generations of, of a plant within a plant. And that that, you know, makes it a little bit more difficult when we're trying to standardize and bring all this data up, you really have to work with a number of technologies. And it's possible, you know, we do it a number of cases, we're working with
one of the largest wastewater plants in Georgia right now, to do just this.
We're taking, you know, two to three decades worth of controls and standardizing it and making it one unique, standardized system that's being replicated up and analyzed, they just got tired. In this particular water, they just got tired of all these multiple systems and multiple sources of data. You can't really, if you're pulling data from one side, and another side, it's hard to reconcile or whatever what's important, there was a, I would imagine that that, that becomes unwielding, right, it just becomes a mess. It does and that. And that's a great point. Because if you want to make data rich applications, you need to spend most of your time at the edge where the data is being generated. You know, a lot of people when they think of data science and ml, they think of this top level operation where we're just going to throw some algorithms at it or throw some insights at it. And then we get this great application. But that's really backwards. Because, you know, you could have the best ml tools available, you could have the best data scientist, you could have the most pretty trends and the most beautiful graphs, but it's not going to mean anything if your data isn't good. So we spend most of our time at the edge or the
edge for the listeners. Sure. So edge is really just where the data is being generated. It's where the control is happening. It's where the process is. And so when we're building our data, we're, you know, doing data engineering on our data pipelines, we'll spend the bulk of our time at the edge or at the plant where the data is being generated. And the reason we do that is good as one single source of truth. Meaning that we want every single piece of information that I need to understand that data point at the edge, and I send it all the way up. so that by the time I bring millions of data points up, I'm not trying to sit there at the server level, figuring out what those data points are, we've already defined them at the edge and it travels with the data. So it's already scrubbed, you're just saying, here's, here's a bunch of data, I don't need that. I don't need that, that might be important, this that the other thing. And then when you do finally send it up into the cloud, where it's, you know, you put some processing on it, you've got good data. Exactly. Sounds good. Sounds all wonderful. What are the roadblocks.
So roadblocks are, you know, initially, it could be stakeholders, you've got people that are reluctant to change, and that's natural for humans, you know, we're all in that category, we all just kind of want to get the work and we've got enough good stuff going on. And when someone comes in and says, Hey, I want to change everything, you know, they're, they're pretty reluctant. And you know, you just have to be patient. I've had some people that were, you know, extremely against the idea of digital transformation at first, and you're patient with them, you hear them out, if they have legitimate concerns, you address them.
But what I found is that, you know, you can usually just work with them one on one, and, and when the over, you know, you start to understand, okay, yeah, you are having issues at your plant. Yeah, we could solve that. Yeah, we could provide that. And they kind of come around. So you know, everyone's resistant to change. But if you're patient with them and work with them, you can win them over, and they can usually become your your biggest advocates. The thing comes to mind as Can you incrementally approach improvement, in this particular case, instead of Big Bang? You just say, Hey, here's a problem. Let's let's just, let's just tackle this right now. Is that a possibility? Yeah, absolutely. It's, it's a, it's a wide spectrum, you could you could do everything from the ground up, or you could just tackle one individual problem. And you can tailor a solution just for that particular problem. We had a case recently where
they are doing, we had a couple of PhDs that were, you know, trying to do something new with the process. And the process wasn't monitor, they didn't have any control, no monitoring, no analytics, and we came in and in a week had something up and running for them that they could start collecting data, and making great decisions and tactical decisions. And, and, and, you know, let's just be candid here, it's got to be safe, it's got to be healthy. It's got to be it's got to meet all those needs, and we can't, and that's that's an important component to our, our water system.
The other area that I'm intrigued with, and especially, that is security, right? I mean, once you start to go down the road of data transformation, you're sort of, in essence opening up possible penetration points, what Talk to us a little bit about that security component.
It's really the most important in this this connected age, especially for the water industry. And it's, you know, no one's immune to attack.
So we have to be very vigilant. There's a lot of smart attackers out there and thankful there's a lot of smart people combating that. So typically, where we'll start is we'll make a data pipeline. So we'll start at the sensor. And we'll track every single stop that that data takes all the way up to the cloud. And the reason that's important is I need to know how that data is traveling even within a piece of software. And we'll have some some applications where the data might move 20 to 30 times before it even lands in the database or in user. And the reason that's important is that we'll take these diagrams and we'll work with it groups to say, listen, we're not trying to blast holes in your firewalls. We're not trying to open things by up, I need this source to talk to this destination only on this port at this times. And this is the type of protocol I'm using. And it's encrypted. You know, just having an intimate knowledge of your data pipeline goes a long way when you're working with it groups. Yeah, you want to get up front with that, too. Unfortunately, many implementations, that's security conversation is after the fact after everybody's like, yeah, that is great stuff. It has to be up front to be able to ensure the level of security but not because everybody starts talking about cybersecurity, and you're trying to prevent me from doing work, whatever it might be. And I am and you got to disagree with that, just because it's all a part of that whole digital transformation, journey, and future success. It just has to happen.
Alright, we've got to wrap it up. How does somebody get ahold of you?
LinkedIn is a great way. And I'm on I'm on there quite a bit and love the posts and love to talk to people. So that's just me there. Lance DOFFLEMYER, last name Dofflemyer. Did I get them? He got it. He got it. Perfect. All right. And I would imagine there's not many duffel miners out there in let's not get you man. You got your own little, you know, LinkedIn domain. Man. That's yeah, that's pretty doggone Cool. All right, listeners, you're gonna say to yourself, Scott, how to? I mean, I hear you. You're not. It's gonna be out on his podcast. It's gonna be out on his landing page. Just go to Industrial Talk calm and find out more. All right, Lance, you were wonderful. Thanks, guys. Appreciate it. Good talking to you. Hey, listeners, stay tuned, we're going to be right back. You're listening to the Industrial Talk, Podcast Network.
Again, lads, thank you very much for being on the Industrial Talk podcast and talking data, talking about the power behind data, everything that I mean, we need to you know, you're building a community of the future no data. You're gonna have to figure that out too. That's what it's all about. Thank you, Lance. Thank you, MR Systems for what you do. Remember, you got to go out to NEOM type in NEOM, Saudi Arabia, find out that he will be dazzled by that doggone website. It's exciting. It gives me all giggly and hopped up on goofballs. Also remember paper and pen. So let's put this down may 11 through the tail 12 2001. This is a digital summit brought to you by those wonderful people at IoT solutions World Congress. They're going to be talking about electric utility does digital transformation journey and it is a journey. You just got to start. All right. Be bold, be brave, dare greatly hang out with people like that you're changing the world. Thank you very much for joining. We are going to have another interview right around the corner. Thank you.