Modern Data-Driven Solutions with Jeremy Clopton
One of the hottest topics in the financial world today is Data Analytics. But how does a CPA firm start utilizing Data Analytics in its day-to-day operations, or even offer Data Analytics services to its clients? Randy talks to Jeremy Clopton, director at Upstream Academy, about the role Data Analytics can play for a firm’s practice—especially as AI and machine learning loom on the horizon—and about the future of the accounting profession in this changing landscape.
Today, our guest is Jeremy Clopton. Jeremy is a director at Upstream Academy. He started his career at one of the top accounting and consulting firms in the country, where he led a firm-wide specialty practice. During his 12 years there, Jeremy gained extensive experience in Data Analytics—which is going to be important to our discussion today—fraud prevention, and business intelligence.
Prior to joining Upstream, he launched his own consulting company, focused on developing more successful cultures by asking better, more strategic questions. He created the SQ Method, a framework designed to help firms overcome challenges and more successfully adopt new technology, analyze and utilize data—data comes up again, we may be talking about that today—encourage innovation and drive employee engagement. Jeremy speaks both in the US and abroad at industry events as a faculty member for the Association of Certified Fraud Examiners. Jeremy, welcome to The Unique CPA!
Randy, glad to be here. Thanks for having me.
I appreciate you being on and I appreciate you being on for a second time! You are the first two-time, full episode guest—we had a few people on for a special episode that were on other ones—but you’re the first repeat, full episode guest. So I’m sure you’re taking much pride in being the first for that!
I am. Well, that makes me a Unique CPA, right? So I’m gonna take a lot of pride in that!
You fit the bill! A Unique CPA, there you go, nice.
Before we jump into it—and I guess I teased it at the beginning there in your intro—we are going to talk about Data Analytics today. But before we do that, I want to ask you a few things about Upstream. I’m thinking a lot of our listeners are familiar with Upstream. You guys have a lot of conferences each year, you deal with firms individually, you do a lot of work in the industry. But I am extremely missing all the conferences that I get to do with you guys every year, and I think I’m usually at three or four. So what’s going on? You’re not having the conferences, I’m assuming, right?
We’re not No, we’ve, we’ve like many we’ve had to pivot a little bit to in 2020. We don’t have any of our in-person conferences for this program here, essentially. June to May is typically how we operate. We start a lot of our programs in June, and obviously, that was not the ideal time to host conferences. One of the conferences in particular that I’ve always seen you at—it was actually coming up here in just a couple weeks from the date that we’re taping this in late October, and it just wasn’t the right time to hold a conference.
So a couple of those conferences that were standalone, we simply aren’t holding this year. We’re hoping that next year is maybe a little different, and we can get back to those. But many of our programs, many of our seminars—we actually pivoted and turned them into virtual. We had one in particular that I’ve been working on the last couple years—speaking of data—“Helping firms launch a Data Analytics service within their firm.” That was an in-person boot camp—two and a half days. It was a lot of time for them to sit down and really work on something together as a team within their firm. We pivoted that to virtual in June of this year.“Fantasy football is a great way to talk analytics. You've got analytics in your pocket to select your team, so you're using analytics, whether you realize you are or not.” Click To Tweet
Actually, it’s interesting, Randy—that aspect worked a little better, because what we found is that more firms can bring more people to some programs and events, which made it a bit more valuable from the firm standpoint. The thing that I think we’re all missing, though, is that networking, You just can’t recreate that as effectively, virtual. Can you recreate it some? Of course you can. But it’s never the same as grabbing coffee before the conference and sitting down and chatting about things.
Or the happy hours!
That’s our firm motto: You gotta be first to the happy hour, last to leave. We’re missing those! Thanks for the update.
The one thing I did want to ask before we transition into Data Analytics, is that I know this was going to be Tim Bartz’s last year—Tim was a partner with Upstream—and I was looking forward to being able to celebrate his retirement with him. Unfortunately, I’m not going to see him. Do you think there’s any chance we’ll see him at a conference, once conferences start up again?
You know, we haven’t officially talked to him or got him on an agenda for something, but like you, I’m hopeful that we can get him to one of our next conferences to give him a proper sendoff. Tim’s meant a lot to Upstream. He’s done a lot for our firm; he’s done a lot for the profession. I know there’s quite a few folks that would like the opportunity to be able to wish him well as he kicks off retirement. So I’m not going to say won’t be at a conference—I can’t guarantee that he will—but I’m with you rooting for him to be at at least one more so that we can all celebrate with him.
I think we need to start a petition, and we’ll get everybody to sign it, and we’ll get in his hands and we’ll make sure he’s there. And one last thing on Tim—I know he’s a big Dodgers fan. I don’t want to jinx him because he thinks you can get jinxed but his Dodgers won one yesterday, and by the time this airs, I’m hoping they’re still playing because as a Cubs fan, I don’t have a team to root for right now, and I’m actually rooting for the Dodgers this year. So we’ll see what happens.
Well, I won’t hold it against either of you. I’m a Braves fan.
It’s okay. I’m not that adamant a fan, but I’ve always been a Braves fan since I was a little kid, even living in Missouri—somehow fell on the Braves bandwagon. I was telling my wife last night, I realize everybody always says, “You know, they’ve always made the playoffs, shouldn’t that be enough?” But I’ve only seen them win one World Series in my life. So I wouldn’t mind at least one more.
No, but you’re more spoiled than I am though. As a Cubs fan, I’ve seen one, which is great. But it took a while. Alright, so enough of sports, although I could do that all day. You want to talk fantasy football, you want to talk COVID in the NFL?
Hey, fantasy football is a great way to talk analytics. You’ve got analytics in your pocket to select your team, so you’re using analytics, whether you realize you are or not.
See, aanalytics is everywhere, and I don’t even understand it. So let’s get into it. I should—and I may have told you this last time on the show—I actually have a computer science degree. That was 35 years ago, but I have a computer science degree that has kind of left my brain since I worked on my Master’s in Accounting and changed the goal of my professional career.
Data Analytics, because it’s so prevalent now—I mean, from the definition of from the word itself, you kind of know what it is. But can you give us a little deeper definition as we start this discussion? What is Data Analytics? That might be a loaded question there, but the simple definition?
Yeah, it is a loaded question, and it’s a common question—I’ll give you the definition, but I’ll tell you, I went the opposite route, so I don’t have a computer science degree. I took two IT classes in college, and they were the two that are required to become an accountant, so they weren’t really IT classes. I think it was QuickBooks and Microsoft Office, if I recall correctly. I went the opposite approach. I went the accounting route, became a CPA and decided that I fell in love with data.
So as I look at it, I’m going to give you a definition, that’s more an accountant’s definition, perhaps, than it is the formal Gartner or the IT definition. When I think about Data Analytics, it’s a process that you use to identify patterns, trends and relationships to answer a question or solve a problem. At the end of the day, that’s the basics of it.
Let’s go back to your fantasy football example, since you mentioned it. Analytics in that context—your problem that you’re trying to solve—is “Who do I put in my lineup this week?” Behind the scenes, you’ve got an app that is analyzing the data, it’s looking for patterns, it’s looking for trends, it’s looking for relationships—that ultimately will give you that red arrow down or that green arrow up that tells you where to put the guy on your team. Either play him or bench him. It’s looking through that data for those patterns, trends and relationships, that gives you the answer to your question, which is, “Do I play this wide receiver or not this week?” So it’s everywhere. The interesting thing is that it’s everywhere.
So that is taking trends, playing percentages—and I’m probably simplifying it there—but how does this player do against this type of defense, a 3-4, or a 4-3. Or this defense in general, how strong is it? Okay! I’m starting to get excited here! Data Analytics is everywhere.
We could talk fantasy football all day, but let’s talk specifically—when we’re looking at Data Analytics and the accounting profession: What are three places it can be used within accounting, but what are those areas you can see it being used within accounting?“Data Analytics is a process that you use to identify patterns, trends and relationships to answer a question or solve a problem.” Click To Tweet
Within an accounting firm, analytics can really and truly be used anywhere. You can use it on practice management. We’ve got plenty of questions that as leaders we ask in our firms: How do we improve AR? How do we improve billing and collections? How do we improve chargeability? How do we improve growth? How do we do better business development? How do we drive employee engagement? How do we have a more successful culture? We can use Data Analytics to help guide and inform how we answer those questions and how we respond to those questions.
You can use it on the consulting side. So my background, I was in the forensics practice of the firm that I was with virtually my entire career, with the exception of a few months where I dabbled in audit, and we all came to the agreement that wasn’t where I should be, because I didn’t really get along with materiality. I like the details—hence, the analytics direction. On the consulting side, that is all about answering clients’ questions and solving clients problems. That’s the very definition of what we do in a consulting practice. So there’s a great a great application there.
But then you’ve also got it on the traditional side of the house, whether it’s assurance or tax—you can still solve questions. It could be, “How do we look for compliance with an audit standard in a more efficient and effective manner?” And there’s those two E’s there that I just used, that we so often hear with analytics: efficiency and effectiveness. No matter where you’re using this within the firm, I always encourage firm leaders—focus first on effectiveness, because that should be why you want to do this. If you can get more effective using analytics or even more advanced technologies—maybe it’s robotic process automation, maybe it’s artificial intelligence, and we can talk about those here in a second—it shouldn’t just be to do the same job faster. There are some reasons to do that. Yes, efficiency is good, but wouldn’t we like to do a better job first? We’ve got to have that balance of the two.
So often, where firms look to apply it as focused on the efficiency and old safety assurance side of the house. In many firms, they want to do their audits more efficiently, and that makes sense. It’s not exactly the area where we’ve got the highest margins in most firms, so more efficiency is better. But at the same time, efficiency doesn’t come with project one. Efficiency comes with time, which means we’ve got to have another reason. That’s that we’re actually doing a more effective audit—we’re minimizing the firm’s risk, because we’re doing a better audit. Therefore, there’s a really good reason to do this. Also, we can get more efficiencies, which is why you can get the benefit of both.
Nice. And of those services, I think I want to ask some additional questions on the consulting end, but before we do that, the question came to my mind of, “Okay, we have these areas in the tax consulting, the practice management, so there have to be tools? Or are you programming something to do these analytics? Are you purchasing off the shelf tools? What do we use to do our Data Analytics?”
I guess my most common answer to that question is, whatever you’ve got is what you should start with. Every firm that I’m aware of has Microsoft Excel. Now there are going to be some analytics purists that are listening into this, data scientists, some IT professionals, that are going to say, “I can’t believe he just told somebody to use Excel to do Data Analytics.” I will readily admit it is not the best tool to use from an analytic standpoint. But if you’re comparing that to simply not doing it because you haven’t spent thousands of dollars on software, it’s way better than that.
So I always encourage firms, start with what you’ve got, and then build to what you need. I never want to start a conversation with tools. I never want to start a conversation with software, Randy, and the reason is, there’s so many categories of software out there. You’ve got your pure play analytics, which would be Galvanize, IDEA, and Arbutus. Those are kind of the three that we most often see—Teammate Analytics might play into that as well, some of your add ins for Excel, and whatnot. Then you’ve got data visualisation tools. Those are the ones that are gonna help you see the data better are going to help you communicate the data better to your clients. So you’ve got Tableau, Power BI, Domo Qlikview. Then you’ve got your Artificial Intelligence. Probably the most common one out there that I hear firms talking about right now is MindBridge.
All of those tools are great tools, but here’s the thing: Unless you know what problem you’re trying to solve for your client, you can’t effectively go choose a tool to solve that problem. I always encourage people—don’t buy the software, turn it into a hammer and go on a hunt for nails. I realize that’s cliché, and I try not to use clichés, but that’s what so many people do. It’s not unique to the accounting profession. I talk to companies all over the all over the place, industry-wise, all over the country—that they do the same thing. At the end of the day, though, what we’ve got to figure out is, “What is the problem we’re trying to solve?”
We’ve had I think right around 70 firms go through our bootcamp on launching new services, launching a Data Analytics service within their firm, and some have said, “Look, we’re not looking to go on consulting yet, we’re looking to go on the audit side.” That problem requires a completely different toolset. On the tax side, it’s going to be a completely different toolset as well. On the audit side, often you see, again, Galvanize, IDEA and Arbutus, because you can drop a general ledger in. There’s a lot of tools that are out there that are already programmed to help you use those to be effective, and now you get a more effective, more efficient audit, and that’s great.
On the tax side, it’s typically “scan and populate” type software, where it’s more using artificial intelligence to read documents in and reduce data input and data entry. There’s a lot of value there.
On the consulting side, you can go anywhere you want. You could go artificial intelligence, you could have somebody that’s going to program something in Python or R or SQL, where it’s more of a pure play programming type. It could be data visualisation. It could be an interactive platform that they’re looking to build. All of that depends on what problem are you trying to solve. It’s really important to go there.
Yeah, let’s do that. So but I’m going to put a scenario out there. And then let’s build on that.
We started Data Analytics now in our firm on our audit engagements. And we’ve observed and realized we’ve got these efficiencies, and it’s effective, and it’s been very helpful to us. I was like, “Okay, we have this knowledge now. We should be looking at our clients and offer this as a service for them.“ Now, obviously not exactly the same, but we see the benefit of Data Analytics. So now we want to start a brand new practice area within our firm of offering Data Analytics services. How do we do that? There’s a problem we have to identify. Does each client have the same problem? Do we have to individually identify clients separately? How do we even start this process of adding the service?
One of the first places to start is really looking at the client base and saying which your ideal clients to go solve problems for. Because at the end of the day, not every client is going to pay for a consulting service. There are probably some industries that firms work with that they’re great from a compliance standpoint, they’re great from an assurance standpoint—but at the end of the day, they’re not going to pay for extra services, because they just don’t see the value. They aren’t going to pay for consulting.
So you’ve got to first identify what industry you can serve the best. Typically, the way that we talk about that is an industry that has some of your best clients in it. I recognize everybody listening to this has their clients and say, “Well, my clients are the best clients.” So let’s talk about it objectively.
If you look at your firm’s A and B level clients, the best of the best clients are the ones that really view your firm as their as their advisor—as their service provider—beyond just compliance-type services. Who are those clients? What industries are they in? What problems are they facing, that you are well positioned to solve? From an industry standpoint, you’ve got some expertise in it, you’ve got your best clients in it. And it’s an industry that historically has been willing to pay for consulting. Over the years, there have been certain industries where they say we’ve got some great ideas, but at the end of the day, they go back and they look at it and say, “But that industry’s never spent a dime on consulting with our firms.” So now you’ve got a whole other barrier to overcome, which is business development—breaking into an industry and a new service. That’s a kind of a challenging place to start. It doesn’t mean you can’t go there, but man, I’d love to start with our best clients and go help them in more ways, rather than trying to start completely from scratch.“What a great problem for a CPA firm to solve—Those decisions you made last month? Here's the impact that they had on your financials. The decisions you're looking at right now? We've taken the data... We've modeled that out.” Click To Tweet
So let’s pick an industry then—an industry you see, that’s very useful. Let’s say we have a construction industry, or whatever our expertise is, and then, what are the types of things, the problems that they have—maybe even don’t know they have—that Data Analytics can help with?
From an industry standpoint, I’m going to stretch the definition of “industry” because I want to make sure this is applicable to as many firms listening as possible. Small to mid-sized companies that are looking to use your client accounting services, or client advisory services—we’ve got small and mid-sized businesses that hire us to be their outsourced accountant/bookkeeper. You’re their outsourced accountant, you’re their outsourced controller, you’re their outsourced CFO. They’re looking for somebody to be their financial arm because they don’t have it.
What a great way to now increase that level of service, because you look at one of the most common problems that small to mid-size businesses that firms work with have—financial literacy and financial transparency. Once a month, typically a couple weeks after close, they get a financial statement, but here’s the thing: Many of those business owners, they know how to read a financial statement because they had to in order to start a business, but they may not know how to interpret it. They not may not be able to tie their operational decisions back to the financial performance. So what a great problem for for a CPA firm to solve—Those decisions you made last month? Here’s the impact that they had on your financials. The decisions you’re looking at right now? We’ve taken the data, we’ve run some scenarios, we’ve modeled that out, and this is what appears to be your best decision going forward.
There’s no guarantee. Even the best statisticians and data scientists out there, they still speak in probabilities: “There’s a 93% likelihood that the one seed is going to beat the 16 seed in the NCAA Tournament, but it’s happened once, so it’s possible.” Now does that mean that the probabilities were wrong? No, the probabilities were right—the unexpected happened. We help our clients do the same thing: “Here are the four possible decisions that you have that you could make. This is the one that looks like it should be the best for you. And you’re going to make that decision, we’re going to keep analyzing the data for you, we’re going to help you “right size” that decision, we’re going to help you improve on that decision. And all we’re doing is taking operational decisions and tying it to financial performance. We’re already good at that! As an industry, we get it. That’s such a great way to do that, because every firm can help their clients better understand their financials.
Especially if you look at some of the physician services groups, veterinary clinics, eye doctors, sole practitioners, pharmacists—anyone where you’ve got an individual that is a specialist providing a service—so professional services very broadly. An individual that is providing a service to the to the public, or to their market, that is an expert in that, that then hires an accounting firm to be their financial back office. You can elevate your ability to help that client by using data and analytics to help them inform their decisionmaking and grow their business. And now, you’re their advisor for the future, because you’ve helped them get better at what they want to get better at, rather than just simply providing an output—a report or something.
What about launching the service then? Is it a brand new service within the firm? Or, we were just talking about client accounting services. Is this just in that scenario? Just in addition to that? How do we go about that?
That’s one of the great things for firms right now is, they have that option. There are some firms that will completely launch an analytics service as a standalone service line, and it’s just focused on helping solve client problems using analytics where people are asking for analytics. There’s some value in that—it helps differentiate the firm, makes sure that you know, folks know that yes, the firm does analytics. But for many firms out there, especially small to mid-size firms, standing up a completely new service line, that’s technology focused that doesn’t necessarily have a foundation in accounting—that’s a daunting task.
What are we going to do? Do we go hire a data scientist? They’re not exactly the easiest folks to hire, especially into the accounting industry culture, because it’s a different world than most IT professionals have lived. What I like about it is, an analytic service can be so complimentary to existing services. Maybe you don’t yet need a service, maybe what you need is the skill set. What you need is the ability to add analytics or use analytics to enhance existing services. It doesn’t have to be standalone.
What you’re doing now is you’re saying, “How can we use analytics to improve upon the services that we’re already offering the market? How can we generate more value for our clients? How can we generate more revenue for our firm?”
That’s one of the reasons, Randy—I love the fact that you went to the consulting side, because I think for a long time firms have looked at analytics as something that informs the assurance side or informs the tax side, and it just makes those processes more efficient and more effective. That’s a difficult ROI to measure. There’s a lot of firms that don’t see an ROI, because maybe the time gets used elsewhere, or it just doesn’t happen.
When you go on the consulting side, you are adding more value to your clients. Now that you know the problem, you’re finding that right solution, And maybe it’s pure analytics, maybe it’s data visualisation—you’re using a solution, you’re using that service to now help your clients get even better. It’s a very advisory thing to do, and as you and I both know, that’s one of the big buzzwords right now is being an “advisor.”
That’s right, firms are changing their names to “advisory firms” instead of a CPA firm. So something you just said there—adding this to an existing service. Do we have the right people in place to do this? Are we going out and having to hire a data scientist? How do we go about that?
Every firm is going to be a little bit different, of course, but many firms probably do have somebody in-house that can do this. There are a lot of young professionals right now that are very analytics-focused. Some of the universities are teaching analytics as part of the curriculum. So what’s nice is, we’re getting more and more individuals that are very tech savvy, that have an interest in using analytics and business intelligence and the various elements of that to serve clients better.
At the same time, some of the best folks that I’ve worked with over the years—some of the best analytics minds have been in the industry well before analytics was a degree that you could go get. It’s individuals that are just really good at serving clients and solving client problems using technology. So I do think that for many firms, they’ll have somebody in-house that can get them started. At some point, they may hit a point—I know a few firms that have hired data scientists that can come in and build and program the algorithms and take it beyond the off-the-shelf type of solutions. But for so many firms, there’s a reason that the programmers are programming the way they are, and the tech companies and the software companies are building the software they are—it’s easier to use, and you don’t necessarily have to have a programmer.
I’ve told firms for a number of years, I would much rather you hire somebody that can use technology, and has the business acumen to help your clients, rather than hiring a programmer. Let the software companies hire the programmers to build the software that our people can go use. We’re much more comfortable hiring people that can use technology and have business acumen than we are hiring IT professionals anyway, because the way that most firms are structured, that is a very challenging environment for someone to come into. To come from a programming background, and I’ve hired programmers over the years—it’s a whole different world when you’ve got billable hour budgets and tracking time. It’s a different mindset. It’s a different culture to be in, and it can be a challenge.
So speaking of employees and hiring, one thing we hear out there is “AI, machine learning—I don’t really understand exactly what it means,” but also I hear the fear of, “Okay, is this taking over for accountants? Are our jobs gonna be replaced by this artificial intelligence?” What can you tell me about that?
Yeah, the robots are coming! I think I’ve heard that a few times. I’ve even been in a few conferences, where I’ve heard people claim that.
As I look at it, and I’ve talked with various folks—futurists in the technology space and how it applies to the accounting industry—it isn’t going to be a full, wholesale replacement. I don’t believe that that’s going to happen. As we think about artificial intelligence—a base definition there is it’s computers performing tasks that are typically performed by people. Many of them are logic-based—decision automation or task automation. Those are the things when we think about artificial intelligence, and yeah, that’s an oversimplified definition of artificial intelligence—I get it.
A subset of that is then machine learning, and that’s something that that’s already being used in the profession. There are solutions out there that help us read documents and learn where the terms of contracts, for instance, are located, so they can pull out the terms. Some of them scan and populate software. It reads the document, it learns the document, it pulls out the relevant information, and populates it into the tax software. Machine learning is essentially, the computer itself is either learning from the user, or it’s teaching itself.
Teaching itself? Now you’re scaring me!
Yeah, that’s where the doomsday conspiracy comes in, right? But at the end of the day, I think a term is left out of this conversation so much, that is so much more important, and that’s augmented intelligence. Augmented intelligence is where we combine the best of artificial intelligence with the best of our human experts. It means that you’ve got really talented people using really sophisticated software to solve problems we’ve never solved before.
So I’m actually quite favorable on the fact that accountants will be around awhile. I think that there’s a need for us.
The software is not going to happen overnight. Now, are there things that will be automated? Yeah, definitely. In my career, and it’s been two or three years since I’ve been with the firm that I was with, but anything that could be automated, I would. That’s where we get the efficiency, that’s where you get the effectiveness, that’s where you get higher quality control, because you know that task is being performed the exact same way every single time. So the things that can be automated, very likely will be automated, and that’s a business decision. That’s not a, “We want to get rid of people decision.”
As I think about the biggest risk in our profession for that, it is compliance-based functions, because compliance in many instances is rules-based: Does it or does it not meet this criteria? If it does, do this; if it doesn’t, do that. That can be programmed, so that can be automated. What can’t be automated—or not automated as effectively or as well, in my view—is the accounting professional that then sits down with that and says, “Here’s what this means for you going forward. This is how it informs your processes. This is how it informs your decisionmaking. This is how it challenges what you do going forward.” That’s what we need people for. We need experts in accounting. I think we’ll always need experts in accounting, it’s going to shift a little bit what we’re doing. It is shifting to advisory and advising clients—
—That’s I was gonna say, advisory, yep.
I was talking with some professionals in our industry yesterday on a call, and there were about fifty folks. Quite a few said, “Not everybody needs to be an advisor,” and that’s true. I don’t think everybody makes an effective advisor. But we also have to recognize that that is the future of the profession—advisory.
So to the extent that we can leverage technology to help us be better advisors, that’s really what this conversation is all about.
I think you just summed it up!
Yeah! You don’t choose the tool until you know what problem you’re trying to solve, so as the future of our profession becomes advisory, it’s all about finding professionals that can leverage technology to be better advisors.
Awesome, I think that’s a great wrap-up of that. I think the information is awesome. The one thing I want from you, is I need some personal information for me personally. So my son’s got an Informatics degree. What does that mean? Do you know?
informatics! I like it. Probably a touch more on the creative side.
Yeah, well, he’s a programmer, but it was within the computer science department. He’s a programmer, but he’s got this Informatics degree that somehow is using computers and information from people and melding them together to create something I don’t understand. I try to!
A really good resource for everyone—and I watched this, it’s a PBS documentary, so that probably tells you I’m a touch on the nerdy side if I’m going to recommend a PBS documentary but I own that—it’s okay! The Human Face of Big Data. It is a really nice documentary. There’s an accompanying book, it’s one of those coffee table books—it’s huge. But it does a really nice job of laying out how information and data and technology interacts with us in our everyday lives, how it can be used; it’s probably more the positive slant on that. I mean, obviously, there’s a dark side of data, and there’s a dark side of analytics. We’re not going to go there—plenty of things out there on that. But there’s so much good that can come from this. I think it’s really looking to how do we use it to help our clients, and it’s so beneficial in that way.
While helping us be more efficient, more effective, helping our clients. That’s everything that we could want as a firm. If we can add new services and make it beneficial to our clients, I think that’s great.
We didn’t get into pricing and all that, and its effects—I don’t think we have time for that today. But that’s probably a key topic that would be interesting. I’m sure people can get more information on that from you.
Before we wrap up today, last time you were on, we did a fun fact about you. We did a pre-call discussion just a few minutes ago, and we think it was about your knowledge of Disney films, and specifically with three daughters, Disney Princesses, right?
That is correct.
So I think today, we’ll go with another fun fact. Is there something else that we all need to learn about you that is not Disney-related?
Yeah, so my team probably knows this more than anybody: I am an avid reader. I am constantly reading—always got a book, sometimes two or three—going. So I like to provide book recommendations where it makes sense. On this topic, one of the big challenges that our profession has is communicating around data.
So I’m gonna use my fun fact to give a recommendation if I may, and that is the book Data Story by Nancy Duarte. We’re actually on a video call recording this, so you can see it on my bookshelf behind me.
I do see it!
It is probably one of the best books I’ve ever seen written on how to communicate data to executives, and that’s what we have to do. We’ve got to communicate the results of all this. We can analyze data all day long, but if we can’t communicate why it’s important to our clients, we don’t actually generate any more value for them. They don’t care about the output, they care about their outcomes. That book does a really nice job laying that out, in a really succinct way. As accountants, we tend to prefer data tables, there’s a time and a place.
But my fun fact is, I’m an avid reader—I’ll give you that relevant recommendation, and I’m sure that I could give you plenty of recommendations for others as well. So if anybody is interested, they’re always welcome to reach out. I’m happy to talk more on tech, I’m happy to offer book recommendations as it’s relevant.
I actually knew that about you. I had actually, in my notes, written down a few books I’ve heard you recommend other places as well. This one I hadn’t written down yet, so I appreciate that. It’s a funny thing in this podcast—everybody’s a reader, it seems like, that I talk to, with business books, and that’s great. I keep writing down books I need to read that people are recommending. One is what you just told me—and I’ve got to start doing this—in the COVID area here. I’m not flying, and not doing any of that, but I’ve got a 21 hour car ride coming up, so I might get some books on tapes and to go through and that might be one that I’ll throw in there.
Before we completely wrap up, I want to go back to one of the things sticking to the sports theme that we’ve gone intertwined in this discussion today. So did Data Analytics somehow show that a 16 seed beating a 1 seed in the NCAA tournament will result in that 1 seed winning the tournament the next year? Is that part of Data Analytics filled in now, because that’s what happened!
Yeah, that was quite interesting. I didn’t see the 538-calculated likelihood on that one, and I may have misquoted what the 16-over-1 percentage was, so if I’ve got anybody that’s detail-focused out there, don’t hold me to that number. Yeah, that was crazy.
We’re gonna have to add some new data into the analytics portion of things now with that, because that was a pretty amazing feat—that was Virginia that did that. Got beat one year, and then the next year after going out in the first game, they went on and won the whole thing, which I thought was awesome to see.
So before we wrap up: This is an extremely interesting area for me. I think it’s an extremely interesting area for everybody out there because it’s very important to our firms and the growth of our firms, and just going forward and giving the services that we need to for our clients. I’m hoping and I’m guessing people are going to want to get more information from you. How would they get ahold of you?
Definitely. They can find me on LinkedIn—Jeremy Clopton—as well as my email
Those are probably the two best ways to get ahold of me. I’m pretty active on LinkedIn, check messages fairly regularly and obviously have email, as we all do. Anyone is welcome to reach out at any time—I’d be happy to answer questions and talk tech.
Thank you for joining us today. You can find all the links and show notes for today’s episode, as well as more about Tri-Merit, at TheUniqueCPA.com. Remember to subscribe and join us for our next episode, where we’ll be going beyond compliance into forging new pathways of delivering value to clients diversifying your revenue streams and leading edge management techniques and styles.
About the Guest
Jeremy Clopton, Director at Upstream Academy, gained his real world experience from his work at BKD CPAs & Advisors, where he led a firm-wide specialty practice. During his 12 years there, Jeremy gained extensive experience in data analytics, fraud prevention, and business intelligence. He now leverages that experience to teach firms the potential that data and technology have to transform firm practice management, leadership, and firm culture.
Prior to joining Upstream, Jeremy launched his own consulting company focused on developing more successful cultures by asking better, more strategic, questions. He created the SQ Method, a framework designed to help firms overcome challenges and more successfully adopt new technology, analyze and utilize data, encourage innovation, and drive employee engagement.
Jeremy speaks both in the US and abroad at industry events, as a faculty member for the ACFE and as an instructor at the Management Development Institute at Missouri State University. He earned his B.A. in Accounting from Drury University in 2005, and is a Certified Fraud Examiner and Data Analyst.