Jeff Anderson With Kaizen Analytix

Intro: [00:00:04] Broadcasting live from the Business RadioX studios in Atlanta, Georgia. It’s time for Atlanta Business Radio brought to you by on pay Atlanta’s new standard in payroll. Now, here’s your host.

Lee Kantor: [00:00:24] Lee Kantor here, another episode of Atlanta Business Radio. And this is going to be a good one. Today on the show, we have Jeff Anderson with Kaizen Analytics. Welcome, Jeff.

Jeff Anderson: [00:00:35] Thank you very much. Lee, how are you doing today?

Lee Kantor: [00:00:37] I am doing well. I’m so excited to learn what you’re up to. Tell us about your firm. How you serving folks?

Jeff Anderson: [00:00:44] Absolutely. Kaizen Analytics was founded back in 2016 here in Atlanta. Our first office was actually in a shared office space over on Pilot Street near a city market. It got cramped over there pretty quickly. And now we have relocated out to Ravinia over near Perimeter Mall. We also have offices in New York, Dallas, in Chicago. We’ve had remarkably consistent growth because what we do is help companies make better, faster and more profitable business decisions with data and analytics. The mission that we created back over on Pilot Street six years ago is true today. And what that mission is, is to make data and analytics actionable and accessible.

Lee Kantor: [00:01:31] So now a lot of firms, you know, you hear about big data and data is everywhere. And now you can keep track of data in places you couldn’t even imagine, you know, five, ten, 15 years ago. How do you help your clients kind of discern what is data that matters? What is data that maybe you can ignore? Or is all data data the matter somewhat and you just got to kind of prioritize it, like how do you help your clients wrap their arms around what seems to be a never ending supply of data?

Jeff Anderson: [00:02:03] Yeah. That’s a that’s an excellent way of asking that question there, Lee. For for Kaizen, it’s all about finding your unique story behind your unique data, quickly understanding what happened, why it happened, how to learn from the outcomes that you’re getting, and then moving on to predicting, optimizing and continuously improving your business performance. Now our name Kaizen, which is Japanese for continuous improvement. It’s core to everything that we do, not just the name of our company, because using Kaizen principles, we rapidly deliver an initial solution for a client in a period of weeks, and then we continuously improve that iteratively based on client feedback. So it’s an ongoing. That’s why I said your question was beautifully worded and that it’s a never ending continual journey that you’re on as companies continue to leverage advanced data and analytics.

Lee Kantor: [00:03:05] So how do they even know where to begin if it’s this giant pool of data that’s constantly being created and some parts that are super important, some parts that are maybe less important. But how do you even begin to know which where should I pay attention? Which is the area that I should focus on, where there’s a lot of opportunity? Where is an area that’s telling me there’s danger around the corner? What? It just seems overwhelming if I don’t have good systems and processes in place.

Jeff Anderson: [00:03:37] Yeah, that that’s a great point in itself. The way we would attack that with our clients is that we start small but we think big. We a lot of times will follow the money, so to speak. So we’ll look for the largest revenue streams, the largest cost buckets, and then attack those with the Kaizen approach of continual improvement.

Lee Kantor: [00:04:03] So that’s where you begin. So that’s a logical place to begin. Then you kind of dig in there because that the places that have the most revenue or the place that have the most cost, therefore you can have the greatest impact.

Jeff Anderson: [00:04:16] That’s typically what we see where the biggest opportunities are. Also, the more complex the business is, the more opportunity that you have. Because with complexity, things like revenue leakage, customer churn happens, fraud, those types of things. And what we can do is apply advanced analytics such as anomaly detection capabilities to find those situations and do that so that you and your team are not having to hunt through and sift through all the data and the spreadsheets and everything else that you use to run the business.

Lee Kantor: [00:04:57] Now, who is the kind of the ideal client for you? Are these these enterprise level, Fortune 100 sized companies that have the resources and have the data that can be attacked in this manner? Or is it relevant to small and mid-sized firms as well?

Jeff Anderson: [00:05:13] That’s the beauty of what we’ve got going here. It ties in. We have created an ability to support both larger Fortune 5500, 1000, even 2000 companies, and basically being able to provide capabilities for them that are to get them to actionable results. And that’s really that actionable part of the mission statement that I mentioned earlier. So for them, it’s all about making data and analytics actionable, finding real value within their data, leveraging analytics. But we also serve much, much smaller companies and we do that through the accessible part of our mission there. We have a suite of products that effectively allow much smaller organizations to take advantage of those same capabilities that the big clients such as, say, a Home Depot here locally or a Delta Airlines that have been investing in these capabilities for for many, many years with lots of data scientists and lots of IT professionals who do great things. But what we’ve set up here with our product offerings is, in a way for the smaller players to actually take advantage of these capabilities and deliver real business value.

Lee Kantor: [00:06:36] So what’s an area where a smaller company could lean on some of your tools to, you know, create more value for themselves? Is it around pricing? Because I think in smaller firms, pricing is kind of a let’s make a deal world and there’s not a lot of analytics behind it other than a gut feeling or what’s the temperature of the of the marketplace.

Jeff Anderson: [00:07:01] You took the words right out of my mouth with that gut feel. That’s that’s typically what we see. In some cases. It’s almost an afterthought. It’s like we got the new business, but then what are we going to price it at? So we have a specific offering. Kaizen Price Think of this as first of all, as an application, which you can consult from any smart device, but think of this as your pricing brain. It forecasts your demand, calculates your customers sensitivity to price optimizes the price, but then also factors in external data which sometimes has huge impacts, you know, things like weather, macroeconomic data. And we’ve created an ability with Kaizen price to essentially democratize the ability to price like much larger companies and do that for a very affordable price.

Lee Kantor: [00:07:52] So is this industry agnostic or does it work better in certain industries.

Jeff Anderson: [00:07:59] In terms of the I guess I’ll speak to that initially more broadly from a data and analytics perspective. I guess the two things that are driving the industry industry adoption overall is basically two things ever expanded data where companies continue to capture more and more data. And then also the pace of change in technology, which allows folks like us to apply new techniques to expand and push the envelope. But specifically speaking, I would say that you look at a couple of different industry groups, consumer centric industries that have extremely high volumes of transactions. You think retail, financial services, travel related industries. These industries are some of the earliest embraces of data and analytics, but honestly, they’re probably due for a facelift. Then you have industries using advanced machinery that have sensors now that capture literally subsequent data activity. Things are. Excuse me, something like chemical energy, industrial manufacturing. These are huge opportunities to leverage data and analytics. Then you’ve got industries such as that have kind of known throughout to be very inefficient from an operating standpoint. Health care comes to mind if you imagine how leveraging data analytics, how much more effective in terms of patient outcomes and more efficient these health care providers could be if they knew exactly who needs to come in to the or the optimal staff to provide the care, optimizing the treatments and really increasing the throughput to care for more folks in the in the operation. And then don’t forget about services industries, specifically where I’m speaking here of law firms. We’ve actually began recently working with law firms to use these same data and analytics capabilities. My lawyer buddies will say that lawyers are people too, and I would extend that to say they also have data too, and they can leverage that data and analytics for huge value within their law operation.

Lee Kantor: [00:10:10] So how does the data analytics work when it’s kind of a creative field or a subjective field where the value is kind of in the eye of the beholder? Like the art world say, like, how could you price a piece of artwork? You know, with any type of certainty or predictability when it’s so subjective. And, you know, you can put one thing up for auction, it could be worth millions and another thing be worth next to nothing.

Jeff Anderson: [00:10:43] With the in the world, like the art world, where there is some subjectivity, a test and learn approach would be really a failed self fail safe approach to that where we establish a price based on what we’ve seen in the past using as much history as we can in some of these cases, going with small and wide data instead of the big data is is a great approach. But what we would do there is establish a price, watch that to see the reaction and then adjust accordingly. So we call it test and learn and we would apply that type of approach in a in an environment such as when you’re selling it like a very unique art pieces.

Lee Kantor: [00:11:33] But that would come into play like say you’re a small producer on Etsy or one of these marketplaces. You know, you’re you produce something, a T-shirt, and you, you know, you kind of can guesstimate, okay, this is how much t shirts sell for. But how do I know if this is something that’s going to be have wild demand or no demand? So it’s this kind of test and iterate approach you think is kind of fundamental to any type of new or creative endeavor.

Jeff Anderson: [00:12:04] Yes, that’s exactly right. So you don’t like if you’re just starting a business and, you know, taking a test and learn approach, just really making sure that you are in fact, looking at it closely and frequently to see based on that price, how how fast or slow is your merchandise moving and then learning from that and then adjusting again. Going back to our our approach to how we deliver for clients, the continuous improvement also falls very much in line with that.

Lee Kantor: [00:12:37] So these are just the fundamentals of how you do what you do.

Jeff Anderson: [00:12:42] That is exactly right. You could probably almost every client engagement will be some element of a test and learn. So whether you’re brand new business getting off the ground and you want to use that approach or we’ve used it especially in the in the last two and a quarter years when we’ve all been impacted by COVID. A lot of those forecasting models for a lot of our clients really went out the window for that period of time. And using approaches like test and learn is small and wide data allow clients to nimbly shift when dramatic things like like a pandemic happens.

Lee Kantor: [00:13:24] But is that a practice that you feel that businesses should be incorporating at all times? Because change is always happening? It may not be to the degree of a pandemic or, you know, just tremendous inflation, but there is incremental change. So you should always be testing and always be optimizing.

Jeff Anderson: [00:13:42] Yes. That’s what we would recommend. If you think about the concept of a decision support optimization solution and there what you’re constantly simulating, what is going on and what you believe is going to happen in your business, taking those different scenarios and probabilistically figuring out which of those are likely to happen. But then preparing for the edge cases and just being being ready to kind of go with the market or go with the direction that the your business is going. But having the the machinery and the horsepower to have done all of those scenarios in advance and be prepared for any number is really that is a best practice that we see out in the market.

Lee Kantor: [00:14:36] Now is that it feels like it’s going against human nature a little bit and in terms of humans want things to be the same and they have this kind of security mindset or stability mindset and and it changes always. They understand intellectually, changes always happening. But you need to have mechanisms that are triggering alarms, right. That are telling you, hey, there’s danger around the corner or hey, pay attention to this, this might be occurring. So you have to kind of have your hand on the the lever in case you need to pull it. And you need to always know where you stand in the data analytics. Part of this is trying to help you if you’re open to it.

Jeff Anderson: [00:15:22] Exactly right, Lee. A lot of times what we will do is put in place, even if we’re not necessarily truly optimizing a solution, if the client is not quite ready for the true optimization business rule based alerts and establishing guardrails that once once these alerts are triggered or we’re seeing a situation outside of what we’re guarding against, then being able to trigger different operations, different processes, different decisions to really keep you more focused on and avoid catastrophic situations where you’re getting to real trouble.

Lee Kantor: [00:16:05] Now, you mentioned that I think that one of your tools is an anomaly detection engine. Can you talk about in a world where anomalies seem to be happening with more frequency or maybe we’re just aware of it more? How did this come about and how can your clients benefit from it?

Jeff Anderson: [00:16:24] Yeah. Our anomaly detection solution, probably one of our most exciting developments, very candidly, but it’s our newest offering in our Kaizen Insights Suite. What our anomaly detection solution does is it automates the delivery of very powerful, but at the same time hidden insights in your data. Importantly, without your team having to scour through and sift through all these different the data that you have, different structured, unstructured data, sources, reports, etc. What the solution does is it systematically looks through and finds patterns looking at all aspects of your data. It establishes what we call the business as usual baseline on key metrics like fraud, customer churn, revenue growth, even revenue leakage. But it’s looking for those metrics which ultimately can potentially drain company profits, and then it finds those outliers against that baseline. Great example of this is for a cable company. We use this solution to identify outliers that resulted in reducing their customer churn by 5 to 10%. So we found pockets of their customer segment combinations where churn was happening that looking at it in an aggregate, they couldn’t really see it, nor could they really act on it. But when you bring it down from your your base of 10 million customers down to a household group of, say, 4500, then you can take action and you can really move the needle. So but you are right in that there’s a lot of anomalies out there and really trying to separate the wheat from the chaff, what’s real and what’s not. That is the key to the whole thing. And that’s what we’ve got set up with this anomaly detection solution.

Lee Kantor: [00:18:21] So what do you need more of? How can we help?

Jeff Anderson: [00:18:25] Well, you know, when you I guess one thing that I wanted to say is that with our presence here in Atlanta, Atlanta’s been an outstanding location to build our business. I would say that without a doubt, we would not have been nearly as successful starting anywhere else but Atlanta. We’ve got great clients here, amazing talent, access to to great institutions, and just a talent pool that is really second to none in this space and also a local community. I almost see them and feel them as champions fans, supporters, mentors like the Atlanta CEO Council. Great, great council that we’ve leveraged a lot. Great airport. Can’t forget about Atlanta Hartsfield-Jackson. That allows us to move really quick and deliver for our clients, too. So it’s really about figuring out ways that your companies can use data and analytics starting small, we think big, but we start small. Really trying to understand that story behind your data, figuring out what happened, why, and then enhancing from there. And I guess just. You know, in summary here, just asking yourself the question, what’s your data really telling you? Where are those opportunities to to really have a huge impact in your business with data and analytics?

Lee Kantor: [00:19:57] Well, if somebody wants to learn more, have a more substantive conversation with you or somebody on the team, what’s a website?

Jeff Anderson: [00:20:03] Website is Kaizen analytics dot com I’ll spell it real quick. A Z in an ally t i x dot com. But we we would love to help and carry the data analytics torch forward in your organization. Lee, I appreciate the time this afternoon. It’s been it’s been great speaking with you.

Lee Kantor: [00:20:30] All right. Well, Jeff, I appreciate you coming on and sharing your story. You’re doing important work and we appreciate you.

Jeff Anderson: [00:20:36] You bet. Thanks. Have a great day.

Lee Kantor: [00:20:38] All right. This is Lee Kantor. We will see you all next time on Atlanta Business Radio.