Mick Mountz: What happens inside those massive warehouses?

19,564 views ใƒป 2015-07-15

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Translator: Bob Prottas Reviewer: Nhu PHAM
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I want to talk to you about,
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or share with you, a breakthrough new approach
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for managing items of inventory inside of a warehouse.
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We're talking about a pick, pack and ship setting here.
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So as a hint,
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this solution involves hundreds of mobile robots,
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sometimes thousands of mobile robots,
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moving around a warehouse. And I'll get to the solution.
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But for a moment, just think
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about the last time that you ordered something online.
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You were sitting on your couch
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and you decided that you absolutely had to have this red t-shirt.
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So โ€” click! โ€” you put it into your shopping cart.
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And then you decided that green pair of pants
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looks pretty good too โ€” click!
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And maybe a blue pair of shoes โ€” click!
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So at this point you've assembled your order.
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You didn't stop to think for a moment that
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that might not be a great outfit.
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But you hit "submit order."
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And two days later, this package shows up on your doorstep.
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And you open the box and you're like, wow, there's my goo.
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Did you ever stop to think about how those items of inventory
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actually found their way inside that box in the warehouse?
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So I'm here to tell you it's that guy right there.
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So deep in the middle of that picture,
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you see a classic pick-pack worker
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in a distribution or order fulfillments setting.
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Classically these pick workers will spend 60 or 70 percent of their day
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wandering around the warehouse.
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They'll often walk as much as 5 or 10 miles
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in pursuit of those items of inventory.
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Not only is this an unproductive way to fill orders,
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it also turns out to be an unfulfilling way to fill orders.
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So let me tell you where I first bumped into this problem.
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I was out in the Bay area in '99, 2000, the dot com boom.
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I worked for a fabulously spectacular flame-out called Webvan.
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(Laughter)
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This company raised hundreds of millions of dollars with the notion that
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we will deliver grocery orders online.
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And it really came down to the fact that we couldn't do it cost effectively.
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Turns out e-commerce was something that was very hard and very costly.
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In this particular instance we were trying to assemble 30 items of inventory
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into a few totes, onto a van to deliver to the home.
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And when you think about it, it was costing us 30 dollars.
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Imagine, we had an 89ยข can of soup
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that was costing us one dollar to pick and pack into that tote.
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And that's before we actually tried to deliver it to the home.
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So long story short, during my one year at Webvan,
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what I realized by talking to all the material-handling providers
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was that there was no solution designed specifically to solve each base picking.
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Red item, green, blue, getting those three things in a box.
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So we said, there's just got to be a better way to do this.
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Existing material handling was set up to pump
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pallets and cases of goo to retail stores.
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Of course Webvan went out of business, and about a year and a half later,
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I was still noodling on this problem. It was still nagging at me.
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And I started thinking about it again.
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And I said, let me just focus briefly on what I wanted as a pick worker,
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or my vision for how it should work.
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(Laughter)
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I said, let's focus on the problem.
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I have an order here and what I want to do is I want to put
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red, green and blue in this box right here.
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What I need is a system where I put out my hand and โ€” poof! โ€”
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the product shows up and I pack it into the order,
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and now we're thinking,
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this would be a very operator-centric approach to solving the problem.
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This is what I need. What technology is available to solve this problem?
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But as you can see, orders can come and go, products can come and go.
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It allows us to focus on making the pick worker the center of the problem,
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and providing them the tools to make them as productive as possible.
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So how did I arrive at this notion?
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Well, actually it came from a brainstorming exercise,
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probably a technique that many of you use,
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It's this notion of testing your ideas.
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Take a blank sheet, of course,
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but then test your ideas at the limits โ€” infinity, zero.
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In this particular case, we challenged ourselves with the idea:
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What if we had to build a distribution center in China,
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where it's a very, very low-cost market?
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And say, labor is cheap, land is cheap.
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And we said specifically,
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"What if it was zero dollars an hour for direct labor
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and we could build a million- square-foot distribution center?"
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So naturally that led to ideas that said,
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"Let's put lots of people in the warehouse."
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And I said, "Hold on, zero dollars per hour,
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what I would do is 'hire'
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10,000 workers to come to the warehouse every morning at 8 a.m.,
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walk into the warehouse and pick up one item of inventory
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and then just stand there.
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So you hold Captain Crunch, you hold the Mountain Dew,
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you hold the Diet Coke.
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If I need it, I'll call you, otherwise just stand there.
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But when I need Diet Coke and I call it, you guys talk amongst yourselves.
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Diet Coke walks up to the front โ€” pick it, put it in the tote, away it goes."
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Wow, what if the products could walk and talk on their own?
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That's a very interesting, very powerful way
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that we could potentially organize this warehouse.
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So of course, labor isn't free,
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on that practical versus awesome spectrum.
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(Laughter)
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So we said mobile shelving โ€” We'll put them on mobile shelving.
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We'll use mobile robots and we'll move the inventory around.
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And so we got underway on that and then I'm sitting on my couch in 2008.
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Did any of you see the Beijing Olympics, the opening ceremonies?
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I about fell out of my couch when I saw this.
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I'm like, that was the idea!
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(Laughter and Applause)
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We'll put thousands of people on the warehouse floor, the stadium floor.
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But interestingly enough, this actually relates to the idea
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in that these guys were creating some incredibly powerful, impressive digital art,
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all without computers, I'm told,
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it was all peer-to-peer coordination and communication.
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You stand up, I'll squat down.
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And they made some fabulous art.
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It speaks to the power of emergence
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in systems when you let things start to talk with each other.
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So that was a little bit of the journey.
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So of course, now what became the practical reality of this idea?
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Here is a warehouse.
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It's a pick, pack and ship center that has about 10,000 different SKUs.
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We'll call them red pens, green pens, yellow Post-It Notes.
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We send the little orange robots out to pick up the blue shelving pods.
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And we deliver them to the side of the building.
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So all the pick workers now get to stay on the perimeter.
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And the game here is to pick up the shelves,
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take them down the highway and deliver them straight to the pick worker.
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This pick worker's life is completely different.
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Rather than wandering around the warehouse, she gets to stay still
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in a pick station like this
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and every product in the building can now come to her.
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So the process is very productive.
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Reach in, pick an item, scan the bar code, pack it out.
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By the time you turn around,
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there's another product there ready to be picked and packed.
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So what we've done is take out all of the non-value added
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walking, searching, wasting, waited time,
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and we've developed a very high-fidelity way to pick these orders,
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where you point at it with a laser, scan the UPC barcode,
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and then indicate with a light which box it needs to go into.
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So more productive, more accurate and, it turns out,
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it's a more interesting office environment for these pick workers.
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They actually complete the whole order.
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So they do red, green and blue, not just a part of the order.
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And they feel a little bit more in control of their environment.
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So the side effects of this approach
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are what really surprised us.
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We knew it was going to be more productive.
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But we didn't realize just how pervasive this way of thinking
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extended to other functions in the warehouse.
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But what effectively this approach is doing inside of the DC
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is turning it into a massively parallel processing engine.
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So this is again a cross-fertilization of ideas.
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Here's a warehouse and we're thinking about
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parallel processing supercomputer architectures.
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The notion here is that you have
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10 workers on the right side of the screen
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that are now all independent autonomous pick workers.
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If the worker in station three decides to leave and go to the bathroom,
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it has no impact on the productivity of the other nine workers.
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Contrast that, for a moment, with the traditional method of using a conveyor.
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When one person passes the order to you,
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you put something in and pass it downstream.
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Everyone has to be in place for that serial process to work.
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This becomes a more robust way to think about the warehouse.
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And then underneath the hoods gets interesting in that we're tracking
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the popularity of the products.
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And we're using dynamic and adaptive algorithms
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to tune the floor of the warehouse.
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So what you see here potentially the week leading up to Valentine's Day.
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All that pink chalky candy has moved to the front of the building
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and is now being picked into a lot of orders in those pick stations.
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Come in two days after Valentine's Day, and that candy, the leftover candy,
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has all drifted to the back of the warehouse
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and is occupying the cooler zone on the thermal map there.
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One other side effect of this approach using the parallel processing
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is these things can scale to ginormous.
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(Laughter)
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So whether you're doing two pick stations, 20 pick stations,
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or 200 pick stations, the path planning algorithms
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and all of the inventory algorithms just work.
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In this example you see that the inventory
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has now occupied all the perimeter of the building
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because that's where the pick stations were.
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They sorted it out for themselves.
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So I'll conclude with just one final video
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that shows how this comes to bear
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on the pick worker's actual day in the life of.
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So as we mentioned, the process is to move inventory along the highway
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and then find your way into these pick stations.
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And our software in the background
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understands what's going on in each station,
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we direct the pods across the highway
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and we're attempting to get into a queuing system
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to present the work to the pick worker.
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What's interesting is we can even adapt the speed of the pick workers.
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The faster pickers get more pods and the slower pickers get few.
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But this pick worker now is literally having that experience
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that we described before.
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She puts out her hand. The product jumps into it.
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Or she has to reach in and get it.
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She scans it and she puts it in the bucket.
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And all of the rest of the technology is kind of behind the scenes.
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So she gets to now focus on the picking and packing portion of her job.
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Never has any idle time, never has to leave her mat.
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And actually we think not only a more productive
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and more accurate way to fill orders.
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We think it's a more fulfilling way to fill orders.
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The reason we can say that, though, is that workers
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in a lot of these buildings now compete
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for the privilege of working in the Kiva zone that day.
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And sometimes we'll catch them on testimonial videos
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saying such things as,
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they have more energy after the day to play with their grandchildren,
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or in one case a guy said, "the Kiva zone is so stress-free
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that I've actually stopped taking my blood pressure medication."
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(Laughter)
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That was at a pharmaceutical distributor, so they told us not to use that video.
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(Laughter)
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So what I wanted to leave you with today is the notion that
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when you let things start to think and walk
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and talk on their own, interesting processes and productivities can emerge.
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And now I think next time you go to your front step
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and pick up that box that you just ordered online,
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you break it open and the goo is in there,
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you'll have some wonderment as to whether a robot
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assisted in the picking and packing of that order.
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Thank you.
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(Applause)
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