Industrial Talk is speaking with to Jon Thompson, Cofounder and CSO with Blue Margin about “Increasing Accountability, Efficiency, Productivity and Profitability through data visibility”. Get the answers to your “Data” questions along with Jon's  unique insight on the “How” on this Industrial Talk interview!

Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2023. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy!

JON THOMPSON'S CONTACT INFORMATION:

Personal LinkedIn: https://www.linkedin.com/in/jon-thompson-37282432/

Company LinkedIn: https://www.linkedin.com/company/bluemargin/

Company Website: https://www.bluemargin.com/

PODCAST VIDEO:

THE STRATEGIC REASON “WHY YOU NEED TO PODCAST”:

OTHER GREAT INDUSTRIAL RESOURCES:

NEOM: https://www.neom.com/en-us

AI Dash: https://www.aidash.com/

Hitachi Vantara: https://www.hitachivantara.com/en-us/home.html

Industrial Marketing Solutions:  https://industrialtalk.com/industrial-marketing/

Industrial Academy: https://industrialtalk.com/industrial-academy/

Industrial Dojo: https://industrialtalk.com/industrial_dojo/

We the 15: https://www.wethe15.org/

YOUR INDUSTRIAL DIGITAL TOOLBOX:

LifterLMS: Get One Month Free for $1 – https://lifterlms.com/

Active Campaign: Active Campaign Link

Social Jukebox: https://www.socialjukebox.com/

Industrial Academy (One Month Free Access And One Free License For Future Industrial Leader):

Business Beatitude the Book

Do you desire a more joy-filled, deeply-enduring sense of accomplishment and success? Live your business the way you want to live with the BUSINESS BEATITUDES…The Bridge connecting sacrifice to success. YOU NEED THE BUSINESS BEATITUDES!

TAP INTO YOUR INDUSTRIAL SOUL, RESERVE YOUR COPY NOW! BE BOLD. BE BRAVE. DARE GREATLY AND CHANGE THE WORLD. GET THE BUSINESS BEATITUDES!

Reserve My Copy and My 25% Discount

PODCAST TRANSCRIPT:

SUMMARY KEYWORDS

data, dashboard, business, company, industrial, reporting, people, sales, systems, create, conversation, area, industry, metrics, private equity, outcome, insights, pull, margin, build

00:04

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

00:22

around once again, thank you very much for joining industrial talk the number one industrial related podcast in the universe that is backed up by data that celebrates industry professionals all around the world, like you, I'm pointing at you, if you are out on the video, I'm pointing at you. Because you're bold, you're brave, you dare greatly. You're changing lives, and therefore you're changing the world. That's why we here at industrial talk our absolute cheerleaders for you, and we want you to succeed, and then we're going to do everything that we can to help industry succeed. Take that to the bag. All right in the hot seat, gentleman by the name of Jon Thompson. Blue Margin is the company he is a well, he's got a long title right here and it says senior partner, co founder and CSO of that organization Blue Margin, we're going to be talking about that data, that data that you have to begin to mine and be able to see it and be able to put it into a way that you can actually take action, gold in that data. So let's get cracking. Yeah, there is, I mean, come on, you know, I have conversations at all of these incredible conferences. And there's, there's, there's three things outside of all the other stuff, but there's three sort of themes that take place with a lot of this conversation is one, it's always a people thing, right? People? Where do I find people? How do I retain people, people, right people is it. The other area is of course, cyber, because I, I, I want to, you know, participate in this digital transformation journey. And the reality is, is that if you're doing that, you need to make sure that that you're properly protected. So cyber is a big conversation, and the other one outside of making it simple. Take that to the bank to make it simple. And that's why this particular conversation with Blue Margin is so important, because I think that it achieves that simplicity. But it's its data. Where do I get my data? How do I pull that data? What data is important? What's not important? How do I? How do I transform my business into a data centric organization that truly acts upon the information being delivered in my organization. That's where we're going. That's what you have to do. And and we need solutions to be able to do that. And and solutions that are easy. Yeah, I can turn it around. Alright, a couple of things that you need to put on your calendar, we've got some conferences coming up, we're going to be broadcasting live from the first one that we're going to be broadcasting from is the IoT solutions World Congress, it's in the end of January, it's going to be a great event. Of course, at that event, they talk about IoT, they talk about AI, they talk about data analytics, they talk about digital twin, virtual twin, you name it, it's it's being discussed there, and plenty of opportunities for you to educate. Because if you're in industry, this market is just just ticking along at a blistering pace. And you need to make sure that you stay current with your knowledge. And then of course, as I always say, find those companies, those individuals so that you can collaborate. That's important to trust it, trust it, so that you can innovate, because you need to, because we depend on you. And so it's a great time to be an industry and put that one down on the bank. Because it is all right. And we're going to have a lot going on at industrial talk. And you're saying you're so Scott, how do I how do I get involved with industrial talk? Well, you just go to industrial talk.com, you reach out to me. And if you have a story to tell, and you need to tell that story, and it benefits people, which it does, because you're an industry professional. Let me know, let's get you on the podcast. If you're going I'm going to have all the list of conferences and then some out there on industrial talk. So if you're going to be at one of those conferences, and you're saying Scott, I'm gonna do a live Yeah, let me know. I can't read your mind. But I certainly love your story. So you got to let me know you got to be forthright and upfront with that. All right. Here we go. Jon Thompson. Blue Margin is the company and the form that is filled out again, if you're going to be on this program, you're going to have to fill out this form because you need to make it simple for me to be able to look at and say, Oh, I get it. All right. Pretty cool. That's a great topic. I think the real component to this conversation that is really needed is the ability to be able to see that data from across, cross, let's say your legacy systems across your businesses, and be able to have those, that that information, boom, right there in a dashboard. Pretty cool stuff. All right. Enjoy the conversation with Jon. All right, Jon, welcome to industrial talk. How are you doing today? Doing great, Scott,

05:33

thanks for having me.

05:35

It's great. I'm pretty excited about this conversation, we're gonna be talking a little bit about insights into your business, looking at data, being able to sort of track that in a dashboard type setting, because you need a listener, that's you, I'm pointing at you, right? They're pointing at you. You need to make better decisions. And you need data, you need insights, you need that ability to be able to do that. And Jon, and Blue Margin, bring that to the table. Before we get into that conversation, Jon, for the listeners, give us a little background on you. Why you're such a great professional and a little bit about Blue Margin. And then we're going to talk a little bit about the solutions we're talking here.

06:14

Yeah, sure. So I went to school out east Colby College in Waterville, Maine, froze my butt off. But enjoyed that then went to the Peace Corps in Africa to counteract that weather was a game warden, which obviously led directly into business. When I came back, my brother and I had cell phone dealerships, and we ended up deciding to do a.com. Back when that was all the rage, we went out and raised some venture capital and built a business that analyzed telecom expenses for large enterprises back when that was a significant line item. And after about four years, we attracted the attention of a private equity backed backer, one equity partners, we became the platform company of a five business roll up, and suddenly had 500 employees, my brother was a CEO, I was doing biz dev. And we found that despite the fact that he is a Excel geek to the extreme, our instrumentation was lacking. And we found ourselves spending like, like, half our time managing the board, as we put it, and the rest of the time trying to figure out which way it was up. And that experience, and now this business, Blue Margin, where we've had 200 Plus clients, we have found that our basic hypothesis is that at the root of most, if not all business problems, is poor visibility somewhere, whether that's job ownership or alignment between business units, or accountability to the outcomes of the business, that kind of thing. And so that's what got us going.

07:50

But my legacy systems are super important. So you know, I'm not gonna let them go. I like that spreadsheet. Yeah, right. No spreadsheets, a lot of time and effort in that spreadsheet that creating those macros, and the tabs and all that stuff. They're done. For, for clarity sake, here, we've talked about private equity, PE, we've talked about venture capital briefly, for the listeners, give us a little differentiation between a venture capital in a private equity.

08:20

Yeah. So venture capital is just earlier in the growth phase of a company, sometimes pre revenue, sometimes pre profit. Private Equity tends to come in later, typically, in the mid market, maybe 50 million to a billion in revenue. And so they're looking to take an established business, often a non rationalized industry, if you will, or a niche, whether that's, you know, pet food supplies, or you name it in industrial this or that, where there's all kinds of entrepreneur owners out there, and no one has really turned it into the Toys R Us of their niche. And so they look to do that roll up, get those efficiencies of scale, increase the value of the company significantly, and then sell it again.

09:06

Thank you. Yeah, that makes complete and utter sense. I like that. All right. Let's talk a little bit about data. Let's talk a little bit about having that insight. You're absolutely correct. I think that many companies struggle with visibility. And then it might be visibility, but it's 45 days late. And then by that time that the problem is festered into full blown, full blown infection. And so take us through how you layer I've got all these legacy systems, right? I've got my ERP and then maybe I've got my asset management platform over here, and I've got this and the other and I got this spreadsheet and I got and I'm not I'm not shooting any of those platforms down. How do you layer and consolidate to create that vision? The API's take us through that.

09:57

Yeah, it's particularly relevant in in private equity where you often have a buy and build model where you're not just organically growing the business through new markets and better sales and higher productivity. But you're also adding new companies to fill out your offering and to consolidate for economies of scale. And so you've got these new business units coming on, they have their own ERP or their own homegrown whatever. And you're trying to integrate them just you know, gluing together companies doesn't get you the impact, you want to integrate them. And that can take some time, it's very disruptive, if you've ever deployed an ERP system I hated you may have FYI. Yeah, it can. It can take you to your knees for sure. So instead of saying, We're going to wait the 18 months till we get this integrated, you can integrate at the data layer and create a virtual single view of the business and get everyone focused on those consolidated numbers. And so we'll tap into those various systems with API's, as you said, various data connectors, pull that into a central database, and then connect that to whatever reporting you want. In our case, we're a Microsoft shop, gold partners and Microsoft's we have their high competency rating, we don't actually make any revenue from Microsoft, but we'd like to train. So we've been on it for quite some time. And then we produce reports that the connection to that central database sustains and is automatically updated as new data is entered into those transactional systems further downstream, or upstream. And on a daily basis, whoever the target is, the user gets an update of that dashboard via their email, or they can log into the Power BI system or wherever you want to place those dashboards so that they can see up to the day, here's what's happening, not dissimilar to a scoreboard at a sporting event where you have all the fans and coaches and, and players really glued to that that information. And it's not extraneous information, it is the critical info, they need to know what to do next to win the game. So that's what we

12:07

Yeah. And I hear what you're saying. And that's all good. But there's still, I think there's a lot of heavy lifting in defining and deciding which data is important. I might be, I might just be married to this data. But really, is that data important? How do you walk a client through? Now this is important, this is important. I know that you love this one. But that's not important. How do you walk us through that?

12:32

So the typical process, one of the main stumbling blocks that companies run into as they try to use their data and get better visibility, which is every company is they'll send out a analyst or report writer to talk to the various subject subject matter experts around the company and say what metrics matter to you. And they create a catalogue of that. And then they go back to the lab, and they build reports that display those metrics and say, Here you go. And that invariably, because we've tried it, ends in this, or results in this endless tail chasing where the the person that requested the report says, Oh, thanks. Not quite what I was thinking. And in fact, seeing these numbers up in lights has given me new insight, I need to now have these questions answered in context, and I forgot about that goes back, and you never get there. And adoption is is marginal, and the impact is anemic. So having learned that lesson more times than we'd like to admit, when a client says, Here's what we want to see for our sales funnel, or the gap in our projection in sales, or whatever the case is, we start out with the end goal. So we say what is it you're looking to impact for the outcome in your business? Is it? Is it total sales? Is it sales by customers, that customer lifetime value? Is a diversity of products and services that each customer buys? Is it making sure that your best customers are well taken care of? What is it and they will outline those? Here's the things that matter most for us to get where we're going in the next one to three years. And then we work backwards from that outcome. We'd like to say, what's the measurement of it now? Where does it need to be? And when do you think you can get it to that point by when? And then working backwards from there? What are the drivers that most influenced that outcome? And who do they map to? who's accountable for those drivers? Whether it's production efficiency, or salespeople, and their outreach activities, or you name it? And then we look at where's the data come from for that? And is that the most salient information? Is that the highest impact metric that will influence that outcome? Or is it a nice to have? Since we have the data, we'll put it in there. We get that a lot where customers say, well, that's just informational. And that sets off a red flag or says it shouldn't just be information and you don't see a baseball scoreboard with just informational stuff. It's the things you have to know to progress. And so we pressure test that quite a bit. And one more comment, we'll do a quick what we call a wireframe. It's a sketch or a storyboard. Here's the dashboard based on what we've gathered that you're trying to achieve by this time, here's the drivers that influence that. Let's go through it and ask the questions. If this was in the red, rather than the green, or if it's in the yellow, what does that spur as far as questions or decisions or actions? And what is that next piece of information you need? So you see that your sales are lagging? Your first question is I want to see sales by product category, and see where my problem areas are. And then I want to filter to those. And my very next question is, show me the sales teams and who's doing well with those and who isn't? Okay, let me focus on the isn't filter to those now, let me see a list of the salespeople and let me see their history of sales and how they're doing currently. And now I know who to talk to. So it's that pressure test testing and keeping that end goal as the primary driver of what we're designing.

15:58

But really, it's still you have to have these conversations of saying, Okay, this date is important. Everybody shakes her head. Yeah, that date is important. And that date is important, because of these reasons. Yep. Everybody shakes her heads are saying yeah, that's, that's correct. You still have to, let's say, look at that data. When is that data available? Is there a lag with that? Because you're trying to compress that time dramatically? If it's saying, yeah, the data is great. And it's 45 days old, that's not good. So you got to figure out how to get that data quicker. That's one. And then two, I would imagine you're trying to create some curves around the whole thing, too. You know, if I go this way, that's bad. And this way, it's good. But be able to have that, that those parameters all defined, and then get everybody to say, Yeah, that's right. Yeah. Am I looking at that correctly?

16:43

You are? Absolutely. And so half of that discovery, is the data digging into the database, just saying does the data support this. And oftentimes, it's about data entry compliance, people have been sloppy about it, because it hasn't been up in lights, and there hasn't been accountability to it. And so there's a sweet spot of going ahead and putting those things up in lights in the form of dashboards, that drives that compliance, because the sales manager looks and says, it looks like there's nothing in your funnel, Scott. And you say, No, I've got a lot going on one cn zero. And that's going to the CEO. And now Scott has suddenly inputting his opportunities and making sure they're up to date. So that can drive that compliance. Sometimes the data is not there, and you need to leave a hole in the dashboard until a new process is put in place. You don't want to, however, wait until your data is perfect to put up a dashboard, because you never will. Because data never is. So it's it's sort of a balance in there. And then the parameters, I think you're talking you're talking about KPI thresholds, when's it Red wins? Yeah,

17:48

you just gotta it has, you have to put some level of meaning on it. Yeah. And again, I being a simple guy, green is good. So why would green is good. And then, and then, of course, yellow and red, and you don't want to be red. So yeah,

18:03

we sometimes get tripped up there, because the client is unsure of what those thresholds are. And we have found that it's best to take a guess. You know, we're a bi company, and we never stop evolving our dashboards, it's, it's been a bit of a eye opening experience in our latest iteration that, hey, this never ends where our business is always evolving. We're finding what we think drives our outcomes best. This insight is okay, but we really don't do much with it, what is it we're actually trying to get to. So you use that wireframe to try and get close to the bull's eye. And then you put up a dashboard, you take some guesses at those thresholds. And then the user acceptance testing, and the ongoing use really drives the refinement of that. You don't want to start too far off the marker, you end up in that tail chasing iteration nightmare.

18:57

So let's let's talk a little bit about I call it or I term it a pencil whipping. So if I'm, if I'm just if all of a sudden, you're saying hey, this data, this information is gonna go up to the CEO, then all of a sudden, I'm walking on water, and I'm going to be able to put my data in there and I'm walking on water, and therefore, no bad news gets to the CEO, my, you know, my, what I do, and that dashboards looking doggone green. How do you how do you ensure that good data is getting in there? You know, and you're able to sort of say, Yeah, we're good, bad, whatever ugly?

19:33

Yeah, I mean, how do you make sure that people aren't fudging the numbers? Yeah. Sales that would probably mostly apply in sales. You know, it's tougher in machine productivity, that kind of thing. You need really good alignment with that leader, that sales leader and they need to know their team but one of the mistakes companies make is to create topical dashboards. This is our sales dashboard has all our sales data The problem with that is dashboards are not read by a department or a topic area, they're read by a human being. So the whole point of this exercise is to render data for a human to consume, to touch nerves to improve their decision making in their actions that they take for better outcomes. So we have found that you need to design the dashboards to fit the role. What is their narrative for walking through their day to understand how am I doing? Why am I doing that way? And what details do I need to take action? And when you get that in, in a nice narrative form that really maps to the roll, it makes it hard to hide? I would say,

20:40

Yeah, because that's key. Because, honestly, you want it to be as accurate as you possibly can make those tactical decisions based off of data that is clean and scrubbed. And whatever. A question I do have is, a lot of people are discussing the ability to simulate. So I see it here. But if I go out a couple of years, are these is this data trending in the right and being able to do that? And And are we looking at that too, as well?

21:12

You mean scenario planning, putting in different numbers for for variables and seeing what happens? Yeah, you can do that as well. There's nice tools that integrate with most mainstream BI platform, certainly Power BI, where you can set up forecasting and put in an assumption, see what it does the outcomes, play with that, get get consensus among leaders, and then go with with Plan A.

21:35

Yeah, and I don't see any other way to get around it, you kind of have all those tools in your, you know, quiver, and being able to pull them out and be able to have those insights is I think it's a non negotiable. One of the areas that has always been a challenge, especially with anything that's technology, anything that's innovative, and it is always that culture, that's it's a human equation. Do you guys work in in that areas, and hey, here we go, we're going to be coming in here. And we're going to, we're going to be able to expose and look at all this data, and we need your buy in. Yes, you get a look back on that,

22:12

you've hit one of the top stumbling blocks. So we found that there are very few companies that are really wired for data where every role in the company has their own instrumentation knows the bogey thereafter, it's aggregated to the team. And there's this this team accountability, there are just, you know, low single digit percentage point companies that have that done. And part of the reason is that buying in alignment, we have found that a good way to fix that is to start with a company scorecard, or an OKR dashboard, depending on what framework they'd like to work in. And that's something that you can stand up quickly to three weeks, where you highlight here are the top six to eight metrics that really define our business model and our success plan. If we are hitting these than we are doing, and we've covered 80 plus percent of everything we need to do stand that up early, that becomes the beacon on the hill, the North Star that says okay, here's where we're going with our data visibility. And that can be manually populated by someone half an hour a week, puts in that information. So you're not spending three, four months connecting to eight different systems, building a data warehouse, eventually getting to that vision, you get that alignment and buy in at the most influential layer of the company, the management layer. By standing that up quickly getting it centrally located, having an automated email pinging people once a week and say, here's the company scorecard. And that gels, it coalesces for them, Okay, those are the metrics, usually, there's refinements very easy to adjust that manual dashboard, so that they can zero and there's our plan. And here's the area that were suffering the most sales or throughput or order to cash or whatever the case is. And now you go into connecting the data sources and building a dashboard that feeds that quadrant of the company scorecard and maps to the person that owns that area of the business. And you begin to take off. You do make another interesting point, though, around the change management, the human side, it's it's another aspect of where companies stumble, is they say, Okay, we want to do more with our data that sounds like it, let's send it to them. And it certainly is integral to these projects. But if it takes it on as the lead, they're looking at as as a technical project, and what invariably happens is you end up with a data warehouse that takes several months to build the the idea being we're going to connect to all of our data sources, get them in one place, and then we can create any report you want. That runs into several problems. One is you get this arcane data warehouse that's built to whoever built it in their idiosyncrasies for modeling data somewhere in the basement and it There's two people that understand it. And that creates this ongoing technical debt when you want to write reports. And you've got this difficult convoluted data warehouse that wasn't driven by the business model or the reporting requirements, but was more an academic or a more of a technical exercise to collect all the data in one place. That makes a mess. And so what we found works much better is to say, what's the first area we can get the highest impact for the lightest lift. And let's build to that, let's connect to Salesforce. Let's build that funnel reporting and get that gap in our forecast. Let's put those out to the right folks. Let's get people starting to use it. This is after you've got that company scorecard these stand up quickly. And then once we've nailed that, let's add the next data source our HR system or accounting or whatever the case is, and integrate that. But let's pull in the tables from those systems that are most relevant to the reporting that we need in our business model and not create this behemoth that no one can navigate and has performance issues. And it's difficult to deal with. So that's another key to to getting to a good start and not getting bogged down.

26:09

A lot of questions. And when we start talking about quickly, there's a couple of things. I don't want to post it that can we do this incrementally? Because sometimes I'm a business owner, I have got all my other problems over here. And you're asking me to do this thing over here? Is there a way of being able to do it one incrementally?

26:29

Yeah, I think you have to, to be successful. If you do the waterfall approach. By the time you're done building this massive database that's going to feed all reports it is out of sync with the company and where it's going. Also, if you don't get wins early, and often you lose that momentum, the lights don't go on, oh my gosh, if we can do this, then here's where I would really want to get better visibility. You just it gets lost among all the other tech initiatives that sort of have marginal impact? Yeah. So you want to do it incrementally, you want to do it modularly. And that can be done in the modern data warehouse, not some big thing you build for 18 months, but in two weeks, you stand up that piece of the data warehouse, you get out.

27:14

My next question is that time, so I, I've got and I'm coming to you, I knock on your door, I've said hey, I'm either I'm in private equity, or I'm in a standalone manufacturer, I just need insights. And I want to be able to pull data. And I think this is important data. And you mentioned a couple of weeks to sort of stand that up.

27:36

Yeah, I would say two to six weeks, depending on the complexity. And the left, if it's an entire ERP system, and you're covering of a broader set of, of reporting areas, then it takes longer. But we will try to talk clients out of pasting together three scopes, because it's much better to take one standalone scope that delivers value. It's the last thing you ever do with business intelligence dashboards, it'll have long lasting benefits. So it's standalone. Why do that three times at once and learn your lessons times three, learn them once on that first project, then go into those other ones. And as you get rolling, and you really get a feel for the organization and the data, you can have multiple streams where you're covering inventory, and you're covering throughput, and you're covering other areas all at once.

28:27

Yeah, it just seems like that would be the way to go. And I like the incremental approach. I think that that's vital. I love the fact that, let's just say it on the outside, let's say six weeks to prop something up. And I think that the way I see the seed in my mind, because there are a lot of a lot of systems out there that deliver a sort of a dashboard type of approach. But what you see is that I've got this dashboard, and recognition that there are multiple systems and being able to pull all that data together, do the data analytics on it, this divided by this gives you this sort of whatever that might be. That's where the the power lies. That's you're not you don't have silo systems, you're able to sort of pull it all together in a meaningful way.

29:17

It's funny because the benefits of a BI system like Power BI or Tableau or Domo or you name it are pretty simple. It's about getting that playbook to a centralized spot that everyone access is equally, it's not in an Excel spreadsheet that floats around. It's not a point in time it's being updated hourly or daily, or whatever the case is. So it's not this, this snapshot. It's sort of this ongoing view. And it's interactive. So it allows you to look at the dashboard and say I'm going to click on this region. I want the whole dashboard to filter just to that region so I can see how they're doing and whatever metric we're after. Those simple things are absolute game changers. It's not It's not rocket science. And each of those systems has reporting. We have a CRM, we use HubSpot. We use HubSpot reporting a lot. We build reports in there for, you know, sort of isolated views within the sales team. But we also pull that into an aggregated view of the company and cross reference views into how our sales impacting productivity, and are they balanced and things like that. So there is a place in the Venn diagram between the reporting of a source system and your BI dashboards does overlap. There's some some art and some science into figuring out where you want to move from one to the other. But that central view is, is uniquely powerful that you can't get on any given system. Yeah. Yeah.

30:47

And also, you're an author. Tell us about your book.

30:51

Yeah, so the dashboard effect. If you read it, you'll note that at the beginning, we heavily reference Chuck Coonrod, who wrote a book called The game of work. And I recently interviewed him on our podcast, he's was called the grandfather of gamification by New York Times or someone. And he basically says that for people to be most effective in an organization, whether it's a line worker or an executive, they need to know first, are they winning in their role? And second, how do they win. And if they don't have that, as he says, when people don't know the rules in the score, they tend to not want to play or they play safe. So giving a man clarity makes all the difference in the world. And he came to that conclusion, when he was consulting with a company that was manufacturing manufactured houses, and saw this team out on the floor that was sluggishly nailing in nails, and then the break, alarm went off. And they whipped their shirts off and ran to the basketball hoop and had the most intense focused effort on this game that had a score and a timer and a winner and a loser. And then the buzzer went off again, and they drag themselves back to their work. So his premise is give people that same incentive, leverage human nature, because people want to do things better, faster, more successfully, naturally, where they probably shouldn't be in the organization, give them the scoreboard that allows them to do that. And so the dashboard effect is largely about that if you can take these numbers that you already have access to they're in a Excel spreadsheet or in a transactional system, but put them in a format and centrally located so that they take on life and they really touch nerves, and they have KPIs that draw conclusions, instead of just information that then you have to draw conclusions from. You get that same gamification, that same athletic spirit that desire to achieve into the work environment, we tend to leave it at the office door and assume that what applies on the playing field doesn't apply at work. And that's a mistake. That's the general premise.

33:04

Well, clearly, you have an eBook out there. I have a link to it.

33:09

And an audio you can hear me narrate the whole thing. It was my first shot at that.

33:14

How did that go? It was hard. Yeah. Okay. Go to say I'm not sure. Yeah, well, kudos, man. Yeah, thank you. You put yourself out there. I like we're gonna have a link out there at industrial talk. All right. How do people get a hold of you there?

33:32

So they can reach us at Blue? margin.com. They can reach me at Jon at Blue. margin.com JLN. I'm on LinkedIn. Yeah, all sorts

33:41

of way. All right, we're gonna have all the contact information for Jon. We're going to have all the information and Blue Margin. We're gonna also have this ebook. You can listen to Jon or you can actually read it. It's both both available out on industrial talk. We will have the back links ready to go. Nothing fancy. Jonny, we're great. Thank you, Scott. All right, listeners. Yeah, this was great. I am all alone. I like books and stuff. I don't know why. But I do. I feel like I can't learn enough. Hello. All right, listeners. We're gonna wrap it up on the other side. Please do not go away. We will be right back. You're

34:23

listening to the industrial talk Podcast Network.

34:28

All right, that conversation delivered to you buy industrial talk through Jon Thompson. Blue Margin is the company. We're gonna have all the contact information for Jon and Blue Margin out on industrial talk beer night, go out there, find his conversation. We're also going to have past podcasts. Apparently, he's been on some of the podcasts. We've got some blogs there. We've got some videos there. Look into them. They're all there on his profile that we create and industrial talk. We also have the link to his Book, the dashboard of fact, I've read it, you need to read it too. So go out, download it, do what you need to do, right there. All the links. Again, we're going to be broadcasting from conferences, if you're going to go out to industrial talk, look for conferences, if we're going to be there, you know, contact us and say, Hey, Scott, I want to do a lot. Yeah, I do a lot. We need to tell your story. We need to continue to tell industry story and you are the heroes in that story. So don't shy away. Industrial talk.com All right, be bold, be brave. dare greatly I say it all the time. Because you are and hanging out with people like Jon, and you're going to continue to change the world. We're going to have another great conversation you know, at industrial talk shortly, so never go away. And by the way, go subscribe. You got a lot of great conversations out there. So stay tuned, we will be right back.

The post Jon Thompson with Blue Margin appeared first on Industrial Talk.

Industrial Talk is onsite at the OMG Quarterly Standards Meeting and chatting with Bassam Zarkout, Executive VP with IGnPower about “Solution to navigating massive data challenges to find business gold“. Tune in and hear more about the importance of data and Bassam's unique insights on this Industrial Talk.

Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2023. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy!

BASSAM ZARKOUT'S CONTACT INFORMATION:

Personal LinkedIn: https://www.linkedin.com/in/bassam-zarkout-5081974/

Company LinkedIn: https://www.linkedin.com/company/ignpower-inc./

Company Website: https://www.ignpower.com/

PODCAST VIDEO:

THE STRATEGIC REASON “WHY YOU NEED TO PODCAST”:

OTHER GREAT INDUSTRIAL RESOURCES:

NEOM: https://www.neom.com/en-us

AI Dash: https://www.aidash.com/

Hitachi Vantara: https://www.hitachivantara.com/en-us/home.html

Industrial Marketing Solutions:  https://industrialtalk.com/industrial-marketing/

Industrial Academy: https://industrialtalk.com/industrial-academy/

Industrial Dojo: https://industrialtalk.com/industrial_dojo/

We the 15: https://www.wethe15.org/

YOUR INDUSTRIAL DIGITAL TOOLBOX:

LifterLMS: Get One Month Free for $1 – https://lifterlms.com/

Active Campaign: Active Campaign Link

Social Jukebox: https://www.socialjukebox.com/

Industrial Academy (One Month Free Access And One Free License For Future Industrial Leader):

Business Beatitude the Book

Do you desire a more joy-filled, deeply-enduring sense of accomplishment and success? Live your business the way you want to live with the BUSINESS BEATITUDES…The Bridge connecting sacrifice to success. YOU NEED THE BUSINESS BEATITUDES!

TAP INTO YOUR INDUSTRIAL SOUL, RESERVE YOUR COPY NOW! BE BOLD. BE BRAVE. DARE GREATLY AND CHANGE THE WORLD. GET THE BUSINESS BEATITUDES!

Reserve My Copy and My 25% Discount

PODCAST TRANSCRIPT:

SUMMARY KEYWORDS

data, bassam, digital transformation, organization, people, rolls royce, iot, industrial, sensors, engine, jet engine, business, world, collaborate, supply chain, industry, policy, conversation, debate, transforming

00:04

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

00:22

Alright, welcome Bill to industrial talk a platform that is dedicated to industrial professionals all around the world like the one that's sitting right next to me, because he is bold. Yes. Brave. Yes, he dares greatly. He collaborates. He solves problems. He is a superhero in my mind about that. Thank you, sir. Great. Yeah, I'm still ready to go. And we're broadcasting here in Austin, Texas. Oh, geez, the organization. And again, they get people like Bassam here who really know what goes on and and they are truly passionate about solving. Many of the challenges businesses have today, putting it on paper making us to succeed. You're a hero. Bassam right there. Let's get cracking. Thank you. Yeah, look at you. This is good. This is good. You're my digital friend that I've never seen in person. You're right here in person. Yeah. All the way down from the Great Northwest. Yes. Yeah. It's good. You have a good conference. Yeah.

01:23

Yeah. It's it's good that I mean, it's good to come to these events and see what's what's the state of the art in terms of its

01:32

you know, it's not a comprehensive meeting. You guys meet?

01:35

Yeah. Yeah. Meet, discuss, brainstorm. Fight, debate debate.

01:40

God. I don't know how you guys. Do you go home. Just all worn out?

01:45

Yeah, yeah. But but by the end of the third day or fourth day, you just want

01:50

like, yeah, you're right. You're right. I don't even want to debate that point anymore. You're right. So for the listeners out there, Bassam give us a little background of who you are.

02:00

Yes. So my name is Bassam Zarkout. I'm the founder of a consulting practice called IGnPower. Focusing on digital transformation in IoT industry, digital twins, etc. I'm based in Ottawa, Canada, but I cover the North America as well

02:20

as cover more than that. Assam Yeah, everywhere, man. You're like the dude, the Oracle in digital transformation. You think through this stuff? Yeah, he's downplaying it, folks. Just FYI. You knows more. So you come here. And you recognize that you're, I mean, there's the buzzword. It's digital digital transformation. Everybody's saying and what you you actually go through the process? And you understand what that means?

02:49

Yeah. Well, digital transformation is not new, obviously, been doing digital transformation for several decades. What is new is that we're doing this now, around machines and physical assets. So we're transforming the physical world around us. And we're tying it to the digital world. And we're optimizing it and we're producing better things. And we are changing the value that we deliver to the marketplace through these machines.

03:19

Are we really doing that, let's say industry as a whole? Are we succeeding at that? Do you see a trend that is taking place and say, yep, we're getting it right now. Because there was a lot of people that weren't.

03:29

Yeah, I mean, obviously, this is a slow process. But you can see it around you Rolls Royce is selling propulsion as a service. And the foundation of that is digital transformation whereby the airline doesn't buy the jet engine, they buy propulsion as a service, when they use the engine, they pay for the usage of the engine. And Rolls Royce is responsible entirely for the maintenance upkeep and KPIs or the engine and so on. But General Electric is, is doing the same. So you can see you can see these things happening around you slowly, gradually, but surely, as well. Yeah. And

04:09

that case, case in point, I mean, Rolls Royce is pulling in data, they're, they're managing that asset in a big way. Yes. And we're very grateful for that.

04:19

Yes. And I was told that they are very frustrated, because they'd like and they can do a lot more. But they are limited by the number of sensors that can put inside the engine because of the heat hot conditions inside that engine. The materials to produce the sensors do not exist yet, because it's so hot inside the engine is it's a resource now. It's amazing. Somebody explained it to me, and it's fascinating. They would love to put the 10 times more sensors in the engine and produce so much better results but they can't simply because the material Bill does not exist to produce these sensors.

05:03

All right, there's a business opportunity for anybody out there, right there work with Rolls Royce, develop these sensors. And I guarantee I'll be asking for a loan. Yeah. All right, Bassam, you're here, you're having these conversations, you're debating these conversations around digital transformation. What are the challenges there?

05:21

Well, the challenges is that because you are transforming environments that cross the physical digital divide, you're now doing transformation. Imagine you're transforming, you're changing the jet engine while the plane is flying. So while the plane is flying with changing the jet engine, and that introduces all kinds of challenges, you can't stop operation, you can't. You can't stop complying with your obligations towards regulations, and so on and so forth. So you need to keep on taking care of all these things, while you're making these changes. And that is not simple.

06:01

Okay, I'm gonna have to wrap my head around now. Yeah. So you're saying, Okay, so here's, here's a plane. And we'll just keep on running. I'm using

06:08

that as an example. Nobody is going to change a jet engine

06:11

during flight. But I want to get the analogy there. Because I think that you're onto something here that it creates a a truly valuable word picture that, okay, you have this asset, it's critical. You can't stop it, you can't stop it. Yeah, thank goodness, and you're pulling in information and data off of that engine real time. And eventually, you're gonna you're gonna get information. So let's do some maintenance.

06:37

Yeah. So you know, what is the this is an analogy to a jet engine. But organizations are, are facing this. And there is another problem being created is that the volume of IoT data is going to be exploding. It's already exploding through the roof. And people keep telling us that data is the new oil data is the new oil. Well, that means data has value, what is the value of this IoT data? How do I preserve that value? How do I make sure I'm capturing the tangible and intangible value of that data? And so on, and so forth. So that's another challenge that organizations are facing as well.

07:19

It's a tsunami. It says, and maybe it was you, I don't know, it could have been you. But the amount of data that is just pulled off of a plane on a flight is massive, just on a flight.

07:34

Yes, the the, I saw a figure last last week, an organization called statistics, they, they estimate that the volume of IoT data in 2025 will be 79 zettabytes. And zettabyte is a million petabyte sheet. So massive amounts of data, some of it, you will not need to store it and maintain it, but some of it, you may need to keep it for a long time and manage it. And, and, and, and manage its lifecycle. Because it may be required for compliance, it may be required, because it has value, a future AI may be so much more powerful, you can extract the value from it and sell

08:21

it, see it, but you're bringing up a component. It's so we're still sort of at the beginning of this whole wonderful digital revolution, you know, as we continue on this journey, this train to success, and everybody's saying, yeah, there's, there's gold in that data. And so we're going to just continue to try to get more and more data. I mean, what is it mean? Is everybody going to be a server farm? Is this gonna mean everything? And we're where do we store it?

08:47

The problem is physical, the problem isn't only storing it, the problem is maintaining the context. For example, you have a pressure vessel, and there's a sensor that tells you the temperature is 100. Do you want to store 100? Or do you want to store it's 100 degrees from that sensor from that vessel at this time? So you need to store all kinds of information? And in case of accidents, the authorities will want to investigate? Did you do what you are supposed to do? How do you prove that you did what you were supposed to do? So this information has to be that has to be a strategy about IoT data, what you do with it, and this is not about the engineering team or the operational team, legal may be involved, compliance may be involved. Risk management, maybe all of these people may need to be involved and make some risk based decisions because you can never be perfect. And being perfect is extremely expensive.

09:46

So you're so you get this this, this data, it's just going to continue to grow if if I'm an organization that is committed to transforming digitalizing my business right? I'm going to want more money. just got one more. And there's gonna be a conversation around all that debt type of data like that we don't need that data. So let's get rid of that one. But we need this data and, and how humans can't make that. You can you can create parameters, whatever those that looks like, but I'm not sitting there going, good data, good data.

10:23

I mean, that question you ask is a conversation that can take several hours. But people have been dealing with that on the business side. So for the longest time, people have been dealing in corporations and large corporations have had specialized teams that look at the types of data they have. And they create policies about what you do with that data. Right, because they, they have teams who have analyzed the regulations, and they've analyzed the laws, and they've determined that in order to comply with the law, or, or in order to minimize the risk of noncompliance, speaking like a lawyer, now, you need to apply these policies, and they don't leave it up to the person in the field to make the final decision about what to do, that person in the field doesn't necessarily understand all the requirements. So all they have to do is comply with the law. So the same approach has to be taken for IoT data, because that information is at least as valuable as your business data produced by your back office systems. And, and, and that can be crucial in compliance situations in legal situations. Let me give you an example. You have to comply with data privacy, right. And you are required to delete certain data when you are no longer in need to keep them for data privacy purposes. Well, do you know where all the copies of these data are in your system? No, you do not. So how do you? How do you prove that you've deleted this data?

12:01

You tell me? Yeah. Because here's your profits. I have

12:04

heard of legal cases where you have a large law firms have technology practices that were days. And they have CTOs and technologists who are also lawyers. My brother in law is a lawyer, I can tell lawyer jokes. So lawyers who are technologists are the worst. They are not easy to deal with, but they fulfill a very important function. And these people sooner or later are going to be involved in major compliance and legal cases where IoT systems fail that somebody, God forbid, got hurt, and you need to be able to prove that you've done what you were supposed to do within reasonable efforts. When you had to do

12:55

the same, you're, it's like, Hey, I'm a manufacturer, hey, I got my manufacturer hat on. And I'm, I'm manufacturing these widgets, and you're coming to me and you saying, Hey, Scott, you need to digitalize this more, and whatever, it's like that, that'd be great. Pull the data off of there, pull the data off there, let's analyze it, and you're gonna make some great decisions. And you're gonna, you know, but I'm opening myself up for greater visibility and risk, and I better know what I'm doing, which then I've got another headache to deal with outside of manufacturing or finding my supply or whatever my fees?

13:30

Yes, yes. I was speaking with a gentleman yesterday that. Now in Europe, there will be a new law. Well, it's a law that exists, but it will be strengthened, whereby if you have a supply chain upstream and downstream, you are responsible for the behavior of your partners, and that supply chain is of EDI data. Oh, yes. Yes,

14:01

I'm never doing business again, I'm just going to stay that guy that

14:05

banks, banks have had to do that. For the longest time. If you go to the bank for the first time and you want to open your account, they will pull out a form and they asked you a lot of questions. And basically, they don't want you to be laundering money through your banking institutions, this is called KYC know your customer. So something similar is going to happen with in supply chains. In other words, if you have you operate a supply chain, you cannot accept anybody to become part of that ecosystem because you are responsible to make sure that they are compliant with their obligations. And I say doing

14:46

business all of a sudden with this conversation has gone through it well,

14:49

maybe initially, but eventually like, like, it settles down becomes part of doing business. It's part of the evolution because it was like that 20 years ago in banks.

15:03

Yeah, here you go. So what do we do? I mean, all of a sudden, you've, you've stated a fact, and it is a fact, don't get me wrong. Yeah, I know that data will continue to just continue to grow in and you got to do something with it. And you got to manage it, you got to know where it's at, you know, in when this archive, ID, whatever, you got things around that data. We're how we're still at the beginning of this.

15:30

Yeah, yeah. And the approach is to have a strategy about IoT data. And I'm not talking about the technical aspects of interoperability, all of that stuff is a given at this stage, you need to have a strategy about your IoT data in terms of what's the value? What do I need to keep? What do I get rid of? Where are all the copies? How long do I keep them, and so on, and so forth. Because like I was giving you yesterday, the example of I have a Fitbit. And it's been collecting data for the past five years about my running my walking, etc. And I look at my phone, I see all this historic, historical data, and it's fine. It's nice to look at, but it's technically useless at this stage. But I do not know, maybe a future AI will look at this data and give me some insight about my health, I don't know. So in the future, you may get more advanced analytics that if you point it to historical IoT data, it may give you a new a new insight that you could not get before. So all of these, you have to take them into concert. So

16:45

the moral of this conversation or this story is one, your organization you need to go down that you need to be in the digital game. It just, yeah, if you want to be competitive, you want to have value coming out of that business, even greater, whatever it is, wherever that you need to be in the game. Yeah, that's okay, too. I know that I need to trust somebody I need to figure out how to take and I need a Sherpa to help me along with that. Because I hear you I see it, but I need a Sherpa to help me along with it. And therefore organization, I need to collaborate with trusted Sherpas, right? Not just any Sherpa, a trusted Sherpa to be able to take me on that journey to make sure that I do it, right. And then of course, I need organizations like OMG. And I see all of these organizations that are built on smart people gathering together and collaborating and debating these, these very difficult.

17:43

Yeah, so I look at it. And in a sense, like, like a small commercial, I mean, this is what we do at IGnPower, which is promote ourselves as these Sherpas for organizations. Yeah, help them divide. devise these data strategies for corporations. And again, the problem gets more complex when you're doing digital transformation, because you're making changes and retrofitting, and making changes to the process making changes to your organization. And you want to make sure that things do not fall apart as you don't.

18:17

I'm just, I have this is it, I need to find somebody I trust, I need to know where to start. I don't even know where to start. Because I'm too busy doing all of this stuff over here with my business that's been in business for 20 years or whatever. And I do it this way. Yeah. And I'm dealing with my supply chain issues or whatever it might be. It's vital.

18:36

Yes, the the the silver lining in all of this is you is the head curled is that the regulating bodies. And again, this is not legal advice, but the regulating bodies and the legal bodies and so on, do not want to run organizations out of business, right? They want to make sure that people are doing the reasonable thing. And, and that what is reasonable will keep on evolving. So what was very difficult to do a year ago will become very easy to do next year because of new technologies, new solutions, new thinking, and so on and so forth.

19:16

We haven't even touched upon that. There's a velocity and things change. Yes, yes, tomorrow is going to change.

19:21

But they want to see that. You've analyzed what your requirements are, that you've attempted to write a policy, that you've published the policy and had it approved at the highest level board of directors sometimes that you've informed your stakeholders about the policy and that you have consistently enforced these policies.

19:49

I'm glad you're in it. That's just me.

19:53

Yeah. And again, we've been doing this on the business side for business information. This has been the norm for the past 15 years.

20:03

Yeah. I mean, I am I'm so glad that people are like, like you are, are helping sort of that trail I really am. And how do people get a hold of you there?

20:15

Well, IGnPower.com website. And there's a lot of information on that website and just send us an email and we'll get back to

20:25

you as a user you get you're out there on LinkedIn to read. I am on LinkedIn as well. Okay, we're gonna have his stack card out there to LinkedIn stack card on industrial talk. So you got to reach out to Bassam you will not yes, you can tell until he knows what he's talking about. He's he is the right Sherpa to connect with. You can use that by the way, you can throw that on your way out. But yeah, that's good. All right. All right, listeners. We're gonna wrap it up inside. Stay tuned. We'll be right.

20:51

Bye. Bye. Bye, everyone. You're listening to the industrial talk Podcast Network.

20:59

Again, thank you very much for joining in dust Real Talk in Absolutely. Thank you for your support. It is a platform that is completely and solely dedicated to you industrial professionals. We are here to collaborate. We are here to innovate. We are here to educate, get engaged, go out to industrial talk.com. And absolutely. Thank you, Bassam for saying yes, being on the podcast, and having the opportunity to talk to you at the OMG quarterly meeting. It was great. And I want to just just reiterate the necessity to get your handle on data. There's gold there, it it can be overwhelming. But then there are people like Bassam and others that can help you with that journey in a jet a second, and be able to navigate and direct your attention to where it needs to happen. That's Bassam I'll have all his contact information out there. You know, that go the industrial talk, you'll find is his LinkedIn connection, reach out, and and have a conversation because we are about that education, he can do it. Well, that collaboration. Bassam is right on the money. And of course, innovation, there are so many options out there for you to consider in the world of data, data analytics, and so on and so forth. Reach out. All right, we're gonna be broadcasting, I think, coming up at the IoT solutions World Congress. And if you're going to be there, that's in Barcelona. We're going to have a spot broadcast. Tell your story. Make it happen, Captain. All right. Be bold, be brave, daring greatly. As I always say hang out with people like Bassam and you're gonna change the world because you do. Industry changes the world. Thank you again for joining. And we're gonna have another great conversation shortly coming from that OMG quarterly meeting.

The post Bassam Zarkout with IGnPower appeared first on Industrial Talk.

On this week's Industrial Talk we're onsite at IoT Solutions World Congress and talking to Michel Morvan, Executive Chairman and Co-Founder of Cosmo Tech about “Digital Twin Simulations to Optimize Operational Efficiency”. Get the answers to your “Simulation” questions along with Daniel's unique insight on the “How” on this Industrial Talk interview!

Finally, get your exclusive free access to the Industrial Academy and a series on “Why You Need To Podcast” for Greater Success in 2022. All links designed for keeping you current in this rapidly changing Industrial Market. Learn! Grow! Enjoy!

MICHEL MORVAN'S CONTACT INFORMATION:

Personal LinkedIn: https://www.linkedin.com/in/michelmorvan/

Company LinkedIn: https://www.linkedin.com/company/cosmotechweb/

Company Website: https://cosmotech.com/

PODCAST VIDEO:

THE STRATEGIC REASON “WHY YOU NEED TO PODCAST”:

OTHER GREAT INDUSTRIAL RESOURCES:

NEOM: https://www.neom.com/en-us

Hitachi Vantara: https://www.hitachivantara.com/en-us/home.html

Industrial Marketing Solutions:  https://industrialtalk.com/industrial-marketing/

Industrial Academy: https://industrialtalk.com/industrial-academy/

Industrial Dojo: https://industrialtalk.com/industrial_dojo/

We the 15: https://www.wethe15.org/

YOUR INDUSTRIAL DIGITAL TOOLBOX:

LifterLMS: Get One Month Free for $1 – https://lifterlms.com/

Active Campaign: Active Campaign Link

Social Jukebox: https://www.socialjukebox.com/

Industrial Academy (One Month Free Access And One Free License For Future Industrial Leader):

Business Beatitude the Book

Do you desire a more joy-filled, deeply-enduring sense of accomplishment and success? Live your business the way you want to live with the BUSINESS BEATITUDES…The Bridge connecting sacrifice to success. YOU NEED THE BUSINESS BEATITUDES!

TAP INTO YOUR INDUSTRIAL SOUL, RESERVE YOUR COPY NOW! BE BOLD. BE BRAVE. DARE GREATLY AND CHANGE THE WORLD. GET THE BUSINESS BEATITUDES!

Reserve My Copy and My 25% Discount

PODCAST TRANSCRIPT:

SUMMARY KEYWORDS

simulation, twin, industrial, Michel, industry, data, digital, cosmo, world, asset, simulate, future, people, iot, talk, complexity, ai, happening, conversation, decision

00:00

Industrial Talk is brought to you by Arduino the original all in one IoT platform. That's right, go out to arduino.cc. And you will find documentation you will find devices, powerful boards to help you with your digital transformation journey. It's all there, go out to arduino.cc. Find out more see how you can connect with these professionals to help you along with your digital transformation journey. arduino.cc. Also Industry IoT Consortium. At industrial talk, we always talk about education, we always talk about collaboration, we are always talking about innovation. And if you're a business that has any desire to be resilient to the future, you need to be able to educate, collaborate, as well as innovate with other industry professionals. That's a must. Industry IoT Consortium brings that all together, you need to be a part of this community, you need to be connected with these leaders that are all apart the Industry IoT Consortium, go out to iiconsortium.org. Find out more again, you will not be disappointed, you're just going to be happy.

01:18

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

01:36

Alright, once again, thank you very much for joining industrial talk on ever expanding platform ecosystem that is solely dedicated to celebrating you industrial professionals all around the world. You know why? Because you're cool. I have more to that. But you're just you're doing things. You're solving problems. You're making the world a better place. You're collaborating, you're doing everything that you can to make this world a better place. This is for you this platform. Definitely. All right. We still have great content coming from this year's IoT solutions World Congress and in the hot seat as Michel, more bad. And you know what we're talking about? digital twin simulation solutions. Let's get cracking. Yeah, it never ends. The innovation never ends. And Michel just knocks it out of the park. He is the co founder of Cosmo Tech. About that. That's a cool name, right? Anyway, we were in Barcelona once again, and had these great conversation, Michel. And you know what's interesting, what struck me is just really sort of an aha, it might not you but for me, because I'm sort of simple when it comes to this stuff. I love this. I love the topic around simulation. I love the fact that if you have the ability to be able to use AI, analytics, pull it all together, run simulations, create greater confidence in whatever that outcome is. I think it's just great. And I think everybody is definitely on that bandwagon. So that's cool. Michel, where he's gonna be talking about that. All right. Get out your calendars. Okay, I'm looking at this. I'm looking at IoT Solutions World Congress. It is January 31. To February 2, 2023, right around the corner, right? If I'm looking off in the desert, if you see me on the video, I'm looking off to the distance not that far away. And I go on the website there. IoT solutions world congress.com. And it says game changing Technologies. Yes. From industry trends. For industry transformation. Absolutely. Industry IoT. Yeah. Artificial Intelligence. Yeah. digital twins. Yeah, edge. Yes. Augmented reality, 5g cybersecurity. What else is there? I don't know. But there is some more stuff out there. You need to put this one on your calendar. And as you can tell, I'm a little raspy. I had a cold. Can you believe it? I had a cold. But I survived. And I'm on the backside of that cold. So sorry about the gravelly voice. But anyway, really? This this conversation with Michel at IoT solutions World Congress, really great. Cosmo Tech, simulation digital twin. It's all on the conversation today. So join it. Kevin a good conference. Michel.

04:37

Yes. Great. I'm digging it.

04:41

We're gonna go to a bar tonight. Just a bar. We're gonna go to a bar tonight. Of course. Why wouldn't we have a couple of gin and tonics? Yes. So it's a great, that's a great option. Sure. All right, for the listeners out there and talk to us a little bit about your background. Michel, and then we're gonna get into COSMOTE So what that's all about and then we're going to talk about what? What solutions are being provided.

05:04

Well, my background in in a nutshell, I used to be for many years now, in the past the university professor, I was a specialist of complex systems math, computer science. Hello,

05:15

are you a doctor? Doctor, I see have to see this card. If you're out there. This is the card he has right there. Right there. It's a sticky note. And there's no doctor. So you're a doctor good. I

05:29

used to be a processor. So you know, and, and so and then I developed, you know, Technology, my lab and I decided to bring it from academia to the real world. And that was what we call today's 360 degree simulation.

05:48

Cosmo Tech, you rattled off something that's an acronym, an acronym for something, what does it mean?

05:54

Sure. Oh, Cosmo means complex systems modeling. Say,

05:59

there it is. It's pretty good. Yeah. And you got the URL Cosmo Tech, because nobody had that. That's, that's a good one. So with that, give us a little sort of a definition of digital twin. And then let's get into the simulation component. If that's good, give us a what is a digital twin?

06:17

Sure. But digital digital twin is a digital replica of a system. Originally, it was a digital replica of physical objects. But now we are doing digital twins of systems of organizations. And by the way, that's why we use the word 360 degrees to say that we take, you know, and we present the systems, and we connect to the data in real time. And oh,

06:42

so, you know, everybody uses digital twin, I have a digital twin of my building, I have a digital twin of my substation, and so on and so forth. But what you're doing is you're sort of holistically looking at the whole, you know, whatever the business itself, it says,

06:59

exactly, we don't only look at the at the physical system, the physical parts, but also to all the interactions, the processes, the people who work with the system, what they do, and how they interact with the system.

07:15

So take us through what that looks like. I'm a company. I've got the I'm, I'm interested in digital twin, or I'm, I'm using a digital twin. Take us through that process.

07:27

Well assume that you have a supply chain to manage. And you know that there is a lot of uncertainty. And now more and more complexity in your supply chain. And you want to make that's

07:40

that's an understatement. And in fact, this pandemic, everybody's a supply chain expert.

07:45

Oh, that's right. And you have the problem is what you have to do with the supply chain, you have to reconcile things that seem to be completely impossible to reconcile. So you want to increase the profit, you want to be resilient, at the same time you want to reduce cost and reduce the co2 emissions. That's your problem, right? And all that changes all the time. So what do you need for being able to manage this and make the best possible decisions? You need to have three things? The first thing is what happened in the past? What can I learn from data from the past? The second thing is what is currently happening, you're looking at data from the present. But the most important thing you need is to have access to data from the future, what is going to happen? If I do this? What if what is going to happen if I do that, and what we do with digital twin, we create the replica, we link it to you know the data, and we have the ability and that's the simulation plant to simulate it to see what is going to happen in the future so that you can test 100,000 futures to find the one you want and the resulting one.

08:54

Do you want that future? Look, you have to load the data, some data, you have to load some historical data in some way to paint a possible picture in the future. And then do you? Does the simulation allow you to learn or what help us?

09:13

That's a very that's a very good question. Because we can use data from the past and we do. But what is very important in what we do is that what we put in the digital twin is the knowledge of the different experts. We don't only rely on data from the past, but we are in a system industry or system. You have experts who know very well what is happening on your live production line. What is happening with the robots, what is happening with logistics, what is happening with when people come to work, are they in three eight shifts or do the work? So this knowledge, we put the knowledge and we make the links with the knowledge and because we have all these? Once we have that we just have to connect to the state the current state of the system, and what do we do? We simulate So based on the knowledge, we can add knowledge that we have learned from data from the past, right? But there is the knowledge that comes from the brain of people. And it's

10:11

so deep. So this is cool. This is cool. And as you run multiple simulations, you're putting in different different type of data, different type of parameters, whatever it might be. And then you're is there. Is there a time frame of into the future? Like, can can the future be a year? Can the future be two years? What is sort of that ideal sort of future state?

10:41

There is no ideal we go from 15 minutes to 40 years, depending on the use case. 15 minutes? Yeah, we're doing definitely are sure. We Yeah, for example, assume that you have just a line, a production line. And you you're connected to the data, and you know that you, you're going to make a decision. And you have to go as fast as possible to make this decision. Because you see, for example, that a machine, the product productivity of a machine is dropping. So what is going to be the impact of this drop on your production, right? So you very rapidly simulate, just to know what's going to happen. And once you know that, what you do, you say, here is what I can do here is the different view of the different options. And now I'm going to simulate all these options to make the best possible decision. We do that timescale. And we do that up to 40 years, when we manage very, very big assets and equipments, for example, for maintenance and renewal.

11:44

Yeah, because the life expectancy of some assets are like, like, when I was in a tank farm, right? Those tank farms last like 40 5060, or whatever, whatever the life expenses, you got to run.

11:59

Yeah, exactly. And for example, that's what we do. Mr. Big electric networks. Yes. Electric net? Yes. That's a great example. Yeah. And we are, for example, we have full digital twin of all the high voltage, I mean, transmission, electric utility of France, the whole country, 1 million assets, 4 million interactions. And we have all the teams with where they are their skills, their cost. And every year, the company of T spends 800 million for maintenance. And when you go down that road, yeah, you're absolutely right. And now they're running simulations all the time to find the best decision, because there are a lot of cascading effects. If you delay an investment, this is going to you're going to have more outages on this, then you're going to run the teams there. But the team will not be available to do something else. And maybe you can have a cascading effect. So yeah, do you do you

12:56

got a couple of questions? Do you simulate the need for the workforce to be educated? Like there's a challenge today that there is a future skill requirement? And if I don't do it here, I'm not gonna get it there. Sure. And by

13:21

the way, we are doing that very, very concrete example. The same the same problem than the one I described on the electric grid. Yeah, we you have that in factories, because you have robots, you have fleets of robots, and they're obsolescence. So they, they lost, and they they age, and at the moment, they don't work anymore. So you have to decide to replace them by new ones. But then I have to train the people to be able to manage these years, when am I going to train the people when I trade them, they are not productive. So it has an impact. So you have to optimize all the things. And that's what we do with the simulation digital twin, so different times, but then

13:58

again, at 360, that's where you have to a lot of people are sort of siloed in their digital twin approach or look, do you also in that utility analogy, upload historical maintenance records. And so you'll know that this transformer had the oil changed out and whatever it is, or it's X amount of years old, and that type

14:24

of an exec. So we have that for each equipment, depending on the utility, some have all the data, some other loans, if they have we can from that learn from this data to create a model of each equipment when they don't. We have general equations that are known from this business, and that we can use and then we do that for 1 million asset. And we put all that together, and then we can run these simulations and create value from it.

14:52

So the question I have is, it's like a, again, it's a tsunami of of simulated data. Now how do I, how do I sit there and sort of swim through that. And, and be efficient at that. And now, my, you know, assessment,

15:13

two answers to that. One, the first one is when you create and when you deploy the simulation digital twin, you start by the problem you want to solve. And that is going to tell you what you're going to look at in the simulation. So we provide a huge amount of data to have from the future. That's data from the future. And that's not only one future, it can be hundreds of future depending on what you do and the way you manage it. And this, the first way is you start by knowing what are the KPIs I'm interested in? And these are the one with the platform we're going to show you that's the first answer. But the second answer I would say, is, probably is very, very interesting. Because all these data are what we call synthetic data, there are data generated by the by the twin, right by the simulation. And you know that one, what you can do with this data, you can you can use AI algorithms to be trained with these data, right. And then you can learn from the data you produce about the system, you have. And you can use these tools to find the best course of action when it's too complex. So that we have, I would say AI at the beginning, when you say for example, to get the data for a given asset, and being to learn when this asset with AI or you know, neural networks can upstream us that you put that in the model, you put the knowledge of experts, then you run simulations, and you use AI to learn from the results of the simulation.

16:45

I am a big fan of simulations. I can't put my arm around the level of complexity that you're talking about. I mean, that's if you're looking at just utilities alone. I mean, that's just as it's mind boggling.

17:00

Sure. And by the way, remember the it's complex systems modeling very, and the very important thing is complexity is you, you always want to get rid of complexity, because you say, Oh, if I touch here, it's going to have an impact there. But now assume that you want to have an impact there. And that you have the possibility to know that you just have to touch here, by cascading effect to obtain at very cheap cost, the impact you want. That's the future. See? And that's the President

17:31

says, Well, I gotta tell you, man, I've enjoyed this conversation. It I hate to call it short, but it was too short. How do people get a hold of your Michel? If they want to get a hold of you? How did they get? How do they

17:47

contact you? Oh, they go to our website? Because we'll take that. Very, very simple.

17:52

There it is. Yeah. Thank you. Thank you for your patience. By the way, I really enjoyed the fact that you waited around. That was a good time.

18:00

It was great time. And now the tapas and the gears right.

18:03

genotoxic. Okay. I'll amp it up. Alright, listeners, thank you very much for joining industrial talk by once again, we are broadcasting from the IoT solutions, World Congress, Barcelona is the town. And as you can tell, it's getting close to the evening. And that means it is Janet Donek time. But this has been a great event. Michel, thank you. Thank you so much. All right, listeners, we're gonna wrap it up on the other side. So do not go away. We will be right back.

18:32

You're listening to the industrial talk Podcast Network.

18:38

Hey, as always, thank you very much for joining industrial talk. And thank you for your support. And kudos to our friend Michel bore van, co founder and executive chair, Cosmo Tech, knocking out of the park. You know, you get it's all out on industrial talk.com. Let's just let's just lay it out there, you need to contact this Gent. It's out on industrial talk.com. So make that a priority. Again, put this on your calendar, we're talking about IoT solutions World Congress, we're talking the end of January, January 31 2023. To February the second, that is going to be a barnburner of a great conversation and great conference. Just because you need to know about this stuff. You need to know about IoT, IoT industry IoT, you need to know about artificial intelligence, you need to know about all the stuff that was going to be talked about and collaborate with people who have answers or looking for answers. They're ready to collaborate. It's all out there IoT solutions. World Congress make that a point ours also you gotta go out to industrial talk have already said that. But you got to go out there. We've got a just an on demand on demand, webinar, podcast, whatever industry webinars on demand And what we have is industrial revenue growth series. Now there's five part series. And we really, it's the first one, we're going to be working to improve it. But the reality is, is that we, in industry, have to figure out how to increase our revenue survive, if it's going to be difficult out there, and then do the things that are necessary to create that business that is resilient. We go through topics like corporate governance, marketing, sales, Technology, and how all of that works together to help you bring in greater amount of revenue all out there. It does real talk and you know what it is, it's great. That's great, because it's part of the ecosystem. We're here to be able to do what is necessary to make you a success. It sounds so Pollyanna, but we depend on you. That's just the bottom line. All right. As I say all the time, be bold, be brave, dare greatly hang out with people like be shown. And you will be changing the world. We're going to have another great conversation coming from IoT solutions World Congress, and you need to check that one out. I don't know who had said I don't I don't know who's in the queue, but it's gonna be a great one. And then be a part of this ecosystem. Sign up, do what you need to do. We don't water is nice and warm. Thank you once again for your support. We're going to have another great conversation shortly. So stay tuned.

The post Michel Morvan with Cosmo Tech appeared first on Industrial Talk.