Industrial Automation Companies

The Sound of Automation: Data Analytics 101

Posted on July 21, 2021 by

Bryan Powrozek

Bryan Powrozek

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The Sound of Automation

Ben Smith from our consulting team joins us on this episode of The Sound of Automation podcast to cover the basics of data analytics. Learn what data analytics is, what trends to look at and how to track against your business goals. Ben provides guidance on data-based decision making and explains why it’s important to get started now.

Podcast Transcript

Announcer:

Welcome to the Sound of Automation brought to you by Clayton & McKervey, CPAs for growth-driven businesses.

Denise Asker, Director of Mkt. & Practice Growth:

Welcome back, Brian.

Bryan Powrozek, Senior Manager, Industrial Automation:

Denise, how are you?

Denise Asker:

Good to see you.

Bryan Powrozek:

And you as well.

Denise Asker:

Yeah. So today we have a very special guest, our colleague Ben Smith, fellow senior manager at Clayton & McKervey.

Bryan Powrozek:

Yes.

Denise Asker:

And he’s doing something that few of us understand, called data analytics. So I’m going to try to unpack that a little bit today for our listeners.

Bryan Powrozek:

Yes. I’m hoping that Ben can actually explain to me what it is because I keep hearing it. I know quite a bit about data analytics, but I think that’s our goal here in this episode, right, is to try and demystify that a little bit. We talked about a lot of things on the podcast. We had Tom Kelly on from Automation Alley talking about industry 4.0. A lot of that probably means something different to every single person.

Denise Asker:

Sure.

Bryan Powrozek:

And so really hoping to try and break that down, especially for our business owners. Right? If I’m a small business owner, data analytics is probably far from my mind something I want to invest time in. I’ve got to keep the business going.

Denise Asker:

But doesn’t have to be.

Bryan Powrozek:

No, it doesn’t have to be. And there’s some simple things you can do to get started and then like anything else you start small and kind of grow from there.

Denise Asker:

Okay, good. I’m looking forward to what he has to share today.

Bryan Powrozek:

Excellent.

Denise Asker:

All right.

Bryan Powrozek:

Take care.

Denise Asker, Director of Mkt. & Practice Growth:

See ya.

Bryan Powrozek:

All right. Welcome to the Sound of Automation. Today, my guest is Ben Smith, senior manager from Clayton & McKervey. Ben heads up our consulting practice, but really here today, he’s joining me to talk a little bit about data analytics. So Ben welcome.

Ben Smith, Senior Manager, Consulting:

Thanks Brian. Appreciate you having me on.

Bryan Powrozek:

No problem. So let’s start off at the ground level. What is data analytics?

Ben Smith:

That’s a tough question. Pass.

Bryan Powrozek:

Okay. So thank you for joining us today. This has been a great episode.

Ben Smith:

I think data analytics is a very broad term, so that generates a lot of uncertainty for most business owners, because it can mean a lot of different things. At the core, data analytics is literally just taking raw data and looking at it for trends to develop information and answer questions. Most people hear that definition and they’re like, “Okay.” But truly that’s what the definition is, right? And most people are doing some form of data analytics in their business today. It’s as simple as taking an Excel spreadsheet of your revenue and plotting out revenue over time and trying to understand what’s happening. Right? That is data analytics. But I think in recent years, large companies and starting to be the middle market have kind of expanded their capabilities and knowledge of what data analytics is. And as a result of improvements in technology, data analytics has grown to be something more than just looking at some graphs on a spreadsheet. Right?

Bryan Powrozek:

Yeah. And I think that that’s one of the challenges for if I’m a small to mid sized business owner, right, it’s been blown up to this thing that seems like it’s this huge undertaking and I need special software and I need a data scientist on staff to analyze everything. But as you said, we’ve been doing data analytics forever. You think about the traditional accounting services, financial statements, right? That’s kind of a form of data analytics, looking at your gross profit or looking at your net income over time and comparing those things back? So it doesn’t have to be this huge undertaking to get started, right?

Ben Smith:

Certainly not, no, no. I think that for the middle market where we see a kind of value in data analytics is kind of going wider in the data that we’re analyzing. So it’s kind of combining disparate systems and things like that at first and starting small and maybe you’ve got two different systems and you’re trying to look at get one answer out of two different systems. It’s like the mere motion of combining that information and then developing some results out of that is technically data analytics.

Bryan Powrozek:

Yeah. And I guess you see, in working with clients, there’s probably some of that analysis paralysis, that you’re trying to get it just right. We want to look at these 10 things and how do we get that data all together. And I think that that can slow down and potentially even inhibit a company from going after some of these things.

Ben Smith:

I would agree. If you try to look at it with the ultimate five-year down the road and the answer in mind, you’ll get that paralysis by analysis where it looks like this mountain that you could never climb.

Bryan Powrozek:

Yeah.

Ben Smith:

But really, if you want to be successful, you start by looking at what your organizational goals are for the year. A lot of people, business owners, might not have them written down, but they generally have a sense of what they want to accomplish. And it’s kind of looking at those goals and then understanding what information you have, what information might be useful, and then kind of setting some very specific questions out that you want to answer. And then just kind of setting off to going down the path of combining your data to answer those questions, I guess.

Bryan Powrozek:

Yeah. So I guess, take me through this. Let’s say I’m a small business owner, and we run into this a lot within our client base obviously. You’ve got a business owner started the company, has kind of learned what I think the company takes to be run right? As long as I’ve got cash in the bank at the end of every month, I’m doing good. Right? If my cash gets below a certain level, I start to get nervous. How do you help somebody in that mode who really doesn’t have much in the way of data analytics? Start going through that process, identifying what are the important things that they want to look at. And I think it’s, to some extent, it almost starts out like smaller is better, right? To start with something small and then build up from there.

Ben Smith:

Yeah. And I’ll say that most business owners want to grow. Right? That’s kind of one of their goals. It’s why they became an entrepreneur. So I’d usually start by talking to them just in simple terms about their revenue. There are almost always multiple drivers of revenue and business owners often operate from a point of intuition where it’s like I have a general feeling for what’s going on in my business. But just identifying those revenue segments, plotting those things out over time and starting to watch why they’re increasing or decreasing and tracing that back to your ultimate customers or end markets or things like that gets you started down the path of just a very small starting at the top line, “What does my business look like?” And that starts your pipeline, right?

Bryan Powrozek:

Yeah.

Ben Smith:

So you get that information. And then as you progress, depending on your goals, you can look at, if I put a little bit more investment here, does that grow this market?

Bryan Powrozek:

Yeah.

Ben Smith:

And then you can kind of trace that down to costs. But really kind of starting at the top and just getting a handle, a true handle on your revenue on a regular basis is a great start.

Bryan Powrozek:

I think you touched on something there that’s pretty important, right, is you mentioned that, okay, I’m seeing my revenue go up or go down or whatever it might be, but it’s that next step of okay, now let’s try and figure out why that happened. I think, like you said, a lot of folks will see that in intuitively say, “Oh, well, it went up because I landed a big job that quarter,” or a big job fell through and they write it off to this easy explanation, as opposed to really digging into see what the data’s telling you. And that could completely change your approach or some of the things you do.

Ben Smith:

That’s absolutely it. It changed because of, well, it’s the mix. And it’s like, okay, well, what in the mix changed? And it’s like, well, I think it’s this. Okay. And then you actually go through and crunch the numbers and it’s like, well that’s only 50% of what drove that change. The other 50% is something that’s in your control to do something about that you just weren’t aware of frankly, before. And nine times out of 10, you learn things just by going through that analysis.

Bryan Powrozek:

Yeah, and that’s another interesting point that you bring up. I mean. When you think about it, right, implementing some data analytics controls into your process is like any other change, right? You’re now asking this person who was used to running their business purely on intuition to now say, “Hey, trust this other thing over here. Trust this tool that I’m giving you.” What are some of the challenges you see within clients, as they’re starting to move into using data analytics, and they get to that first point, right? And like you said, “Hey, 50% of it was out of your control, 50% was in your control,” getting them to agree to that and believe that?

Ben Smith:

Yeah. Initially what usually comes to light is that everybody in the organization, while you might be talking about one thing, has a different definition of what that one thing truly is. So it’s understanding the data that you’re using, how it’s going into your systems, understanding the people and their mindset when they’re entering that information and then making that definition very clear for the organization. So that way everybody understands how we’re getting to this end result. Right?

Bryan Powrozek:

Yep.

Ben Smith:

And then the next thing that happens usually is if you’re putting a KPI into place or you’re putting a measure into place it’s for a reason, and usually it’s because they’re trying to drive some certain outcome, which means that certain people are going to have to change in your organization to meet that outcome. Right? And the general progression, anytime you’re kind of presenting new information to people is they’ll look at the data. If they accept that the data is true and the data ultimately just doesn’t align with how they feel, they move from a data-based argument or conversation to an emotional conversation. Right? And it’s like, okay, I can’t fight this with data, but I’ve got X, Y, and Z going on. And that process in itself, I think brings a lot to light for cultural change in our organization, to what you’re speaking about.

Bryan Powrozek:

Yeah. And I think that there’s also, and having seen this within our organization as we’ve tried to implement some of these more database decision-making approaches and within client organizations, there’s also a challenge with the underlying data itself, right? This data was being collected initially with no intent of this kind of analysis being performed on it. Right? And so now you kind of compound things of, we’ve already got people resistant to change, and now the analysis is giving them results different from their expectations. So clearly the data’s got to be wrong.

Bryan Powrozek:

And now you’ve got to go back through that process and try and help people understand that, “Hey, this is part of the process.” Right? It’s going to take time. We’ve got to work through this. Okay, we found that sales were being recorded differently than we thought they should be, or we weren’t consistently, like you talked about segmenting your revenues, if things weren’t being consistently recorded in the accounting system, well it didn’t matter before because nobody was looking at it. But now we are and it helps feed that emotional argument of, “Oh, this isn’t right.” Well, it’s not right because the tool is wrong, it’s garbage in, garbage out.

Ben Smith:

Right.

Bryan Powrozek:

The data coming in was wrong. And so how do you help people kind of navigate through some of those challenges?

Ben Smith:

Yeah. To an extent, what I’ve seen is it’s kind of like the chicken or the egg scenario where you start off and you’re working with what you have. So a lot of times people will think, “Oh, no, this is our process, our data is pretty clean.” And more often than not, it’s not. And you have to go through some form of kind of shoring up the data sets that you have to a degree, or you kind of make the call that, yeah, it’s not great, but it’s good enough and we’re going to start tracking this. We’re going to tell people why. We’re going to start showing people that we’re actually using this information to make decisions that impact them and kind of raise that awareness with the folks that are entering the data. Because oftentimes people don’t want to change, it’s hard to get organization change like that. And without kind of demonstrating the why and using that information, people are reluctant to really take a serious approach to how they might be entering a certain data set or approaching a certain process or something like that.

Bryan Powrozek:

And because of that, and a lot of this, if you look at any kind of organizational change, you’ve got to find some way to get that momentum going, right, to be able to show people that this is going to work, right? It’s going to be work. People’s way of doing business is going to change. Some people are going to have to pick up some responsibility. Other people are going to lose some responsibilities, but that’s almost kind of a best practice, right? Maybe start small with a team or a group that’s looking at it. I know within our firm, as we’ve been doing some stuff on segmenting our revenues and looking at where our segments are and our service lines, you started with a smaller group, right, that was looking at the data. So you could go through some of those things and you could discuss the challenges and the issues before it gets out to the firm as a whole. Right? So that’d be probably a best practice is starting small with a contained group.

Ben Smith:

Certainly. Yeah. I think setting a very narrow kind of problem or definition on the onset leads to a greater success in the long run. Yeah, absolutely.

Bryan Powrozek:

And so with that, any suggestions for folks, and kind of going back to what you talked about initially, was identifying what it is you want to measure. So really in some extent, you got to understand where you’re at and where you want to get to. Right? And then kind of take the smallest step you can forward. Right?

Ben Smith:

Absolutely. Yeah.

Bryan Powrozek:

Keep things going.

Ben Smith:

Yeah. Yeah. Most time you start with the vision or where you want to be. And then it’s like, “Okay, if I want to be there, where am I now?” And that becomes a matter of descriptive and diagnostic analytics where we’re looking at what has this been for us over the history? Why has that been? Okay, now what is it that we need to change or what are the metrics that we need to measure going forward to drive this particular action to get to this particular outcome?

Bryan Powrozek:

Yeah. So I guess any kind of examples that you’ve either seen, I don’t know whether it’s within our client base or just things that you study that kind of shows the impact of what some of these analytics you can do for a company or for analyzing a situation?

Ben Smith:

Sure. I think that there’s a varying set of things that we’ve seen. I’ll take an example where we were helping a company start to aggregate their sales information. Right? And they had multiple locations and they’re trying to figure out why some locations might do better than others. Right? We were able to help them compile information amongst those locations and present that to them in a fashion that really helped them to start to actually drive individual changes in those locations and their operations. So instead of looking at their financial statements or their operations as a whole, and then saying, “I’ve got to run 30 different reports to ultimately get to this one answer every time I want to track where we’re at,” we were able to kind of help automate that process and bring them from a historic management, I guess, perspective of managing by intuition.

Ben Smith:

I don’t have this information. It takes me a long time to compile this information to, well, now we can compile this relatively quickly. Now, if you automate something, you can essentially push a button and get this answer if you’re confident that this is the right measure or the right thing to be tracking, to drive change in your organization. And I think ultimately that drives outcomes in efficiency, in those organizations or in that organization in particular. So all of a sudden, you’re able to benchmark your locations against each other and then have them start working together to all kind of learn from each other and move in a consistent direction, in line with your goal.

Bryan Powrozek:

Yeah. It’s interesting you mentioned that because I know in working with a number of different clients of mine, who they developed their own internal spreadsheets right, of, “Hey, we take whatever is in QuickBooks or within our ERP, we dump it into this spreadsheet and then somebody spends a bunch of time going through. And some of that, I think, also inhibits people from getting into data analytics because they’re like, “Oh my God, the time I need to spend getting this formatted properly, getting it in.” But there are those automation tools now that’ll help do it. Like you said, you can do it daily, you can do it at the press of a button. You get the most recent data. I think our, was our dashboard updated daily, automatically? It goes in, pulls the most recent data.

Bryan Powrozek:

And now there’s no question about, “When was this last updated? Oh, you’re looking at the February report, but I’m looking at the January report.” And so now you start solving some of those internal operational issues because all that goes to credibility, right? If people are already doubting that this works properly or that it’s giving you the information you want, any little hiccup, an account being grouped improperly, or somebody didn’t pull the right report to update the report. Now people just, they don’t say, “Oh, there’s a flaw in our process.” They say, “Well, it just doesn’t work and let’s scrap it and go back to what we were doing.” So yeah, it’s important to kind of get those things in place and use the tools that are available to you, right?

Ben Smith:

Absolutely, yeah. And I think that over the last few years there have been some new tools introduced, at least to the middle market, that you can get some mileage out of at a relatively low cost. You look at things like Power BI, a Microsoft product has been, I think, an excellent solution for starting small and you’re dipping your toe into data analytics. You might want to combine two spreadsheets, two data sources, something like that, just to get an answer. It’s a great pilot type application to get your feet wet at a low cost.

Bryan Powrozek:

Yeah. And so for folks who might not be overly familiar with it, so Power BI is kind of, for lack of, it’s like Excel on steroids, right? It uses some of the Excel functionality, but it builds on that.

Ben Smith:

Yeah, I think in Excel, the capabilities in Excel have grown over the last few years as well, but Power BI is kind of that next level that is much better at distributing information to a group of people, your management, distributing the information that you want to be distributed to them on a regular basis. And it’s a more of a proactive pushing information out to people versus a reactive, I got to go find this spreadsheet and then get to the right tab and find the right answer type of thing.

Bryan Powrozek:

Yep. And also solves the problem that a lot of companies have, right? That spreadsheets probably on their network somewhere. And so if I’m traveling, not that too many people are traveling right now, but if I’m traveling and I want to see the latest revenue report, you can publish those dashboards and things out to people so they can pull it up on their phone, they’ve got ready access to it, which I think also helps. Right? The more you can do to give people different options to access these reports, to see these reports, if it’s something I can only get to when I’m in my office, at my desk logged onto the network, it just makes it harder for people to get to and be able to use these things.

Ben Smith:

Yeah. One of the things that comes to light, I think relatively quickly is just how much of a barrier even going four folders deep and pulling up a report can be. You would think it’s four or five clicks. You wouldn’t think that mentally, that that would be a barrier for people. But oftentimes it is versus if I can go to one place that has all my information and it’s one click away, the tendency for people to start using data is much greater if you can remove just even a few clicks for them and isolate data to one place.

Bryan Powrozek:

Exactly. I think we’ve all experienced that, somebody hyperlinks out a file in an email and then you pull it up on your phone and you can’t get to the file because you’re not on the network anymore.

Ben Smith:

And then you ultimately just ended up trying to make a decision based on your intuition on, well, this is how it’s gone in the past. It’s it’s going to be within this range. Let’s just keep doing this. And I think one of the dangers that you see here is that everybody’s aware the world moves faster and faster every day and things are changing on a quicker and quicker basis. And it’s like that just drives the inherent need to look at data real time and make sure that you’re making decisions based on what’s happened in the last few months and not just what you know to be true over the last 10 years. Things have changed over the last 10 years more.

Bryan Powrozek:

Well, I’m going to throw you a curve ball here. I’m going to script a little bit. But let’s talk about the Holy Grail, I think is what probably a lot of people think about when they’re talking about analytics, predictive, prescriptive analytics, right? I want to be able to go to a dashboard and see, “Hey, you need to change your business in this way based on what’s going on in the market and things like that.” And that’s where everybody wants to get to, right? But you kind of got to go through the knothole you’re talking about here first because you can’t just jump right to that. Right? You’ve got to get all these things sorted out at the outset, get your data sets clean, get your employees and your management team using data to make decisions before you can get to that point. Right?

Ben Smith:

Absolutely. Yeah. So the typical progression in value in data analytics is you start with a descriptive analytics, right? It’s just describing what’s happening or what’s going on in your business. The next stage is really diagnostics where it’s like, “Well, why is this happening?” The third stage is predictive, meaning, “I think this might happen in your business based on this history that I’ve seen,” to prescriptive being, “We think this is going to happen. We know you want to do X, so we think you should do Y to achieve X outcome.” Right? And that is kind of the Holy Grail and what people are working towards. But in the middle market, by and large, we’re still in the descriptive and barely into the diagnostic phase. So to your point, it is a matter of you got to get your arms around the data that you have, the true problems that you’re trying to solve, the why, and then you’ll naturally have to work through that progression to get the information you need to be able to make those prescriptive and predictive outcomes, I guess.

Bryan Powrozek:

Which it kind of serves then as motivation for business owners, right? This isn’t something you can just wait two years say, “Oh, I’ll wait until years and there’ll be Power BI version 2.0 that’s going to do all this for me.” Right? The tool can only do so much. And so you have to start incorporating the culture, the habits, making sure that data is being collected consistently, accurately. So if you want to get to that stage, if you want to grow to that prescriptive stage of analytics, guess are now to get there in a couple years. I don’t know, there’s probably statistics out there on that on how long it takes to get to that point. But getting started now is the important thing, right?

Ben Smith:

Yes. Yeah, absolutely. Things will advance, but at the end of the day, there is a lot of tailoring that happens in anybody’s ERP system and everybody does something a little bit different, so it’s getting your arms around, okay, this is the general use case or scenario, but here’s how we do things and mapping that difference between how we do things and the problem is kind of what you need to start doing now if you want to get there. Yeah.

Bryan Powrozek:

Yeah. So I guess Ben, if someone listening to this, one of our hundreds of thousands of millions of listeners is looking to learn a bit more about this or has a question, may want to reach out, what’s the best way for them to get ahold of you?

Ben Smith:

This is audio. Email me anytime. You could stop by our website, I have a couple of articles out there. And through that, there’s a contact form that they’re more than welcome to drop us a note. And I would be more than happy to give them a call and talk them through any situation.

Bryan Powrozek:

Denise, I’m going to use that as a test going forward for people who are, A, listening, and B, that they pass the marketing test and direct people to our websites. So you pass Ben. Unfortunately, Ruben, if you’re listening to this, you did not pass. Well, Ben, I appreciate you coming in and spending some time with folks and hopefully we’ll give some people a few things to think about. And by all means, reach out to us if there’s any way we can help. Thanks.

Ben Smith:

Thank you, Brian.

Announcer:

Thank you for tuning in. Don’t forget to like us, subscribe, and share on social. To learn more about Clayton and McKervey, visit us at claytonmckervey.com. That’s claytonmckervey.com. We thrive on finding the opportunities and solutions you deserve.

Bryan Powrozek

Senior Manager

A CPA and engineer, Bryan leads the firm’s industrial automation group and hosts The Sound of Automation podcast. He’s known for being optimistic & solutions oriented.

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