Mr. Manufacturing Tells All | Data Secrets with Frank Borovsky (Ep 006)

In this episode of the DATA SECRETS Podcast, we crack open a manufacturing data “case file” with none other than Frank Borovsky – Mr. Manufacturing Cloud. If you think every Fortune 500 factory has their act together, think again! Frank spills the beans on busted systems, mysterious KPIs, and the questionable "data alibis" companies use to dodge hard truths.

Get ready for:

• The tale of Project Titan at Honeywell – a data sleuthing operation that uncovered double-dealing, cross-division chaos, and “customers” playing both sides
• The showdown between real KPIs and “vanity metrics” (hint: NPS is in the lineup for questioning)
• A behind-the-scenes look at how Frank survived complete system shutdowns, corrupted floppy disks, and more hair-raising data horror stories
• How private equity firms are shaking things up with their relentless chase for EBITDA, and why Frank loves solving their cases
• The secret ingredient to every successful manufacturing operation: on-time to first promise (a.k.a. your statistical “say-do ratio”)
• Frank’s “weirdest KPI”? Customer Expected Lead Time (CELT), and how it can make or break your operational alibi

Frank also reveals why most leaders would rather believe a “pretty dashboard” than interrogate the real data, and why every exec needs to get ready for AI to reveal inconvenient truths.

If you’re itching for the data drama beneath the surface of manufacturing, this episode is packed with shocking reveals, hilariously nerdy moments, and actionable forensics for your next analytics initiative.

Connect with Frank:
🔗 LinkedIn: https://www.linkedin.com/in/frankborovsky/
🌐 B2Beyond: https://b2beyond.com/ 
📧 Email: frank.borovsky@b2beyond.com

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Chapters

• 0:00 Salesforce Manufacturing Solutions Guru
• 5:21 Surprising System Inventory Discovery
• 7:36 From Startup to Success with Salesforce
• 11:03 Inconsistent Customer Treatment for Commercial Projects
• 14:10 Personalized Customer Solutions Journey
• 16:23 Surprised by Customer Overlap
• 19:49 Budget Woes Halt Project Progress
• 23:00 Rethinking Business with CRM Systems
• 27:51 Forget Vanity Metrics: LCV Rules
• 30:37 Understanding Customer Expected Lead Time
• 32:28 Boosting Customer Value Strategies
• 35:46 Clean Up Data with Master Management

Transcript

Nathan Settembrini [00:00:00]:
What's a, what's a vanity metric in manufacturing?

Frank Borovsky [00:00:02]:
This is going to be so controversial. I will. I'm going to. Ready? Yeah. I don't know that it's vanity, but I don't think it matters as much as folks think it does. So I'm going to say.

Nathan Settembrini [00:00:18]:
Your data has secrets, secrets that could change everything if you only knew where to look. Welcome to the Data Secrets podcast. Welcome to the Data Secrets podcast where we uncover how business leaders crack the code, find truth in their data, and turn insight into action. Today's guest is Frank Borowski, Mr. Manufacturing Cloud. If you're in manufacturing and you're on Salesforce, you already know Frank probably. He spent many years in leadership roles at manufacturers from high tech electronics to to golf carts. Then he actually joined Salesforce and is now helping companies adopt technology at his own firm, B2 Beyond. Frank, welcome to the podcast.

Frank Borovsky [00:01:12]:
Thank you so much. Glad to be here. Great intro.

Nathan Settembrini [00:01:17]:
Well, I mean, you are the man. So why don't you just take a second and introduce yourself and kind of tell us what you're up to these days.

Frank Borovsky [00:01:27]:
Well, as you said, long time history in the B2B world, first in banking and then in manufacturing for the last 25 years. And I should say manufacturing and commercial services. So if you build a product, a physical good, or you roll a truck, that's me. And that's pretty much how I've spent the last 25 years. As you said, I was at Salesforce. I was an industry advisor for them in manufacturing, automotive and energy. Automotive. I'm originally from Detroit, as we call it, and now I've hung up my own shingle under B2 beyond and I'm helping the folks in the manufacturing sector. One of the things that I did when I was at Salesforce was create the manufacturing family. So that's all of the the system providers. So they're called ISVs that manufacturers care about. So ERP on Salesforce, Product Lifecycle Management, PLM on Salesforce, QMS, Quality Management. I built the family and work with them and I also work with other system integrators to help them with their particular clients. And then I do have some end clients myself where they come in and ask me for help with regard to their digital strategy. But I stay in my lane. It is, you know, you build a physical good or you roll a truck and that's what I do.

Nathan Settembrini [00:02:56]:
That's awesome.

Nathan Settembrini [00:02:57]:
I am curious. So like you started in banking, spent 12 years in banking and then made a hard pivot into manufacturing. How how did that, how did you pull that off first of all. But then also how did that go?

Frank Borovsky [00:03:11]:
It was one of the most terrifying decisions I ever made. I was actually in banking for 15 years and I was doing marketing, strategic planning, new product development for commercial banking. I work for the largest bank in Michigan and I knew it inside and out. Loved what I had been doing. I could walk in the chairman's office. But I knew that there was a shift, there was an opportunity in Honeywell. Specifically Honeywell Aircraft Landing Systems made me an offer after grilling me the on a Friday. It was supposed to be a three hour interview. Ended up being a 12 hour interview including dinner. And then the offer was, was made on my phone by the time I got back over the weekend. So yeah, I just, it was a, it was an offer I couldn't refuse. I didn't know what ERP was. I certainly didn't know what anything about the, the, the, the whole aeronautics world. But what they said was we like the way that you think and, and that itself, the problem solving process, using data by the way. So you picked up on that. Well done was what they were really looking for. So for those who are actually looking at changing their industry, it's really the mindset that matters most, not the industry.

Nathan Settembrini [00:04:38]:
Nice. That's awesome.

Nathan Settembrini [00:04:40]:
And so maybe take us through the rest of your journey and how you got here. Maybe some key moments or hard earned lessons. Sure, yeah.

Frank Borovsky [00:04:49]:
You know I started out in, in the aeronautics world. Aerospace at Honeywell. Learned an awful lot. I was responsible first for, I was a CEO CIO for a small division on wheels and brakes. Then went to engine systems and services. And I got to tell you even the largest companies, keep in mind this is a multi billion dollar company. Don't always have their acts together. You expect them to. They expect and then. But what we found out was they didn't even know how many systems they had out there. We had to actually inventory them. So I ran a PMO product or excuse me project management office that was both Six Sigma. So I'm a black belt and it we use data analytics to actually figure out okay, how many systems did we have and how could we rationalize what we found out was over 1100 different systems out there and then how could we pull all of that together? So I would say the biggest aha there was just know what your environment is and then ask how do you make this better? And when that took us on the journey for SAP and that's the, the largest ERP in the world. And I think just knowing your environment is what, what matters most. People speculate a lot, but you actually have to have the data. A lot of other bumps along the road. So at Eden Corp, what I would say is one of my most enjoyable experiences was really at Club Car. So I was the CEO, the Chief Information Officer and the Chief Experience office. So it was both. I was dealing with the end. The customers are dealers as well as all of the IT framework. And it's great to have, you know, both the ability to have to steer and the only person you're really arguing with is yourself.

Nathan Settembrini [00:06:57]:
Right.

Frank Borovsky [00:06:58]:
And that allowed me to put a lot of our front end of the business on Salesforce. So that was great. And then I over. I shot over the experience at Ricoh. Ricoh is the largest manufacturer of copiers, but I ran a business called Technoforce and so that was the equivalent of Geek squad for business. So instead of black and white cars, we had red and white cars. And it was run by the folks in Japan and I had put together a strategic plan and they said, frank, do it. And I said, do what? And they said, build this business. So I went from seven, or, excuse me, nine employees to 34 offices, 200 pre sales folks, 1700 technicians, and we built the whole business, the whole business on Salesforce. So that was the aha for me. And this was years ago where Japan had really adopted Salesforce, well before what we know here, here in the United States. And that was well over a decade ago, almost 15 years ago. So we've come a long way, baby, and thrilled to be riding that. That train. I've only been able to, to learn more and more and more about what you can do on the platform. So I'm now serving the Kool Aid ever after having drank it for all these particular years and trying to help others based upon my past experiences.

Nathan Settembrini [00:08:31]:
That's awesome.

Frank Borovsky [00:08:32]:
How's that?

Nathan Settembrini [00:08:33]:
Yeah, that's fantastic. So thinking about your journey and the decisions you made along the way, and also in the work that you're doing.

Frank Borovsky [00:08:43]:
Today.

Nathan Settembrini [00:08:46]:
What would you say drives you, what motivates you, inspires you, gets you out of bed in the morning to keep doing what you're doing.

Frank Borovsky [00:08:53]:
Yeah. It's now two things. Two months ago it would have been, I would have just said my customers. And that's true. And that's actually the advantage that I have is having been a customer for all those decades.

Nathan Settembrini [00:09:09]:
Right.

Frank Borovsky [00:09:09]:
I know what it's like to be in that seat and in the manufacturing and commercial services world, chances are I've Done it. I've been every Persona you can think of. I've been pricing, I've been marketing, sales. I've actually run factories.

Nathan Settembrini [00:09:27]:
Right.

Frank Borovsky [00:09:28]:
And so I know what it's like to be in that customer seat. And so what thrills me is being able to help customers not make the same mistakes that I did, and being able to know what hurts and what the problems are, and knowing what it's like to have to go into a boardroom and make some hard decisions. I've had to do that my entire career, so that's what I enjoy most. But. But I will say the newest one is that I'm also back to teaching, so I had to take a hiatus because of the corporate life after 30 years, and I am now teaching marketing at KSU. And so the second joy there is my students. They get me excited. I'm learning more from them than they are from me. So it's fantastic.

Nathan Settembrini [00:10:20]:
That's awesome. That's awesome.

Nathan Settembrini [00:10:22]:
All right, well, let's pivot into the Data secrets part of our show here. You know, you mentioned that when you were at Honeywell in the building technologies division, that there was a pretty significant effort that you guys went through. Could you just talk us through that and what the impact was?

Frank Borovsky [00:10:43]:
Yeah, so that was. That was huge. I had been at Club Car for nine years, and I got a call from Honeywell. So this. This time, it was at Honeywell Building Technologies. So I am a boomerang. It's now called Honeywell Automation. They've changed the name, but it's all about commercial buildings. So fire safety, electrical products, security, cameras, electrical H vac, all that sort of stuff just for commercial buildings. And it's all based upon, okay, I got to get this project done, and I got to get it done on time. And so the problem really was our customers were being treated in different ways, even within the same five divisions that we were working with. Moreover, what we found out through data was that many of these customers were working with multiple divisions, and we really weren't. And we weren't treating them as though they were the same customer in each one of those divisions. So, you know, if you weren't buying a whole lot of wiring, we treat you like everyone off the street. But on the other hand, if you were in security and you were knocked in lights out as a distributor, you were treating as a platinum customer.

Nathan Settembrini [00:12:04]:
Right.

Frank Borovsky [00:12:04]:
So why am I getting this. These different treatments based upon who I am? So just actually knowing your customer was essential, and that's kind of where we started. So we built our whole framework. And you're going to hear this probably quite a bit around lifetime customer value. Well, the first thing is you got to know who your customers are. You have to look at their buying behaviors wherever they're buying from you. And they don't care that it's a different division. They don't care about your organization. That's something you have to deal with. So you have to look at it from the customer lens.

Nathan Settembrini [00:12:39]:
Okay.

Frank Borovsky [00:12:41]:
And those insights started to move us down a path ultimately. To what? The project that was called Titan, which was embodied in a brand new E commerce system. You kind of go, Frank, you're getting far afield. No, this was all data driven. We had thousands, literally thousands of customer service folks who were in low cost regions and they would do anything. They'd pick up the phone, they'd answer emails, they would input orders. Think about all that. All the orders coming in from all these different divisions and they were all doing it differently because the systems were different. So we said, stop the madness. And that took us on the idea of, no, we're going to build a whole new e commerce platform that is going to recognize the end customer based upon their value to us. And we're going to suggest, as you would in an Amazon world, you know, what they ought to be purchasing. We're going to put that front and center. We're going to give them everything they can do so they can self serve. That was really where, that's the premise that we put out there. And it was called Titan. We built whole infrastructure starting out with data analytics, journey mapping, so that we could actually see what our customers were doing. Not just from a number standpoint, but from a Persona base. What problems were they having then we had digitization, we had Six Sigma. Again, I'm a black belt. And then on top of that, to pay for all of this, we had our E Commerce and again that, that project Titan. And we built that from scratch and we built it to the specifications of each of these customer groups. So keep in mind Honeywell building technologies, you sell to distributors, you sell to system integrators, you sell to end customers, to contractors, all these different customer types and all these different Personas. We created an environment that treated you as though it was only you, right? Based upon the type of customer you are, what your Persona is, why you wanted to deal with us, what your history was. And we put that all together before the days of AI using machine learning to learn just about Nathan, right. And then treating you in that environment when you got There and that was very data driven and in fact it was a learning process constantly. Every single click that Nathan made in our e commerce platform, we learned from and we used it to provide the next best action for you. So I would say that was the biggest achievement. We learned an awful lot using SAP. Hana. We then had Snowflake as our structure and then we had Tableau as our customer facing data analytics platform. And it was a beautiful thing.

Nathan Settembrini [00:15:59]:
Nice.

Nathan Settembrini [00:16:00]:
Was there a noticeable difference in. Once you stopped treating customers differently across the business and started treating them, you know, the big customers give them the level of service that they deserve. Did you notice anything change with customer satisfaction, buying patterns, growth, any of that kind of stuff?

Frank Borovsky [00:16:23]:
Well, yes, there were a lot of surprising things to our management. First of all, our, our executive management, the president, denied that there were any crossover customers. They said we don't have that. We use the data to actually prove it. We said, here are 20 of our top customers and they're buying across our entire divisions. And oh, by the way, in some cases they're buying the same widget at a discount price at your store versus the other store. So there's disintermediation occurring. So that was hurting our margin. And we actually showed them, here are the transactions in which they're doing it. They're, they're picking which business they do to get the best price they possibly can. And in some cases they're pitting each other against each other. So we found that. But then the other thing was, to your point, now what we did was we established a, I call them the metallics. Platinum, Gold, Silver, Bronze.

Nathan Settembrini [00:17:25]:
Right.

Frank Borovsky [00:17:25]:
And then we provided the best service to the folks who were across the entire division of Platinum.

Nathan Settembrini [00:17:34]:
Right.

Frank Borovsky [00:17:35]:
So even if they were not the best in that one division, they were given Platinum status across all. And yes, they, they definitely appreciated that.

Nathan Settembrini [00:17:45]:
Yeah, it's interesting. I mean, everything you're saying makes so much sense and you know, but if you've never worked in such a large enterprise, then that has tentacles out everywhere that, you know, it may seem like, oh well, this, this seems like an easy thing to figure out, but it took an immense amount of effort, I imagine.

Frank Borovsky [00:18:08]:
Yeah. And so what I would tell you now is I'm actually, I've spent most of my, my career in very large Fortune 500 companies. But now I would say the largest amount of my current customers are private owned, privately owned, it's private equity. And so what I get energized with them is it's all about ebitda.

Nathan Settembrini [00:18:34]:
Right.

Frank Borovsky [00:18:34]:
It's ebitda. Ebitda, ebitda. And it's all about how quickly can we go. Generally speaking, Fortune 500 companies move very slowly. The private equity firms work at my speed, right. They're trying to solve a problem and once they latch onto it, it's how quickly can I get it done? But they don't have that knowledge about how to get it done. And that's where I can help.

Nathan Settembrini [00:19:02]:
That's awesome.

Nathan Settembrini [00:19:04]:
Let's talk about a data horror story. So this is a scary moment where things went wrong. Either we made a bad decision from data or the whole system went down or something like that. What's, what's your data horror story, Frank Nathan?

Frank Borovsky [00:19:20]:
I got, I have, I have so many, but I'm going to, I'm actually going to do two. I'm going to do two. Sorry about that. I will say that I correctly predicted a crash of an AS4,400. And that is meant. That's one of those IBM systems that say, People say, well, that never goes down. We had not done an upgrade in years. And I set, when I first came in as the CIO for Club Car, I said, we got a problem here. And everyone did their best, but there wasn't the money to solve it for that fiscal year. They just didn't have the money. And we had everything prepped to make it happen and then it failed. And so we actually weren't able to order anything, build anything, pay any bills for two weeks for the whole company. So it went down, but from a data analytics standpoint, because that's the, that's the biggest failure. And we didn't sleep for months. But the biggest failure is actually very old school. And you're probably not going to remember this, but I remember our teams back at the bank working on huge data analytics projects for our corporate customers. And everything was on a disk. Think about a hard disk. And we put it in after huge amounts of work and it was corrupted and we couldn't bring it back. So that's how old I am. Sounds, you know, ancient. But those are the horror stories that we used to have in the bad old days before we had the cloud.

Nathan Settembrini [00:20:59]:
What does data analytics look like on a floppy disk? Or is it just like we talking reports? Just like cross tab kind of Excel reports? For the most part, yeah.

Frank Borovsky [00:21:11]:
Well, oh no, we had whole.

Nathan Settembrini [00:21:15]:
We had customer.

Frank Borovsky [00:21:17]:
We had a whole customer analytics done. I, you know, it's, it sounds crazy. I built my first CRM in the 1990s. That's how, again, how old I am. But that's how he had to live. It was hard disks and you moved from one system to the other carrying a floppy.

Nathan Settembrini [00:21:38]:
But anyway, that's hilarious. All right, so let's move on to chasing data secrets. So thinking about, obviously any sort of business intelligence data analytics infrastructure, there's going to be a significant amount of investment. You know, these days it's a lot cheaper to get things started than it was, you know, back in the floppy disk days. But, you know, as you think about business leaders investing in technology and analytics and trying to drive an ROI from that, what, what comes to mind for you?

Frank Borovsky [00:22:21]:
People spend too much time talking about the system as though it's going to solve the problem. You've got to figure out what problem you're really trying to accomplish. So if it's around customers, then it could be your CRM. If it's about supply chain, it may be around your ERP and how you're doing. Your available to promise. You got to figure out where it hurts and what it is you're trying to approve and talk less about the system and more about the problem you're trying to solve. And I try to explain that to customers. They're saying, well, we need a CRM. Okay, well what are you going to do with that CRM? What decisions are you going to make? How are you going to run your business differently? And what if it wasn't called a CRM, it was called something else? What does that system look like? And in today's day and age, I mean, I had to actually unlearn a lot of stuff that I learned 25 years ago and talk less about whether it's sale, SAP, Oracle, Salesforce, you name it. And there are new contenders as well. It's more about, okay, well what are you trying to do? And then are you willing to do the hard things to change your business to accommodate it?

Nathan Settembrini [00:23:40]:
Right.

Frank Borovsky [00:23:40]:
So a CRM doesn't solve your all your customer issues.

Nathan Settembrini [00:23:44]:
Right.

Frank Borovsky [00:23:44]:
You have to put in the hard work to say, okay, well now hold it. I'm going to hold you a salesperson accountable. I'm going to hold you a customer service person accountable. And guess what? I'm going to hold my customer accountable.

Nathan Settembrini [00:24:00]:
Right.

Frank Borovsky [00:24:00]:
If they what's their say do ratio? That's what a CRM is all about. Is that what you're signing up for or what is it you're trying to actually accomplish?

Nathan Settembrini [00:24:10]:
Yeah, that's, that's fantastic. That, and that's the songbook that we sing from as well. We always are talking about business first driving impact for the business. What are you trying to accomplish? Not leading with, oh, we can build you the prettiest tableau dashboard or you need a data warehouse. It's like, well, why do I need a data warehouse? Why would I spend months and many, many thousands of dollars to build that out? Unless I'm trying to achieve some specific business goal.

Frank Borovsky [00:24:46]:
I'm going to go over the top on that one. I think the other thing is, particularly in the data analytics space is people look at data analytics as the nice pretty charts and graphs and all that sort of stuff. Okay. That tends to be reporting. That's not analytics, that's reporting. And people tend to like the eye candy as opposed to, okay, well what does it mean? What's the decision that, that you're going to make as a result of that? If you can't tell me, then all the pretty charts in the world don't matter.

Nathan Settembrini [00:25:19]:
Couldn't have said it better. So speaking of reporting, let's pivot into our KPI corner.

Frank Borovsky [00:25:28]:
All right.

Nathan Settembrini [00:25:29]:
This is our lightning round, our metric mystery theater. We talk about key metrics that you've come across or that you find interesting. So, so let's start with. I'm actually very, very curious about. So you know everything about manufacturing from all different angles. So pretend I don't know anything about manufacturing. And let's actually go through these. So a fundamental KPI in manufacturing, what would you say?

Frank Borovsky [00:25:59]:
Okay, it's on time to first promise.

Nathan Settembrini [00:26:01]:
Right.

Frank Borovsky [00:26:02]:
So that's your say do ratio and it has a lot of different names, but that's the one that matters most. So on time delivery or on time in full. And that's what gets highly debated in supply chain. But really it comes down to what's the number one metric. When someone buys something in the B2B world from a manufacturer, they want to know when am I going to get my widget right, whatever that is.

Nathan Settembrini [00:26:30]:
Right.

Frank Borovsky [00:26:31]:
And they're probably going to want it from the person who can get it to them fastest, but maybe not in, in the commercial buildings world, it's just, can you get it to me when that project is needed? Right. So that may be 18 months from now.

Nathan Settembrini [00:26:46]:
Right.

Frank Borovsky [00:26:46]:
But you got to get it there. You have to have it there because if you don't get it there, my customer is not going to pay me. So yeah, it's your promise, it's your say do ratio against what you said and that, that that delivery matters most in the manufacturing world.

Nathan Settembrini [00:27:05]:
That's awesome.

Nathan Settembrini [00:27:06]:
Yeah. We had a CIO of a cabinet Manufacturer. And he said that, that, that manufacturer. Because, you know, when you're building a house, the cabinets have to go in before all the other stuff.

Frank Borovsky [00:27:16]:
Exactly.

Nathan Settembrini [00:27:17]:
Can happen. And if you're not on time complete.

Frank Borovsky [00:27:22]:
Yes.

Nathan Settembrini [00:27:22]:
Then you're in big trouble.

Frank Borovsky [00:27:25]:
Yeah. It's called on time in full.

Nathan Settembrini [00:27:27]:
On time. And pull. He. Yeah, he called it on time complete, which is interesting, but. All right, so let's go to vanity metrics. So these are, these are things that people track. But, you know, they're, they're really just, they make me feel good, but they don't really mean much. What's a, what's a vanity metric in manufacturing?

Frank Borovsky [00:27:45]:
This is going to be so controversial. I will. I'm going to tell you.

Nathan Settembrini [00:27:50]:
I'm hooked already.

Frank Borovsky [00:27:51]:
Yeah. I don't know that it's vanity, but I don't think it matters as much as folks think it does. Okay, so I'm going to say NPS and csat, and you're going to go, frank, you've been in customers, the customer experience world for decades. How can you say that? The problem is that those numbers get misinterpreted and fewer and fewer people are answering surveys at all. So you're getting less and less data. And then that means that you are, you're, you're probably not getting the right feedback from the right people that you need to. And so while that was great for almost 20 years, I would say it's now getting to be a vanity KPI. What matters more, and I got to, I got to, I got to do this one, and it always will matter, is lifetime customer value.

Nathan Settembrini [00:28:54]:
Right.

Frank Borovsky [00:28:54]:
You've got, that's the metric that sales, service, executive management. That's what they look at. Why? Because you want to look at. Are your customers buying from you again?

Nathan Settembrini [00:29:08]:
Right.

Frank Borovsky [00:29:08]:
And the way to measure that over time is lifetime customer value as opposed to NPS or csat. Those are helpful, but they're eroding as your North Star.

Nathan Settembrini [00:29:23]:
Yeah, yeah, for sure. Yeah. I think related to lifetime customer value is. Or maybe just another way of computing it is kind of net revenue retention. So it's like, as I move forward with my customers, how much of that revenue am I retaining? Which would also encapsulate any sort of revenue growth that you get at the customer level, too. Well, so you already hit the most impactful KPI, which was up next. Well, let's move.

Frank Borovsky [00:29:53]:
Hold on, hold on. And I've learned from my private equity folks, right? The number one, the number one metric for any company is ebitda, right? But then how do you do how the second one. Yeah, it would be lifetime customer value. It's underappreciated and under expressed because what happens is everyone thinks that every customer is equal. That's not true. It's all around lifetime customer value and the recency, frequency and monetary value of that customer. That's what you got to look at.

Nathan Settembrini [00:30:28]:
Yeah, for sure. All right, let's for a little entertainment value here. What's the weirdest KPI that you've come across in manufacturing?

Frank Borovsky [00:30:37]:
I'm the one who created it, so I'm going to get. So, so in manufacturing it's either called Culture or kelt. So that's customer expected lead time. And I don't know too many firms at all that are addressing this, but this goes to the on time, the first promise. If you, you can use your order management data to get a sense of, well, what, how long is your customer willing to give you? And essentially it's what it's saying is from the time that I placed the order to the time that I say I want it delivered, that's your customer expected lead time. And it changes for every widget and every customer. So we would, we at Honeywell Building Technologies, we actually had a CELT for every customer and SKU for the entire, everything that we sold.

Nathan Settembrini [00:31:31]:
Interesting. So is that something that's written anywhere in a SLA or a contract or.

Frank Borovsky [00:31:37]:
That's just the emotional expectation it was used for us to be able to see can we meet those expectations? Right? Can we get it to that widget on time, in full to the customer? And every, you know, so not everyone, not, not every part needs to be, you know, there instantaneously. But you have to meet the customer expectations. And if you're, if your lead time is not within calt, then you got to do, you got to figure out, well, how do I do that? How do I change what I do operationally within the organization to get, to get that widget to that customer in the time that they expect?

Nathan Settembrini [00:32:17]:
Okay, the Celt. Spread the word, everybody. KELT is where it's at. All right, Frank, what, what about your North Star metric? Maybe you already said it with ebitda.

Frank Borovsky [00:32:28]:
But it, well, EBITDA is for the financial side. And then lifetime customer value, I pound the heck out of that because. And then again recency, frequency and monetary value help you segment the, the customer. So how they're treated, how, how you behave with them, whether they're, you know, electronic, you got to push them onto E commerce because they're Low LCV and then treating your high profitability customers best. And then also the downside of the that on low lcv, you got it. You have to find a way to either make those customers more profitable so you lower their cost to serve. You push them online and you say hey, we're not going to, we're not going to answer the phone if you call because you're not, you know, you're not stepping up to where we need you to be.

Nathan Settembrini [00:33:19]:
Right.

Frank Borovsky [00:33:20]:
And that's a hard decision to make.

Nathan Settembrini [00:33:22]:
That is, that is.

Nathan Settembrini [00:33:23]:
But I do really appreciate your, your customer centricity with your whole ethos. So I love that. Let's start to land the plane here. So what about. So just kind of final takes and reflection. One thought would be what do you wish more businesses or business leaders understood about data analytics or technology?

Frank Borovsky [00:33:50]:
Well, okay, so I think every leader should have a plan for every customer and a plan for every part. And that should all be data related in the ways that we've described here thus far. And then what I would tell leaders overall is you got to be willing to handle the truth. And that's where I have been in more board meetings where people want to point to the bright shiny reports because it supports their point of view whether they want to get something done, they want to make an investment, but they're, they're often not willing to look at the data dispassionately.

Nathan Settembrini [00:34:37]:
Right.

Frank Borovsky [00:34:38]:
And that's where I'm going to jump the gun a little bit here. I think that's where AI is changing the game because anyone with now with AI can be the smartest person in the room and you can say hey, here's the data boss or boss's boss's boss. And you got to be okay with the answer. Not supporting your current point of view.

Nathan Settembrini [00:35:01]:
Yeah, totally. What is your perspective on companies like mid market manufacturing? What is their first step into AI? Is it, is it like kind of a build versus Buy? You know, Salesforce is investing millions and millions of dollars into AI. Should I just use Salesforce's stuff, agent force and all that or should I go buy build it myself?

Frank Borovsky [00:35:26]:
Well it depends on the environment you're in. But I would say most mid market manufacturers don't have their data in the right order to be even to do anything. To do anything. So don't talk to me about buying or building AI. It doesn't matter if your data is in disarray.

Nathan Settembrini [00:35:45]:
That's right.

Frank Borovsky [00:35:46]:
And, and, and most of the data, customer data, part data, etc. Out there needs to be clean. Now, the good news is that I can help you in that cleaning, and it's fantastic. But you got to know how to, how to go about it. So the first thing is in the. It's the least sexy thing. It's master data management. And then beyond that, what's the problem that you're trying to solve? And then choose the AI accordingly. Once you got your data in order, don't worry about whether it's build or buy until you know the problem that you're trying to address.

Nathan Settembrini [00:36:22]:
That's right.

Nathan Settembrini [00:36:24]:
That's great. Thank you, Frank. Any other final words or thoughts for the listeners?

Frank Borovsky [00:36:30]:
Always. So, always the most, the most important question to ask is why. And that's just it. Most folks, folks figure out, okay, what's the what, but they don't figure out the why. And what Six Sigma teaches you is you got to get into the five whys, and that is arduous to get to root cause. And that is the number one most executives should be asking is why is that occurring? Let's dig into that.

Nathan Settembrini [00:37:03]:
That's awesome.

Nathan Settembrini [00:37:04]:
If our listeners want to connect with you, learn more about what you're up to, what's the best way for them to connect?

Frank Borovsky [00:37:12]:
Well, certainly connect with me on LinkedIn. I try to keep a presence there for the family as a whole. Visit me at ww.b2 with the number b2beyond.com or email me at Frank.Borovsky@b2beyond.com 

Nathan Settembrini [00:37:30]:
Awesome. And we'll put all that in the show notes. And I would encourage you, if you're listening on the podcast app. We do also place these on YouTube and put the videos on Spotify as well and would encourage you to like the video. Subscribe, comment. We're gonna, we read every comment, respond to you. Would love to engage with you. And well, thank you so much, Frank, for being on the podcast. And keep sleuthing, everybody.

Frank Borovsky [00:38:05]:
Take care.