Patty Seifert with Eaton
On this week's Industrial Talk we're onsite at Distributech 22 and talking to Patty Seifert, Ph.D. at Eaton about “Utility Innovations and Solutions for Future Success”. Get the answers to your “Grid of the Future” questions along with Patty's unique insight on the “How” on this Industrial Talk interview!
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PATTY SEIFERT'S CONTACT INFORMATION:
Personal LinkedIn: https://www.linkedin.com/in/patty-seifert-ph-d-6a450b/
Company LinkedIn: https://www.linkedin.com/company/eaton/
Company Website: https://www.eaton.com/us/en-us.html
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PODCAST TRANSCRIPT:
SUMMARY KEYWORDS
utility, data, industrial, model, industry, analytics, solar, people, Patricia, vegetation management, happen, suddenly, put, power, measure, fast, professionals, interesting, outages, historical data
SPEAKERS
Scott MacKenzie
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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 Alright, once again, welcome to industrial talk the number one industrial related podcast in the universe. Patricia I'm not I'm not that's that's that's factual. By the way, it's all driven by data. That's why I'm the number one podcast in the world. And this is where we celebrate industry professionals from all around the world. Because you are bold, you are brave, you dare greatly. You solve problems. You innovate like nobody's business, and you're changing lives. And therefore you are changing the world each and every day. Why not celebrate. As you can tell, by the I guess the buzz in the background, we are broadcasting last scene live from DistribuTECH 2022. And incredible then you put this on your bucket list, because there are a lot of great professionals roaming around here. Again, solving problems. It's a great venue. I like it. All right in the hot seat. Patricia, say your last name petition was signed for cipher. eaten as the company. How are you doing? I am so thankful that you were so flexible to just pop on the podcast because you're busy person
will be eaten. And luckily we all I mean, everything changes at the moment in the utility industry. I mean, from you know, when I talked to my son, but 10 years ago, he was not like Mommy, I'm not really cool industry. But now oh, now I'm cool. And a cool mom. So that's I mean, the energy industry becomes really interesting. Also for the younger generation. They think about you know, global warming, the impact, how much energy should they use? What is the future? renewables? We have just installed solar, lots of them excited. And we have a battery at home. So
yeah, did you have a solar and battery? Yes. solution at your house?
I'm in the PSPS zone. So public safety power shut off multiple times last year. So I'm at the point. Well, I want to say
wouldn't mean you're out of California. Yes, exactly. I'm telling you. I don't know how to process this, that the utilities have to shut off power. Growing up in the utility my dad was with Southern California I was alignment. And that that conversation never happened. Oh, never. And now it's like, this is how we manage this is what we do. This is the expectations. It's just bizarre. Do you think that we'll ever get to a point where, I mean, we're transitioning and it's all you know, pretty dynamic out there. But shutting down power is just an interesting challenge. And
it's just a customer, you're absolutely not happy, especially when your sewer system or I happen to a pump doesn't work. You feel like you know, you're gonna feel dwells completely. So yes, it's it's frustrating, but I understand. I mean, we've had horrible fails in California. I think some of the utility maybe have not invested enough. And that's me as a customer speaking. But, I mean, you know, if it's a trade off not having electricity on your house building down, I will always take not having him. So it's up to you. Oh,
Yeah, that's, that's yeah, that makes sense. Definitely. But it's, it's, it's but but but what I do here, there are people talking companies like yours and others, talking about solutions on how to transition into this, this new thing. It's happening so fast, but they're able to, they're starting to think through that.
They'll definitely analytics I mean, you can measure it in different ways but you Um, one of the analytics I worked on, was looking at momentary outages momentary outages is when a branch hits a line or something like that
relays test that's exactly required.
And so you can begin to measure those and say, hey, well, where does it happen along the network. And when you know, wherever it happens, you can begin to more effectively cut to the bushes, and
you start talking about vegetation management. But the reality is, you're right. If you are tracking these interruptions, then you can also pull in some weather, you can pull in, you can pull in various sources of data to create that picture of say, get a Triq crew out there.
Get caught it early, you know, vegetation management is one of the most expensive costs or utility.
And it's, it's, it's, it's part of that whole delivery of service. And it's constantly having issues and it's expensive. And everybody's trying to figure out the best way to
do it exactly. In many ways. I mean, momentary outages, this one, putting sensors out there to measure these, or outages. And that's, that's fairly a way to do it. And I think that's, that's something we have to do. Otherwise, you have to undercount everything, which is also expensive. Yeah,
you can't do that too, because then you have all the other, can I underground here? Do I have to get the easement? Do I, what do I do here? How do I do? There's just so many other things? And that's not gonna
happen overnight? No. And then monitoring goes again, you don't see it anymore? No, you don't. If you do need more equipment in the field to monitor those lines to make sure what you don't see you still have some insights into it. And, again, analytics, and I think analytics is fairly well we go in with do you tell if
you're, I think you're spot on. And I think what I'm hearing clear, loud and clear that these this event is that utilities, and let's just be honest, utilities are the ones that are really driving, that they're the ones right, they're the ones that have this obligation to serve their territory, and therefore, how do we do it most effectively, they've got, you know, pressures on it. So they're going to drive this adoption in this this going forward. But what I do here is that there are a lot of, you know, arrows in their quiver to be able to provide that insights, data analytics, all of the stuff that is necessary to make sound decisions, tactical decisions.
Exactly. And especially people like me, suddenly, we say, I want to have my own electricity. And if I have too much, I will give it back to the network. And that's a challenge for utilities too. And I think that's something a lot of people don't realize, they all think it's the customer, it's the customer, the customer is very, very important. But having the distributed network, the distribution network is really up and running. It's a major challenge.
Again, I'm sort of old school, old school, when I say this, though, when I went to the system operators, for watching the system, and seeing how they app manage that. It was challenged back when you had the centralized generation, and they you know, now it's all distributed. And and you have a battery, they have batteries, and be able to do it in such a way that makes sense. And in fact, if I don't know how to do it,
and interesting data analytics to you see that? It is solar, it's clustering. So it's really, oh, my neighbor has solar, they had to add, let's get an EV. Let's get solar maybe to talk to each other. And they find out oh, that's really cool. Let's have to do you have this clusters. And that makes it difficult for utility to Because suddenly, an EV can use as much as your whole house and electricity. But the transform was not laid out for that
the infrastructure is not there. How do we do
that? Suddenly, it doubles your electricity consumption. So how do you build a network that it holds up that you're aware of it? What's happening out in the field? And solar very often you have to mention to the utility and you have to get a permit for that can't just plug it in?
You know, it's just like air. There we go. So let's talk a little bit about that bright layer. What is that
white layer is really our digital solution. Looking really at what we just talked about? Collecting the data mainly on the distribution network, collecting the data, looking at the data and making informed decision for the utility helped them. Well, like we have one planning tool. And well, do you want to put your solar installation, your wind installation? What will be the impact on your network? Information like that? So that that really helps you to think about what will be the impact? And where do you want to put additional resources in Dell? Or if you want to build an extra neighborhood, what will be the impact on the distribution network? How do I have to build it? What kind of cables do I need? What kind of transformers do I need?
Do you also speculate or look out into the future to and say, Hey, this is a growing community, therefore, you don't need three, you need 954 wire you need whatever, you need a bigger capacity because it's going to expand
exactly what customers forecasting. So you have to forecast you do at load analysis thinking as to what will be the future loading, then you can put in the planning model, and then you can calculate what is the infrastructure? And where do I best put it in without have the least impact on changing our infrastructure?
So you have this platform? Do I Do I put in historical data within a community? Does it learn does? Is there an AI analytics component or what? So I have to put data in to get some sort of information out? Yes, take us through that process. So
normally, when you don't different ways to do analytics, one is you fail the test the model, you get data, historical data, to look back up the future, that's really testing and informing the model. That is another way to just give the data and say, Hey, where are the outliers. So let's say put pictures of dogs and cats and, and the system will say, Oh, this, these are two legged, these are four legged, they look the same, but they will not say this is a duck, this is a cat. But when you do Bailey trained a model, you say this is a duck, this is a cat, and it will find the toxic cats and label it this is this is so different ways to do. Machine.
Because here's an interesting, you know, as well as I do utilities, there's been that sort of singular focus and the singular focus is deliver power at the lowest possible costs. For the consumer, they're sort of pretty simple. And it makes sense, reliable, right? Don't interrupt things like that. So that's pretty simple. And it's and your decisions all revolve around that from a utility perspective. Do you find that utilities as this, this journey begins and it's fast? It's just oddly fast? Able to sort of, do it be nimble enough, sort of retain that same sort of thinking, but do you find that, you know, are you getting good data to be able to do what you need to do? I mean, it's sort of interesting.
We looked at, you know, consumption to predict consumption, how, ultimately, you know, COVID consumption change quite a bit, because people begin to work at home. And Sunday, the coal consumption, pedal change. And so you know, you need weather data to predict what will be the consumption. And these models change over time, like, two years ago, in California, we had this huge piles. And suddenly, we had all the smoke in the air. And a lot of the solo didn't work anymore, because we almost had a nuclear winter, it got colder, and the solar didn't work. And so then we had to change our model again and say, Oh, we have to take this parameter. So and analytics is not just done, your environment changes, and you have to adjust to that.
But those are statistical outliers. You can, although you have to model it. Is it going to happen again? Or do you see this as this?
But you can you can, you know, you see, okay, Napa Valley, you have a fire, you know how the wind goes. So you can make some assumptions? Say, Yes, it could come in this direction, what would be the impact? You have another 20%, something like that, but still some certainty what could happen?
Yeah, you can do this. So you run simulations to absolutely he's like, okay, here, well, let's, let's use this and this. What does that look like? Okay, let's change this parameter. That parameter. Let's see what it looks like.
Yeah. So I will hold Sam software. It's all about planning. What if model? What if I do a put a tee? Or what if I do that? Yes, exactly. So that you make the best decision you can with the least cost.
So let's say I'm a utility. And I'm interested in having this type of data visibility. So I contact you. Then he says, Yep, got it. We can do something we see it we have. How long does it take for you to deploy a system like this? I'm sure it evolves. It sort of grows and learns and does what it needs to do. But just from a baseline perspective, being able to generate real information that helps them make tactical decisions.
That's not an easy question, because very often we need that historical data to thank them All and very often is how fast can utility providers? How often can they get people to get that data, gather that data? And then we have to cleanse the data first, and then analyze it very often, we can really work together for a proof of concept or something in the beginning to really, do we solve their pain points? Do we measure the right stuff? I would say, somewhere between three to nine months, depending on how big the project is, and how close we are. Yeah. And
what I hear is there's a human component, and if they had a major focus on saying, Okay, let's get the data. They're asking for this, this, this, this, this, whatever, whatever it is, but then we can do it much faster. That's exactly correct. And it's always but but this, this, this, this, this, and then I have to do that, that, that that that and then there's a there's a, but you bring up an interesting point that there's that necessity just to scrub that data? Yeah,
absolutely. I mean, you get the data and suddenly think, is that data like that? And then you go back and said, I had one example. Well, we measured phases, and one was 0236. And suddenly, we had a minus 180. And it's like, what is that? And I said, Oh, we have made of the measure plus 180 minus 100. I didn't say what two 360. So and simple case, but if you don't know that you think a negative value, but what's wrong here? But it's just a different medium. And so you have to normalize and clean the data.
And again, that's on a case by case basis most definitely because we've all been there.
Some there are still some very old needles out there as well. Infrastructure with
Yes, and each utility is different. Each service territory is different each every everything is different. Construction Standards, wiring, you name it, it's different.
And some devices don't give take on some gift data. So you also have often to estimate stuff. If I don't get data here. What is the estimation what is the best estimation I can do?
I hear job security. Because it never ends. I will never
end I think you know that people think that will be out of a job. No, I think that what's interesting chops. Yes.
That is spot on. All right. How did they get a hold of you? Patricia? They're saying that she is talking my talk. How do I get a hold you
just reach me at Patty Seifert.
Easy peasy. All right. Listen, this, we're gonna have all the contact information for Patricia out there on industrial talk.com. Once again, we're broadcasting from DistribuTECH 22, here in Dallas, excellent. Perfect. Like, like, like Patricia's professionals, follow on like her like they're Enjoy. Thank you very much for joining and we will be right back.
You're listening to the industrial talk, Podcast Network.
FireEye. Once again, thank you very much for joining industrial talk, and definitely your support. We truly appreciate it. And it is a platform. Industrial talk is a platform that celebrates you industrial professionals all around the world. You're making the world wonderful. And that's why we want to celebrate you, Patti, the interview, no difference. She's passionate, she knows exactly what's going on. She is a thought and industry leader right there with Eaton reach out to her contact information at industrial talk. So you've got to be about educating and collaborating and innovating. I think events like distribute tech and others is a wonderful opportunity to be able to collaborate with people who just just continuously think through these challenges, and what are the innovative solutions to be able to solve those problems, and you're just gonna have to be connected. So you can you're gonna you're always gonna have to learn. So reach out to Patti team Eaton doing marvelous things for the utility space because it is changing in a big way. All right, people be brave, daring greatly. And you're just starting out, you're hanging out with people like Paddy and you're gonna change the world. Thank you very much for what you do. And we're always here. So if you ever want to get a hold of me, you know where to go. Industrial talk.com Reach out. And just let's have a conversation. All right, we're gonna have another great conversation from DistribuTECH shortly so stay tuned.
Transcript
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,
scene live from DistribuTECH:will be eaten. And luckily we all I mean, everything changes at the moment in the utility industry. I mean, from you know, when I talked to my son, but 10 years ago, he was not like Mommy, I'm not really cool industry. But now oh, now I'm cool. And a cool mom. So that's I mean, the energy industry becomes really interesting. Also for the younger generation. They think about you know, global warming, the impact, how much energy should they use? What is the future? renewables? We have just installed solar, lots of them excited. And we have a battery at home. So
yeah, did you have a solar and battery? Yes. solution at your house?
I'm in the PSPS zone. So public safety power shut off multiple times last year. So I'm at the point. Well, I want to say
wouldn't mean you're out of California. Yes, exactly. I'm telling you. I don't know how to process this, that the utilities have to shut off power. Growing up in the utility my dad was with Southern California I was alignment. And that that conversation never happened. Oh, never. And now it's like, this is how we manage this is what we do. This is the expectations. It's just bizarre. Do you think that we'll ever get to a point where, I mean, we're transitioning and it's all you know, pretty dynamic out there. But shutting down power is just an interesting challenge. And
it's just a customer, you're absolutely not happy, especially when your sewer system or I happen to a pump doesn't work. You feel like you know, you're gonna feel dwells completely. So yes, it's it's frustrating, but I understand. I mean, we've had horrible fails in California. I think some of the utility maybe have not invested enough. And that's me as a customer speaking. But, I mean, you know, if it's a trade off not having electricity on your house building down, I will always take not having him. So it's up to you. Oh,
Yeah, that's, that's yeah, that makes sense. Definitely. But it's, it's, it's but but but what I do here, there are people talking companies like yours and others, talking about solutions on how to transition into this, this new thing. It's happening so fast, but they're able to, they're starting to think through that.
They'll definitely analytics I mean, you can measure it in different ways but you Um, one of the analytics I worked on, was looking at momentary outages momentary outages is when a branch hits a line or something like that
relays test that's exactly required.
And so you can begin to measure those and say, hey, well, where does it happen along the network. And when you know, wherever it happens, you can begin to more effectively cut to the bushes, and
you start talking about vegetation management. But the reality is, you're right. If you are tracking these interruptions, then you can also pull in some weather, you can pull in, you can pull in various sources of data to create that picture of say, get a Triq crew out there.
Get caught it early, you know, vegetation management is one of the most expensive costs or utility.
And it's, it's, it's, it's part of that whole delivery of service. And it's constantly having issues and it's expensive. And everybody's trying to figure out the best way to
do it exactly. In many ways. I mean, momentary outages, this one, putting sensors out there to measure these, or outages. And that's, that's fairly a way to do it. And I think that's, that's something we have to do. Otherwise, you have to undercount everything, which is also expensive. Yeah,
you can't do that too, because then you have all the other, can I underground here? Do I have to get the easement? Do I, what do I do here? How do I do? There's just so many other things? And that's not gonna
happen overnight? No. And then monitoring goes again, you don't see it anymore? No, you don't. If you do need more equipment in the field to monitor those lines to make sure what you don't see you still have some insights into it. And, again, analytics, and I think analytics is fairly well we go in with do you tell if
you're, I think you're spot on. And I think what I'm hearing clear, loud and clear that these this event is that utilities, and let's just be honest, utilities are the ones that are really driving, that they're the ones right, they're the ones that have this obligation to serve their territory, and therefore, how do we do it most effectively, they've got, you know, pressures on it. So they're going to drive this adoption in this this going forward. But what I do here is that there are a lot of, you know, arrows in their quiver to be able to provide that insights, data analytics, all of the stuff that is necessary to make sound decisions, tactical decisions.
Exactly. And especially people like me, suddenly, we say, I want to have my own electricity. And if I have too much, I will give it back to the network. And that's a challenge for utilities too. And I think that's something a lot of people don't realize, they all think it's the customer, it's the customer, the customer is very, very important. But having the distributed network, the distribution network is really up and running. It's a major challenge.
Again, I'm sort of old school, old school, when I say this, though, when I went to the system operators, for watching the system, and seeing how they app manage that. It was challenged back when you had the centralized generation, and they you know, now it's all distributed. And and you have a battery, they have batteries, and be able to do it in such a way that makes sense. And in fact, if I don't know how to do it,
and interesting data analytics to you see that? It is solar, it's clustering. So it's really, oh, my neighbor has solar, they had to add, let's get an EV. Let's get solar maybe to talk to each other. And they find out oh, that's really cool. Let's have to do you have this clusters. And that makes it difficult for utility to Because suddenly, an EV can use as much as your whole house and electricity. But the transform was not laid out for that
the infrastructure is not there. How do we do
that? Suddenly, it doubles your electricity consumption. So how do you build a network that it holds up that you're aware of it? What's happening out in the field? And solar very often you have to mention to the utility and you have to get a permit for that can't just plug it in?
You know, it's just like air. There we go. So let's talk a little bit about that bright layer. What is that
white layer is really our digital solution. Looking really at what we just talked about? Collecting the data mainly on the distribution network, collecting the data, looking at the data and making informed decision for the utility helped them. Well, like we have one planning tool. And well, do you want to put your solar installation, your wind installation? What will be the impact on your network? Information like that? So that that really helps you to think about what will be the impact? And where do you want to put additional resources in Dell? Or if you want to build an extra neighborhood, what will be the impact on the distribution network? How do I have to build it? What kind of cables do I need? What kind of transformers do I need?
Do you also speculate or look out into the future to and say, Hey, this is a growing community, therefore, you don't need three, you need 954 wire you need whatever, you need a bigger capacity because it's going to expand
exactly what customers forecasting. So you have to forecast you do at load analysis thinking as to what will be the future loading, then you can put in the planning model, and then you can calculate what is the infrastructure? And where do I best put it in without have the least impact on changing our infrastructure?
So you have this platform? Do I Do I put in historical data within a community? Does it learn does? Is there an AI analytics component or what? So I have to put data in to get some sort of information out? Yes, take us through that process. So
normally, when you don't different ways to do analytics, one is you fail the test the model, you get data, historical data, to look back up the future, that's really testing and informing the model. That is another way to just give the data and say, Hey, where are the outliers. So let's say put pictures of dogs and cats and, and the system will say, Oh, this, these are two legged, these are four legged, they look the same, but they will not say this is a duck, this is a cat. But when you do Bailey trained a model, you say this is a duck, this is a cat, and it will find the toxic cats and label it this is this is so different ways to do. Machine.
Because here's an interesting, you know, as well as I do utilities, there's been that sort of singular focus and the singular focus is deliver power at the lowest possible costs. For the consumer, they're sort of pretty simple. And it makes sense, reliable, right? Don't interrupt things like that. So that's pretty simple. And it's and your decisions all revolve around that from a utility perspective. Do you find that utilities as this, this journey begins and it's fast? It's just oddly fast? Able to sort of, do it be nimble enough, sort of retain that same sort of thinking, but do you find that, you know, are you getting good data to be able to do what you need to do? I mean, it's sort of interesting.
We looked at, you know, consumption to predict consumption, how, ultimately, you know, COVID consumption change quite a bit, because people begin to work at home. And Sunday, the coal consumption, pedal change. And so you know, you need weather data to predict what will be the consumption. And these models change over time, like, two years ago, in California, we had this huge piles. And suddenly, we had all the smoke in the air. And a lot of the solo didn't work anymore, because we almost had a nuclear winter, it got colder, and the solar didn't work. And so then we had to change our model again and say, Oh, we have to take this parameter. So and analytics is not just done, your environment changes, and you have to adjust to that.
But those are statistical outliers. You can, although you have to model it. Is it going to happen again? Or do you see this as this?
But you can you can, you know, you see, okay, Napa Valley, you have a fire, you know how the wind goes. So you can make some assumptions? Say, Yes, it could come in this direction, what would be the impact? You have another 20%, something like that, but still some certainty what could happen?
Yeah, you can do this. So you run simulations to absolutely he's like, okay, here, well, let's, let's use this and this. What does that look like? Okay, let's change this parameter. That parameter. Let's see what it looks like.
Yeah. So I will hold Sam software. It's all about planning. What if model? What if I do a put a tee? Or what if I do that? Yes, exactly. So that you make the best decision you can with the least cost.
So let's say I'm a utility. And I'm interested in having this type of data visibility. So I contact you. Then he says, Yep, got it. We can do something we see it we have. How long does it take for you to deploy a system like this? I'm sure it evolves. It sort of grows and learns and does what it needs to do. But just from a baseline perspective, being able to generate real information that helps them make tactical decisions.
That's not an easy question, because very often we need that historical data to thank them All and very often is how fast can utility providers? How often can they get people to get that data, gather that data? And then we have to cleanse the data first, and then analyze it very often, we can really work together for a proof of concept or something in the beginning to really, do we solve their pain points? Do we measure the right stuff? I would say, somewhere between three to nine months, depending on how big the project is, and how close we are. Yeah. And
what I hear is there's a human component, and if they had a major focus on saying, Okay, let's get the data. They're asking for this, this, this, this, this, whatever, whatever it is, but then we can do it much faster. That's exactly correct. And it's always but but this, this, this, this, this, and then I have to do that, that, that that that and then there's a there's a, but you bring up an interesting point that there's that necessity just to scrub that data? Yeah,
measured phases, and one was:And again, that's on a case by case basis most definitely because we've all been there.
Some there are still some very old needles out there as well. Infrastructure with
Yes, and each utility is different. Each service territory is different each every everything is different. Construction Standards, wiring, you name it, it's different.
And some devices don't give take on some gift data. So you also have often to estimate stuff. If I don't get data here. What is the estimation what is the best estimation I can do?
I hear job security. Because it never ends. I will never
end I think you know that people think that will be out of a job. No, I think that what's interesting chops. Yes.
That is spot on. All right. How did they get a hold of you? Patricia? They're saying that she is talking my talk. How do I get a hold you
just reach me at Patty Seifert.
Easy peasy. All right. Listen, this, we're gonna have all the contact information for Patricia out there on industrial talk.com. Once again, we're broadcasting from DistribuTECH 22, here in Dallas, excellent. Perfect. Like, like, like Patricia's professionals, follow on like her like they're Enjoy. Thank you very much for joining and we will be right back.
You're listening to the industrial talk, Podcast Network.
FireEye. Once again, thank you very much for joining industrial talk, and definitely your support. We truly appreciate it. And it is a platform. Industrial talk is a platform that celebrates you industrial professionals all around the world. You're making the world wonderful. And that's why we want to celebrate you, Patti, the interview, no difference. She's passionate, she knows exactly what's going on. She is a thought and industry leader right there with Eaton reach out to her contact information at industrial talk. So you've got to be about educating and collaborating and innovating. I think events like distribute tech and others is a wonderful opportunity to be able to collaborate with people who just just continuously think through these challenges, and what are the innovative solutions to be able to solve those problems, and you're just gonna have to be connected. So you can you're gonna you're always gonna have to learn. So reach out to Patti team Eaton doing marvelous things for the utility space because it is changing in a big way. All right, people be brave, daring greatly. And you're just starting out, you're hanging out with people like Paddy and you're gonna change the world. Thank you very much for what you do. And we're always here. So if you ever want to get a hold of me, you know where to go. Industrial talk.com Reach out. And just let's have a conversation. All right, we're gonna have another great conversation from DistribuTECH shortly so stay tuned.
About the author, Scott
I am Scott MacKenzie, husband, father, and passionate industry educator. From humble beginnings as a lathing contractor and certified journeyman/lineman to an Undergraduate and Master’s Degree in Business Administration, I have applied every aspect of my education and training to lead and influence. I believe in serving and adding value wherever I am called.
