HOST Clinton Laron Corporate Communications Manager  Eide Bailly

CO-HOST Jenni Huotari Partner-in-Charge  Eide Bailly’s Business Outsourcing & Strategy jhuotari@eidebailly.com

GUEST Nathan McMurtrey Principal Eide Bailly’s Data Analytics nmcmurtrey@eidebailly.com

 

The Transcript

Clinton Larson Hello and welcome to EB & Flow. I'm your host, Clinton Larsen. And joining me today again as my co-host is Jenni Huotari. Terry, partner in charge of business, outsourcing and strategy. Hello, Jenni. Hello, Clinton.

Jenni Huotari, CPA Thanks for having me back.

Clinton Larson I am glad you're back. And I am excited for today's show because we have as our guest, Nathan McMurtrey, who is a Principal at Eide Bailly and leads our Data Analytics group. Welcome to the podcast, Nathan.

Nathan McMurtrey Thank you very much. It's super exciting to be with you today.

Clinton Larson And you know, Jenni, we've been talking lately on the podcast about how last year really forced businesses to have to adapt and change the way they do business. And now looking forward, they are realizing that, you know, they maybe can't ever go back to doing business the way that they used to do it.

Jenni Huotari, CPA Yes, certainly Clinton, you know, in addition to some of the things we discussed, like more reliance on technology, whether it's allowing our teams to work in a virtual environment or it's using processes and systems and ingesting information in that manner. And in addition to all the changing business models as a result to the pandemic, whether it was supplying your product or service in a different way or slightly modifying what it is that you were offered.

I think the need to understand how those things are performing in measuring results becomes critically important to the success of the business in what is a continually changing environment. And I think that leads us right into our topic today when we talk about data analytics and what is it that we're measuring and what are we looking for? So, Nathan, we're super pumped to hear from you about data analytics. So maybe you give us a little background on what that means.

Nathan McMurtrey Yeah, I'll let go what you started with, which is companies are definitely looking at the way they operate. And data analytics is a huge part of this. In our world, everything is just happening faster. That's what's happened over the last year. Satya Nadella, CEO of Microsoft and their quarterly call said that they had two years of digital transformation happen in two months. And that is what's happening for us, is it's not necessarily new. It's that everything is just happening faster. People need to adapt faster, they need to move faster, and they need to pivot faster. And at the heart of a lot of that is data analytics.

Jenni Huotari, CPA And you've been in this space long before the pandemic, before any of this was ever dreamt would happen and accelerate this change. So what prompted that interest in data analytics for you?

Nathan McMurtrey You know, it's fun because I graduated in accounting. I'm an accountant by a degree. And I was in my first I was kind of in my first job and just kind of in the if you've been in that, you're creating the financials every month. And it was a little bit of what is this new job look like? And they hired somebody to come in and do business intelligence. And it was this awesome title. I was like, what is this business intelligence? I sat down with this individual and after a ten minute conversation, he explained how he was going to come in and use the company's data from all of its different sources, bring that together and kind of create this holistic view of the company and the customer, the company, and how he was going to analyze that customer. And we were going to segment the profitable ones from the unprofitable ones. And I fell in love. It was it was a ten minute conversation. I was like, I thought that's what accounting was.

I went from that conversation, begged my boss to go be part of this new initiative and really just feel grateful for kind of being at the start of a movement, this data culture that we've seen just kind of peripherally through all sorts of industries. And so, yeah, that's how I kind of.

Now what's interesting about that career path, though, is I find myself now in an accounting firm. And I think that's exactly and we can talk more about this later. But the trajectory of accounting and data analytics is coming together. This is not two career paths where maybe 20 years ago for me it was. These are coming together and they're coming together very quickly. And so that's a little bit of my story and happy to be here.

Jenni Huotari, CPA Fantastic. Well, Nathan, to your point, yet, data and accounting all coming together collectively to serve clients and not those small and mid-sized business clients. So you alluded it to it with your interest in data, but tying in more with the mid-sized businesses. What things, how are they using data in their business and how do they get started?

Nathan McMurtrey Yeah, let me start with like the far end and the really successful data successful companies right now. And so this really interesting trends happened where you have these companies like Uber. Uber is the world's largest taxi company that has no vehicles. Facebook is the world's largest media owner and creates no content. Alibaba is the most valuable retailer, but they don't have any inventory. Just like Airbnb is the world's largest kind of accommodator and they don't have any real estate.

And the one common thread between these massively successful companies today is they're monetizing their data. They are data companies. And we are seeing this trend of every company. We kind of have the slogan that one day every company will become a data company. And we're seeing that trend in every industry.

I mean, we have coming down to kind of the Eide Bailly clients in the small and medium sized businesses, the ones that are looking at their data and finding ways to use that data to compete better, to operate better, to be more lean, to be more strategic. Those are the ones that are winning. And it's awesome.

We go into a lot of companies and the first conversation we have data is this giant liability in the words of the accountant. Right. We come in and they have spreadsheet anarchy. They've got data in too many systems. They've got financials or analysis that they're doing that's taking thirty, forty five, sixty days to get. And then by the time they get the answer, it's already passed. And there's this whole like liability of data. And as we work with them and watch that liability swing into an asset, it is the most awesome transformation. You see all of a sudden, they can't live without this ecosystem of data that they created. The decisions they're making are better. They're reacting and faster.

Kind of tying back to where we started this conversation with COVID, they're more nimble and they're able to respond faster. And it all comes back to understanding their business better and really understanding their customer better. And that kind of leads into data.

Clinton Larson So, Nathan, in terms of that change in business, is how do you think that's affected culture and strategy at these firms? How are they how are they looking ahead and how are they using this, like you said, to be more nimble?

Nathan McMurtrey You know, I think that the really interesting thing is, is that everybody's on their own journey. This isn't like an on and off switch where a data company, we're not a data company. We like to think of it as a maturity model. And so there are companies who are way over on one side that are kind of data unaware, if you would. There are very spreadsheet driven. They're very manual process driven. And then you've got some of these, like leading data leading companies and you kind of have everybody in between.

And the important thing is, is just trying to figure out how to move up the maturity level. And there's some really important things that tend to happen there that, I think will point out the most significant one that affects culture and strategy, which is data is not seen as an I.T. initiative. Meaning it's really easy to look at the tools that come with this data analytics and say they're technical tools, they belong in IT, which they do.

I mean, we're talking about servers. We're talking about the cloud, and AWS and Azure. And there's some technical things that are coming on there. But the most significant part of this data maturity that we see in organizations is when the leadership of an organization steps up and takes ownership of the data and identifying the key metrics and building out this data ecosystem. And as soon as it's not stove piped, even in finance and accounting or I.T., as soon as it's seen as a leadership initiative, just magic happens with organizations.

Jenni Huotari, CPA Now, Nathan, along that point you alluded to who should be involved in the important certainly. I got to think just getting started is overwhelming for some small businesses. How do, what are the key pieces to initiating that data strategy?

Nathan McMurtrey Yeah, it can be, when you, if you went to, I promise, if you went down to like looked at some of these companies I talked about at first with Ubers and the Facebooks. If you looked at the stack they were using, you would just die. You'd be like, there's no way I'm getting into any of that.

But what is really cool is the tools that have happened over the last 10 years, I'll say, have really, really come down to the mid-market and the small business. There are fantastic tools and the tools are not just great, but the affordability of the tools, which is so important for a small business, a medium sized business going through kind of growth phases is you've got to make sure, I'll kind of go back to that maturity model.

You've got to make sure the value always stays ahead of cost. And that's probably one of the, to the listeners out there, that's probably one of the biggest things that I would say is, you've got to prioritize this initiative because it's really easy to try to boil the ocean when we're talking about data. Let's get all the data from all of our systems and let's create this holistic view of our company. And 12 months later, we've got some of the data and we spent all this time on the backend stuff. You've really got to prioritize what are the key metrics that that matter to you.

And so to answer your question, Jenni, identify a few very key metrics if you're right at that level one, hey, we just want to get started, identify a few of those key metrics, find tools that are valuable and affordable and just great fast to value kind of tools. We're going to leave hard, impossible things that are valuable for later. We're going to start with what we call a business prioritization matrix, which is just a fancy word of saying we're going to start with the things that are valuable, the easy to do. And it's important to get both of those things. And that's where you start. What's the most valuable, easiest thing that we can do today?

Clinton Larson Nathan, are there some common metrics you've seen popping up in the last year for businesses and industries about what they're looking for? Has there been some common pain points in some of those areas?

Nathan McMurtrey Yeah, finding what metrics. There is a story I love this so I'm going to tell a story here. So I lived in the Ukraine for a couple of years and they have this story back to the USSR where they had some of their factories, that they picked a metric and the metric they picked, it was a nail factory and the metric they were judged on was how many nails they could produce.

And they came in and they found out that these factories were making millions and millions of nails that were just the lowest quality nail. You could kind of like pencil break it in half, a bit of a nail. They said, oh, my gosh, what are we done? We picked the wrong metric. And so then they said, well, let's not measure it off of the number of nails. Let's instead we'll switch to the weight of the nails so we get a nice sturdy nail. Fast forward 12 months, and you probably guessed, they were creating massive, massive, heavy, heavy nails. And they totally, they came in, what is going on here and they actually created a law. It's Goodwin’s Law.

It's kind of a funny story there. But the importance of picking the right metric for your organization has never been more important. So, you know, Facebook would call this their North Star metric. And I'd say, what is the, that's a thing to ask yourself. What's the North Star metric for our organization that as long as we're moving towards it, we're insuring ourselves that we're better than we used to be.

And Facebook's was daily active users. They knew they were growing daily active users, DAUs they called it then they knew they were headed towards their North Star. And so that's probably kind of tying into the leadership of an organization. Sit down and say, what is our North Star metric? What is the one thing that we know if we're tracking, it's leading to the right direction.

And so the next part of kind of identifying the metrics is identifying leading indicators. And, you know, we typically talk to a lot of accountants. Eide Bailly we're kind of targeted this office of accountancy. And a lot of accountants really get the financials right. They're so good at the PNL and they're really good at that. But those are generally lagging indicators, right?

I mean, just think of preparing the financial statement. The period's already passed. And just by nature of what it is, it's a rearview mirror into the business. What we want to do is we want to look at the things that are leading indicators that are ahead of the curve. And one of the most interesting things to ask yourself as you look to identify leading indicators is what are the metrics that our customers care about?

And so if I'm an airline and I'm asking myself, what are the metrics that a customer cares about, I'm caring about delayed flights. I'm caring about lost luggage. I'm caring about the surveys of the flights and understanding that the financials are lagging indicators from those leading indicators. And so it's a really good question. If you kind of identified your North Star metric, then ask yourself, what are the metrics that our customers would judge us by? And it really centers the organization like every organization should be toward their customer. And that's the most leading part that's important.

Hey I don't know if this is supposed to be a lecture or a conversation. You ask me a question, I'll just go.

Jenni Huotari, CPA Good thoughts on that. So obviously with the example of the nail story and then the airlines and the customer story, those are nonfinancial items. So you're probably working with information coming from multiple systems for these clients. If I'm a business owner, I've got to figure out how to get you information from multiple systems in order to analyze my data. How does some of that backside organization look like or what are my next steps?

Nathan McMurtrey Yeah, the first thing to highlight on that is that the number of systems is bigger than ever before. I read a report last week that said if you're in the technology industry, you're probably using more than a hundred different applications and systems in your organization. It's exploded.

And that's more than it was before COVID. But that's part of one of this digital transformation that's happened is the number of systems people are relying on to run the organization is bigger than it's ever been. And what that means is, it's great because now accounting has systems and marketing has systems and the sales team has systems and it's very custom to their needs.

But the problem is, it's creating silos. Those systems aren't talking to each other. And so if I'm looking at my organization and I'm saying I want to understand my customer, I want to know what they're buying, who they're buying it from and how long they're staying. I've got data in a lot of different systems. And that's where this organization of data comes in.

And so there's some technical words here that I'll bring in, but it's kind of the industry standard. And so what a normal business would do is you would be pulling data from the accounting, marketing, all of these systems. And you first land it in what you call a data lake. And what a data lake is, just think of a copy of all of the data of the business in one central location.

We haven't changed that data from the system, but now we have one central place so that if somebody wants to see what the data straight out of Salesforce looks like or say straight out of NetSuite looks like, we don't have to go back to NetSuite and Salesforce. We don't have to put a load on those on those systems themselves. And so that data lake is the first kind of the first step.

The next step is to take that data out of the data lake and build a data warehouse. And what a data warehouse is, it's really where, if you can imagine a cook in a kitchen taking all sorts of raw ingredients and applying recipes and kind of making a dish, that's what's happening. And data warehouses, we're applying business rules or making a dish data accurate. We're kind of creating a single source of truth by the time we're done. And there's kind of a lot of heavy lifting that happens there.

But when we're done with the data warehouse, we have this single source of truth, one place for the whole organization to go and get accurate, clean and timely information. And then the last piece of that kind of three step process, data lake, data warehouse and then data visualization. The visualization side is it's all about kind of, if you can imagine the dining room of a restaurant. Right. We care about how people are interacting with data.

We want to make sure they're understanding the data that they're getting that the definition of what they're looking at. So somebody is looking at revenue and they're looking at sales. They know exactly what has gone into that data. We're making it really as wide as possible. We really want as many people in an organization coming to that data and helping them make better decisions for their part of their job as possible. And so that's kind of the data visualization side of business.

Jenni Huotari, CPA So, Nathan, hitting on some of this and the changes that we're seeing going forward, which may be known, but probably filled with a lot of unknown, how are businesses using this data to help forecast and anticipate future results?

Nathan McMurtrey You know, that's a really good question, because on the higher levels of maturity, you start getting into some really exciting things that are happening with data science, machine learning and A.I. And it goes right into forecasting for a business. All of the tools that we embrace at Eide Bailly come with data science pieces now. It's just data science. It kind of snuck up on us, right? It's in our applications. It's not something outside. There's something in Salesforce and NetSuite that they have all these data science pieces.

But it's the same way with the data visualization tool. So if I'm forecasting revenues, there are some drivers in my head. Right. So I know that if I get this many users, this many new customers next year, I'm going to get this result as a business. But there's also some awesome regression analysis. There's also some algorithms that I can apply to the data to really get smart about where we're projecting for forecasting.

And so there is and this is probably its own podcast, but there is a very advanced analytics, things that are happening that are meaningful. I think 10 years ago, all of these things would have been completely out of reach for middle, small, midsize small business. And today they're extremely accessible and valuable to helping a fast growing, medium sized businesses be more successful.

Clinton Larson You know, Nathan, you mentioned that in the future, every company will likely be a data company. What have you seen in terms of adoption rates? How are people embracing this technology? I mean, what's been your track sort of since you started in data analytics till now? How has it grown?

Nathan McMurtrey Yeah, it's tremendous. There's not a single industry that Eide Bailly helps that is not using data more than it was a year ago, two years ago, five years ago. From health care to government to retail to dentists. It truly it's amazing. It doesn't matter. Construction is another one. It doesn't really matter what industry it is. The embracing of how are we going to use our data to make smarter, better decisions so that we can really be more valuable to our customers? And, you know, in the end, it's all about in business it's all about creating a sustainable competitive advantage. And today, organizations that are using data better are creating that sustainable competitive advantage. They're building walls around what they know and what they do.

And it's awesome. It's such a cool thing to be a part of it. There's just, the wind is definitely blowing in this direction. And, yeah, I just, it's been a whole lot of fun to see this transformation.

Jenni Huotari, CPA Nathan, I think one of the struggles for small mid-sized businesses is just getting started. What are their first steps or what are the things that they focus on first in order to start this digital journey towards data analytics?

Nathan McMurtrey Think top down, not bottom up. So what I mean by that, so instead of going, hey, we're going to do this analytics thing, let's find out, let's talk about all our systems, which is a very kind of IT way to do things. So it's all the systems that we have. Gather your leadership team together, identify what that North Star metric is for your organization, what those leading indicators are that you want, and then deliver it to a team and say, what would it take? Which of these is the easiest? What would it take to get the data in a centralized location?

And I would very much focus on those three levels of the data lake, data warehouse, data visualization. Start with the data visualization, even though that's the last step. Start with the data visualization, because we've got to get data into the hands of the users so that they can start seeing, understanding and questioning. Is this data right? Is this, why can't I get this data faster? I actually need this other metric to go with this metric to make sense of this. You need the business to start engaging and that all happens in the data visualization layer. And so start there.

The caution is it creates a little bit energy. All of a sudden everybody's got their own report and they're own numbered. And if you hit that point, it's actually a really exciting point because you're saying, isn't this wonderful? We've got so many people trying to be smarter at their individual jobs. Now we've got to start paying more attention to those back end things. And that's where things do get more technical.

But keep that value ahead of costs as you try to organize your data into one single source of truth and think of it as a maturity model, how do we get better? How do we get better? How do we get better? Instead of trying to boil the whole ocean at once.

Jenni Huotari, CPA I think this is our second straight podcast with that phrase, don't try to boil the ocean. Just the key takeaway for the EB & Flow podcast.

Nathan McMurtrey Yes, there you go. That's your podcast.

Jenni Huotari, CPA So Nathan, from one accountant to another, how have.

Nathan McMurtrey One ex accountant to another ex accountant.

Jenni Huotari, CPA You're never really an ex accountant, right? You can't leave it behind, it's in your blood. What have been the effects of data on that office of accountancy?

Nathan McMurtrey It's tremendous. So I mentioned earlier that they're kind of coming together. I think the best way to see that is some of these proposed changes they're making to the CPA exam. And if you haven't seen it, a lot of the talk right now is creating three different tracks. One would be a tax track, one would be a reporting and analytics track, and one would be more of an I.T. and systems and controls track. And I would say two of those tracks are analytics. And so the future of where even a licensed CPA individual is going, it involves analytics.

Now, at Eide Bailly, we do a tremendous amount of tax and audit work and a lot of specialty services and every single one of those industries. I'll give an example with, you know, audit work. We've now enabled, through this exchange program, we've taken individuals who are very good at audit and we train them in data analytics. Well now they're going and doing their audit with new better tools, faster tools, they're able to provide more value inside of their audit than they've ever been able to before.

And this is where accountancy is going, is the accountant is getting moved upstream. He's becoming more and more valuable. And the manual things that used the 80 percent of that data prep and that audit and that tax work, all of that's been automated. And so if I was graduated in accounting today, I would understand that machines and bots and software is going to do all of that low end stuff.

If I'm Dick and I'm going to come in and become fantastic at moving data around, understand a machine's going to do that better than I ever will. And it already does. And so what I've got to do is I've got to figure out how to be consultative, how I can use this data in the Office of Accountancy to be more strategic in an organization. And that's exactly where accounting is going. It's a really fun time to be in that office of accountancy, because I think we've become more valuable than we've ever been before. But we've also got to understand that there are systems that are automating a tremendous amount of what we might have seen as our job before.

Jenni Huotari, CPA Yeah, I would say gone are the days of relying on stale financial statements to make some critical business decisions.

Nathan McMurtrey Well said.

Clinton Larson Well. Wow, Nathan. That was really illuminating. I think I have a better grasp of data analytics. Definitely better than I did when I signed on to this podcast, that's for sure. So thank you very much for being here. It's been a really great conversation.

Nathan McMurtrey Yeah. I wouldn't be very good at my job if I couldn't talk about analytics for a very long time. So there's obviously a lot that could be said. I think know just as a winding up, if there's anything I would say, it's really think top down with your metrics.

Think of how you can be more nimble with better data at your organization, and really see yourself and your leadership team as the champions of your data strategy. I think those are kind of the key points that I would just tell everybody listening to take away.