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Inside the Robot-Powered Warehouse · Speaking of Supply Chain

• 0:00
  Speaker 1: Everybody wants to push the innovation further, and that is
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  Speaker 1: also creating, you know, a lot of interesting opportunities. Robot
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  Speaker 1: technician will be as common as plumber or electrician in
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  Speaker 1: your house is the same.
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  Speaker 2: I agree, and I think one of the things that
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  Speaker 2: draws an interesting parallel here if we look back at production,
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  Speaker 2: and we look back historically over the last hundred years,
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  Speaker 2: we had people, usually men, who were in these facilities,
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  Speaker 2: and they were the engineers or the repair guys, or
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  Speaker 2: the guys who worked on the machines, and they were
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  Speaker 2: the ones who were in charge of maintaining this equipment
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  Speaker 2: and making sure that it worked. So I think that
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  Speaker 2: this is just the next evolution of that. Hello and
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  Speaker 2: welcome to Speaking of Supply Chain, where we explore trends,
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  Speaker 2: current events, and innovations impacting the logistics and supply chain industries.
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  Speaker 2: I'm your host, Ellen Wood. Labor shortages, high turnover and
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  Speaker 2: safety risks continue to challenge warehouses, with some facilities seeing
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  Speaker 2: annual turnover rates above forty percent. At the same time,
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  Speaker 2: demand for faster, more reliable fulfillment has never been greater.
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  Speaker 2: I'm joined today by doctor jan Jishka to explore how
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  Speaker 2: bright pick is using robotics and AI not just to
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  Speaker 2: boost efficiency, but to create safer, more sustainable, and more
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  Speaker 2: engaging workplaces for the people who keep supply chains moving.
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  Speaker 2: Welcome ya, thank you. It's great to have you here today.
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  Speaker 2: Before we get started, let's jump into our icebreaker, and
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  Speaker 2: today's question is as a child, what did you want
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  Speaker 2: to be when you grew up?
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  Speaker 1: So I don't remember exactly, but my mother told me
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  Speaker 1: that when I was really young, I told something like
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  Speaker 1: I was very impressed by, you know, trash man and
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  Speaker 1: the you know, I think that the mechanical car was
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  Speaker 1: very interesting to me or something like that. So the
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  Speaker 1: very first one later, I think I promised to my
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  Speaker 1: parents that I will I will paint a picture and
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  Speaker 1: solid for one million. The second so it looks like,
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  Speaker 1: you know, the ambition was up and down.
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  Speaker 2: Yeah, you know what, I can understand that I have
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  Speaker 2: little boys myself, and anything with a big truck that
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  Speaker 2: moves big things, whether it's construction equipment or the trash truck,
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  Speaker 2: they are very excited about that. So I feel like
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  Speaker 2: that seems pretty reasonable for all little boys they want
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  Speaker 2: to drive the big trucks. Let's see for myself when
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  Speaker 2: I was really little. I mean, of course, when you're
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  Speaker 2: when you're very small, you have all sorts of dreams.
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  Speaker 2: But once I was actually thinking about realistically what I
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  Speaker 2: wanted to do, I wanted to be an art teacher
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  Speaker 2: at the at the elementary or you know, an primary
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  Speaker 2: school level. I wanted to be an art teacher, and
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  Speaker 2: I started pursuing that career and then realized very quickly
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  Speaker 2: that I would not be I don't have the patience
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  Speaker 2: to be a teacher. I love art and I love kids.
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  Speaker 2: I love my kids. I love doing art, but trying
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  Speaker 2: to turn it into a profession was just not going
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  Speaker 2: to work for me. So I had to abandon that
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  Speaker 2: fairly early. And then I thought I might be a
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  Speaker 2: marine biologist for a while. But yeah, I don't know
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  Speaker 2: why that kind of fell by the wayside. I think
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  Speaker 2: life just, you know, started taking me in a different direction,
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  Speaker 2: and I really enjoyed some of the other things I
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  Speaker 2: was doing, so I just kind of dropped that one.
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  Speaker 2: There wasn't any you know, big dramatic thing like there
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  Speaker 2: was with trying to be an art teacher. But yeah,
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  Speaker 2: I've explored a lot of different careers over over the
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  Speaker 2: time that I've been working. But now I think that
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  Speaker 2: what we what were interested in as small children gives
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  Speaker 2: a lot of insight into where our mind is looking.
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  Speaker 2: So let's see if we can get into some of
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  Speaker 2: those technical aspects of big trucks that appealed to you
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  Speaker 2: so early in your childhood. In our discussion today, which
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  Speaker 2: is about robotic picking and using robots within the four
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  Speaker 2: walls of a facility, mostly fulfillment centers, but you know
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  Speaker 2: there is the opportunity in just regular warehouses as opposed
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  Speaker 2: to giant dcs. So let's talk a little bit about
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  Speaker 2: some of the labor issues that are affecting warehouses today.
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  Speaker 2: And I know that my information is mainly about the US,
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  Speaker 2: but I know some of these things are universal and
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  Speaker 2: globally applicable. So labor shortage, I was talking about it
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  Speaker 2: just a minute ago. And sometimes those rates, those turnover
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  Speaker 2: rates are as high as forty percent, and it's becoming
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  Speaker 2: very difficult for especially US companies to employ people who
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  Speaker 2: want to work in a warehouse or a fulfillment center.
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  Speaker 2: And there are a lot of different reasons for it,
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  Speaker 2: and we could get into those, but I think the
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  Speaker 2: net of that conversation is it's not going to change.
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  Speaker 2: We're not going to all of a sudden get this
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  Speaker 2: generation of workers who want these more manual positions, who
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  Speaker 2: want this you know, it's heavy work, it's physical work,
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  Speaker 2: and I think as a society we're starting to move
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  Speaker 2: away from some of those types of professions with the
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  Speaker 2: advent of some of this technology that is available. So
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  Speaker 2: from your perspective, is there anything else that's driving that
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  Speaker 2: gap other than the labor market pulling away from those
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  Speaker 2: more manual types of job positions.
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  Speaker 1: So in general, I would compare it directly to you know,
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  Speaker 1: agriculture and industryal revolution. It's very very similar from some viewpoint, Like,
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  Speaker 1: you know, even one hundred years ago, still there was
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  Speaker 1: a lot of people working in agriculture. Today it's very
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  Speaker 1: little and and yes, people have to invent machines to
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  Speaker 1: kind of solve that issue to some extent. But again,
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  Speaker 1: solving that issue is pulling that those people out of
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  Speaker 1: those jobs even more from some viewpoints. So I would
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  Speaker 1: say it is part actually chicken egg, but definitely the
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  Speaker 1: primary driver is exactly as you're told. It's just people today.
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  Speaker 1: You know, in many cases, I tell that today everybody
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  Speaker 1: wants to be YouTube ery. So that is still you know,
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  Speaker 1: kind of much more attractive job compared to you know, walking.
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  Speaker 1: I think in many cases it's uh, you know, five
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  Speaker 1: even maybe maybe ten miles per day. In many cases
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  Speaker 1: in manual fulfillment centers, it's not really you know, in
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  Speaker 1: principle your boss is hunting that pickerate. There's not much
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  Speaker 1: fun into it. You know. It's probably from like mentally,
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  Speaker 1: it's a pretty simple job from some viewpoint. Physically it's
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  Speaker 1: quite difficult. It's very rapy table and and I just
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  Speaker 1: feel like there's not much sunlight in those warehouses. You know,
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  Speaker 1: there's I would say a lot of aspects and people
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  Speaker 1: don't see it. In many cases warehouses are kind of clean.
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  Speaker 1: It''s not terrible, but it's not exactly fancy office space,
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  Speaker 1: you know. So I would say there's a lot of
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  Speaker 1: small details that simply add up and and it's simply
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  Speaker 1: not attractive, you know. And if we would and we
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  Speaker 1: don't need to do that, but if we would do
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  Speaker 1: some kind of pool like, we would get clearly clear results.
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  Speaker 1: And the result is you know, if you if you
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  Speaker 1: open today, you know, indeed or glass door or whatever,
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  Speaker 1: any of these platforms, probably there's like between fifty to
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  Speaker 1: one hundred thousand open positions, and that is specifically wair
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  Speaker 1: house speaker. You know, it's not a fair house worker
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  Speaker 1: or something, it's warehouse speaker. And it's really high number.
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  Speaker 1: And and this number is so to some extent we
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  Speaker 1: increase automation, but it's still kind of little from some viewpoint.
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  Speaker 1: And I remember I'm checking the number, you know, maybe
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  Speaker 1: each quarter, and it's kind of the same. Of course,
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  Speaker 1: during the peak season is even higher, you know, when
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  Speaker 1: Amazon and Walmart and other companies are hire even more.
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  Speaker 1: But it's simply a huge number of people. And and
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  Speaker 1: as you say, like like it's definitely is not going
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  Speaker 1: to improve, and I would say it's clear it's going
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  Speaker 1: to be worse. You know, it's like it's obviate that
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  Speaker 1: it's going to be worse. And plus there's also different
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  Speaker 1: factors like in many cases you want to have a
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  Speaker 1: warehouse outside of the city, if your last mile allows
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  Speaker 1: that it's outside of the city, potentially quite far around
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  Speaker 1: the city. Again, you know, the other adding another argument
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  Speaker 1: like I have seen actually people really organizing a special
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  Speaker 1: bus tours for those workers to even get them there,
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  Speaker 1: you know, so it's like a special line in principle,
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  Speaker 1: so and and maybe as you said, forst and Plant,
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  Speaker 1: I can compare Asia, I don't know much, but the
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  Speaker 1: Europe and the US I can compare quite well. And
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  Speaker 1: I think it's almost exactly the same. The only difference
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  Speaker 1: I probably see mainly in let's say Central Europe Germany,
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  Speaker 1: is that there's a lot of people from more like
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  Speaker 1: Eastern Europe, you know, because it's more or less free market,
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  Speaker 1: you know, labor market. Of course, there are some limitations,
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  Speaker 1: but it's it's kind of easy, and those people usually
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  Speaker 1: would would earn let's say, half maybe third of the
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  Speaker 1: salary in their original country, so it's kind of simple
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  Speaker 1: to Sometimes they even travel like regularly, you know, for
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  Speaker 1: example to Germany and so on. On the other side,
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  Speaker 1: we see that German companies they are they are moving
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  Speaker 1: their warehouses for example, to each other public or Poland
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  Speaker 1: or whatever, Slovakia and so on. So it's kind of
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  Speaker 1: people are trying to solve that problem, and it's partially
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  Speaker 1: about cost efficiency. But I would say that is in
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  Speaker 1: principle totally secondary. You know, I remember very well, you know,
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  Speaker 1: I have been I don't know, maybe fifty warehouses and
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  Speaker 1: and and maybe warehouse number ten I have ever seen.
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  Speaker 1: I remember the manager telling me that, yeah, I'm so tired.
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  Speaker 1: I was like, okay, well what is wrong? And he's like,
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  Speaker 1: I'm doing interview number I don't know, twenty today or
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  Speaker 1: something like that. You know, looks like his on the
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  Speaker 1: main job was he was like a manager in all
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  Speaker 1: the given very house and looked like he's spending a
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  Speaker 1: lot of time with interviews. And he was really telling
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  Speaker 1: that and it's almost baste of time. Because I hire someone,
• 10:36
  Speaker 1: the chance they will show up is fifty percent. You know,
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  Speaker 1: it was not fifty you know, he was kidding, but
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  Speaker 1: I think he was. He meant like maybe ten percent
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  Speaker 1: they don't show up, which is still very high. You know,
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  Speaker 1: if you if you have all that effort, maybe you
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  Speaker 1: see ten people. Then you say like and then the
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  Speaker 1: guy is not, you know, showing up. I think it's
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  Speaker 1: really almost you know, you describe it well that the
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  Speaker 1: turnover is forty percent, you kind of you know, replaces
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  Speaker 1: all the people so often. Oh yeah, I would say,
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  Speaker 1: how to tell it from A big part is a
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  Speaker 1: motivation of those managers. You know, of course it's the
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  Speaker 1: owner of the warehouse. But ultimately I think it's just
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  Speaker 1: very difficult for those managers.
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  Speaker 2: Yeah, I think there are a number of factors that
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  Speaker 2: affect the volatility of that, whether it's the seasonality where
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  Speaker 2: people people need jobs all year around, not just when
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  Speaker 2: the employers need workers, and so you know, that's a
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  Speaker 2: detriment to an employee for you know, even signing up
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  Speaker 2: for that type of labor knowing that it's temporary, or
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  Speaker 2: you know, knowing that it is that. I don't want
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  Speaker 2: to say that that these types of facilities are are
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  Speaker 2: uncomfortable or or unpretty to work in. I mean, it's
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  Speaker 2: it's a warehouse. It is what it is. But it's
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  Speaker 2: it's honest work. It pays well for those who who
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  Speaker 2: want to, you know, participate in it. But you know,
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  Speaker 2: to your point, when labor is scarce in a particular area,
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  Speaker 2: sometimes that it ought to be a factor when companies
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  Speaker 2: are building their facilities. It's it's clearly something that they
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  Speaker 2: need to address in that location evaluation. However, things change
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  Speaker 2: over time and if that, you know, local community disperses
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  Speaker 2: and then that facility is left without labor, they're kind
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  Speaker 2: of in a tough situation looking at potentially moving their
• 12:34
  Speaker 2: entire location to where the labor is or having to
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  Speaker 2: come up with a different solution, whether the labor has left,
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  Speaker 2: whether the labor in the area is not interested. Automation
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  Speaker 2: is a solution, and that's where bright pick comes in.
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  Speaker 2: So I think when we start looking at some of
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  Speaker 2: these improvements and reducing that dependence on the manual picking
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  Speaker 2: and we start bringing in some automation, does it allow
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  Speaker 2: them to you know, work alongside the automation. What does
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  Speaker 2: it do in terms of you know, safety and security
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  Speaker 2: or accuracy for that warehouse, Because that is a very
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  Speaker 2: big decision to have to come to to start replacing
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  Speaker 2: part of your workforce with an automated solution. And these
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  Speaker 2: I mean this is not you know, some some small solution.
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  Speaker 2: This is this is a major undertaking. So I know
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  Speaker 2: companies need to do their due diligence and understand what
• 13:29
  Speaker 2: the costs are going to be. You know, where are
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  Speaker 2: they able to recoup some of that in whether it's
• 13:36
  Speaker 2: a direct cost or an indirect cost like employee safety.
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  Speaker 1: I think you know, for me, I have seen it
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  Speaker 1: in many cases. You know, it's either our automation, different
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  Speaker 1: types of automation. Before I work more for automotive. You know,
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  Speaker 1: similar story from some Vipan and I think the major
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  Speaker 1: point for me is that they always keep the best people,
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  Speaker 1: you know, the people who are probably longer with the company,
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  Speaker 1: people who who who had you know, pretty good pickert,
• 14:05
  Speaker 1: who who was kind of active, engaged, and ultimately I
• 14:10
  Speaker 1: feel like, okay, that's a that's a great news from
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  Speaker 1: some viewpoint, you know that it's nobody is really I
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  Speaker 1: think the best pickers. You know, it's like it's clearly
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  Speaker 1: the some kind of assets they have, you know, and
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  Speaker 1: they're very proud probably and and and that that means
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  Speaker 1: we are potentially improving that the job for for those
• 14:30
  Speaker 1: who were engaged and who wanted to help, you know,
• 14:32
  Speaker 1: in that given warehouse. So from this weep and I
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  Speaker 1: think it's it's it's pretty good in terms of you know,
• 14:38
  Speaker 1: the all the walking distance and these I would say
• 14:42
  Speaker 1: it's obvious that they suddenly have to walk muchulized. That's
• 14:45
  Speaker 1: kind of obvious, you know. Benefit We always explore that
• 14:48
  Speaker 1: for example, when you have G two P station or
• 14:51
  Speaker 1: or you do resktock of our system or any of these, uh,
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  Speaker 1: you still have to be there either you know, for
• 14:59
  Speaker 1: ours with some break or you know, maybe even seven hours.
• 15:03
  Speaker 1: I'm not sure you know, depends on the country and
• 15:05
  Speaker 1: then the rules. So you know, in many case we
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  Speaker 1: also explore like it has to be at least somehow ergonomic,
• 15:12
  Speaker 1: you know, because still it's usually standing, not sitting, you know,
• 15:16
  Speaker 1: so it's usual standing. So in many cases we even
• 15:19
  Speaker 1: kind of intentionally introduce few steps between the peaks because
• 15:24
  Speaker 1: I think just standing, you know, I would hate it.
• 15:27
  Speaker 1: So in many cases I think doing those you know,
• 15:31
  Speaker 1: two steps left, two STAPs right. I think it in
• 15:34
  Speaker 1: principle it's a good thing, you know, because at least
• 15:36
  Speaker 1: you are moving. And and also I would say you
• 15:39
  Speaker 1: are probably adjusting your posture or how to tell it,
• 15:42
  Speaker 1: you know, it's it's kind of because because otherwise you
• 15:45
  Speaker 1: are probably leaning, you know, in that one spot here
• 15:48
  Speaker 1: you have to walk, and walking is actually very you know,
• 15:51
  Speaker 1: good for your you know, how you stand or how
• 15:54
  Speaker 1: to tell it. So from the oop, and I think
• 15:56
  Speaker 1: there's a lot of small details that could be of
• 15:58
  Speaker 1: course improved. You know, It's not like suddenly it's you know,
• 16:02
  Speaker 1: pure heaven and you like, it's still the same very house.
• 16:05
  Speaker 1: It's still you know, the same environment and so on,
• 16:08
  Speaker 1: still not so much sunlight. But but I think what
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  Speaker 1: they really appreciate is I think suddenly they are working
• 16:16
  Speaker 1: with you know, in our case like really cutting the
• 16:19
  Speaker 1: high end robot. We also try to be you know,
• 16:24
  Speaker 1: more more human. Let's call it. You know, every robot
• 16:26
  Speaker 1: has its name, you know, so they they really like it,
• 16:30
  Speaker 1: you know, they call it like okay, Carl, you know whatever, James,
• 16:34
  Speaker 1: you know, and so on and so on, so uh
• 16:37
  Speaker 1: and and pluss our robots are are you know, collaborative,
• 16:41
  Speaker 1: so they are really working in the same environment. After
• 16:44
  Speaker 1: Still you have to be careful. It cannot you know,
• 16:46
  Speaker 1: jump from the wreck in front of the robot and
• 16:49
  Speaker 1: similar things. But I think it's still very you know
• 16:52
  Speaker 1: safe and and and from this viewpoint it's not so visible.
• 16:57
  Speaker 1: But but again that was another manager telling me once
• 17:00
  Speaker 1: that they have some kind of injury almost every day
• 17:04
  Speaker 1: and it's like, okay, what is happening. It's just people walking,
• 17:07
  Speaker 1: you know, what is what is wrong? And he's like, okay,
• 17:09
  Speaker 1: but they are pulling or pushing you know, big wreck.
• 17:13
  Speaker 1: You know, it could be even fifty kilograms maybe even
• 17:16
  Speaker 1: more so it cannot stop so quickly and it's mainly
• 17:19
  Speaker 1: you know traffic jam, like it's people suddenly in one
• 17:22
  Speaker 1: spot you know, someone is behind the corner just jumping
• 17:26
  Speaker 1: in front of your card, you are hitting him with
• 17:29
  Speaker 1: the card or you know, just maybe falling. It was
• 17:32
  Speaker 1: not like you know, mortal you know some some some
• 17:36
  Speaker 1: crazy things. It was it was really simple things. But
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  Speaker 1: he told that, yes, we have small injuries almost every day. Yeah,
• 17:44
  Speaker 1: and I was a little surprised. And yes, it's it's
• 17:46
  Speaker 1: suddenly much easier with robots because kind of the traffic
• 17:51
  Speaker 1: jam is mostly between the robots. Suddenly, you know, there's
• 17:55
  Speaker 1: much less humans and they are there, I would say,
• 17:58
  Speaker 1: much better organized. You know, they are either in the
• 18:01
  Speaker 1: grip to person station or close to restore station or somewhere.
• 18:05
  Speaker 1: So it's suddenly, you know, yes, not so not so dense,
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  Speaker 1: and I would say it is definitely lowering the chance
• 18:13
  Speaker 1: of injury.
• 18:15
  Speaker 2: All right, so let's talk a little bit more about
• 18:17
  Speaker 2: the uh the bright pic Giraffe, which is a new
• 18:22
  Speaker 2: storage density solution and it increases that density by up
• 18:29
  Speaker 2: to three times if I have that correct. So what
• 18:34
  Speaker 2: does that translate into in terms of reduction of labor
• 18:39
  Speaker 2: needs when you've got that's that robotic, that automatic storage
• 18:43
  Speaker 2: solution that's going to go and pick from that location
• 18:47
  Speaker 2: you've got that density. So obviously our listeners out there
• 18:51
  Speaker 2: probably understand the difference between a manual warehouse and an
• 18:54
  Speaker 2: automated warehouse. Hopefully they've they've seen an example of both.
• 18:58
  Speaker 2: I know I have, you know, manual warehouses, you've got
• 19:02
  Speaker 2: a much wider aisle, so you're spending a lot of
• 19:04
  Speaker 2: space on you know, the ability to move within that facility,
• 19:09
  Speaker 2: whether you need a forklift, whether you've got a manual
• 19:13
  Speaker 2: palette jack or anything of that sort, you have to
• 19:15
  Speaker 2: be able to maneuver. Whereas within the automated facilities and
• 19:20
  Speaker 2: these very highly automated facilities, that robot whether it's Carl
• 19:24
  Speaker 2: or James or whatever you name it, so that you
• 19:26
  Speaker 2: can make the repair to the right one when it
• 19:28
  Speaker 2: needs it and differentiate between the various components. You know,
• 19:32
  Speaker 2: those need a very a much smaller space in order
• 19:35
  Speaker 2: to go up so that that racking aisle is is
• 19:38
  Speaker 2: much more condensed and you're able to fit much more
• 19:40
  Speaker 2: in that in that square footage because you have this
• 19:45
  Speaker 2: robot that doesn't need all of that maneuverability. So when
• 19:49
  Speaker 2: we're looking at these and looking at this one specifically,
• 19:53
  Speaker 2: where are we looking in terms of that labor reduction
• 19:57
  Speaker 2: or optimizing how much time HU means spend in that area,
• 20:02
  Speaker 2: and is is that a genuine ROI or is it
• 20:07
  Speaker 2: just a trade off?
• 20:09
  Speaker 1: Great question, So how exactly as we described it, it's impressible.
• 20:14
  Speaker 1: In development of giraffe, the kind of the biggest challenge
• 20:17
  Speaker 1: was that we wanted to have still the narrow aisle
• 20:21
  Speaker 1: out topicker is three three meter tall and the aisle
• 20:25
  Speaker 1: is I think ninety meters or something like the ninety
• 20:28
  Speaker 1: two ninety four depending on the you know, how flat
• 20:32
  Speaker 1: is the surface actually the flop floor, I mean, And
• 20:37
  Speaker 1: here the challenge was that, okay, we want to go
• 20:39
  Speaker 1: to six meters. So suddenly you see that the base
• 20:44
  Speaker 1: is compared to to how tall is the robot, it's
• 20:47
  Speaker 1: one to six, you know, more than one to six.
• 20:49
  Speaker 1: So but we we we we were able to still
• 20:53
  Speaker 1: make it. It was not simple, but we were able
• 20:55
  Speaker 1: to make it. And that means those us are still
• 20:59
  Speaker 1: very narrow. And I would even say that for humans
• 21:02
  Speaker 1: it's it's like borderline comfort table, if you if you
• 21:05
  Speaker 1: can imagine, it's really not not much, but you know,
• 21:08
  Speaker 1: there's no motivation for people to be there. You know,
• 21:11
  Speaker 1: mostly you know this part is kind of fully automated.
• 21:13
  Speaker 1: You know, there's no point for people to be there.
• 21:16
  Speaker 1: Uh so uh, the kind of im mediate you know,
• 21:23
  Speaker 1: the outcome is that when when you when you are
• 21:26
  Speaker 1: two times taller, kind of the era you use is
• 21:29
  Speaker 1: two times smaller, and and that is of course super
• 21:32
  Speaker 1: difficult with with humans. Like either you are building completely
• 21:36
  Speaker 1: new mezzagine and so like another floor which is usually
• 21:40
  Speaker 1: quite expensive and and not exactly modular. You know, people
• 21:44
  Speaker 1: tell it's modular, but but usually it's there at least
• 21:48
  Speaker 1: ten years. Nobody's building you know, mezzagine for one year,
• 21:51
  Speaker 1: so uh and otherwise simply people cannot reach, you know,
• 21:56
  Speaker 1: even even three meters it's already challenging, you know, so
• 22:00
  Speaker 1: and then uncomfortable and then probably not very secure six
• 22:03
  Speaker 1: meters it's impossible. So so from this viewpoint, we say,
• 22:10
  Speaker 1: in some cases we tell that one goal could be that, okay,
• 22:16
  Speaker 1: let's improve efficiency of people. But in some cases you
• 22:20
  Speaker 1: could tell that, okay, it's it's like let's build superhuman
• 22:24
  Speaker 1: or out at all. You know, I want to reach
• 22:25
  Speaker 1: like a giraph you know, this is the name. You know,
• 22:27
  Speaker 1: there's the logic I want to reach so high, so
• 22:32
  Speaker 1: you know, sometimes we are kidding that we should build
• 22:34
  Speaker 1: cheetah now, you know, to be super fast, you know,
• 22:37
  Speaker 1: and so on. So so I think it is really
• 22:40
  Speaker 1: you know, now when you see all the humanoids and
• 22:42
  Speaker 1: you know, the entire trend, sometimes people look at the
• 22:46
  Speaker 1: problem like like, let's let's be as good as as
• 22:49
  Speaker 1: humans and or people. And I'm like, okay, I want
• 22:52
  Speaker 1: to go further, you know, I want to reach higher,
• 22:54
  Speaker 1: I want to be faster. And ultimately that's yes, it's like,
• 22:59
  Speaker 1: let's built super humans, you know, and an autopicker, and
• 23:02
  Speaker 1: you have to some extent, you know, of course, it's
• 23:05
  Speaker 1: it has some superhuman capabilities, you know. And I think
• 23:08
  Speaker 1: that's where ah, it's it's different, you know. It's it's
• 23:13
  Speaker 1: not you are not you are not replacing labor. You
• 23:15
  Speaker 1: know you are. You are you have solution that is
• 23:18
  Speaker 1: simply better than the previous one. And of course the
• 23:22
  Speaker 1: side effect is that you replace some some labor. And
• 23:26
  Speaker 1: I think that's perfectly fine. You know. We you know,
• 23:29
  Speaker 1: now you have washing machine, you have you know, dishwasher,
• 23:32
  Speaker 1: you know, you have all those nations that are improving
• 23:34
  Speaker 1: your life and and and simply that progress. It's interesting
• 23:39
  Speaker 1: that you know, people will never stop, you know, me
• 23:42
  Speaker 1: definitely not. You know, like I it's kind of my
• 23:46
  Speaker 1: you know, like I have to do it. You know,
• 23:47
  Speaker 1: when I see that someone could be done better or
• 23:50
  Speaker 1: more efficient, I want to do it. And nothing's perfectly fine.
• 23:54
  Speaker 1: And as we as we just concluded in the previous topic,
• 23:59
  Speaker 1: it's kind of in hand, you know, like people don't
• 24:01
  Speaker 1: want to have those jobs. We have solutions that is
• 24:04
  Speaker 1: solving that problem. Okay, perfect, how is it? Well?
• 24:07
  Speaker 2: No, And you make an excellent point that you know,
• 24:10
  Speaker 2: as a society, we have automation to do the things
• 24:14
  Speaker 2: that we feel are drudgery. A dishwasher, a washing machine,
• 24:19
  Speaker 2: even a clothes dryer, which is even less prevalent because
• 24:24
  Speaker 2: a lot of people still use you know, lines to
• 24:26
  Speaker 2: dry their clothing. And but we do embrace those opportunities
• 24:31
  Speaker 2: to find the automation that releases us from having to
• 24:36
  Speaker 2: do the work that we don't want to do. And
• 24:38
  Speaker 2: I feel like that's what the statistics and the trends
• 24:41
  Speaker 2: are telling us in terms of warehouse labor, is people
• 24:44
  Speaker 2: aren't wanting to do this particular labor, so it makes
• 24:47
  Speaker 2: sense to have this automated solution. One thing I would question,
• 24:51
  Speaker 2: because we talked about it earlier in terms of a
• 24:54
  Speaker 2: disparity between different regions of the world different markets. For
• 24:59
  Speaker 2: one thing, in the UA, while we you know, do
• 25:01
  Speaker 2: have a forty percent turnover labor rate when it comes
• 25:04
  Speaker 2: to warehousing, we also have a ton of space. So
• 25:08
  Speaker 2: for companies looking to place a warehouse or a facility
• 25:12
  Speaker 2: in the US where they're going to manage their distribution,
• 25:16
  Speaker 2: they have square footage available to them at relatively reasonable cost.
• 25:20
  Speaker 2: I mean, there's always a cost, but the cost of
• 25:24
  Speaker 2: going out is typically a lot less than the cost
• 25:27
  Speaker 2: of going up. Now, in other areas of the world,
• 25:30
  Speaker 2: that's not as much of an option. We've got the
• 25:33
  Speaker 2: population density in Europe, we've got the Asian markets where
• 25:37
  Speaker 2: they're it's super dense, and so you know, when companies
• 25:42
  Speaker 2: are looking to have a fulfillment center near these largely
• 25:45
  Speaker 2: densely populated areas, they have to make this trade off.
• 25:49
  Speaker 2: First of all, they know that the people in the
• 25:51
  Speaker 2: cities are not as willing to do this type of labor,
• 25:54
  Speaker 2: and second, land availability is scarce, so going up makes
• 25:58
  Speaker 2: a lot more sense. And enter the giraffe and being
• 26:02
  Speaker 2: able to support that facility's aims and goals. So I
• 26:07
  Speaker 2: think when we talk about the concept of robots taking
• 26:11
  Speaker 2: jobs away from people, you know, what types of things
• 26:16
  Speaker 2: do you talk about with your clients when you're discussing
• 26:19
  Speaker 2: these types of technology implementations. You know, if there is
• 26:24
  Speaker 2: that pushback of you know, we don't want to take
• 26:27
  Speaker 2: jobs away from people, because that argument has to come
• 26:31
  Speaker 2: up more than once again.
• 26:33
  Speaker 1: Going back to the managers I was mentioning, I think
• 26:38
  Speaker 1: in many cases, maybe five six years ago it was
• 26:44
  Speaker 1: maybe a little different. But today I would say every
• 26:47
  Speaker 1: single manager I see or supply chain office here and
• 26:52
  Speaker 1: so on, I would say they are nobody's really discussing
• 26:56
  Speaker 1: if automation is kind of table or or efficient. I
• 27:02
  Speaker 1: would say we are probably over that period. And I
• 27:05
  Speaker 1: would say again going back to the hiring and training,
• 27:09
  Speaker 1: you know, we were not mentioning that all that trending necessary.
• 27:12
  Speaker 1: Then again, you know the guy is not showing up
• 27:15
  Speaker 1: and so on. So so I would say, it is
• 27:17
  Speaker 1: forcing almost everybody into into automation. And isn't that I
• 27:24
  Speaker 1: think again, maybe maybe ten years ago, five years ago technologies,
• 27:31
  Speaker 1: maybe we're not so major it was not so clear.
• 27:33
  Speaker 1: Today you can count it probably probably hundreds of thousands
• 27:38
  Speaker 1: of robots in their houses. Uh, you know Amazon itself,
• 27:45
  Speaker 1: it's it's already one million if I remember correctly. You know,
• 27:47
  Speaker 1: it's kind of funny. They are one of the largest
• 27:50
  Speaker 1: manufacturers of robots in the world, you know, Amazon, but
• 27:54
  Speaker 1: if you count all the rest, you know, including US,
• 27:57
  Speaker 1: it is already hundreds of towns of robots. And simply
• 28:01
  Speaker 1: it's proven. I feel that there's very little arguments against
• 28:07
  Speaker 1: the automation. And and even even again, maybe five years ago,
• 28:14
  Speaker 1: probably common row I was sometimes maybe even ten years
• 28:19
  Speaker 1: when when it was very complex, you know, big automation,
• 28:23
  Speaker 1: but probably it was suitable for maybe twenty years, so
• 28:26
  Speaker 1: it's okay. Then then people started to develop more kind
• 28:30
  Speaker 1: of compact quickly to deploy solutions and and and I
• 28:35
  Speaker 1: think that also plus, you know, like technological component motors
• 28:39
  Speaker 1: PLC is whatever, any any of those components, they are
• 28:42
  Speaker 1: cheaper riders. All of that is going down. And that
• 28:46
  Speaker 1: really means that today you can really get I would
• 28:49
  Speaker 1: say three years is in many cases simple, two years,
• 28:52
  Speaker 1: it is feasible in many cases. Plus you have robotics
• 28:56
  Speaker 1: as a service, you know, which is kind of in
• 28:58
  Speaker 1: mediate ROI from some point. So all of that I
• 29:01
  Speaker 1: would say, I really, I'm struggling to find, you know,
• 29:04
  Speaker 1: some some real arguments. I think. Still sometimes it's really
• 29:09
  Speaker 1: like it integration, you know, because it's for some reason
• 29:12
  Speaker 1: sometimes companies struggle with them. And and maybe still it
• 29:17
  Speaker 1: takes some time and some effort, and and and I
• 29:20
  Speaker 1: would say there's still some small risks connected to that.
• 29:23
  Speaker 1: I would say, it's pretty small. I like, we have
• 29:28
  Speaker 1: very good experience, you know, so so I do. But
• 29:30
  Speaker 1: but I understand, I understand that someone who never did
• 29:33
  Speaker 1: any automation, he he can still see automation as some
• 29:37
  Speaker 1: kind of risk. It's it's perfectly fun. And you know
• 29:39
  Speaker 1: that's why we are here, you know, as other other
• 29:42
  Speaker 1: players in the industry to convince them. But again, I
• 29:46
  Speaker 1: and you know, what I wanted to tell is that, honestly,
• 29:50
  Speaker 1: I haven't heard someone telling me that what we will
• 29:53
  Speaker 1: do like there was there was one case where it
• 29:58
  Speaker 1: was more like, let's really talk about you know, ergonomics,
• 30:03
  Speaker 1: you know, how to make it comfortable, how to and
• 30:06
  Speaker 1: all these I would say, they still deeply care about
• 30:10
  Speaker 1: the employees, you know that that is still perfectly fun.
• 30:12
  Speaker 1: And I would say, this is this is probably something
• 30:15
  Speaker 1: that we should solve. So long term, you know, like
• 30:19
  Speaker 1: like it should be still very very human or you know,
• 30:23
  Speaker 1: it should be and and I mean the collaboration, the
• 30:28
  Speaker 1: kind of kind of that feeling, you know, because you know,
• 30:30
  Speaker 1: we don't want people to be seen as a you know,
• 30:33
  Speaker 1: s kind of you know, terminator whatever you know it
• 30:36
  Speaker 1: should be. You know, ideally it is perceived as Okay,
• 30:40
  Speaker 1: this is helping me, is helping company. Uh, you know,
• 30:44
  Speaker 1: it's it's making that company probably more profitable, so probably
• 30:47
  Speaker 1: my job is maybe even more safe, and so on
• 30:50
  Speaker 1: and so on. I would say that's we need to
• 30:53
  Speaker 1: create good perception. But I think it's it's it's perfectly fun.
• 30:55
  Speaker 1: You know, over over the last five years, as I said,
• 31:00
  Speaker 1: it's default, and people really are not questioning aut to
• 31:04
  Speaker 1: mention anymore.
• 31:06
  Speaker 2: Yeah, I think I've seen that as well, where the
• 31:10
  Speaker 2: idea of automation is less controversial in that regard because
• 31:16
  Speaker 2: it's not so much about the people, although you know,
• 31:19
  Speaker 2: we do want to make sure that people are employed. However,
• 31:23
  Speaker 2: I think one of the things that you just brought up,
• 31:25
  Speaker 2: and it kind of leads into my next question, is
• 31:28
  Speaker 2: how can companies use those robotics as part of a
• 31:30
  Speaker 2: broader labor strategy. So they're not just hiring those entry
• 31:35
  Speaker 2: level unskilled workers, but now they're looking to attract and
• 31:40
  Speaker 2: retain talent that can help move their organization forward toward
• 31:44
  Speaker 2: their own goals. So you were mentioning it being, you know,
• 31:48
  Speaker 2: an area where a lot of times that could be
• 31:50
  Speaker 2: the sticking point in getting an automated solution is having
• 31:54
  Speaker 2: the IT infrastructure in place. And this opens up the
• 31:57
  Speaker 2: opportunity for skilled individuals who who have these capabilities to
• 32:02
  Speaker 2: be able to come in and work alongside these technologies
• 32:06
  Speaker 2: in order to move the organization further, you know, in
• 32:10
  Speaker 2: their own aims. So what other parts of you know,
• 32:15
  Speaker 2: or what other areas can people be working alongside these
• 32:19
  Speaker 2: these technologies in these facilities. That's going to open up
• 32:22
  Speaker 2: the labor market for these companies exactly.
• 32:26
  Speaker 1: You know, that's a great question, right. I like this
• 32:28
  Speaker 1: one because you know, in many cases I talk about
• 32:30
  Speaker 1: it that you know, I'm really convinced that in the future,
• 32:34
  Speaker 1: one of the top positions, top jobs we will see
• 32:37
  Speaker 1: is you know, robot maintenance, robot technician. You know, even
• 32:42
  Speaker 1: today we have many of them, and and and simply
• 32:45
  Speaker 1: it's you know, it's like a manager of robots you know,
• 32:50
  Speaker 1: if you want to talk in human language or how
• 32:53
  Speaker 1: And partially it's it's really operational, you know, how to
• 32:56
  Speaker 1: help those robots to solve potentially something that is you know,
• 33:00
  Speaker 1: complicated or or kind of like h case that they
• 33:04
  Speaker 1: have never seen. You know. It's all also connected to
• 33:07
  Speaker 1: all the AI. You know, AI is working, works you
• 33:10
  Speaker 1: know very well. You know it like we do all
• 33:12
  Speaker 1: the picking. There's a lot of things where where you
• 33:15
  Speaker 1: can use it. But still, you know, I remember cases
• 33:18
  Speaker 1: where I don't know, we have seen you know, it
• 33:23
  Speaker 1: was a box and usually we are looking for a
• 33:26
  Speaker 1: box with AI, you know, and it worked very well.
• 33:28
  Speaker 1: But sometimes I have seen pictures where the box was
• 33:31
  Speaker 1: flipped and there was a lot of carrot, you know,
• 33:33
  Speaker 1: the green carrot, and like, yes, AI was a little
• 33:36
  Speaker 1: confused that you know, doesn't look like a box, you know.
• 33:39
  Speaker 1: So then then you have to then you have to
• 33:41
  Speaker 1: kind of employ someone who is really kind of solving
• 33:45
  Speaker 1: all the EDU cases. And exactly as you said, it's
• 33:47
  Speaker 1: it's it's a little different, you know, probably you know
• 33:50
  Speaker 1: kind of maybe it's like more value for the employee,
• 33:55
  Speaker 1: more valued for the employee, and I think it's seriously,
• 33:59
  Speaker 1: if you take you warehouses. They are well structured, and
• 34:03
  Speaker 1: that is one of the reasons why automation is strong.
• 34:07
  Speaker 1: They're automotively historically you or very strong. But we will
• 34:10
  Speaker 1: see more and more in potentially you know, restaurants everywhere,
• 34:15
  Speaker 1: like probably everywhere. When with human it's even more. But
• 34:17
  Speaker 1: it's still the same, you know, self drawing cars. It's
• 34:21
  Speaker 1: just different type of robot. You know, it's exactly the
• 34:23
  Speaker 1: same guys in Google and everywhere. They are solving exactly
• 34:26
  Speaker 1: the same issues as we are, you know, and there's
• 34:29
  Speaker 1: usually uh, you know, someone behind the scenes, probably probably
• 34:34
  Speaker 1: kind of managing entire fleet or fleet of fleets, you know,
• 34:38
  Speaker 1: or and on and on. So there's someone who is
• 34:40
  Speaker 1: helping those robots. Not always you know, like in many
• 34:43
  Speaker 1: cases not needed. In many cases it's simple, but sometimes
• 34:46
  Speaker 1: you have to do it. And I think that is
• 34:51
  Speaker 1: how do they like if someone would tell me that
• 34:54
  Speaker 1: that this would happen, you know, when I was a child, like, yes,
• 34:57
  Speaker 1: robot technicians would be potentially one of the top job.
• 35:00
  Speaker 1: It's actually pretty cool. I know that is valuable job,
• 35:04
  Speaker 1: and I really hope that it will actually happen, you know,
• 35:07
  Speaker 1: from this viewpoint. And so there's and it's so operational,
• 35:11
  Speaker 1: then there's more like you know, spare parts, maintenance and
• 35:16
  Speaker 1: all these so that is even more potentially technical and
• 35:19
  Speaker 1: that is also needed. You know, it's still mechanics, it's
• 35:22
  Speaker 1: still you know, electric you know, electrical things and so on.
• 35:26
  Speaker 1: So so there's a lot of things that can over
• 35:29
  Speaker 1: time be replaced. You know, it's like all the predictive
• 35:32
  Speaker 1: maintenance and you could and there's a lot of these,
• 35:35
  Speaker 1: and I think even now it's happening. You know, all
• 35:39
  Speaker 1: all the companies that have such a technicians you and
• 35:41
  Speaker 1: we have them. And again I think it's pretty cool.
• 35:44
  Speaker 1: And you know, for larger customers, I actually expect that
• 35:48
  Speaker 1: we have those that they are solving these, you know,
• 35:50
  Speaker 1: for smaller customers, we provide the service. So I think
• 35:54
  Speaker 1: from this viewpoint, it is on the operational side and
• 35:59
  Speaker 1: also on the technical side, and it's creating a lot
• 36:01
  Speaker 1: of having very attractive jobs. You know, you are working
• 36:05
  Speaker 1: with cutting technology and and and you know, helping building
• 36:10
  Speaker 1: those you know, you could imagine that now you see
• 36:14
  Speaker 1: auto picker to two point oh, you know, that's how
• 36:16
  Speaker 1: we call it. But fundamentally it is revision number eight
• 36:21
  Speaker 1: maybe or something like that. You could eveine. We were
• 36:23
  Speaker 1: improving that over time. Now, so there's still as I said,
• 36:29
  Speaker 1: it's not only me, you know, is the entire company
• 36:31
  Speaker 1: an anti industry. Everybody is hunting efficiency. Everybody wants to
• 36:35
  Speaker 1: push that that that innovation further, and and that is
• 36:38
  Speaker 1: also creating you know, a lot of interesting opportunities. So yeah,
• 36:43
  Speaker 1: as I told you, robot technician will be as common
• 36:47
  Speaker 1: as as you know, plumber or or or I don't know,
• 36:50
  Speaker 1: like like electrician you know in your house. It's it's
• 36:53
  Speaker 1: it's the same.
• 36:54
  Speaker 2: I agree, And I think one of the things that
• 36:56
  Speaker 2: that draws an interesting parallel here if we look back
• 36:59
  Speaker 2: at not necessarily distribution centers, but if we look at
• 37:04
  Speaker 2: production and we look back historically over the last hundred
• 37:07
  Speaker 2: years of what that workforce looked like in a production facility.
• 37:11
  Speaker 2: We had you know, people usually men who were in
• 37:15
  Speaker 2: these facilities, and they were you know, the engineers or
• 37:18
  Speaker 2: the repair guys, or the guys who worked on the machines.
• 37:21
  Speaker 2: And it wasn't robotic, but it was mechanical, and so
• 37:26
  Speaker 2: you know, they were the ones who were in charge
• 37:28
  Speaker 2: of maintaining this equipment and making sure that it worked throughout.
• 37:31
  Speaker 2: You know, the industrial boom in the twentieth or nineteenth
• 37:36
  Speaker 2: and twentieth centuries. So I think that this is just
• 37:40
  Speaker 2: the next evolution of that, where we're working on a
• 37:43
  Speaker 2: different type of machine. Maybe there's a different skill set needed,
• 37:46
  Speaker 2: but the crux of the matter is still the same
• 37:49
  Speaker 2: that we still need those individuals to help with industry.
• 37:53
  Speaker 2: It's not a replacement. It's simply a shift in roles
• 38:00
  Speaker 2: a little bit or a shift in responsibility that instead
• 38:03
  Speaker 2: of doing the function of the machine, they're maintaining the
• 38:07
  Speaker 2: machine so the machine can do the function and be
• 38:09
  Speaker 2: more efficient at it and safer because if the machine
• 38:13
  Speaker 2: is going up and picking up these heavy items, for instance,
• 38:16
  Speaker 2: you're you're mentioning the size of these pickers, they can
• 38:19
  Speaker 2: pick something that is much larger than a human or
• 38:22
  Speaker 2: even a team of humans could do safely on a
• 38:26
  Speaker 2: repeated basis.
• 38:28
  Speaker 1: No, imagine forklift. You know, it's some kind of robot
• 38:31
  Speaker 1: from some viewpoint, you know of because you are usually
• 38:34
  Speaker 1: in control. They are also cell driving forklift, But ultimately
• 38:38
  Speaker 1: it's it's superhuman you know lifting, you know two tone ballet,
• 38:42
  Speaker 1: you know easily and yes, there's a I think from
• 38:47
  Speaker 1: some new point it's exactly the same as industry or revolution.
• 38:50
  Speaker 1: You know, there's like something that I think we should
• 38:54
  Speaker 1: study is kind of speed of change because with ailet's
• 39:00
  Speaker 1: much robotics, robotics is I think let's go it slow
• 39:04
  Speaker 1: enough for now, you know, But but I think AI
• 39:06
  Speaker 1: AI and and kind of software improvement software robots, you
• 39:12
  Speaker 1: know agents, those are software robots, you know. I think
• 39:15
  Speaker 1: that could be that could be quite fast. You know,
• 39:18
  Speaker 1: it's not the topic of today's discussions, but I like
• 39:21
  Speaker 1: to talk about it because I feel that, you know, what,
• 39:25
  Speaker 1: what if Microsoft Excel will be suddenly or people will
• 39:30
  Speaker 1: be suddenly five times faster, do we need all of
• 39:32
  Speaker 1: those people working with Excel spreadsheets? Maybe no, you know. So,
• 39:37
  Speaker 1: so I think this digital revolution actually could be because
• 39:40
  Speaker 1: in many cases people talk about robotics and how how
• 39:43
  Speaker 1: how you know, how they are worried about the labor
• 39:46
  Speaker 1: I would say I wouldn't be worried about that one
• 39:48
  Speaker 1: that you know that that is that is slow enough
• 39:50
  Speaker 1: from some viewpoint. But but but here I think it
• 39:53
  Speaker 1: could be pretty quick and people have to think about it. Well.
• 39:57
  Speaker 2: I think we have a great outlook on what the
• 40:00
  Speaker 2: labor market is going to be looking like and how
• 40:03
  Speaker 2: robotics and automation will will play a role in that.
• 40:07
  Speaker 2: Let's say that labor availability continues to shrink, We're facing
• 40:11
  Speaker 2: these same issues in the next five years. So what
• 40:15
  Speaker 2: role will the autopicker two point zero the giraffe play
• 40:19
  Speaker 2: in ensuring resilience and that operational continuity through you know
• 40:25
  Speaker 2: hills and valleys of that labor uh shortage availability ups
• 40:32
  Speaker 2: and downs. How are how our business is going to
• 40:34
  Speaker 2: achieve continuity with this type of technology?
• 40:37
  Speaker 1: From many viewpoints, you could tell that humans are extremely flexible,
• 40:43
  Speaker 1: you know, the most flexible you can get. You know
• 40:46
  Speaker 1: that that is with robotics. I think you have to
• 40:51
  Speaker 1: understand the system to some extent. But if you understand it,
• 40:54
  Speaker 1: then you can you can you are probably safer and
• 40:58
  Speaker 1: and kind of kind of each just easier to predict
• 41:01
  Speaker 1: because you know, if you know the system next time
• 41:04
  Speaker 1: is doing the same what it did yesterday, you know,
• 41:07
  Speaker 1: there's no surprises mostly no surprises. And and there are
• 41:11
  Speaker 1: you know, features like for example, we introduced last year.
• 41:14
  Speaker 1: We call it overnight picking. So there are some human
• 41:18
  Speaker 1: pickable items, but okay, we can pick them in the morning.
• 41:22
  Speaker 1: You know, when pickers are coming to the to the
• 41:25
  Speaker 1: G two P stations, but all the robotic pickable items
• 41:28
  Speaker 1: in many cases, you know, like we have seen examples
• 41:31
  Speaker 1: where it's ninety five percent. We see examples when it's
• 41:34
  Speaker 1: sixty five percent. You know, typically I would say, let's
• 41:36
  Speaker 1: say seventy seventy five percent it's robot pickable. We can
• 41:40
  Speaker 1: still run those robots overnight, and you could imagine this
• 41:43
  Speaker 1: is helping you quite a lot, you know, suddenly in
• 41:46
  Speaker 1: the morning, potentially let's say, I know, sixty seventy percent
• 41:50
  Speaker 1: of the job is done. From some viewpoints, you know,
• 41:52
  Speaker 1: you just kind of top all the all the all
• 41:55
  Speaker 1: the orders with the human peaks. So there's there's a
• 41:58
  Speaker 1: lot of tricks that and you know that is really
• 42:01
  Speaker 1: lights out the warehouse, you know, during the night, like
• 42:03
  Speaker 1: there's potentially zero people, you know. So so from this viewpoint,
• 42:06
  Speaker 1: I think this is giving you again some kind of superpower,
• 42:10
  Speaker 1: you know, and as we know that it is very
• 42:13
  Speaker 1: common super power of robots. Yes, they can work free shifts,
• 42:18
  Speaker 1: and they are not you know, kind of peace or
• 42:20
  Speaker 1: how to tell it. You know, they are not angry,
• 42:22
  Speaker 1: they are not you know, they're very happy with with it.
• 42:27
  Speaker 1: Of course, there are some weird or something you know, yes,
• 42:30
  Speaker 1: but but still that is very very small text you
• 42:33
  Speaker 1: have to pay for having, you know, potentially potentially lights
• 42:38
  Speaker 1: out the warehouse over free shifts. Yes, that is you know,
• 42:41
  Speaker 1: I would say, still we are not there. You know,
• 42:42
  Speaker 1: you need still someone there. But I think I think,
• 42:47
  Speaker 1: like again, if you know the tool, you can use
• 42:50
  Speaker 1: it very well, and probably you are you are, it's
• 42:53
  Speaker 1: much safer and and and also also you mentioned you
• 42:57
  Speaker 1: know ups and downs, so I think easily what can
• 43:00
  Speaker 1: happen is that for some reason the season is not
• 43:05
  Speaker 1: as good as we expected and so on. So then
• 43:07
  Speaker 1: there's this is more like a business innovation. I would
• 43:10
  Speaker 1: call it. You know, all the robotics as as service
• 43:12
  Speaker 1: and all these, but you have sometimes, you know, pretty
• 43:15
  Speaker 1: good flexibility. You can tell that, Okay, I'm going to
• 43:18
  Speaker 1: rent additional ten robots. Now, you know you can probably
• 43:22
  Speaker 1: if you if you estimate at least somehow well, you
• 43:25
  Speaker 1: can pretty much match your your rate, you know. And
• 43:30
  Speaker 1: and in principle you know another thing above the rate,
• 43:33
  Speaker 1: probably you overpaid. So if you are able to exactly
• 43:37
  Speaker 1: match that curve over the entire year, let's say, yes,
• 43:41
  Speaker 1: you are saving money, you know, because because probably you
• 43:45
  Speaker 1: you can predict let's say three months period should be okay,
• 43:49
  Speaker 1: you see some trend and that really means that, yes,
• 43:53
  Speaker 1: you are again saving and kind of your company is
• 43:57
  Speaker 1: more robust. You know you you you are not you
• 44:00
  Speaker 1: are paying for their performance you really needed. You're probably
• 44:04
  Speaker 1: or abidized slightly better. Great.
• 44:07
  Speaker 2: Yeah, and I so I've been in a facility that
• 44:10
  Speaker 2: you're talking about where they're they've got the picking taking place,
• 44:13
  Speaker 2: the robotic picking taking place at night, and then the
• 44:16
  Speaker 2: workers arrive in the morning and they've, like you said,
• 44:18
  Speaker 2: sixty percent of the work is done. All they have
• 44:21
  Speaker 2: to do is finish off the processing of these orders
• 44:24
  Speaker 2: and you know, get them over to you know, whether
• 44:26
  Speaker 2: it's it's cartonizing or palletizing these orders, you know, getting
• 44:30
  Speaker 2: them sent out. But all of the heavy work is done,
• 44:34
  Speaker 2: and so then you've got the humans for the more
• 44:36
  Speaker 2: dynamic things, the things that need a thinking, breathing person
• 44:41
  Speaker 2: paying attention to this order. Because you know, that's I
• 44:45
  Speaker 2: think there's a balance there when it comes to robotics
• 44:48
  Speaker 2: and automation within these types of facilities. Is when when
• 44:51
  Speaker 2: companies are trying to find a solution to solve whatever
• 44:56
  Speaker 2: problem in their facility, one of the things that they're
• 44:59
  Speaker 2: always trying to do is improve their customer satisfaction. At
• 45:03
  Speaker 2: the bottom of everything is serving their customers better and
• 45:07
  Speaker 2: more efficiently. And sometimes efficiency is not the better solution.
• 45:13
  Speaker 2: Sometimes you need more hands on human customer service. And
• 45:17
  Speaker 2: I think that this hybrid approach of having robots picking
• 45:22
  Speaker 2: throughout you know, a third shift or even a second
• 45:24
  Speaker 2: shift when it's more expensive to have humans on site,
• 45:29
  Speaker 2: this is a great way to show how that can
• 45:32
  Speaker 2: balance you maintain your your customer service rigor and having humans,
• 45:38
  Speaker 2: you know, participating in the in the work that's being done,
• 45:43
  Speaker 2: but you leave a lot of the heavy, repeatable and
• 45:46
  Speaker 2: non value add to the technology that's capable of achieving that,
• 45:53
  Speaker 2: and freeing up your human capital for the things where
• 45:56
  Speaker 2: humans are truly required.
• 45:59
  Speaker 1: I just came to my mind, you know, for example,
• 46:01
  Speaker 1: misspeaks with humans, it's it's it's very difficult to make
• 46:06
  Speaker 1: sure that you are not sending wrong items to the customers,
• 46:11
  Speaker 1: and and again it's a training and so on and
• 46:14
  Speaker 1: so on. But just again, we are not machines. We
• 46:17
  Speaker 1: do mistakes, you know, and it's it's natural, you know,
• 46:19
  Speaker 1: when you pick item number ten thousand in the given day. Yes,
• 46:23
  Speaker 1: it's okay to do a mistake, you know, it's perfectly fine.
• 46:26
  Speaker 1: But again here, you know, we have seen customers who
• 46:30
  Speaker 1: were able to improve these by some combination, you know,
• 46:34
  Speaker 1: and and robots in principle they do very little systematic
• 46:41
  Speaker 1: mistakes or how to tell, you know, they are not
• 46:42
  Speaker 1: going to pick wrong items. But we have seen, you know,
• 46:45
  Speaker 1: things like there are two boxes glued together, so we
• 46:49
  Speaker 1: pick one, the one is below so you don't even
• 46:52
  Speaker 1: see it, so you actually pick two, you know, you
• 46:55
  Speaker 1: do double pick yes, and then pecker, you know, picker
• 46:59
  Speaker 1: probably can understand, Okay, this looks a little suspicious. You know,
• 47:02
  Speaker 1: it's two boxes good together, so he's checking and probably
• 47:05
  Speaker 1: you know, fixing that. And ultimately we have seen that
• 47:08
  Speaker 1: easily people can do four to five times lower amount
• 47:12
  Speaker 1: of misspeaks, which is a big deal if you know
• 47:15
  Speaker 1: all the returns and all the costs. The reality to that,
• 47:18
  Speaker 1: and plus I would say even probably bigger piece of
• 47:21
  Speaker 1: it is that your customer is not a happy emailer.
• 47:23
  Speaker 1: So from this viewpoint, I would say it's obvious choice,
• 47:27
  Speaker 1: you know, like, there's there's no better combination.
• 47:30
  Speaker 2: So beyond automation, which we've talked about, a lot today.
• 47:34
  Speaker 2: What strategies do you see some of these companies using
• 47:37
  Speaker 2: to mitigate the labor challenges over the next five to
• 47:40
  Speaker 2: ten years besides robotic picking.
• 47:44
  Speaker 1: That I think the difficult question because I would naturally
• 47:48
  Speaker 1: answer that, you know, automated one more. But but I
• 47:52
  Speaker 1: would say that exactly as we already told it. I
• 47:56
  Speaker 1: think if there's any chance to attract better talent, it
• 48:02
  Speaker 1: will always help that company, you know, Like I'm always
• 48:04
  Speaker 1: telling that that, you know, there's I'm always telling everybody
• 48:08
  Speaker 1: like hire ten out ten out of ten. You know,
• 48:11
  Speaker 1: people you know like that, if you hire nine out
• 48:14
  Speaker 1: of ten, you are still perfectly fine, you know, but
• 48:16
  Speaker 1: but you have to have that very high standard. And
• 48:18
  Speaker 1: I think this is very important also for the future
• 48:22
  Speaker 1: that you know, technology and AI is going to penetrate
• 48:29
  Speaker 1: more and more. It's it's super clear. And and I
• 48:32
  Speaker 1: think having that talent that that can utilize these tools
• 48:36
  Speaker 1: automation AI, you know, better w M as anything connected
• 48:41
  Speaker 1: to these, I think that is what is going to
• 48:44
  Speaker 1: grow those companies. And and and ultimately it is competitive market.
• 48:50
  Speaker 1: You know, they you know, three pls, all of them,
• 48:53
  Speaker 1: like they have to they have to have the best
• 48:56
  Speaker 1: customer service, the fastest possible fulfillment, you know, all of
• 48:59
  Speaker 1: those parts. It's clear that you know, in ten years,
• 49:04
  Speaker 1: I can easily imagine that you would expect the Amazon
• 49:08
  Speaker 1: in five hours. I think it will happen, you know,
• 49:11
  Speaker 1: probably not the entire portfolio, but I think it will happen,
• 49:14
  Speaker 1: probably maybe even three hours. And companies will need a
• 49:21
  Speaker 1: kind of kind of you know, people who can utilize
• 49:25
  Speaker 1: those tools. And I think I would always recommend that
• 49:30
  Speaker 1: that you know, it is it is not so simple
• 49:33
  Speaker 1: to attract the talent, but you have to do anything
• 49:36
  Speaker 1: you can to get the best talent. I would say
• 49:38
  Speaker 1: that that is the best guidance.
• 49:40
  Speaker 2: I guess well, I agree. Thank you so much John
• 49:44
  Speaker 2: for joining us today for this discussion. As labor pressures persist,
• 49:48
  Speaker 2: the future of warehousing will hinge on finding that ideal
• 49:51
  Speaker 2: balance between human talent and intelligent automation. So thank you
• 49:56
  Speaker 2: for showing us how some of these innovations and technology
• 49:59
  Speaker 2: can ease today's workforce challenges while building stronger and more
• 50:03
  Speaker 2: resilient operations for the future. To our listeners, if you
• 50:06
  Speaker 2: found today's episode valuable, be sure to hit the subscribe
• 50:09
  Speaker 2: button so you never miss an episode and If you're
• 50:11
  Speaker 2: interested in being a guest on our show, you can
• 50:13
  Speaker 2: reach me at podcast at meboch dot com at any time.
• 50:17
  Speaker 2: Thanks for listening to speaking of supply chain