In this episode, Tomasz Blicharski, EVP and Managing Director, talks about autonomous stores, achieving a transition to the cloud in only 3 months, leveraging Snowflake’s marketplace, and so much more.
In this episode, Tomasz Blicharski, EVP and Managing Director of Żabka Future, talks about autonomous stores, achieving a transition to the cloud in only 3 months, leveraging Snowflake’s marketplace, and so much more.
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Steve Hamm: [00:00:00] Tomas, welcome to the podcast.
Tomasz Blicharski: Uh, hi. Great to be.
Steve Hamm: Yeah, many of the international listeners of the podcast are probably not familiar with Jaka Group, so please describe the company. Its markets, the competitive landscape.
Tomasz Blicharski: Yeah. Um, Shakka is a retailer. Uh, we operate in convenience. Uh, run more than, uh, 8,000, actually close to 9,000 convenience stores in Poland. Uh, but uh, more importantly, we're also, and we describe ourselves as a convenience ecosystem that, uh, uh, is between the physical, the stores and digital, uh, worlds.
And within digital, we have the quick commerce. We're the leaders in quick Commerce in, uh, Poland, e grocery. We're the leaders in direct to consumer meals in Poland, and we're, uh, operate the [00:01:00] largest consumer retail app with millions of, uh, monthly active users. And all of this, uh, the stores, the traditional, as well as the autonomous stores, uh, surrounds the consumer and our mission is to, uh, make this the consumer's lives easier, pre-up their free time.
Steve Hamm: And you're, you're in Poland. Are you, are you also in other countries in Europe?
Tomasz Blicharski: Actually, Yes. Uh, we also, uh, a few months ago opened our first stores, uh, outside of Poland in Germany. We operate, uh, a couple, uh, of autonomous stores in, in Germany. Uh, we're testing this and, uh, seeing how this progressed.
Steve Hamm: Good. Good. Now, the war in Ukraine has put incredible pressure on Poland. How has that affected job's business and how has the company.
Tomasz Blicharski: Yeah, it's, uh, [00:02:00] it's a very sad situation. Uh, you know, Poland, being neighbor, uh, to Ukraine has, um, has seen an influx of, uh, Millions of refugees, uh, over the last, uh, nine months, especially at the beginning, first few months of the, of the war of the conflict, uh, that, uh, effectively, uh, changed the way the people in Poland think generally.
And, um, as you may have heard, uh, The entire nation almost, uh, started to help refugees. Uh, we accepted, uh, more than 3 million refugees in Poland, um, to our homes, actually not, uh, refugee centers, but to our homes. Uh, and as a company we have, um, Actively participated in the, uh, in the help program and the number of different help programs that we have, uh, created.
We, uh, we have sent, uh, hundreds of tons of food via trains [00:03:00] to Ukraine. To help, uh, those who stay there. Uh, we have, uh, rented, uh, flats for, uh, several hundred of Ukrainians and, uh, provided, uh, free accom, uh, accommodation to them. Uh, here in Poland. Uh, we have launched, uh, uh, help to, uh, to help those at the border.
And, uh, and many, many other, uh, initiatives that we did as a company. Um, of course, you know, Poland has always accepted Ukrainians and, uh, they have been working, uh, in our country for a number of years and they work in our company as well. Uh, so we help those employees as well. And, um, from the business perspective, purely obviously that also meant that there is more consumers, right?
We are a consumer retail company, right? And, uh, and these consumers have. Being the customers of our stores. So we adapted the offer, uh, slightly of the, of the stores. Uh, uh, we have, uh, added in our [00:04:00] communication, also the communication in, uh, Ukraine language in certain channels.
Steve Hamm: Right now you have a broad set of responsibilities as managing director at Jaka Future, including m and a venture investments, new business ventures and technology. So how do data and analytics contribute to the ZA future portfolio?
Tomasz Blicharski: Yeah. Um, it's a, it's a super important part of. Uh, an ingredient of our success, Actually, the data. We broadly believe that Java is a data driven company. Uh, the way we, uh, look at the decision making processes and the way we take decisions, uh, is, uh, based on the data. We are very analytical and, uh, this is no different in, uh, the new businesses that we create.
Uh, be it, uh, before we. Decide to start a [00:05:00] business. Uh, when we look at the data, uh, look at the consumer data, look at the third party data, whether we purchase or we we got from other sources. Um, be it when we launched new, new businesses. Uh, and we try to. For example, a transplant or, uh, use some of the data that we have from other businesses, uh, to create synergies with these new, uh, businesses that we decide to run.
Um, in fact, um, I would say the data for us, uh, future, but also in the, in the J group is a source of, uh, competitive advantage and we treat it.
Steve Hamm: Okay. Yeah. Let's drill down on some of that. Tell us about the new approaches to retailing. The, the job is testing and what's the role of data in those ventures?
Tomasz Blicharski: Yeah. Uh, look at, um, uh, one of the new business that we launched last year, Autonomous [00:06:00] stores, right? Jaka Nano, Uh, just to describe how it works. Um, effectively these are the stores, uh, where there's no traditional checkout, right? Physical checkout. There is no actually staff inside the store on a permanent basis.
You as a customer enter the store with a app or a credit or debit card. You pick the goods, uh, and then you leave. Uh, and then the settlement, the checkout process is done automatically using, uh, using, uh, deep learning cameras, uh, and software that links the behavior of the customer in the store to, uh, to the data and the, and the finally the bill.
Um, this. Wouldn't be able to exist, you know, some years ago, um, because, uh, that technology wouldn't, you know, there wasn't there, right? But now, when it exists, it exists, uh, uh, and is successful also because, uh, we are able to [00:07:00] successfully leverage the data that we have, uh, to personalize, uh, offers for the customers, uh, to, uh, track, uh, the behavior and, uh, adjust the offer, uh, to the, to the need of the customer.
And, uh, many, many, many more, right? Uh, but in fact, uh, as I mentioned, the data is, is key to be able to successfully launch and roll out and operate, uh, those kind of business.
Steve Hamm: Yeah. I want to go back to something you said about the deep learning cameras. So how does that checkout work? Do the, the cameras just observe each person and what they touch and what they put in their, in their, you know, basket. And then based on that it, it charges them through the app or, or how does that work exactly?
Tomasz Blicharski: Yeah, you're spot on. Uh, there is, uh, a number of cameras, uh, they record video. The video actually, uh, which is important, uh, for, you know, especially in Europe, given GDPR [00:08:00] stays in the store, on the service in the store, right? Doesn't, the video doesn't move, leave the store, right? Uh, , uh, and, uh, it identifies the customer, the respective person.
And whatever is taken by the customer, the products taken by the customer is then being, uh, identified and, uh, charged, uh, ultimately, uh, to the credit or debit card of the, of the customer.
Steve Hamm: That's really interesting. You know, it's funny, I, I haven't read or heard of, you know, that exact model being used in other places. Is, is this unique to your company?
Tomasz Blicharski: Um, well, we're, uh, in leader, uh, we're the leader in Europe, uh, with, uh, these kind of, uh, uh, stores. Uh, some of the other players that, uh, operate, uh, let's say pilot stores of similar kind, uh, they typically use. Uh, fusion of sensors. So, so [00:09:00] they have some camera, but they rely on weight sensors in the shelf to, to get it done right.
And, uh, as far as I know, we're one of the very few players that rely, uh, purely on cameras.
Steve Hamm: Mm-hmm. . That's really interesting. Um, so an early adopter or an, in some case innovator that's, it's really interesting to see how you're using technology. Um, now obviously cloud is a major, a major issue here and a major strategy for the company. When and why do the company start migrating applications and data to the cloud?
Tomasz Blicharski: Yeah, that was many years ago. I actually don't even remember the exact date, to be honest with you, but I could tell you why we did it. Um, I think the main reason was that we were growing. So fast. I mean, we open 1000 stores, actually more than 1000 new stores per year, right? So we're a kind of very dynamic company, uh, on top of these [00:10:00] new businesses, right?
Uh, and with, uh, with such a velocity that we have, uh, in our business we've had for a number of years. Uh, you always wanna make sure that you don't, you know, you're, you don't have any blockers, right? For growth and obviously, um, cloud, uh, Enables you to increase capacity on the tech side. Just put it, uh, that way, uh, in a continuous and, uh, you know, seamless manner.
So that was primary reason for, for, you know, back then several years ago, uh, for start of the migration to cloud.
Steve Hamm: Yeah. Yeah. People talk about the elasticity of the cloud, and it seems like that's very important for a company growing as fast as yours is. So at some point you engaged with Snowflake. So tell us when that happened and why.
Tomasz Blicharski: Yeah, that was um, uh, [00:11:00] Four to five years ago, um, we were then running this big initiative at our company, uh, and I mentioned about that, the data driven approach, right? So we were, uh, we're, we're kind of moving the philosophy of decision making process from. Let's say this more of a intuition based to more of a data driven, right?
And, and for that, we, we had to pull all of our data, uh, in a single source, uh, visualize all the data for respective users and effectively, uh, create. Friendly environment, um, them to, to, to be able to make this decision in a different way, right? In data driven approach type of way, uh, in new environment, right?
And, uh, this is, uh, where we kind of, uh, started to look for the best. Tax stack to effectively achieve that. And, uh, and honestly, I mean, [00:12:00] we, we worked with a few other, uh, companies, uh, actually much bigger, uh, than Snowflake at the time. Uh, but the tag that they provided was, was not sufficient to our needs.
I mean, we, we wanna have a live data, we wanna have real time data. We gonna have, or almost real time data we wanna have. You know, plenty of vi visualizations and then, you know, we couldn't have it done. Right. And this is where, how, when we. I would say even stumbled across Snowflake, uh, one of the, one of the founders of Snowflake is, uh, Polish.
And, uh, and so I think that was the real reason why we kind of connected and, uh, we tested the, uh, the software. We tested, uh, the solution briefly, uh, and we said, Bingo, right? This is what we. What we're looking for, uh, that would, uh, solve our problems. And, uh, three months later, uh, we moved our, our stack to, to Snowflake already.
I mean, that was very seamless.
Steve Hamm: [00:13:00] months later. That's incredible.
Tomasz Blicharski: yeah. Yeah. And I could tell you that it is the only that I know of at least, and I remember instance when the data guys, the data engineers, you know, effectively said that. Move made their lives so much easier. So much better. And they were really thankful to the, you know, super management team that they gave, that they received the budgets to kind of be able to do that.
Right. So that, that's, that's a very, uh, interesting story.
Steve Hamm: No, that's a good story. Very good. Now at this point, what are the most important applications that you run on? Snowflake.
Tomasz Blicharski: I mean, all of our data effectively is, is on Snowflake, right? So, so we, uh, you know, I could probably easier tell you what, what we don't want using Snowflake than what we do run
Steve Hamm: Well, tell us about a key one or two key applications that are really, that really have some sizzle to 'em.
Tomasz Blicharski: Yeah, no. Look, if you think about it, [00:14:00] how we use effectively Snowflake, uh, snowflake is always in the background, right?
For us as a kind of data lake, as a data warehouse, or whatever you're gonna call it, right? But effect all the data from all, all the systems that we have, go to Snowflake, and then Snowflake, uh, enables us to, to use this data, uh, you know, uh, from, you know, for the, for the consumer rights of the, the users inside the company and. all of our kind of internal reports that we have use, uh, visualize using Par BI for example. And we have several hundred of different reports, actually around 700 different reports, uh, internally that we run on Snowflake, right? We visualize on, uh, on.
Steve Hamm: So that's Power bi, that's The Microsoft, um, kind of visualization application on top of Snowflake. I get that. Okay.
Tomasz Blicharski: Yeah. Then the other, uh, you know, I think quite unique one is that we use Snowflake as a data source, uh, for, [00:15:00] uh, for all our kind of, uh, machine learning models, right? So whenever we. Uh, use, uh, you know, build machine learning models. You know, we prepared this in a snowflake environment and obviously then we use different, uh, kind of, uh, environments later on.
Uh, although we increasingly, you know, test also some, some of the snowflake's, uh, latest uh, You know, products and solutions in that, uh, space as well. And finally, um, one of the things that we've done with the data once we kind of, uh, pull it all together and, uh, and we had it readily available is, is we, we run, uh, what we call data monetization, uh, product for, uh, CPG suppliers.
Uh, and, uh, this is something that we run, uh, on Snowflake and we built a web interface, uh, for. Uh, for the suppliers of the ones that subscribe to the service, um, uh, on top of it.
Steve Hamm: Yeah. [00:16:00] So let me drill down into that just a little bit. So you're selling data that the company collects
Tomasz Blicharski: Yeah,
Steve Hamm: and you're, you're basically selling packages of that to your supplier. So kind of passing the insights upstream, when did that emerge and, and how, how does the, the Monet Sensation Strategy work?
Tomasz Blicharski: Yeah, that's something that I think started in our heads like three years ago. We launched it, uh, as an MVP two years ago, uh, to our suppliers. I mean, think about the biggest CPG suppliers globally, right? You know, the brand, the biggest brands that are out there, right? And, uh, and uh, the way it works is, uh, we, we offer them, uh, access to curated data, uh, in different formats and different layers.
Uh, some that is real time, uh, which enables, uh, them to make a better decision. And we actually work hand in hand, shoulder and shoulder with them. We have actual kind of like [00:17:00] advisory team as well. You know, helps, uh, CPG suppliers to, uh, to effectively, uh, CPGs to, to effectively interpret data and, uh, draw some joint conclusions.
So it's not like just the selling the data part, but also, you know, like a win-win type of solution that, uh, enables both parties to make better decisions together, right? Working on the same data together, uh, to effectively make better decisions, both for, uh, CPGs and also for, for, for.
Steve Hamm: Yeah. Hey, back to Snowflake for just a second. Where do you see the relationship going in the future?
Tomasz Blicharski: Look, I, I think the way I look at it, um, we're, you know, generally the companies globally are more and more governed by data and there is more and more automation going on right out there. And, uh, and to be able to fully utilize data. Uh, we, we, uh, we effectively look at, uh, machine learning solutions, right?[00:18:00]
Uh, we are increasingly, and we have been increasingly using machine learning in almost all area of our company. And I think the way I look at the, uh, the, the, the snowflake and solution and the, the road, uh, ahead of us is, is actually to incorporate. More, more of the machine learning into native snowflake, uh, environment, right?
That would, that enables us already, right? Uh, because it's already happening to, to simplify our architecture and, uh, and also to save on, uh, on cost. So, so I think snowflake and machine learning and, uh, and uh, that, that's something that, that certainly is, is for. You know, uh, the way to go. The other, uh, aspects that I would mention is, um, we, you know, we obviously have plenty of data, right?
But in, in, in the world of data, there's no such thing as enough data, right? [00:19:00] So the other part is effectively, how can you know, we work with Snowflake and already do. To effectively use more of the data from other, uh, from, you know, third party from other players and, and can use this, uh, to really create, uh, even better, uh Applications, right?
Steve Hamm: Yeah. So you're looking at the marketplace or, or what's the, the format that you're looking at?
Tomasz Blicharski: Yeah. The marketplace. Yeah, the marketplace. Uh, and, and we, we work, uh, we, we actually, um, have, uh, submitted some of our data to the marketplace. We're also. Some of the, uh, some of the data from the marketplace. I think that's something that, uh, that is also, um, you know, looking forward, uh, something that would create a lot of value for, for us..
Certainly.
Steve Hamm: Yeah. Very cool. Now, Covid, fortunately, is starting to wane around the world, but I wanna go back to that for just a second. [00:20:00] I understand that after the global Covid outbreak, Jka used data analytics to quickly adapt its business and set it on a positive track. Also, you help the, the Polish government marshal its response.
So please tell us how you use data and analytics in the wake of covid.
Tomasz Blicharski: Yeah, I mean, um, I remember that time very well. Uh, it was, uh, uh, a lot of uncertainty. Uh, a lot of, uh, change of, uh, customer behavior. Very sudden, uh, a lot of, uh, you know, completely new environment and situations right. And uh, and obviously that changed our business from one day to the other completely, right?
And, um, we were at this situation at a time, uh, you know, one, one of our hero product, uh, is a hot dog, right? We sell. Several hundred thousand hot dogs per day to our, you know, [00:21:00] busy consumers. They can just grab it in one hand and just go and, uh, and, uh, and with their busy lives and, uh, And obviously when the Covid started, uh, you know, people have locked themselves up, right?
Uh, at homes and, uh, I mean, the store were open, but, uh, but the behavior of the customer was completely different, right? And, uh, and after, um, a few months, once the Covid restrictions have been, uh, relaxed and uh, was already possible to go out, We, we, we seen that some of the behaviors that were before did not immediately come back.
Right? One of them was actually consumption of the hot duck. The, the, you know, the, the consumption dropped 80% or so.
Steve Hamm: Wow.
Tomasz Blicharski: And, um, luckily we had the, the data, we had the real time data, and we also had a communication tool. Uh, to communicate directly with the customers that I mentioned before, the consumer app that we, that we, we had already at the time, and [00:22:00] we used some personalized, some exp uh, promotions, some exploding offers, uh, and very kind of aggressive communication based on the data that we analyzed to effectively attract the customers back, uh, into the.
You know, maybe not a hundred percent, about 80% back to the habits they had before. And all of that happened in the, in this panel of, uh, of couple of weeks, right? So the data and the great analytics that we had, and the great tool that we built based on the data at the app, uh, enabled us to effectively get our business back on the right track within the weeks of, uh, you know, once that became possible.
Steve Hamm: Yeah, that's a great story. I mean, you really restarted a pattern, a behavior pattern. And then of course once you brought people to buy the the hotdogs, they bought other things as well. So in a sense, it kind of restarted the business, right?
Tomasz Blicharski: Yeah, exactly, Exactly that.
Steve Hamm: Yeah. [00:23:00] Well that's really cool. So, um, I wanna talk about the future a bit here.
Um, what are the major trends in data analytics that you see emerging in the coming year or so?
Tomasz Blicharski: Yeah, great question. Um, I, I think I mentioned already about generally the automation. I, I think, I think the automation is the, is the key word that I wanna wanna use here. Uh, we. You know, we already are reasonably advanced in the, in the data part, right? We, we, we run machine learning on the, uh, on the prices that we have in our store.
So differentiate prices based on machine learning models. We, uh, We differentiate assortment, uh, based on the machine learning models that we created. We, we look for new location based on machine learning model, and we select these locations where the models suggests are, uh, where the best place for the source would be.
You know, we optimize the transportation based on similar tools, uh, [00:24:00] and, and many, many other aspects of our business. We have automated replenishment in our stores that we, we've kind of built, uh, based on similar approach and. The, the, the, you know, when you look at it, uh, going forward, it's, uh, it's, uh, a little bit of a, kind of a decreasing, uh, returns type of game.
So it's, you know, that we have more and more data, uh, but the biggest things have already been, been done, and in order to be able to successfully tackle the other aspects, you. Automation. You need machine learning. Uh, you need, uh, something that increases, uh, efficiency of people, uh, in creating, you know, these new use cases, these new approaches to data.
And, and I think that's, that, uh, is something that's gonna be happening so, so effectively, how to get your [00:25:00] data ready and take advantage of these, of the data. Quicker, faster, and easier. Uh, and, and I think that's, you know, that's, that's gonna be, that's gonna be one of the trends that we see, at least for.
Steve Hamm: So that's over the next year or so, I'm gonna ask you to put on your visionary cap. Now, looking forward five years or more, how do you see data analytics affecting business and even society?
Tomasz Blicharski: Well, um, of course, uh, you know, five years out the, it's always, um, more challenging, but, but like putting my hat on, look, I think that, I believe that all the businesses. Will have to be the data businesses to, to be successful
Steve Hamm: Right,
Tomasz Blicharski: in five years. Right. So, So I think those who do not take full advantage of the data will have. We'll be struggling effectively, We'll have challenges in, in remaining, uh, competitive. As I mentioned, [00:26:00] I, we, we, we believe that the data for us is a source of our competitive advantage. And, and I think that's gonna be increasingly true. Uh, so I think that those who will not build the capabilities will not, uh, invest in the tax tank to be able to, uh, to effectively manipulate and take advantage of the data.
I think those will. They risk to be left, left behind. And, and that's gonna be the, you know, the, the one of the key drivers. Uh, I see that already.
Steve Hamm: Yeah. So are there, are there new technologies or new capabilities that you anticipate coming in several years that will really make, you know, take, take data analytics to the next level?
Tomasz Blicharski: Yeah, look, uh, you know, if you look at our business, uh, for example, Job Canna, right? Uh, we. 50 plus stores at the moment. It's [00:27:00] an early stage of the growth of the business. Uh, you know, it's physical stores with digital kind of, uh, interface to them, uh, in a way purely relying on, uh, modern data technology to, to be able to function.
I think in five to 10 years, these kind of businesses, which are effectively built on from the scratch on the, let's say, modern use of the. Uh, will become more. Uh, uh, more popular, well, more, more, more, more developed not only in the store space, right, on retail space, but also in other, other areas. So you, when we kind of, uh, take a step back and look behind, like the traditional businesses have changed themselves.
To be able to use the data and take as much of the data. I think in the next five to 10 years, there's gonna be increasing number of new businesses, different business model, different services, which in a [00:28:00] way serve the customer better in some way, uh, because of the use of the data. In a, which, in a different way.
Right. You know, scaling and using the, the technologies that they're out there. Right. So, so I think that's gonna be the, the, the thing that's gonna be progressive, right. The, the digital data native companies in a way.
Steve Hamm: Yeah. No, I think that's a good term. In fact, I just wrote that down cuz we talk about digital native, web native kind of companies, but data native companies that where, where the opportunity is built on the data and on the analytics. I think that's a really great insight by you. So thank you for that.
Um, we typically end the podcast on a lighter note, a more personal note, and I understand, I understand that, uh, Theca is a beloved brand in Poland, so help us understand that. Explain why that is and how that happened.
Tomasz Blicharski: Yeah, I mean, indeed Java is, uh, as we call the, the loved [00:29:00] brand in Poland. It's, you know, it's known by almost everyone, uh, in, in the country. Uh, we, uh, Of. We have almost 9,000 stores, as I mentioned, we're almost everywhere, although we're still opening new stores. Um, an average pole, or let's say 15 mil, uh, millions of, of poles visit, uh, our stores, uh, many times, uh, every, every month. In fact, uh, one of the reasons for, for that success, obviously, um, more anecdotally than that is, uh, is our name. Jka. In Polish means, uh, little. Cute frog and, uh, and uh, and, uh, don't ask me why this name was chosen, chosen by the founder many years ago.
Uh, it's, it's, uh, it remains a mystery, but, uh, what is true is that, uh, a lot of polls in certain areas of the [00:30:00] country, uh, carry the small job car. Uh, medallions in a way, uh, in their, in their wallets for, uh, for a good luck and maybe that, uh, contributed to that name. And, uh, and we're, I, I think we're, uh, we're, we're trying to, to bring good luck and more of a smile into the faces of our customers.
We're trying to make their, uh, lives easier. We're trying to finally free up their free time so that they can spend that time, uh, with the loved ones and, uh, and love us for it.
Steve Hamm: Okay. Wonderful. Well said, well said. Now this has been a, it's been a really cool conversation. I'm, I think, you know, we started off talking, I'm sure very few of our podcast listeners. Have heard of the company before, but I think it's fascinating to see what a kind of a thought leader and innovation leader is.
I love this whole idea of the autonomous stores and you, you talked about the kind of the deep learning cameras and, uh, for checkout and things like that. [00:31:00] So, uh, it's. It's a surprise and it's a really interesting, uh, story. And I think, uh, job could give lessons on innovation to other retailers around the world. So thank you so much for being on today.
Tomasz Blicharski: Thank you and uh, have a great day.