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.
