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Data Center of Excellence - Ross Koenig

Within the Shore Resource Team is a specialized group called the Centers of Excellence (COE). COEs came from operating careers to provide subject matter expertise and support to portfolio companies. COEs directly support companies on projects, share best practices between companies, and promote connectivity between companies so that 40+ companies create a competitive advantage through collaboration. 


In this episode, we discuss Shore’s COE focused on Data. Ross Koenig, Chief Data Officer for Shore, talks about what good data infrastructure looks like, misconceptions about data, and how answering a few simple questions can lay the foundation of a powerful data strategy.




Anderson Williams: Welcome to Bigger. Stronger. Faster., the podcast exploring how Shore Capital Partners brings billion dollar resources to the microcap space. Centers of Excellence at Shore Capital are subject matter experts who provide their functional expertise to support our portfolio companies.

COEs, as they're known, share best practices, and engage with our portfolio to address real business challenges and to create opportunities far beyond what a traditional microcap company could do on its own. In this episode, we highlight Shore Capital Center of Excellence focused on data. 

Ross Koenig: My name is Ross Koenig. I am the Chief Data Officer for Shore Capital Partners as part of the Centers of Excellence team.

Anderson Williams: So what does a Chief Data Officer do as a Center of Excellence?

Ross Koenig: That's a great question. I like to think that I wear a lot of hats. Data can mean a lot of different things to our microcap portfolio companies, some of which are just starting out. A Chief Data Officer is there to set foundation, more PowerPoint work, less technical work.

What is a data strategy? What are the important data elements that we're tracking? What are the data elements that we're not tracking? Kind of more in line with strategic, and then as our companies grow, as their operations become more complex, the Chief Data Officer's role changes, right? We start introducing more technical conversations.

What is a data warehouse? What is infrastructure, what does good data infrastructure look like? Let's make sure as your company grows the complexity and sophistication of the data infrastructure to support that growth is maintained well, has the right foundation, and then when we have infrastructure in place, kind of the third phase is analytics.

In my personal opinion, that's the fun part. That's when we are taking business problems and we are applying a quantitative approach to solving them in a way that a person with good business instincts might not otherwise have immediately available in their toolkit. 

Data Misconceptions

Anderson Williams: When you think about the Shore Capital portfolio, when you think about the microcap space, what are some of the misconceptions or challenges that people have about data or when data is important or, what's the right time to invest in data?

Ross Koenig: This is a loaded question.

Anderson Williams: I know that.

Ross Koenig: Because a lot of my conversations with our microcap portfolio companies, they read a really exciting article or watch an exciting podcast about artificial intelligence and predictive analytics, and they want to talk about doing that. And the unfortunate reality is that it's certainly not the right place to start for most of our microcap businesses.

I think what's exciting for me and where it's never too early to start is laying the right foundation, for a data strategy in terms of collection and organization and standardization, such that in X years, sometimes it's two, sometimes it's five, sometimes it's 10. You can start experimenting with more impactful efforts like predictive analytics and artificial intelligence.

So, I think the biggest misconception is big data is only reserved for Google. Now, while there's a lot of truth to that statement, there are a lot of really foundational, impactful efforts that our microcap businesses can undertake that's gonna make everything easier. And it's not just analytics, it's day-to-day operations.

It's reporting to your internal stakeholders. It's reporting to your customers, it's reporting back to Shore. These processes take time and with good data infrastructure, they can take less time. Because you're just more organized and those are the first conversations I usually have when our portfolio companies want to talk to the Data COE.

Anderson Williams: And, who do you work with at a portfolio company?

Ross Koenig: It varies. There is not usually a Chief Analytics Officer or Chief Data Officer at our portfolios, nor should there be. Most of the time it's a combination of the Chief Financial Officer, I talk to a lot of CFOs. They're usually the most quantitatively oriented person, frankly, who's feeling a lot of the pain from lacking sophisticated data infrastructure just due to reporting requirements and different analyses that they're trying to accomplish.

So, work with a lot of CFOs. I work with a lot of CXOs, Shore's CXO program. I love working with the CXOs. By definition, they're the generalist jack of all trades. We know what the Chief Marketing Officer does. We know what the Chief Technology Officer does. The CXO is kind of the other, and a lot of times data is the other.

The Role Data Plays

Anderson Williams: And, what role does data play or should data play as you think about the acquisitive nature of our portfolio? How does that play when you may have a platform who's getting its house in order, but you're acquiring businesses left and right that have different data strategies, or no data strategy, or a ton of data, or no data, whatever that might be.

Ross Koenig: Data can be a wonderful avenue to maintain consistency during acquisitive phases of a company's maturation. I think we spend a lot of time upfront in some of our early stages, they only have one or two assets. Really defining what reporting looks like and what we want our basic questions, in our healthcare businesses is, what is a visit?

You know, that's a data, right? A data element is the count of visits or is that different from an appointment? Is that different from an encounter? And as we establish that and feel really good with our management team in place to say these are one of the fundamental things that we talk about from Data COE is you need a data dictionary.

You need a KPI glossary. You need to understand what everything that's showing up on all these reporting means. Once we have those definitions in place, we go out and we can acquire a business or we can evaluate an acquisition and we can look at their visit data. And we've spent a lot of time thinking about how our portfolio company defines what a visit is, and we can poke and prod in very consistent ways to make sure that not only is this a valuable asset as we think it is, But we can also get a really, really good sense of what our consolidated business is going to look like post acquisition, because we've already done some of that work within that company's data, alongside our well-defined, managed internal data.

Anderson Williams: And, that's a good example of the types of data and foundations, right? A dictionary understanding what sort of principle activities, like a visit or an encounter or what those things are that makes sense in the healthcare space. What about an example from business services or food and beverage in terms of how they're thinking about data?

Ross Koenig: Yeah. My favorite of all time, and if you google around like baseline data infrastructure, good data governance practices, this is always one of the go-to examples, but it's really interesting to see it in practice. What is a customer? And business services customers are a little bit trickier.

If I service a firm that has four different divisions, do I have one customer? Do I have four customers? Do I have a way to make sure that when I acquire another business, if my acquisition serves subsidiary, am I acquiring new customers? Am I not acquiring new customers? I need to define these hierarchies in a way that most importantly, I know what's happening.

Data Strategy

Anderson Williams: When you're talking about data and you're describing some really fundamental understandings of the business, like who is a customer and what is a visit, I don't think that's necessarily what people are thinking of when they're thinking data strategy.

Ross Koenig: Yeah. Data strategy is this loaded term that people almost are intimidated by. The cold reality is if there was a dictionary for business terms and you looked up data strategy. It's pretty flexible. I always talk about, hey, what's the most important information that you can have? And let's talk about how you get it, how you organize it, and what you do with it. That's your data strategy.

And for business services, we can talk about all of the millions of quantitative information that they're collecting around their daily revenue or their daily production numbers. And those are all, don't get me wrong, extremely important data, but for most of our microcap businesses, the most important information that they have is the information on their customers.

So, if I talked to a recently acquired business services, you know, Shore portfolio company, say, well, what do we want your data strategy to be? Maybe the first most important thing is making sure all of our customers are properly categorized and we have a really good ingestion process for new customers and maintenance process to make sure that their contact information is as up to date as possible.

That's a data strategy. So it's a great call out, Anderson, because data has this, you know, what are we doing, predictive analytics and statistics and all these things. And don't get me wrong, those are fun, but if we don't have a consistent definition of a customer, we're not gonna be able to run any kind of predictive model on what the best customer is because we can't even define it in the first place.

One of my favorite, go-to quotes, is you want an artificial intelligence strategy. You want a predictive analytics strategy. Let's talk about your data strategy first so we can get there.

Anderson Williams: So it's a lot less, sexy than AI, but also a lot less scary.

Ross Koenig: Correct. Yeah.

Anderson Williams: And, how does somebody come to you? How do you, just from a functional standpoint, if I am the CEO or a CFO or a CXO of a company, how do I present an opportunity or a challenge or a question to the Center of Excellence?

Ross Koenig: I hope you just give me a call, shoot me an email. Shore is such a vibrant network of events, you know, whether it's formal board events or informal events like our ELA Summit every year, just get approached.

You're the data guy, I gotta talk to you about something I've been thinking about and that conversation, it's five minutes in passing, maybe over a cocktail, maybe not. And that leads into an hour long discovery call where we say, okay, that sounds like a really good idea. Some of it jumps to the more ambitious part, and we don't wanna lose sight of that.

But I'm here to anchor you into a more practical roadmap to get there. Let's start with, you want to predict customer churn. Where are you collecting attributes around the customers in a consistent basis? Oh, is it in Excel file in this place? And some of it's in Salesforce and some of it's in our ERP.

Before we build this predictive model to do customer churn, which I promise you we'll do, we gotta get everything organized first and then we kind of stage it out like that. So, I don't think I'm very intimidating guy. I hope if anyone wants to talk to me about data, they can just reach out to me. No problem.

How to Prioritize Data

Anderson Williams: And, how do you suggest people think about or prioritize data? We've talked a lot about what it is and what it isn't and what it can't be, but when I am sitting at the early stage of my journey as the new CEO of a new platform, for example, what's your recommendation for what even opening the
conversation with you about data is and when that should happen and so forth?

Ross Koenig: Yeah. I mean, there's never a bad time. You have a real business question. You have a testable hypothesis, which can be hard. A lot of times I just start with your instincts, right? You have a business problem you wanna solve, let's talk about your business problem you solve. We sit down, we go back and forth for a while.

We can essentially move some of the insights in the strategy sessions that you and Dr. Bertram are at the forefront of. If I want to think about a data strategy, the first thing I think about is I pull up that document and I say, okay, what are our top five business priorities? And then we just work backwards.

I think I can take almost any business priority and deconstruct into a data initiative. Sometimes it's a really huge jump because the information that you need to support it is not very available or it's really ugly, or it's in legacy systems and it's not worth it. So, we deprioritize it and other times it's like, oh, this is pretty straight up and down in front of us.

We just have to put some dedicated time and effort assigning the right person. Again, like not everybody's got a VP of Analytics, but somebody probably has an FP&A analyst who's hot to trot on something that's really interesting. Let's assign work. Let's give a framework and let's go for it.

Anderson Williams: And, it does sort of resonate with the whole Shore playbook concept, right?

Because I feel like data is a prime example of where and how you can build a playbook. It doesn't mean that all the data's the same, but it means there's a pattern and a structure and a way of thinking about data, whether you're in manufacturing or in healthcare, whether you're defining a customer or a client or a visit or whatever it might be that there's a certain way of thinking about data that is applicable across companies.

Ross Koenig: Agreed.

Anderson Williams: And that's where this does become a universally sort of valuable resource, regardless of a vertical.

Ross Koenig: Yeah, and I'll say this is, I think what I've been most excited about is back to something I mentioned earlier, is we have unbelievably smart, intellectually curious founders and executives and departmental leaders who are asking all these questions, but because they're a microcap business, they don't really have time to put in the, you know, data's a wonderful thing, but it is not a small task.

To do a comprehensive analysis, to clean up a giant data set takes time, and these folks are asking the right questions.

Anderson Williams: And you don't just do it on Tuesday.

Ross Koenig: No, no.

Anderson Williams: Right. It's not, it's not a, it's not a weekly check-in.

Investing In Infrastructure

Ross Koenig: I wish. If we really invest in really good infrastructure and a few years, we might be able to do some of this stuff on a Tuesday, but that's also a monumental effort at first.

I think what fits so perfectly, because it's like, these folks are asking these questions, they just don't have time to sit down and say, okay, I want to know what my most profitable customer profile looks like. That's a really standard question that a lot of people are gonna ask and you can get there with a couple of reports and you can get a pretty good answer.

You can create a competitive advantage if you leverage data and analytics to answer some of these questions, that a typical microcap company just wouldn't have the bandwidth to otherwise do.

Anderson Williams: Well, and I think that when you've had the startup experience, right, and these are successful companies that we're acquiring, but they're microcap companies.

Ross Koenig: Yeah.

Anderson Williams: In some ways, this idea of shifting from growing to scaling requires data.

Ross Koenig: Once you start harnessing the power of something, you know this idea of comparables is so powerful, right? What does the best customer look like? And you can think about, and again, like so many people have these ideas intuitively, like when we worked with our urgent care business, we were able to find a couple of patterns that resonated.

Like, what does our ideal customer look like? Well, what does that mean? Who's coming back? Who comes back to our urgent care business within the next six months? We can quantitatively test that and we can start to look at spikes in patterns that say, okay, well it's actually the patient that's most likely to return in six months is a female patient who's between 28 and 35, who's primary home address is within five miles of one of our clinics.

Let's run some numbers to figure out what the customer persona is, who's the most likely to never return if they have a wait time of, and we can solve for that number.

Anderson Williams: Well, and it could be true to fill times in manufacturing or anything like that too, right? It's about serving the customer better.

Ross Koenig: Always. Always.

Data Drives Value

Anderson Williams: And to your point, with more precision, which then is, driving more value because you have the data to know what they value?

Ross Koenig: Every time. In ways that they might not even know, right? That's the most exciting one. You can tell a customer what they probably want next quarter before they know it, you better believe they're gonna come back to your business before they go to a competitor.

Data is the most collaborative. You can talk to the best data scientists in the entire world, and the first thing that they'll say is, we wouldn't be anywhere without our amazing business stakeholder. You need somebody to be back and forth. You need that creative type or strategic type to say, hey, look, here are the things that I'm thinking about.

Can you take these ideas and go run with it? If there's one thing that we can also say, it's do not think as an intelligent, as an intuitive business leader, that data and analytics is supposed to come in and replace your intuition. Because it's not and it shouldn't. And anyone who says that it should, I would run the other way on.

It really should be thought of as a supplementary way to help your intuition be more precise, be more exacting, make you feel better about the decision that you're making already under certain terms, or maybe make you doubt something a little bit more. And that could be the deciding factor that ultimately translates into a no, right? It works both ways.

Anderson Williams: So, data and Ross and the Data Center of Excellence are all about deepening our understanding of the business and where to best invest time and energy and resources. And, we don't have to wait on AI to create a meaningful impact with data. We can start now, and if we start with the right foundation early, data can become a competitive advantage that distinguishes a Shore portfolio company from the competition.

This podcast was produced by Shore Capital Partners with story and narration by Anderson Williams. Recording and editing by Andrew Malone. Editing by Reel Audiobooks. Sound design, mixing, and mastering by Mark Galup of Reel Audiobooks.

Special thanks to Ross Koenig.

This podcast is the property of Shore Capital Partners, LLC. None of the content herein is investment advice, an offer of investment advisory services, nor a recommendation or offer relating to any security. See the terms of use page on the Shore Capital website for other important information.

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