[Dave Lorenzo]
There's value hidden inside your business. You just don't know where it is. Lucky for you, we've got the guy who's going to find it, who's going to extract it, and who's going to share it with you so that you can monetize that thing that you've hated for all this time.

Curious? Want to know more? You've got to join us for this edition of the Inside BS Show.

Hey now, I'm Dave Lorenzo. I'm the godfather of growth, and I'm here with my old pal, Nikki G. Hey now, Nikki G.

How are you doing today?

[Nicola Gelormino]
Hey, Dave. I'm doing fantastic. How are you?

[Dave Lorenzo]
I'm doing great. We're talking about the thing that everybody is absolutely confounded by in their business, their data. And for you and me, when we look at a business and we want to extract the most value from it, we often don't have to dig that deep to find that most people don't understand the acres of diamonds they have in their backyard.

And that's the value that's buried deep, deep, deep within their data. So we're going to explore that today with the absolute best person. Why don't you share with the audience who's here and what he's going to tell us?

[Nicola Gelormino]
Happy to do that. So before I bring on our guest today, I just want to add to that, to one point to that, Dave, which is that this, meaning IT systems and cybersecurity, falls right in line with our 10 key drivers. It's so important for any business to help you add value.

It's not just an expense, business owners, not just an expense, your technology, your systems. It helps create efficiencies, helps create you scaling opportunities. So we brought in the expert today to really dig into this and to help you stop shying away from discussions about your tech.

Let's bring on our guest for today. It's Ken Scales, the founder and CEO of Scalesology. Ken, welcome to the show.

How are you?

[Ken Scales]
Hello, Nicola. How are you doing?

[Nicola Gelormino]
I am fantastic. I can't wait to talk tech with you.

[Ken Scales]
I love talking tech, data, scaling. It gets me all very excited.

[Nicola Gelormino]
I can imagine. So speaking of, we got to talk about how you got into this because I imagine that you were that kid who was walking around the house, taking electronics apart, trying to figure out how to put them back together. Am I close?

[Ken Scales]
You are absolutely correct. It was electronics. It was Legos.

It was anything I could do to probably tear something apart and then learn how it worked and then put it back together.

[Nicola Gelormino]
And put it back together in a better way, right? In a better way.

[Ken Scales]
Well, not always in the beginning, but it did work. So.

[Nicola Gelormino]
My nephew-in-law did take apart a laptop recently, a brand new laptop given to him by his grandfather. He probably could use a few pointers from you as a young budding possible tech entrepreneur.

[Ken Scales]
Make sure you're grounded. That's the first thing. You'll take a motherboard and you'll just short it out.

Don't know how I know that, but I do.

[Nicola Gelormino]
So we won't ask. We won't ask. So tell us, how did you really get into this?

So you're as a kid, you're playing around with electronics. You realize this is something that interests you. So take us to the point where you start realizing this might be a viable career option for you.

[Ken Scales]
Yeah, I think part of it was my undergraduate was believe in liberal arts and political science. And the other part of it was I always enjoyed programming and looking at computers, electronics and things. So it was more of a, I always had a kind of a one foot in the, do I want to be a lawyer?

One foot in, do I want to be more of building things? And really the internet right after college just kind of started to explode. And a lot of it first started with cable TV for me, started building cable systems.

Later I got into fiber optics and then eventually got into programming into different ways. Later web programming, first it was doing programming in basic, which is a very archaic language now, but that's the first language that I learned and I kind of went from there.

[Nicola Gelormino]
And how about the first job you took out of college? What were you doing?

[Ken Scales]
The first job I took out of college. Uh, let's see. I was actually building, um, coaxial cable and fiber optic systems.

That's what I did right out of college.

[Dave Lorenzo]
So Ken, from where you were then to where you are now, it's quite different. Let's talk about how you spend most of your time. Those of you who are longtime fans of the Inside BS show will remember Ken scales was with us back in episode five 41.

That was on June 1st, 2023. So for those people who have not followed the Ken scales career trajectory, like I have, let's catch them up as to what's been going on from the Legos and electronics all over the living room floor, June 1st, 2023, you were trapped in London for like a month. And then you came back and I interviewed you after that.

And now here we are in 2025. The sun never sets on the Ken scales empire. Let's catch everybody up as to where we are today.

[Ken Scales]
Sure. Well, Hey, we scales all as you made it to five years, uh, December 20th, 2024 was our five-year anniversary. We had a nice little celebration.

It was here in Chicago. Very exciting. Um, and, and we're continuing to do some fabulous things.

We're really take really looks at that whole data analytics journey, um, and really embraces that and get some from whether you're collecting information all the way to actually using AI and some different things with what, with what they're doing with data. So that's our, that's what we do. And we continue to build those things out and have great clients.

And on the horizon is going to be, we're going to have some other, um, subscription services that we're going to be having out there. So that's, what's going to be in the future.

[Dave Lorenzo]
So what is, in terms of scales ology, the company, what is your, what is your bread and butter? If I said to you, Ken, where, where does your company get the bulk of its revenue? What would be, what would be the main revenue stream for scales ology?

[Ken Scales]
I mean, really the main revenue stream for us is it's all around. If you think about the services that way, it's all around the data and the analytics journey. And so if all of our service really revolve around that, whether it's collecting data, you know, that journey is what collecting data, processing that data, centralizing it, analyzing it, achieving insights, and then taking those insights and deploying them into action.

So when you're on that journey, it's really, we build a lot of applications to help our clients collect that information, display those reports. We build a lot of databases, data warehouses, data lake houses. We talked about that a lot last time, but mostly though, it's really, as we do the analysis with a lot of our team and our data scientists and data analysts, it's really about how do we put those insights into action to really show a quick ROI for our clients.

And then some of our clients, we have long-term relationships where we're continually adding more data and we're continually integrating other systems that they're using.

[Nicola Gelormino]
So for those listening, Ken, give us an example of something you've done with a company where you've taken the data, you've employed analytics to it, and have been able to turn that into value. Just an example, so they can really be thinking about this is what Scalesology does.

[Ken Scales]
Absolutely. One of my favorites is a company that we've been with, that's been with us since 2020. It's a used cooking oil collection company.

And so they go around and they collect cooking oil from different restaurants across the country. And so their first issue was, okay, Ken, we need to understand exactly how much of that used cooking oil is going to go to our certain plants on a certain day. Because we're having trucks that are coming in and they're not full.

How do we, we need to figure this out. So a lot of that was taking data from a lot of disparate data sources, grabbing that information, building a data lake at that time. It's more of a data lake house now, but a lake, and then taking that and then analyzing that information.

And so, because what we did, we then looked at it and said, okay, now we can look at this and say, we know how much oil came in last week, came in yesterday, going into a certain plant. We then also looked at it from over a hundred thousand restaurants. How many used cooking oil, how much used cooking oil are we collecting from those different restaurants?

We then started building predictive models and those predictive models started to tell us how much oil is going to be coming from those restaurants on a particular day, a particular week, per month, particular month. And that was based on historical information. And then also predicting things that events that might happen.

We then took that and said, okay, how about routing optimization? So in their business, one of the things that trucks, they would have is you don't want to collect a cooking oil and have a truck come in half empty. And then also from a restaurant perspective, you don't want to have that use cooking oil.

You can't just put it down the drain. So once that tank gets about 50% full, those business owners are going, oh my goodness, are you going to come? Are you going to get this?

And so once that's all worked out and you have a schedule and there's a lot of trust when you're picking it up and you have those routing things all secure and ready to go, then that's like a seamless process. And so that's what we really helped them with. Ironically enough, we found some interesting things in the data as we continued to do more insights.

We found a cluster of restaurants in the New Jersey area and the Pennsylvania area that weren't producing the amount of used cooking oil that we thought. So we said, this doesn't seem right. We think our analytics is correct.

So they sent out private investigators to go and watch these different sites and they found people stealing used cooking oil. And that footage then led to over 35 arrests. And so they've taken the used cooking oil and they're actually selling it to their competitors.

So that's the journey of taking that information eventually and putting that into action for real ROI for the clients. The fun thing is too, they gave me these great videos, my client does, of people that still use cooking oil and they're not always the smartest people out there. And so they got one guy that has a van, he rented it obviously, and it started leaking and apparently it leaked all the way in the cab.

And so in my mind, I hear this Benny Hill music going on and he's going to the truck, opening up the door and cooking oil goes everywhere. So what do you do when you're stealing used cooking oil and it goes everywhere? Well, I guess you get back in the truck and that's what they did with all that sludge and everything else, shut the door and just drive off.

So those are the fun things I get to play with, with our clients.

[Nicola Gelormino]
I've never heard of stealing cooking oil. We've got to explore that a little. Go ahead, Dave.

[Dave Lorenzo]
I hear this story and I immediately think to myself, if you can do this with cooking oil, imagine what you can do with customer data. And I think about, I've got like a hundred different applications in mind, but the first thing I think about is someone who's got one line of product or service and in order to onboard their client, they're collecting valuable information from that client that could be used to sell them other lines of service, but they don't know how much demand there is for their other lines of service. All they need to do is meet Ken Scales and they immediately take this mountain of information that they're already collecting.

They're already collecting it. And you can go through the information and overlay it with other services they provide and say, look at the demand for service number two. Your people are out there cold calling, generating new leads for these services when you've got clients on this side of your business who already have a need for the services that you're currently providing.

I mean, that to me is the acres of diamonds in your backyard, truly. And that's where, like if everyone doesn't have a conversation with you or somebody who does what you do, they're missing out on a huge opportunity. If you're collecting information from your, any information from your customers, from geographic information to demographic information to psychographic information, all of that has a value for other application in your business.

[Ken Scales]
Absolutely, Dave. Absolutely. And sometimes, you know, folks don't want to do that because they don't think they have the right kind of data or it's not cleaned up.

It's not all those things are possible. You can clean the data, you can get the data correct, you can normalize it. And sometimes there's third party data that you add to it that gives you even more insight into the story that you're trying to understand.

[Dave Lorenzo]
So a secondary thing that I see all the time in an application that I see for the service that you provide, and this is just from my own personal background, is you could have just your customer's name and email address, maybe a phone number, create a five-question survey, create the survey in consultation with you so that they know what information they should collect and in what form they should collect it. And those five questions will tell them what the five next things they should approach their client to sell to them are.

So they could do market research on their own customer base. If you've got 1,500 customers, you'll never have to go out and generate another lead again. Just ask them five questions, let Ken aggregate the data for you, and you'll figure out three other things you can sell to them.

[Ken Scales]
Dave, would you like to sell Skelzology Services? I mean, I feel like there's a bond here.

[Dave Lorenzo]
I got to translate the way that data seems so complicated to the average person. All you're doing is you're taking information, intelligence about their customers, giving it to them so that they can figure out what to sell. On the other side, you're taking information about their own operations, giving it back to them so that they can operate their business more efficiently.

That's essentially all you're doing. And what happens is we become victims of our own success. We build and grow our businesses so fast that we just keep doing what we're doing and we don't realize all the information that we have that can help us do it more efficiently.

So, Ken, what is step one? Somebody who just heard me rant for four minutes about, you know, collecting data from your customers. If they want to weaponize their data immediately to make more money, what's step one for them?

[Ken Scales]
I mean, really, you know, contact us and let's talk about a scale. I call it a scaling session. And it's something that, you know, I put together something and this won't cost them anything.

We'll just sit down with them. We'll just say, let's kind of map out where you are in your data analytics journey. And that's something that we do a lot with our clients.

And then when we do that, it's like, let's now identify what are those roadblocks? What are those pain points that you have that you're not being able to solve? And usually that then gives us an idea of how we can then tailor a strategy that's going to enable them to really maximize the data that they have with those insights to really get that ROI.

And when we do that, that's something that it's, you know, we're calling right now scaling sessions. And it's free. We'll just work with you, have a couple, two or three, maybe scaling sessions.

And at the end of it, you're going to have really that roadmap to, hey, here's our suggestions of where you should go next.

[Nicola Gelormino]
So that's the strategic piece, right? You sit down and you decide, here's what we're going to do strategically with your data. And you're that person who really translates what the business needs and its requirements into something that's functional on the tech side, because the business owners aren't speaking tech.

You're the translator. You say, okay, here's the plan. We've got this down.

What we're going to do now, I kind of want to walk through like, how does that actually look for them? So they have already been collecting. I assume most companies that come to you have already been collecting data using some type of databases.

So let's start there, like where they're holding that data and like concerns you see there with like where it's being housed and maybe if it's being kind of spread out in different areas, which you mentioned earlier.

[Ken Scales]
Yeah. I mean, sometimes we'll go through it. We'll look at it in two different ways.

One way is they know they have some kind of an issue, some kind of a roadblock, some kind of a pain point. And are there insights in their data that can help them out? That's one to start out with.

The other part of it is I have no idea, Ken. I have no idea. I mean, we're just at these bottlenecks.

I don't know if it's efficiency. I don't know if it's processes. I don't know.

I don't know where to start. And so both those situations, Nicole, we're going to go into the data a little bit, right? So we'll get access into their data.

And then what we can do is sometimes we'll do proof of concepts. Sometimes we'll review that information and we'll see little kernels of things like, hey, did you know this? And sometimes with the collection process, they're not collecting the data in a way that's easy to aggregate.

It could be a lot of folks might be filling out the information rather than having pull down menus, for instance, right? I mean, there's ways to organize information and collect it easier for them so you have the right kind of information that you want. So the first step, again, is, hey, let's dig into the data.

Let's understand what you have. Let's see if does that correspond to one of the pain points, the problems that we can help you solve.

[Dave Lorenzo]
So Ken, when someone goes to acquire a business, oftentimes there is a huge amount of hidden value in the data. And we don't necessarily know it's there until after the business gets on boarded and we dig into it. How can we move data into our due diligence process so that we identify what's there and we can uncover potential uses for that data in other ways once we bring that new business on board?

[Ken Scales]
Oh, that's a great question. I think part of it is in that due diligence process. You know, as you've signed the, you know, I'm sure after an LOI or whatever else that's going through, you've got access to that information where you can ask those questions.

And the first part of it is let's understand your technology infrastructure. Let's understand where things are located. What are you collecting?

And then maybe doing a little cursory dive into the data because there's probably a lot of things that you might not, maybe the company doesn't even know. Things that they're collecting that, you know, there's so many, especially larger corporations, there's so many different applications that folks are using and things that they're using it for and systems don't talk to one another. So it's real important that when you're going and doing your due diligence with purchasing a company, really understanding every part of the process of what they're doing from a business standpoint and what are the systems that they're using.

When you identify those things, we call them data assets. When you identify those data assets, what happens then is, okay, we then can understand what data might reside in those data assets that could be very valuable.

[Dave Lorenzo]
Let me give you an example of what I'm talking about. So there's a publishing company that I've had interaction with over the years and the publishing company does a phenomenal job of churning out like incredible bestsellers, okay? And I have to be kind of cryptic here because people will eventually figure out what I'm talking about.

And the way that they do this is they have, they have a free offer on their website that allows them to capture contact information. And marketers know this is a lead magnet. Nicola and I call it a honeypot, but their lead capture program is incredibly strong.

So they churn out millions of the lead magnets on an annual basis. This has given them a database and then they go back to the database and make, and they're sharp about it, they make additional offers to get additional information. So over the years they've collected name, first name, last name, email address, mailing address.

When they produce a new book, what they do is they'll do a free chapter via email and they'll offer something to them via mail as well. If they, you know, go to a bookstore and request the book, if you order the book from Amazon, if you leave a review, and they do a great job of doing these marketing campaigns for their books. So you can imagine their database is like 35 million names.

They send out an email, they do a direct mail piece, and they do a three-step sequence to get them to go request the book, do a review, and order the book on Amazon. And they sell millions of books and make best sellers. I've approached them about doing other things with that database.

Can you imagine, like other, you could do an event and you could fill a 20,000 seat arena. You've got 35 million people who are in your database asking for your books. That's content.

If you did a whole day of that content, you could fill a stadium with people. And they don't, they don't want to do that. There's just multiple uses.

So what do people look for? So I've tried to put a group together to make an offer just to have access, to give them money to have access to use that database. So what do people, what questions do people need to ask to understand unutilized databases?

Like where, how can we uncover data equity either in our business or in other businesses that are adjacent to ours that people just aren't using them? Like these people, they're happy with the current use of their data, but it's like they have a race car and they're only driving the race car to the supermarket. I just want to use it on Sunday and go to the track for two hours and I'll bring it back washed and cleaned and everything.

So how do we get to borrow our neighbor's race car? That's the question I'm asking you. What do we ask for?

How do we identify those opportunities?

[Ken Scales]
That's another great question. I don't think I've been asked that question in a certain way. So typically then that would be what I call third party data.

And so you're using that third party data to do something else with it. Maybe that wasn't intentionally used for that or whatever else. So probably for that company to feel safe, for you to use their car on Sundays and everything else and drive it nice and fast is maybe to put some guardrails on that car.

And the guardrails is really looking at the, if they have any PII information, that personal identifiable information that's with that data. If they can do something and scrub that information out or obscure it in some way, redact it in some way, there's still probably a lot of great kernels information to do. And sometimes you can do that from an aggregate form where you're not releasing the individual data and you're making decisions based on looking at it in an aggregate form.

So there's ways to do that. So basically we can put a nice bumper shield around the car and then you can still take it to the track. And if you hit the wall a few times a little bit, it's not going to hurt the car.

And that way it's not going to hurt the reputation either. But I think if there's a way that you can do that and they're okay with using the data for those different purposes, then there's a way that they could sell their third party data. Because there's a lot of folks that collect data, like you said, that if they can figure out a way to monetize that, that would be huge for their business.

[Nicola Gelormino]
So let me pick up on this because, Ken, you've now touched on some of the risks of, you have all this data, what are you doing to protect it? And highly regulated industries, for example, the medical field where you know you're subject to HIPAA compliance and you have that personal identifying information, you have medical records, then you know you have to meet certain standards and requirements to even have that data. Otherwise you're going to be subject to penalties by the government regulatory agencies.

But what about those companies that they're not heavily regulated? Because those are the ones that really know, they're aware of the requirements they have to comply with. So they already come to you asking, we want to make sure we're in compliance, or there's been a change in the law that we have to now comply with and update our systems.

But what about the companies that don't know? Talk to us a little bit about when they come to you, some of the measures that you help them put in place to be careful about protecting the data that's in their possession from being exposed.

[Ken Scales]
Yeah, a lot of times we'll do a software penetration test or a penetration test that's looking at, you know, breaking into their application that they're using or breaking into maybe their infrastructure that they have where they're housing that data. And so with a lot of our customers, we work with their managed service provider. And so we're like that third-party auditor that comes in.

And we do it in a way that's, you know, there's different ways to do it. One, you can, they'll know you're breaking into some things and there's ways that you're trying to do it from an external software penetration test where you're breaking in like you're an external user. And putting those safeguards in place is the key.

Most of the time what happens is it's not the external users that they have to worry about as much as internal users and employees. And it's not always malicious. It's just things that, you know, not using multi-factor authentication.

A lot of companies and, well, yeah, you know, I've got Joe over here and Joe's never really used multi-factor authentication. And so that's bad for Joe and Joe doesn't want to do that. Well, okay.

That's bad for Joe, but it's really bad for you if you have a, you know, someone breaks in or someone, you know, gets into. Yeah.

[Nicola Gelormino]
And like, especially now, I mean, employees are, you're overwhelmed with data. We all are. Data is hitting us from all different angles and all it takes is a moment where you're not focused on something and you click on that link to your point.

It's not malicious. You're just overwhelmed. You click on a link, all of a sudden there's malware or you're not paying attention and you open something else you shouldn't.

So those, those situations will arise and we have to be protective against them and put measures in place to help that, to help reduce that risk, even though, you know, it will happen, but we've reduced the risk. We've trained these employees, but you know, there's got to be a balance.

[Ken Scales]
Absolutely right, Nicole. I mean, there has to be a balance. And if there's not a balance, then, you know, it, look, if I see three homes and one has a, I can see- Big old dog.

[Dave Lorenzo]
One has a big old dog in the front door.

[Ken Scales]
Yeah. One has the big dog. One has a little dog.

One has no dog. And, you know, one security system, one doesn't have to, you know, which one am I going to break into? Well, it's pretty obvious.

The one that's the easiest one to get into. And so hackers look for the same thing. It's exactly the same way.

And so there's so many things with phishing attacks that are happening right now. And, and again, these things happen, right? But the more that you can protect yourself from them, just with simple process, putting that process in place, putting those, you know, at least the things like multi-factor authentication, password managers, things that you can put in place that really will, employees get used to it.

It does get easier. And it's really, there's, there's some simple things you can do to really help protect the data in that regard.

[Dave Lorenzo]
I'll tell you three things that I did after going through, you know, just a simple class on cybersecurity. Screen, screen protector on my laptop so that when I travel, and Nicole has always had this, but I was a knucklehead because I was like, I can't see it. So I put a screen protector on my, on my screen.

I use a YubiKey to log into my computer so that if I don't stick my key, my thing in my laptop, nobody can open it. I have a backup, like literally pinned to my wall over here in my home so that only those two keys, if that, if we don't have those, you can't get into the, can't get into the laptop and the secure router with a VPN when I travel. And I don't plug directly into hotel or airline internet anymore.

In fact, when Nicole and I traveled together, we both go through the same router so that our traffic is, is secure. It's not, it's not the foolproof, but it's doing what a reasonably prudent person would do when they travel.

[Ken Scales]
Absolutely. The one, the one thing you said that I want to, I want to point out really quick that was probably the most important as well is the backup. If you, you know, say, say you get a phishing attack, say someone gets into your system, say someone has ransomware.

If you have a backup that isn't that old, okay, fine, take it. I don't care. Let me, you know, you don't want them to do it necessarily, but at least you have a way to get up and running from a business perspective again.

And so having backups and backing up regularly, again, having that security process. I mean, Dave, you just went through a phenomenal security process that you and Nicola really go through. And those are things that will help protect you because look, I don't want to steal stuff off your computers really hard.

I'm going to go to someone else. It's a little bit easier. Right.

[Dave Lorenzo]
And I'll tell you, I learned this when I, so I got a, during the pandemic, I got a dedicated business internet line into my home and it was a static IP. And I didn't know the difference between a static and a dynamic IP. And when the guy installed it, he said to me, he said, you need to make sure you have a firewall and make sure it's a good external firewall because you have now have a static IP people who are hunting for IP addresses are going to find this very quickly.

And like, I, that just went in one day. I like, I didn't know what the hell, like he might as well have been speaking a foreign language. I had no idea what the guy was talking about.

So the first day I plug in my computer, it's separate, you know, this is literally in the pandemic. I separate from my kids. The thing is fast.

It's always on. I got no, I got consistent speed. It's fantastic.

I plug in my little server into it and I leave everything, you know, on when I go to bed, it's on. I come down the next morning into my office and I move my mouse for the screensaver. And on my main screen is a text file that says you should have a firewall and like this digital digitized happy face.

And below the happy face, it says, you're lucky. You don't have anything of value to steal. And I, I like go over the wall, I'm pulling the thing out of the wall.

I'm like, Holy, I'm like, I got to go to staples and figure out how to install a firewall. I was freaked out, Ken, like I got nothing. And somebody like in 24 hours, somebody found my static IP and got in.

Yeah.

[Nicola Gelormino]
So the bottom line here is like, you have to have multi layers of defense in place when you are dealing with data. And you want to hold that responsibly because you can be held accountable to your customers and others, especially if there's some type of data breach, you can be liable legally to customers if that data gets out and they are harmed by it. So got to have those protections in place.

I do want to move into Ken. So we kind of touched on how we protect our data. I want to move into like why your Scalesology, like I want to talk about scaling.

I want to understand for our listeners, like how can you use data to scale businesses?

[Ken Scales]
All right. Well, it depends on what kind of business you're in. But usually it kind of, you think about it in a couple of different ways.

One is it to, as Dave alluded earlier, how do you find those right customers? Right. I mean, looking at data and figuring out who is my target market?

How do I get to my target market? And then what are some and collecting different things that are going to help us do maybe a customer segmentation analysis, right? And say, OK, here are the right customers you go for.

Let's test this theory out. And it's an iterative process. The other way is operationally.

Operationally is a way that we do with a lot of our manufacturing clients. And a lot of it is really looking at their operations, making sure the process and their technology kind of fit like a glove and that they are doing things in a way that's the most efficient they can be. A lot of times it's looking at machine data.

Sometimes it's looking at the operational data where, you know, I go into a lot of places, I do technology needs assessments and I see, well, this is interesting. Why do you do it this way? And I get the answer.

Usually it's always the same. We've always done it this way. OK.

And so they've had a legacy system. They put in a new system, but they're still doing it the old way from the process standpoint. So you're not helping yourself out there any.

So again, there's that marriage between that process and the right technology. And, you know, that's why I talk a lot a lot of times about making sure you have the right data insights, but also the right technology in place so you can implement that seamless flow.

[Nicola Gelormino]
So what are some questions that you ask when you sit down and you mentioned the technology needs assessment that you perform with a business owner? What are some of the questions that you're asking high level?

[Ken Scales]
I love to walk through a day in the life. In fact, we've got a client we're going to be doing this with in a couple of weeks. And I like to just walk in there and I want you to tell me about what you do on your day.

You know, the company we're going to be talking to here soon is they've got a lot of different divisions, a lot of folks that are doing things. And sometimes it might be a laboratory, it might be order processing, it might be looking at walking the distribution floor of a company. And when I walk through what they do on a daily basis, and I just then can understand their day in the life of what they're doing.

And by doing that, you then really pick up things that are frustrating to them. And they don't have to tell you, you just watch them what they're doing. And usually they will tell you.

And they'll say, well, this is this is good. We're doing this in but this all my Lord, this is horrible. And so why do you do it that way?

Well, well, we've always done it that way. And two, they want us to do this way because of this reason. Oh, that's interesting.

And then and then I'll ask the person above. Okay, why do you have to do this way? I don't know.

We've always done that way. Well, yeah. And then you get to an understanding of okay, let's really kind of walk through a day in the life of this journey.

So a lot of it starts there. And my questions then really revolve around where are they in what they're doing, and trying to understand, okay, why are you doing this this way? What system are you using?

What data are you capturing? And so those are the you know, in every stage, every little division I go into, I'm asking those types of questions to understand the process, understand what systems are using and understand what data they're collecting. And eventually, then we and that's really identifying all these data assets that we can use to help them scale their company.

[Dave Lorenzo]
So Ken, I'm going to ask you about something else you probably don't do all that often. Because this is like, you know, instead of you and I like sitting down having a beer, this is we're just we're just recording the conversation for me to figure out ways that I can work with you. All right, how about this?

I, I've identified some data that's hidden in a business, I call I call you, you're coming in, we're going to figure out a way to monetize this data. But I know that it's like the chimpanzee scene in 2001, A Space Odyssey over at this company, right? They're literally like, you know, bouncing around trying to figure out what this giant object is.

And we got nobody that we can teach to use the data that you and I both know they can use. Can you help find people to put on site that can make the best use of the information that we've uncovered? Because I'm now demonstrating to these people, these folks, how and you're, you're finding the data, and I'm demonstrating how we can monetize the data.

So you're gonna, you're gonna turn on the data fire hose. And there's nobody on the other end with a bucket. And they don't know once they catch it in the bucket, how to use it.

And they don't even know how to hire somebody who has these skills. So would you do you have the expertise? I mean, you hire these people for your company, do you have the expertise to consult on hiring people to staff up a data department, a data analytics department in a company?

[Ken Scales]
Absolutely. We've actually done that for some of our clients, long term clients in the past. And we've actually interviewed folks that business analysts that have worked with us hand in hand to remedy, you know, whatever they're trying to solve.

And, and a lot of it has to do with, I start with there's this analytic flow, it's descriptive analytics, going to diagnostic analytics, to predictive analytics, to prescriptive analytics. And so for everyone here, you know, it's listening to the podcast here is, you know, descriptive analytics is that BI dashboard. It's right, that power BI, that's, it's the nice, you know, bells and whistles.

And that's really where you start, because you're trying to look at what's happened in the past. Eventually, then you're looking at pain points, you're looking at, okay, why did this happen? And that's when you're getting into the diagnostic analytics.

Eventually, then, like you said, how do we monetize this? How do we predict when this is going to happen? How do we make these data insights actually do something for us?

And that's when we get into predictive analytics. And that's when sometimes you're getting into decision tree modeling, you're getting into large language models, regression analysis, not to get too much in the weeds here for everyone. And then you eventually you're getting to prescriptive analytics, which is how can I make whatever I want to happen, happen.

And that's that data analytics journey. So when you first start, you're really just trying to gather all that information and say, all right, let me make something out of this. What do we have?

And that's where, you know, a lot of our companies we work with, we gather that information for them, we might even create those initial reports. And then we bring someone in that says, OK, now side by side, let's show you how to create some of these reports as well. And then we kind of go from there.

And so a lot of times then you're going up that ladder.

[Dave Lorenzo]
So for those of you who, you know, you're listening to this and you're thinking to yourself, yeah, I mean, I, you know, I got an old fashioned business that I don't know this data analytics stuff is not going to help me. Somebody thought that related to baseball and then 20 years later, look what happened. If you're a Red Sox fan or a Cubs fan, you understand that analytics is the only thing that has enabled your team to ever have an opportunity to get to a World Series and potentially win and win a World Series in 40 years.

Analytics, if analytics can transform the game of baseball, it can transform how you do business. And it doesn't have to be complicated. It's it's as simple as knowing what questions to ask everyone in your customer flow and then figuring out how to take all of that information and use it to make better decisions.

That's that's all you're that's all you're doing. That's the simple it's the simplest way to boil that down. Or in your cooking oil example, take all of the information related to your supply chain or your waste product and figure out how to take that to to put that information in one place, squeeze out of it what's valuable and use it to make better decisions.

That's all we're doing here. You don't need to be a Corinth. You don't have to go back to school and figure this out.

You've got to get good people who can translate the data into actionable items for you. That's what we're talking about.

[Nicola Gelormino]
You need a Ken Scales to come in and say, and I want to go back to that cooking example, too, that you have in what you did with that company. I was already hearing, OK, you know exactly when those pickups need to happen, when they are happening now, when they should be happening so that you can minimize that downtime in between. So that's operational efficiency.

That's making you more money. And then I'm hearing. So they were stealing right with the cooking oil that was used.

And let's set aside why it was being stolen. But that's stealing. So they're wasted product like that product that should be getting picked up that isn't.

Now we have cost savings associated with the data that came. So the cost savings came out of it. Operational efficiency came out of it.

And now we're able to predict what we can do in the future to be able to run even more efficiently. All of that came from the data because someone knew how to analyze.

[Ken Scales]
Nicole, you're absolutely correct. And then let's take it to what Dave was going with some some. How do we get more customers?

Well, who is the ideal customer that we're collecting most used cooking oil from? Right. I mean, probably it's not going to be.

I mean, Buffalo Wild Wings, Burger King, right. They produce a lot. They a lot of used cooking oil, probably when they're doing it on the college football last night.

Right. A couple different different things that you see with the playoffs and football games and March Madness and all those different events that those are, you know, those are going to be high flying companies or restaurants are going to produce that. So so you then see trends.

You have a target market you're trying to go after. And that that also helps as well.

[Dave Lorenzo]
All right, Ken, how can people get a hold of you if they want to continue the data conversation?

[Ken Scales]
Yeah. So you can always reach us at Scalesology, which is WWW dot Scalesology dot com. You can always reach me at Ken dot Scales at Scalesology dot com.

And we have our number is three one two eight zero nine three nine nine six.

[Dave Lorenzo]
All righty, folks. You heard it here from the man, Mr. Scalesology himself, the guy who changed his name to match the name of the company, Ken Scales. He's been our guest today.

We we hope I really hope that this shone a light on the hidden value in your business for you, because I can't tell you the opportunities that you may be missing out on by not digging deep into the data that you have. And I don't want you to go get a shovel to go dig it up yourself. I want you to call Ken because Ken knows where it's buried and he can find it for you and he can help you make more money with the information you already have in your business.

[Ken Scales]
There's gold in those hills, Dave.

[Dave Lorenzo]
Gold in those hills. There's gold in them, their hills. And speaking of information, we are back here with great information every day.

You can come back here tomorrow at 6 a.m. for more information. Join me and Nikki G every Wednesday at 6 a.m. for another great interview. Thank you to Ken Scales of Scalesology.

My name is Dave Lorenzo. I'm the godfather of growth and she is Nikki G. We'll see you back here again tomorrow.

Until then, here's hoping you make a great living and live a great life.