Latest / Speaking of Supply Chain / Cut Costs, Boost Productivity: AI’s Role in Modern Warehousing

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Cut Costs, Boost Productivity: AI’s Role in Modern Warehousing · Speaking of Supply Chain

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Speaker 1: You're listening to Speaking of Supply Chain, a meeboch podcast.
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Speaker 1: This is a show for logistics professionals looking to learn
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Speaker 1: more about the latest innovations in supply chain. Each episode
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Speaker 1: will feature a conversation on topics such as mitigating supply
0:19
Speaker 1: chain disruption and reducing risk, current automation trends, sustainability initiatives,
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Speaker 1: and more. Let's dive right in.
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Speaker 2: Hello, and welcome to Speaking of Supply Chain, where we
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Speaker 2: explore trends, current events, and innovations impacting the logistics and
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Speaker 2: supply chain industries. I'm your host, Ellen Wood. In today's
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Speaker 2: rapidly evolving warehouse and distribution landscape, operations grapple with significant changes,
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Speaker 2: including labor shortages and escalating operational costs. Recent statistics reveal
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Speaker 2: that labor expenses can constitute up to sixty five percent
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Speaker 2: of a warehouse's total budget. To address these pressing issues,
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Speaker 2: labor management solutions like labor ai offer advanced tools designed
1:05
Speaker 2: to optimize labor efficiency and productivity. In this episode, we're
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Speaker 2: going to explore how this tool can help warehouses navigate
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Speaker 2: the complexities of modern operations. And to join me for
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Speaker 2: the discussion is laborai founder Lee Rector. Welcome Lee, great
1:20
Speaker 2: to have you.
1:21
Speaker 3: Thank you Ellen.
1:22
Speaker 2: All right, So let's get to our topic today, which
1:25
Speaker 2: is your tool labor AI. So can you share the
1:29
Speaker 2: origin story? How did this all come about?
1:31
Speaker 3: Well, I'd been in the industry for well over thirty
1:35
Speaker 3: years and over the last we'll call it fifteen years.
1:40
Speaker 3: Part of the problem in the industry from a technical
1:42
Speaker 3: point of view, is that we were building we'll call
1:46
Speaker 3: it management systems, whether it's WS or LMS, labor to
1:50
Speaker 3: manage labor, and the cost of implementing those systems was
1:55
Speaker 3: actually outstripping the benefit, and.
1:58
Speaker 4: So essentially the services were four to five to one
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Speaker 4: for the cost of the software, which made it punitive
2:06
Speaker 4: for any company to actually try and install it, and
2:08
Speaker 4: then to try and get an ROI on.
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Speaker 3: That was very difficult, and only one percent of the
2:14
Speaker 3: companies could actually afford that risk. Going back to twenty fifteen,
2:20
Speaker 3: I had already envisioned a simpler system by building the
2:26
Speaker 3: engineering sort of all the services already into the software. So,
2:30
Speaker 3: rather than pay for a system that enabled an engineer
2:34
Speaker 3: to put in values, what if we were to pre
2:36
Speaker 3: populate a solution with engineered values. So we started that model.
2:43
Speaker 3: I started, took a hiatus on that through acquisitions and
2:47
Speaker 3: companies growing and things like that, and in twenty twenty
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Speaker 3: two I decided that I would revisit that and build
2:53
Speaker 3: it as a new way of handling labor. And our
2:58
Speaker 3: model was to build it, make it affordable and applicable
3:02
Speaker 3: to essentially any company on the planet, whether you are
3:04
Speaker 3: a small mother and poshop or you know you're one
3:07
Speaker 3: of the largest companies on the planet. Make it scalable.
3:11
Speaker 3: And the only way to do that was to make
3:13
Speaker 3: engineering essentially at a base rate that it didn't matter.
3:18
Speaker 3: So if you take a look at our standards, we
3:21
Speaker 3: actually have almost one thousand standards in our database. Now.
3:25
Speaker 3: The standard for stepping on the fork is stepping off
3:27
Speaker 3: the fork, which is as low as you can get
3:31
Speaker 3: in terms of a task. But at one point six seconds,
3:35
Speaker 3: whether I'm in the US, I'm in Asia, or I'm
3:38
Speaker 3: in Europe. You know, if I'm asure then maybe they're
3:41
Speaker 3: a little bit shorter, it's one point six to two seconds,
3:44
Speaker 3: and in Germany, because they're a little bit taller, it's
3:46
Speaker 3: one point five to eight. At one point six seconds,
3:50
Speaker 3: that change that differential is so nominal that we've taken
3:55
Speaker 3: out sort of all the swings and averages from side
3:58
Speaker 3: to side around the globe. And so by building a
4:01
Speaker 3: database that is at that level of elemental side and
4:05
Speaker 3: we build things up, we are now able to translate
4:09
Speaker 3: that to whether you're a company that's got a full
4:11
Speaker 3: blown LMS or you are just you know, you're running
4:15
Speaker 3: almost like a garage type operation. You've got three people
4:18
Speaker 3: in the back, and we can then calculate the tasks
4:21
Speaker 3: on that. So the idea was to make a universal solution,
4:25
Speaker 3: but then make it scalable so that it's attractive enough
4:28
Speaker 3: to the top one hundred or two hundred companies on
4:31
Speaker 3: the planet that it would replace their their thought process
4:36
Speaker 3: of building a full LMS. So we've now got to
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Speaker 3: the point where labor Ai is enterprise as well as standalone.
4:45
Speaker 3: And for a company, you know, a large global operation,
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Speaker 3: they could get up and running once the API is
4:53
Speaker 3: built in five days so and get calibrated results. We've
5:00
Speaker 3: just recently done a blind study with another company that
5:03
Speaker 3: has an LMS system. They pay well over six figures
5:07
Speaker 3: for that operation, and within a day and a half
5:10
Speaker 3: we calibrated our solution to their solution. Their standards are
5:15
Speaker 3: set at eighty five percent, and our software came back
5:18
Speaker 3: and calculated at eighty three point two. So having something
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Speaker 3: that's accurate and quick to get up and running is
5:26
Speaker 3: far more applicable in today's market than something that's being
5:29
Speaker 3: precise that takes you months and months and months of
5:32
Speaker 3: services to get up and running to get to the
5:35
Speaker 3: same answer.
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Speaker 1: Right.
5:37
Speaker 2: So that reminds me of a saying that one of
5:40
Speaker 2: my mentors used to say, good enough today is better
5:43
Speaker 2: than perfect tomorrow.
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Speaker 3: Yeah, and Hunderd touch cheaper.
5:48
Speaker 2: It sounds yeah, it sounds like your solution is quick
5:53
Speaker 2: to implement, which I can see essentially a great benefit
6:01
Speaker 2: to that. But I know that there are you know,
6:04
Speaker 2: individuals out there who are going to question, if it's
6:07
Speaker 2: that easy, what are we missing with that increasing complexity
6:11
Speaker 2: with those operations? You know, when you scale up, we're
6:14
Speaker 2: experiencing labor shortages right now, you know, across across the industry,
6:18
Speaker 2: all over the place. So how can it assist these
6:23
Speaker 2: warehouse managers forecasting those labor needs if it's so easy
6:28
Speaker 2: and quick to do it? Like, how accurate are we
6:31
Speaker 2: are we able to get?
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Speaker 3: How accurate? I always use the term it's how long
6:34
Speaker 3: it's a piece of string because there's really no answer
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Speaker 3: to how accurate. But if we're within two percent of actual,
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Speaker 3: you can make a management decision on that. And how
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Speaker 3: easy is it? Well, typically our model you would run
6:50
Speaker 3: the software, You would run a model today for tomorrow's
6:54
Speaker 3: work profile, so we would tell you how many hours
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Speaker 3: of labor you have where those people need to work.
7:01
Speaker 3: So you know, if we look at typical, where else
7:03
Speaker 3: I've got people. In receiving, I've got people and put away, picking,
7:07
Speaker 3: replan so and then all that we'll call it the
7:10
Speaker 3: subcategories of that. I'm picking units, versus cases, versus pallettes
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Speaker 3: and things like that. We would then come back and
7:15
Speaker 3: say you need one hundred and sixty four hours worth
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Speaker 3: of labor tomorrow, and in that you need twenty four
7:22
Speaker 3: hours in receiving, you need thirty two hours and thirty
7:25
Speaker 3: three point seven hours in picking and such, so that
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Speaker 3: you could build your labor plan for tomorrow now, because
7:33
Speaker 3: we're using AI in the software as well. The AI
7:36
Speaker 3: the more models you run, So if you run this
7:38
Speaker 3: daily over the next six months, Let's say we set
7:41
Speaker 3: our target standard at seventy five percent, so a modest level,
7:45
Speaker 3: and then what would happen is our software would learn
7:48
Speaker 3: as you approach to be continuably at seventy five percent,
7:52
Speaker 3: so in other words, I'm not using more or less.
7:54
Speaker 3: Then the software then would actually micro size raise your
8:00
Speaker 3: your levels. Like flying an airplane. You make small moves
8:03
Speaker 3: so that at the end of the year, your standard
8:05
Speaker 3: that you're actually working toward is considerably higher than where
8:08
Speaker 3: it was. Maybe it's three percent, maybe it's thirteen percent.
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Speaker 3: But what happens is by making small changes to the
8:16
Speaker 3: way you do things and when you're ordering people, you
8:20
Speaker 3: then can forecast your day's business and then intra day,
8:26
Speaker 3: which is a very big thing, is if I said
8:28
Speaker 3: I needed to do one hundred units today and at
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Speaker 3: eleven o'clock in the morning, I've already done sixty units,
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Speaker 3: I don't need to have those people. Conversely, if I
8:39
Speaker 3: get the one o'clock in the afternoon and I've only
8:42
Speaker 3: done forty percent, I'm actually working at a lower standard.
8:45
Speaker 3: I've had something that's caused me the software and then say, well,
8:48
Speaker 3: you're probably looking at fourteen hours of overtime? How am
8:52
Speaker 3: I going to handle that? So we're not fixing the
8:55
Speaker 3: labor problem, but what we're doing is that critical operational
8:59
Speaker 3: planning of not having waste right, or if I said, oh,
9:04
Speaker 3: by the way, you're going to need one hundred and
9:06
Speaker 3: thirty four hours of overtime today because somebody dropped in
9:10
Speaker 3: a massive order for you, it's in your best interest
9:13
Speaker 3: not to pay overtime and to go in and hire
9:15
Speaker 3: thirty tempts to handle that and to mitigate your cost.
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Speaker 3: So these are the things that would call critical operational
9:23
Speaker 3: planning that you can do inside of our tool. All right.
9:29
Speaker 2: So recognizing that, you know, one of the one of
9:33
Speaker 2: the critical aspects of labor managing labor managing people is
9:38
Speaker 2: employee engagement satisfaction in order to reduce that turnover. So
9:45
Speaker 2: how does labor AI contribute to, you know, creating that
9:49
Speaker 2: work environment that supports and motivates the warehouse you.
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Speaker 3: Know, part and parcel of this will refer to as
9:57
Speaker 3: the gamification inside the building. Use an analogy, if you
10:01
Speaker 3: give me two minutes on this. If you're driving down
10:03
Speaker 3: in Chicago to Nashville and I say to you, how
10:07
Speaker 3: long is that gonna take? You're gonna say to me, well,
10:09
Speaker 3: you know, it usually takes four and a half hours,
10:11
Speaker 3: And I say, okay, great. But if you're gonna leave
10:14
Speaker 3: now and you're gonna go to Nashville. What's the first
10:17
Speaker 3: thing you do. You go to some mapping application, either
10:24
Speaker 3: Google or Wave, and it says it's gonna take you
10:27
Speaker 3: because there's traffic on sixty five. You're probably gonna go,
10:31
Speaker 3: you know, I eighty and around the corner or whatever
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Speaker 3: and go sixty seven whatever the numbers are right, and
10:36
Speaker 3: it says, oh, if you're gonna take this, you choose
10:39
Speaker 3: I'm gonna go sixty five, and it says it's gonna
10:41
Speaker 3: take you four hours and twenty one minutes. Okay, so
10:44
Speaker 3: that's the standard. Now you get in your car and
10:47
Speaker 3: you're going four four hours and twenty one minutes. Do
10:51
Speaker 3: you drive with the thought process that I'm gonna go
10:53
Speaker 3: four hours and twenty minutes or do you save yourself? No,
10:57
Speaker 3: I'm gonna do that in four hours. I'm gonna be
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Speaker 3: that state. And that's the gamification. Now, if I do
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Speaker 3: that same thing inside the warehouse and intra day, I'm
11:06
Speaker 3: showing people that we think that we need to do
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Speaker 3: all this work by five o'clock today, and we can
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Speaker 3: do this many orders, and you gamify that and people
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Speaker 3: then start to see that we are getting better, then
11:20
Speaker 3: you get engagement, and you also have things where the
11:23
Speaker 3: company then can do shift type incentives. If we do
11:26
Speaker 3: this work today, we'll have a barbecue on Friday. And
11:30
Speaker 3: because it's no longer subjective, my warehouse manager says, we
11:34
Speaker 3: either did or we didn't, the staff can work as
11:38
Speaker 3: a team. We got to speed up today because you know,
11:41
Speaker 3: we got to get all this stuff done, and or
11:44
Speaker 3: you know what, there's a hockey game on tonight. I
11:46
Speaker 3: want to get home. I don't want to have to
11:48
Speaker 3: stay late. I want to do things better. And so
11:52
Speaker 3: the gamification is whether I work inside of a lot
11:55
Speaker 3: of businesses. We have different business units. I have E Commerce,
11:58
Speaker 3: I have B to be, I have commercial or whatever.
12:01
Speaker 3: You can then compare performance from business unit to business
12:05
Speaker 3: unit using different metrics but the same ideal performance rate.
12:10
Speaker 3: So what it does is it allows the organization and
12:14
Speaker 3: the people on the floor to actually see their performance
12:17
Speaker 3: in a measurable model versus all those guys got the
12:20
Speaker 3: easy orders, that's the easy part of the business. We're
12:23
Speaker 3: never going to approach them. Or if I'm comparing site
12:27
Speaker 3: to site, you know, all those guys they've got a
12:30
Speaker 3: little tiny building, they're always going to be faster and
12:33
Speaker 3: stop looking at comparing activity as a function of productivity. Okay,
12:41
Speaker 3: so those are the things that will in turn get
12:44
Speaker 3: better engagement. And if I get more people, I don't
12:47
Speaker 3: have the requirement for temporary people. I'll be more likely
12:50
Speaker 3: to hire the right people and not have to swell by.
12:55
Speaker 3: You know, I'll use you know, some of the big
12:58
Speaker 3: we'll call it consumers of labor. These days, they order
13:03
Speaker 3: labor in the morning like it's and all you can
13:05
Speaker 3: eat buffet. They don't know if they need it, but
13:08
Speaker 3: they bring it all on. And what they do is
13:11
Speaker 3: they're driving up the price of labor. They're driving up
13:13
Speaker 3: the scarcity of labor, even though they don't use it,
13:18
Speaker 3: and that's one of our major problems in the market
13:22
Speaker 3: these days. The other problem is we don't build warehouses
13:26
Speaker 3: where people live, so they have to get there. And
13:29
Speaker 3: because we're building warehouses further and further out, then we
13:32
Speaker 3: have a transport issue, right, so that makes labor even
13:37
Speaker 3: more scarce. So getting the right size labor the day
13:41
Speaker 3: before is going to be far more efficient than actually
13:44
Speaker 3: trying to order you know, all you can eat buffet
13:47
Speaker 3: and hope that I've got the right people right, we've
13:50
Speaker 3: heard this our whole lives hope is not a plan.
13:55
Speaker 2: That's true, absolutely true, And I love that you you
14:01
Speaker 2: likened that to the challenge accepted of the time on
14:06
Speaker 2: when you're navigating somewhere, because I know I do that
14:09
Speaker 2: when I map out somewhere and it gives me, you know,
14:12
Speaker 2: my destination time, it's like, all right, I think I
14:14
Speaker 2: can beat it by two minutes, you know, even if
14:16
Speaker 2: it's a short drive and I think, oh, well, you know,
14:20
Speaker 2: if I hit all the lights right, or I make
14:21
Speaker 2: this other turn or take, I can get there faster.
14:24
Speaker 2: I think that's a great way to really engage your
14:28
Speaker 2: team in trying to you know, continuous improvement, make sure
14:32
Speaker 2: that things are getting better all the time, but not
14:34
Speaker 2: only improving, just informing and letting the employees and the warehouse,
14:40
Speaker 2: you know, whether they're temporary or whether they're they're full employees,
14:45
Speaker 2: have some stake in the game and really feel like
14:49
Speaker 2: the work that they're doing is important and it's valuable
14:52
Speaker 2: and it's making a difference toward the company's bottom line.
14:56
Speaker 2: Because nothing is more demoralizing than feeling like the work
14:59
Speaker 2: you're doing is just time spent doing something and it's
15:04
Speaker 2: not important. That's a terrible feeling that my contribution isn't
15:09
Speaker 2: worth anything to the bottom line.
15:11
Speaker 3: It's not a dichotomy, but it's a misconception in the market.
15:16
Speaker 3: Most people, and you've just pointed out, don't aspire to
15:20
Speaker 3: be average. They want to beat the average, right, But
15:23
Speaker 3: most operations, all they deal in is trying to be average.
15:28
Speaker 3: Most WMS systems out there set the target as the
15:31
Speaker 3: average of what we've done. Right. So one of my
15:36
Speaker 3: larger customers, like a global supply chain group, the chairman
15:41
Speaker 3: of that company says, we've spent millions of dollars over
15:44
Speaker 3: the last five years figuring out everything we've done, and
15:48
Speaker 3: he says, you have how much money we've spent on
15:51
Speaker 3: what we should have done? Zero? So what happens is
15:55
Speaker 3: we have people in the buildings that want to aspire
15:57
Speaker 3: to be better than average, and yet all all we
16:00
Speaker 3: do from a corporation is try to be average. Right.
16:04
Speaker 3: So that's part of the gamification side. Right. If I'm
16:09
Speaker 3: doing fifty four cases an hour, is that good? Is
16:12
Speaker 3: that thirty percent of the standard? Is it ninety? Most
16:16
Speaker 3: companies don't know, so they're saying, well, we measure ourselves
16:19
Speaker 3: we did thirty four cases an hour this week, we
16:21
Speaker 3: did thirty five hours. Next week, we're ten percent better. Great,
16:25
Speaker 3: but then product mix changes and we go down to
16:27
Speaker 3: twenty seven cases an hour, and then all of a sudden, well,
16:31
Speaker 3: we're not performing at the right standard because the average
16:34
Speaker 3: is as you know, there's such a huge swing and
16:36
Speaker 3: average that that doesn't do anything, and that really demoralizes
16:41
Speaker 3: the employee because the manager's looking at averages and depending
16:47
Speaker 3: on your luck of the draw, you may get a
16:49
Speaker 3: crappy day or a crappy assignment and you're being compared
16:52
Speaker 3: to average. Yeah, but your order wasn't an average. Those
16:55
Speaker 3: are the things that bother people.
16:57
Speaker 2: So that brings up an interesting point. So considering you know,
17:01
Speaker 2: the the challenges of integrating something like this. You were
17:05
Speaker 2: just talking about the customer who spent millions of dollars,
17:08
Speaker 2: you know, trying to find these answers to bring in
17:11
Speaker 2: the technology that will help them have this level of
17:14
Speaker 2: visibility given all the effort that's put into it. How
17:17
Speaker 2: does labor Ai you know, number one, address some of
17:21
Speaker 2: that resistance that we know happens with any type of implementation.
17:26
Speaker 2: But you know that the level of customization that's available
17:29
Speaker 2: to address that issue of having averages that aren't necessarily accurate.
17:35
Speaker 3: So because we calibrate a standard, it's unique for every
17:39
Speaker 3: single operation. So part of the process of implementation is
17:43
Speaker 3: tell me the size of the building you've got, what
17:45
Speaker 3: type of equipment are you running, how do your orders
17:48
Speaker 3: come out? You know, what is your process. These are
17:52
Speaker 3: all things that are like tickboxes in our application, and
17:55
Speaker 3: then it chooses which standards are apply to that particular task.
18:00
Speaker 3: So we take out all of this customization. So typically
18:03
Speaker 3: our interface is at the inventory level and at the
18:07
Speaker 3: order profile level, the order itself level, so we're not
18:11
Speaker 3: talking about a massive integration. So we're still not talking
18:16
Speaker 3: about an execution level solution, so we're talking about from
18:20
Speaker 3: a planning solution. So we get a dump of the
18:22
Speaker 3: activity file and then we run that through our standards
18:26
Speaker 3: and within thirty seconds you've got your standards for the
18:30
Speaker 3: timeframe that you're looking at. If you want to change things,
18:34
Speaker 3: you can rerun the standard. So let's say you're no
18:38
Speaker 3: longer shipping toothpaste this week, you're shipping cases of laundry detergent.
18:44
Speaker 3: Now a case is not a case. You get two
18:46
Speaker 3: hundred and sixteen cases a toothpaste on a pallet, you
18:49
Speaker 3: get thirty six of Lindry detergent. So now my work
18:53
Speaker 3: content's considerably higher. I could change my standards to accommodate
18:58
Speaker 3: that work standard for that period versus looking at a line.
19:03
Speaker 3: Oh what's a line again? You know when companies compare lines,
19:07
Speaker 3: it's how long is a piece of string? Right? I
19:09
Speaker 3: got the line that had one unit two or one
19:12
Speaker 3: line two units, and I got the other one that was, oh,
19:15
Speaker 3: it's twenty seven pallets. So my work content is two
19:18
Speaker 3: and a half hours on one and thirty seconds on
19:21
Speaker 3: the other. So we want to take those anomalies out.
19:25
Speaker 2: So dialing in to get super specific. But also you know,
19:30
Speaker 2: having all of those variables as part of the system,
19:36
Speaker 2: that you're able to have that agility to switch it
19:40
Speaker 2: up when something has changed that you want to measure
19:44
Speaker 2: accurately against what's actually happening. It's apples to apples instead
19:48
Speaker 2: of apples to oranges.
19:51
Speaker 3: Yeh one, And that's exactly you know the point. You know,
19:54
Speaker 3: we still talk about we want to be agile. The
19:57
Speaker 3: only way the solution makes it versal is that if
20:01
Speaker 3: it's simple to use, simple to implement, and agile to change.
20:05
Speaker 3: So you're not calling me to redo your samples or
20:09
Speaker 3: your standards. You just rerun a model. Right, So you
20:13
Speaker 3: hit a button. If you want AI to make our recommendation,
20:16
Speaker 3: you hit the AI button. What does AI recommend based
20:20
Speaker 3: on our current operation? Oh, maybe you should look at
20:25
Speaker 3: reducing your distance between skews by three inches. That will
20:28
Speaker 3: then increase your profitability by you know, seven percent. So
20:34
Speaker 3: these are the small things. We're not telling you to
20:37
Speaker 3: go out and buy automation, but if you buy automation,
20:40
Speaker 3: you could actually model that inside the software. How will
20:42
Speaker 3: it affect us?
20:46
Speaker 2: So that's that's an interesting point because that could be
20:48
Speaker 2: something where people use the tool to say, okay, here's
20:51
Speaker 2: where we are today, this is what's going on, this
20:53
Speaker 2: is our model, this is our you know, our average,
20:56
Speaker 2: and then run a model to see we're considering this
21:00
Speaker 2: piece of technology. Will this make an appreciable difference? Will
21:02
Speaker 2: I get a return on this investment? Will will this
21:06
Speaker 2: help our our warehouse operations? And then you know, comparing
21:11
Speaker 2: you know, maybe this versus that, this this particular you
21:14
Speaker 2: know AGV versus you know this shrink wrapper or whatever,
21:18
Speaker 2: you know, any type of technology that would come into
21:21
Speaker 2: a warehouse, you could model that scenario to see if
21:25
Speaker 2: it's going to have the ROI that at least that
21:28
Speaker 2: that supplier is promising given the very detailed way and
21:33
Speaker 2: processes in your own facility exactly. You know.
21:37
Speaker 3: And part of the gap in the industry right now
21:40
Speaker 3: is that only two percent of automation projects hit their ROI.
21:44
Speaker 3: And as we keep continuing to push for AI and
21:48
Speaker 3: continue to push for automation, actually having a better understanding
21:53
Speaker 3: of what it's going to do for me based on
21:56
Speaker 3: my unique operation. So one of the big I guess
22:00
Speaker 3: overstatements in automation these days is that, oh, our machine
22:05
Speaker 3: will do twelve hundred units an hour, So I put
22:08
Speaker 3: that in and I buy a machine, but I only
22:10
Speaker 3: do six hundred units a day, so I bought it
22:13
Speaker 3: in and my machine works one hour a day and
22:16
Speaker 3: does nothing for the rest of the twenty four hours,
22:18
Speaker 3: so I don't get anywhere near the utilization. Or it
22:22
Speaker 3: does twelve hundred units an hour, that's great, but I
22:26
Speaker 3: do thirty units an hour for till five o'clock at night,
22:30
Speaker 3: where I put in three thousand units, and now I
22:32
Speaker 3: have a scalability issue that my automation can't actually do
22:36
Speaker 3: the work when they need it to be done. So
22:40
Speaker 3: these are things that you can model inside of our tool.
22:44
Speaker 2: Well, and not only that, but you know, whatever technology
22:47
Speaker 2: you're looking at for automation, you know, is that twelve
22:50
Speaker 2: hundred units an hour? Is that overkill? Is this too
22:54
Speaker 2: large a purchase for what I need? Or you know, conversely,
22:58
Speaker 2: is that not going to be sufficient? Do I need
23:00
Speaker 2: you know, multiple things? Do I need to look at
23:02
Speaker 2: a larger a larger scale solution, automation solution, because this
23:09
Speaker 2: one thing by itself is not going to deliver on
23:13
Speaker 2: the return that I need on that investment. It's it's
23:16
Speaker 2: just not enough. It's not enough of an appreciable difference
23:19
Speaker 2: or improvement that that makes sense. Let's look at something else.
23:23
Speaker 2: So I think this is this is giving some great
23:26
Speaker 2: insights what measurable impacts. So we're talking about ROI. What
23:33
Speaker 2: have some of your clients achieved with this tool that
23:36
Speaker 2: you can talk about because I know sometimes when it
23:39
Speaker 2: comes to our clients, they want to keep their secrets
23:42
Speaker 2: close to their chest, but they all want that competitive advantage.
23:49
Speaker 3: Well, nobody really wants anybody to know, you know, where
23:53
Speaker 3: they were. I was just at a one of the
23:56
Speaker 3: largest supply chain companies on the planet doing one of
24:00
Speaker 3: their sites and one of their clients, and in five
24:03
Speaker 3: days we reduced their labor component by fifty people. We've
24:11
Speaker 3: done other projects where you know, the client was making
24:15
Speaker 3: the changes while we were still in the building and
24:19
Speaker 3: they basically generated a quarter million dollars of savings in
24:23
Speaker 3: two days. So you know, there's things where people just
24:27
Speaker 3: are they're not doing there's a gap in their business.
24:31
Speaker 3: Our typical ROI for clients is somewhere between we'll call
24:35
Speaker 3: it thirty and forty times the return monthly because we're
24:44
Speaker 3: measuring labor monthly and we're actually charging the client just
24:49
Speaker 3: a small monthly fee. The rois are extremely large. So,
24:57
Speaker 3: as I said, it's an untapped market and if you
24:59
Speaker 3: can make a solution that's rapid implementation, and as you said,
25:03
Speaker 3: I can measure accurately today. You know, the biggest problem
25:08
Speaker 3: right now is most companies actually have no idea what
25:11
Speaker 3: their own performance is, so they're not managing it. And
25:15
Speaker 3: if you use the old adage, if you don't measure it,
25:17
Speaker 3: you can't manage it. The first time we do a site,
25:21
Speaker 3: we turn on the light bulb. They are already making changes,
25:28
Speaker 3: and our software can say, oh, you know, you should
25:31
Speaker 3: probably only have four people in receiving, but you have nine.
25:34
Speaker 3: So right away they figure out what the problem is
25:36
Speaker 3: in receiving, or do I have a problem in picking,
25:39
Speaker 3: Like why do I have six pickers and I have
25:41
Speaker 3: twenty two checkers?
25:43
Speaker 2: All right, So, given that there is a labor shortage
25:49
Speaker 2: and we find some of these inefficiencies, you're saying that
25:54
Speaker 2: right away immediately out of the box. As soon as
25:58
Speaker 2: those inputs are in there, and as soon as organizations
26:01
Speaker 2: are seeing where things are not ideal in different departments,
26:04
Speaker 2: they're able to reallocate those resources to where they're actually
26:08
Speaker 2: needed within the facility. You know, I mean, obviously, we
26:12
Speaker 2: don't want to get rid of labor that is quality labor,
26:16
Speaker 2: you know, employees that show up every day on time.
26:20
Speaker 2: You don't want to lose those valuable assets to your organization.
26:26
Speaker 3: But the.
26:28
Speaker 2: Redistribution of the effort within the warehouse can be much
26:33
Speaker 2: better on day one.
26:35
Speaker 3: Absolutely. In the industry, we've referred to that as labor balancing.
26:40
Speaker 3: And what you see is you go into businesses, whether
26:42
Speaker 3: you're a three pl or your a multi business unit operation,
26:46
Speaker 3: they typically silo the labor you work for this client,
26:50
Speaker 3: you work in this business unit, and so they operate
26:53
Speaker 3: as silos and they don't say, oh, well, collectively we
26:56
Speaker 3: need one hundred people, but because each business unit has
26:59
Speaker 3: sort of siloed, they end up having one hundred and
27:02
Speaker 3: twenty two in the building. Okay, And then we want
27:05
Speaker 3: to cross train people. Don't just hire somebody to do receiving.
27:09
Speaker 3: Teach them how to pick or whatever. You know, if
27:12
Speaker 3: you have somebody on one type of equipment, maybe get
27:15
Speaker 3: them to learn how to use a man up or
27:17
Speaker 3: an order picker or something so that if there's no
27:19
Speaker 3: task associated with that equipment, I just moved them to
27:22
Speaker 3: a different vehicle. So that labor balancing is critical in
27:27
Speaker 3: being functionally effective on your labor.
27:31
Speaker 2: Well, and back to the other topic that we were
27:35
Speaker 2: we were on a few minutes ago, where it's talking about,
27:37
Speaker 2: you know, the work environment and employee engagement and satisfaction.
27:40
Speaker 2: When you have someone who is only trained on one
27:43
Speaker 2: thing that gets very hard on physically on their body
27:47
Speaker 2: to do that repetitive task over and over and over
27:50
Speaker 2: and never have any change. So the cross training really
27:55
Speaker 2: gives the organization the opportunity. Number One to have a
27:59
Speaker 2: more flexible labor but number two, to really look out
28:02
Speaker 2: for the employee's well being mentally and physically that they have,
28:07
Speaker 2: you know, different tasks that they can do throughout the day.
28:09
Speaker 2: Obviously they might need a break, you know, from from
28:13
Speaker 2: doing picking all the time. Now we're going to put
28:15
Speaker 2: you over here on you know, palatizing or something like that.
28:19
Speaker 2: There's there's different ways to keep your team engaged by saying, look,
28:23
Speaker 2: we're you're not just a robot here. You're not only
28:28
Speaker 2: doing this one thing. That's not where your value is.
28:31
Speaker 2: Your value is in the breadth of different things that
28:34
Speaker 2: you can do for this warehouse or within this this warehouse,
28:37
Speaker 2: within this facility. That makes you a more valuable employee,
28:41
Speaker 2: and we want you to be that because that means
28:43
Speaker 2: you're more valuable to us as well.
28:45
Speaker 3: And one of the points in there that we haven't
28:47
Speaker 3: done a lot at this point of qualifying, and you've
28:50
Speaker 3: pointed it out, soft tissue injuries by repetitive task in
28:54
Speaker 3: the warehouse because I only do one thing is actually
28:57
Speaker 3: a very large concern, especially e commerce, where it's you know,
29:03
Speaker 3: unless you're using AMR or something the traditional ware else
29:06
Speaker 3: in North America, is still picking small items and the
29:10
Speaker 3: people are standing. They're not using equipment, so they're pushing
29:15
Speaker 3: shopping carts or they're pushing tote carts and things like that.
29:18
Speaker 3: And these these soft tissue injuries are one of the
29:21
Speaker 3: greatest causes for employee absence and employee turnover because they
29:27
Speaker 3: just they're either they can't take it or the monotony
29:30
Speaker 3: of it drives them crazy. So cross training is a
29:34
Speaker 3: big thing. And at the same time, you know, one
29:37
Speaker 3: of the ways to engage people is receiving is a
29:40
Speaker 3: pretty easy physical task, but it's also where you want
29:44
Speaker 3: your people that are actually the most meticulous people. Right.
29:47
Speaker 3: So you know, I always use the analogy, you know,
29:51
Speaker 3: and I'll use a football analogy. But you've got the
29:54
Speaker 3: best center on the planet with Jason kelce best center
29:59
Speaker 3: on the planet. Okay, it's great at you know, doing
30:02
Speaker 3: one thing, but nobody ever said, you know, we're going
30:04
Speaker 3: to promote Jason Kelcey to be our quarterback, right because
30:09
Speaker 3: he's good at one thing, but he's not good in
30:11
Speaker 3: another thing. And in warehouses, we tend to promote people
30:15
Speaker 3: because they've been good at one thing when we don't
30:18
Speaker 3: look at what their skill set is we just promote
30:20
Speaker 3: them because the natural progression is that the people that
30:24
Speaker 3: work in the business the longest end up in receiving
30:26
Speaker 3: because it's the easiest job.
30:28
Speaker 2: Okay, well, and you know one other thing I was
30:31
Speaker 2: thinking about when you were talking about that the soft
30:33
Speaker 2: tissue injuries is not only does this give them the
30:38
Speaker 2: opportunity to you know, cross train and do something else,
30:41
Speaker 2: but it could have an impact on you know, whatever
30:44
Speaker 2: health benefits and medical benefits that the company is providing,
30:49
Speaker 2: if they're able to create a more balanced and healthy
30:53
Speaker 2: environment for their employees to work in through that cross training.
30:57
Speaker 2: And I know we've gotten a little bit off topic,
30:59
Speaker 2: but I.
31:00
Speaker 3: You know, no, but it's actually it's all it's all
31:03
Speaker 3: on topic. And I guess the one piece when we
31:06
Speaker 3: talk about reduction in labor or unnecessary labor, let's put
31:10
Speaker 3: it that not reduction unnecessary labor is for a lot
31:14
Speaker 3: of companies. They could then turn this around to ESG
31:16
Speaker 3: grants environmental sustainability grants because you have less equipment, require
31:21
Speaker 3: a less travel, less carbon footprint, and all of these
31:24
Speaker 3: things that are now on the government grants list. Allow
31:28
Speaker 3: companies then to start focusing on what we're taking these
31:30
Speaker 3: measures to actually reduce our carbon footprint by getting the
31:35
Speaker 3: right size of people, so not having a parking lot
31:38
Speaker 3: that's full of cars, it's eight hundred people. Right, So
31:41
Speaker 3: this should be part and parcel of when you're looking
31:45
Speaker 3: at the entire plan of your operation. And obviously ESG
31:50
Speaker 3: grants are a big topic these days, and rather than
31:53
Speaker 3: just putting solar panels on your roof, look at things
31:55
Speaker 3: outside of the box.
31:57
Speaker 2: All right, So the ROLI isn't only in the labor
32:01
Speaker 2: there's so many other areas that can be improved that
32:04
Speaker 2: will contribute to the return on the investment for this
32:08
Speaker 2: part particular tool.
32:10
Speaker 3: Yeah, we're not greed. We'll just talk about the stuff
32:12
Speaker 3: that's the easy, little hanging fruit. But the rois typically
32:17
Speaker 3: for our clients range anywhere from forty to one hundred
32:20
Speaker 3: to one on a monthly basis.
32:22
Speaker 2: Okay, Well, and I know that PROMAT is coming up,
32:27
Speaker 2: so that you said you were just traveling recently. We've
32:31
Speaker 2: got some more travel in our future in the upcoming months.
32:35
Speaker 2: And PROMAT is the largest material handling show in North America.
32:38
Speaker 2: For those of our listeners who are not familiar with it,
32:41
Speaker 2: I've talked about it a few times. I know, obviously
32:43
Speaker 2: MEBACH is going to be there and labor AI will
32:48
Speaker 2: be there as well in the Embassy data at booth.
32:51
Speaker 2: So what can attendees or what can our listeners if
32:55
Speaker 2: they're on the fence about going to PROMAT, what do
32:58
Speaker 2: they have to look forward to with labor AI at PROMAT.
33:02
Speaker 2: What what is exciting this year.
33:05
Speaker 3: Well obviously introducing the enterprise version and more importantly understanding
33:11
Speaker 3: and seeing what AI will recommend for you and what
33:15
Speaker 3: critical operational planning is actually affordable affordable operational planning is
33:20
Speaker 3: available these days versus just getting you know, dashboards that
33:25
Speaker 3: for a lot of people are very confusing and having
33:27
Speaker 3: something that's simple, you know, and tying it back in,
33:31
Speaker 3: you know. And one of the things that we also
33:33
Speaker 3: want to outline that labor AIS is really a performance
33:38
Speaker 3: measurement tool. You still require companies like me back to
33:42
Speaker 3: actually come up with these solutions that will help you,
33:46
Speaker 3: you know, make your operation more efficient. Productivity can be
33:49
Speaker 3: measured as throughput of the building and we measure the
33:53
Speaker 3: productivity of the people. So there are two different measures
33:56
Speaker 3: of productivity. Your people can be running it one hundred percent,
34:01
Speaker 3: but you know, a consulting company me back could bring
34:04
Speaker 3: you in process changes that will actually increase your throughput
34:08
Speaker 3: of the business by one hundred percent. Right, But what
34:10
Speaker 3: we want to do is we focus on the people,
34:13
Speaker 3: but bringing in automation. What automation's right for you. Those
34:17
Speaker 3: are things where we actually then look back to companies
34:21
Speaker 3: like a Meeback who will be partnering with labor Ai,
34:25
Speaker 3: and you'll be the ones that will drive the benefit
34:29
Speaker 3: for the clients because we're only getting a certain part.
34:32
Speaker 3: What are we doing today? How can we manage better?
34:35
Speaker 3: But how do I get you know, how do I
34:38
Speaker 3: get to the next eighteen months or where are we
34:40
Speaker 3: going to be in twenty four months? We don't do that,
34:43
Speaker 3: So I think that there's a good synergy and whether
34:47
Speaker 3: you're going to promat for the first time, it's kind
34:49
Speaker 3: of like supply chain Disneyland. So anything that's in the industry,
34:54
Speaker 3: you'll be able to see. And one of the beauties
34:56
Speaker 3: of going to the Meeback booth or coming to the
34:59
Speaker 3: labor Ai booth is that we'll be able to tell
35:01
Speaker 3: you if it's just from the top end, maybe it
35:04
Speaker 3: benefits you, maybe it doesn't. By running through that, if
35:07
Speaker 3: you're on the fence get off the fence, get out
35:10
Speaker 3: and see y'all. Get out the promat anything else. It's
35:14
Speaker 3: a learning experience, and if you don't know about it,
35:18
Speaker 3: you'll never be able.
35:19
Speaker 2: To implement it, all right, So real quick, you know what,
35:25
Speaker 2: I'm going to make sure just to put the booths
35:27
Speaker 2: because I can't remember our booth number off the top
35:30
Speaker 2: of my head, and I doubt that anyone you know
35:32
Speaker 2: would remember it from the podcast anyway, So we'll put
35:35
Speaker 2: the booth numbers in there so that they can come
35:37
Speaker 2: visit us at Promat next month. Looking forward to seeing
35:41
Speaker 2: you in person and getting to say hello, because you know,
35:46
Speaker 2: here here in my little podcast studio it's a it's
35:49
Speaker 2: a little lonely. I don't get the interaction. So I'm
35:52
Speaker 2: really looking forward to seeing you and all of our
35:55
Speaker 2: listeners and potential new listeners at Promat. It's a great event.
36:00
Speaker 2: I know we got completely off topic. They're talking about
36:02
Speaker 2: the show. Well, that brings us to the end of
36:06
Speaker 2: this episode. There are some great insights. Thank you so
36:10
Speaker 2: much for bringing them into the warehouse process optimization and
36:14
Speaker 2: labor the impact that it has on these facilities. Thank
36:20
Speaker 2: you so much, Lee for joining us today and telling
36:23
Speaker 2: us about your amazing new tool.
36:24
Speaker 3: Thank you, Ellen.
36:27
Speaker 2: I'm sure there are a bunch of listeners out there
36:29
Speaker 2: who could find this benefit beneficial to their operation, and
36:33
Speaker 2: I will make sure that they have access to embassy
36:37
Speaker 2: data from our description and a link directly to you
36:40
Speaker 2: if they have any questions. If any of our listeners
36:44
Speaker 2: out there have a suggestion for another topic or would
36:47
Speaker 2: like to be a guest on our show, likelye we'd
36:49
Speaker 2: love to hear from you. You can contact me at
36:51
Speaker 2: podcast at meboch dot com at any time. As always,
36:56
Speaker 2: thank you for listening to Speaking of Supply Chain. If
36:58
Speaker 2: you've enjoyed our show, please rate and review us on
37:00
Speaker 2: whatever podcast platform you prefer. We're on Apple Podcasts, Amazon Music,
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Speaker 2: and Spotify. Be sure to tune in next time.
37:13
Speaker 1: Meeboch Consulting is one of the largest and most globally
37:16
Speaker 1: recognized supply chain consulting, engineering and advisory firms. For nearly
37:21
Speaker 1: fifty years, we've helped clients achieve supply chain excellence and
37:25
Speaker 1: sustainable competitive advantage across the entire spectrum of the supply
37:29
Speaker 1: chain by delivering improvements and innovation strategically, tactically, and digitally.
37:35
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