Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston
-
0:10 - 0:15For the next few minutes
I want to talk to you about... -
0:15 - 0:18or share with you a
breakthrough new approach -
0:18 - 0:21for managing items of
inventory inside of a warehouse. -
0:21 - 0:24We're talking about a Pick,
Pack and Ship setting here. -
0:24 - 0:27So as a hint,
-
0:27 - 0:31this solution involves
hundreds of mobile robots, -
0:31 - 0:33sometimes thousands
of mobile robots, -
0:33 - 0:36moving around a warehouse.
And I'll get to the solution. -
0:36 - 0:37But for a moment, just think
-
0:37 - 0:40about the last time
you ordered something online. -
0:40 - 0:42You were sitting
on your couch -
0:42 - 0:46and you decided that you
absolutely had to have this red t-shirt. -
0:46 - 0:48So click you put it
into your shopping cart. -
0:48 - 0:50And then you decided
that green pair of pants -
0:50 - 0:52looks pretty good too, click.
-
0:52 - 0:54And maybe a blue
pair of shoes, click. -
0:54 - 0:56So at this point you've
assembled your order. -
0:56 - 0:58You didn't stop to think
for a moment that -
0:58 - 0:59that might not be a great outfit.
-
0:59 - 1:01But you hit
Submit Order. -
1:01 - 1:05And two days later, this package
shows up on your doorstep. -
1:05 - 1:08And you open the box and like
Wow, there's my goo. -
1:08 - 1:11Did you ever stop to think about
how those items of inventory -
1:11 - 1:16actually found their way inside
that box in the warehouse? -
1:16 - 1:18So I'm here to tell you
it's that guy right there. -
1:19 - 1:23So deep in the
middle of that picture -
1:23 - 1:25you see a classic
Pick Pack Worker -
1:25 - 1:29in a distribution or
order fulfillments setting. -
1:29 - 1:33Classically these pick workers
will spend 60 to 70% of their day -
1:33 - 1:35wandering around
the warehouse. -
1:35 - 1:37They'll often walk
as much as 5, 10 miles -
1:37 - 1:40in pursuit of
those items of inventory. -
1:40 - 1:44Not only is this an
unproductive way to fill orders, -
1:44 - 1:48it also turns out to be an
unfulfilling way to fill orders. -
1:48 - 1:52So let me tell you where I
first bumped into this problem. -
1:52 - 1:56I was out in the Bay area
in 1999-2000, the dot com boom. -
1:56 - 2:00I worked for a fabulously
spectacular flame out called Webvan. -
2:00 - 2:02(Laughter)
-
2:02 - 2:05This company raised hundreds of
millions of dollars with the notion that -
2:05 - 2:07we will deliver
grocery orders online. -
2:07 - 2:12And it really came down to the fact
that we couldn't do it cost effectively. -
2:12 - 2:16Turns out e-commerce was something
that was very hard and very costly. -
2:16 - 2:20In this particular instance we were trying
to assemble 30 items of inventory -
2:20 - 2:24into a few totes, onto a van
to deliver to the home. -
2:24 - 2:28And when you think about it,
it was costing us $30. -
2:28 - 2:31Imagine, we had an
89-cent can of soup -
2:31 - 2:34that was costing us $1 to
pick and pack into that tote. -
2:34 - 2:38And that's before we actually
tried to deliver it to the home. -
2:38 - 2:40So long story short,
during my 1-year at Webvan, -
2:40 - 2:44what I realized by talking to
all the material-handling providers -
2:44 - 2:48was that there was no solution designed
specifically to solve each base picking. -
2:48 - 2:52Red item, green, blue, getting
those 3 things in a box. -
2:52 - 2:55So we said, you know, there's just
got to be a better way to do this. -
2:55 - 2:58Existing material handling
was setup to pump -
2:58 - 3:02pallets and cases of
goo to retail stores. -
3:02 - 3:05Of course Webvan went out of business
and about a year and a half later, -
3:05 - 3:09I was still noodling on this problem.
It was still nagging at me. -
3:09 - 3:11And I started
thinking about it again. -
3:11 - 3:16And I said "Let me just focus briefly
on what I wanted as a pick worker." -
3:16 - 3:18What my vision for
how it should work. -
3:18 - 3:20(Laughter)
-
3:20 - 3:22I said "let's focus
on the problem." -
3:22 - 3:25I have an order here and what
I want to do is I want to put -
3:25 - 3:28red, green and blue
in this box right here. -
3:28 - 3:30What I need is a system where I put out
my hand and poof! -
3:30 - 3:33the product shows up
and I pack it into the order, -
3:33 - 3:35and now we're thinking,
-
3:35 - 3:39"this would be a very operator-centric
approach to solving the problem. -
3:39 - 3:43This is what I need. What technology
is available to solve this problem?" -
3:43 - 3:47But as you can see, orders can come
and go, product can come and go. -
3:47 - 3:52It allows us to focus on making the
pick worker the center of the problem, -
3:52 - 3:56and providing them the tools to make
them as productive as possible. -
3:56 - 3:58So how did I
arrive at this notion? -
3:58 - 4:02Well, actually it came from
a brainstorming exercise, -
4:02 - 4:05probably a technique
that many of you use, -
4:05 - 4:07It's this notion of
testing your ideas. -
4:07 - 4:09Take a blank sheet of course,
-
4:09 - 4:13but then test your ideas
at the limits. Infinity, zero... -
4:13 - 4:16In this particular case, we
challenged ourselves with the idea: -
4:16 - 4:19wWhat if we had to build a
distribution center in China, -
4:19 - 4:21where it's a very,
very low cost market? -
4:21 - 4:25And say, labor is cheap,
land is cheap. -
4:25 - 4:26And we said specificall:
-
4:26 - 4:29"what if it was zero dollars
an hour for direct labor -
4:29 - 4:32and we could build a million
square foot distribution center?" -
4:32 - 4:34So naturally that
led to ideas that said: -
4:34 - 4:36"Let's put lots of people
in the warehouse." -
4:36 - 4:38And I said: "hold on,
zero dollars per hour, -
4:38 - 4:41what I would do is "hire"
-
4:41 - 4:4510,000 workers to come to the
warehouse every morning at 8:00 am, -
4:45 - 4:48walk into the warehouse and
pickup 1 item of inventory -
4:48 - 4:50and then just stand there.
-
4:50 - 4:53So you hold Captain Crunch,
you hold the Mountain Dew, -
4:53 - 4:54you hold the Diet Coke.
-
4:54 - 4:56If I need it, I'll call you,
otherwise just stand there. -
4:56 - 5:00But when I need Diet Coke and I call
you guys talk amongst yourselves, -
5:00 - 5:04Diet Coke walks up to the front,
pick it, put it in the tote, away it goes." -
5:04 - 5:09Like wow, what if the products
could walk and talk on their own? -
5:09 - 5:11That's a very interesting
very powerful way -
5:11 - 5:14that we could potentially
organize this warehouse. -
5:14 - 5:16So of course,
labor isn't free, -
5:16 - 5:19on that practical
versus awesome spectrum. -
5:19 - 5:21(Laughter)
-
5:21 - 5:24So we said mobile shelving.
We'll put them on mobile shelving. -
5:24 - 5:29We'll use mobile robots and
we'll move the inventory around. -
5:29 - 5:33And so we got underway on that and
then I'm sitting on my couch in 2008. -
5:33 - 5:37Did any of you see the Beijing
Olympics, the opening ceremonies? -
5:37 - 5:40I about fell out of my
couch when I saw this. -
5:40 - 5:42I'm like, that was the idea!
-
5:42 - 5:46(Laughter and Applause)
-
5:46 - 5:50We'll put thousands of people on
the warehouse floor, the stadium floor. -
5:50 - 5:54But interesting enough, this
actually relates to the idea -
5:54 - 5:59in that these guys were creating some
incredibly powerful impressive digital art, -
5:59 - 6:01all without computers,
I'm told, -
6:01 - 6:04it was all peer-to-peer
coordination and communication. -
6:04 - 6:05You stand up,
I'll squat down. -
6:05 - 6:07And they made
some fabulous art. -
6:07 - 6:10It speaks to the
power of emergence -
6:10 - 6:14in systems when you let things
start to talk with each other. -
6:14 - 6:18So that was a little
bit of the journey. -
6:18 - 6:22So of course, now what became
of the practical reality of this idea? -
6:22 - 6:23Here is a warehouse.
-
6:23 - 6:27It's a pick, pack and ship center
that has about 10,000 different SKU's. -
6:27 - 6:31We'll call them red pens,
green pens, yellow Post-It Notes. -
6:31 - 6:35We send the little orange robots
out to pick up the blue shelving pods. -
6:35 - 6:37And we deliver them
to the side of the building. -
6:37 - 6:40So all the pick workers now
get to stay on the perimeter. -
6:40 - 6:42And the game here is
to pick up the shelves, -
6:42 - 6:46take them down the highway and
deliver them straight to the pick worker. -
6:46 - 6:48This pick worker's life
is completely different. -
6:48 - 6:51Rather than wandering around
the warehouse, she gets to stay still -
6:51 - 6:53in a pick station like this
-
6:53 - 6:57and every product in the
building can now come to her. -
6:57 - 7:00So the process
is very productive. -
7:00 - 7:04Reach in, pick an item,
scan the bar code, pack it out. -
7:04 - 7:06By the time
you turn around, -
7:06 - 7:09there's another product there
ready to be picked and packed. -
7:09 - 7:12So what we've done is take
out all of the non-value added -
7:12 - 7:15walking, searching,
wasting, waited time, -
7:15 - 7:19and we've developed a very
high-fidelity way to pick these orders, -
7:19 - 7:23where you point at it with
a laser, scan UPC barcode, -
7:23 - 7:26and then indicate with a light
which box it needs to go into. -
7:26 - 7:30So more productive, more
accurate and it turns out -
7:30 - 7:34it's a more interesting office
environment for these pick workers. -
7:34 - 7:37They actually complete
the whole order. -
7:37 - 7:39So they do red, green and blue
not just a part of the order. -
7:39 - 7:43And they feel a little bit more
in control of their environment. -
7:43 - 7:46So the side effects
of this approach -
7:46 - 7:47are what really surprised us.
-
7:47 - 7:49We knew it was going
to be more productive. -
7:49 - 7:53But we didn't realize just how
pervasive this way of thinking -
7:53 - 7:58extended to other
functions in the warehouse. -
7:58 - 8:03But what effectively this approach
is doing inside of the DC -
8:03 - 8:08is turning it into a massively
parallel processing engine. -
8:08 - 8:10So this is again a
cross fertilization of ideas. -
8:10 - 8:12Here's a warehouse
and we're thinking about -
8:12 - 8:16parallel processing
supercomputer architectures. -
8:16 - 8:18The notion here is that you have
-
8:18 - 8:2110 workers on
the right side of the screen -
8:21 - 8:25that are now all independent
autonomous pick workers. -
8:25 - 8:29If the worker in station 3 decides
to leave and go to the bathroom, -
8:29 - 8:32it has no impact on the
productivity of the other 9 workers. -
8:32 - 8:37Contrast that, for a moment, with the
traditional method of using a conveyor. -
8:37 - 8:39When one person
passes the order to you, -
8:39 - 8:41you put something in
and pass it downstream. -
8:41 - 8:45Everyone has to be in place
for that serial process to work. -
8:45 - 8:48This becomes a more robust
way to think about the warehouse. -
8:48 - 8:52And underneath the hoods gets
interesting in that we're tracking -
8:52 - 8:54the popularity
of the products. -
8:54 - 8:57And we're using dynamic
and adaptive algorithms -
8:57 - 9:01to tune the floor
of the warehouse. -
9:01 - 9:06So what you see here potentially
the week leading up to Valentines' Day. -
9:06 - 9:10All that pink chalky candy has
moved to the front on the building -
9:10 - 9:14and is now being picked into a
lot of orders in those pick stations. -
9:14 - 9:18Come in two days after Valentine's Day
and that candy, the leftover candy, -
9:18 - 9:20has all drifted to the
back of the warehouse -
9:20 - 9:25and is occupying the cooler
zone on the thermo map there. -
9:25 - 9:28One other side effect of this
approach using the parallel processing -
9:28 - 9:31is these things can
scale to ginormous. -
9:31 - 9:33(Laughter)
-
9:33 - 9:35So whether you(re doing
2 pick stations, 20 pick stations, or -
9:35 - 9:39200 pick stations, the
path planning algorithms -
9:39 - 9:41and all of the inventory
algorithms just work. -
9:41 - 9:46In this example you
see that the inventory -
9:46 - 9:48has now occupied all the
perimeter of the building -
9:48 - 9:50because that's where
the pick stations were. -
9:50 - 9:52They sorted it
out for themselves. -
9:52 - 9:55So I'll conclude with
just one final video -
9:55 - 9:58that shows how
this comes to bear -
9:58 - 10:01on the pick worker's actual
kind of day in the life of. -
10:01 - 10:05So as we mentioned, the process is
to move inventory along the highway -
10:05 - 10:08and then find your way
into these pick stations. -
10:08 - 10:11And our software in the background
-
10:11 - 10:13understands what's going on
in each station, -
10:13 - 10:16we direct deposit
across the highway -
10:16 - 10:19and we're attempting to
get into a queuing system -
10:19 - 10:22to present the work
to the pick worker. -
10:22 - 10:25What's interesting is we can even
adapt the speed of the pick workers. -
10:25 - 10:29The faster pickers get more pods
and the slower pickers get few. -
10:29 - 10:32But this pick worker now is
literally having that experience -
10:32 - 10:34that we described before.
-
10:34 - 10:36She puts out her hand.
The product jumps into it. -
10:36 - 10:38Or she has to reach in and get it.
-
10:38 - 10:41She scans it and
she puts it in the bucket. -
10:41 - 10:45And all of the rest of the technology
is kind of behind the scenes. -
10:45 - 10:49So she gets to now focus on the
picking and packing portion of her job. -
10:49 - 10:52Never has any idle time,
never has to leave her matt. -
10:52 - 10:56And actually we think
not only a more productive -
10:56 - 10:59and more accurate
way to fill orders. -
10:59 - 11:03We think it is a more
fulfilling way to fill orders. -
11:03 - 11:06The reason we can say
that though is that workers -
11:06 - 11:08in a lot of these
buildings now compete -
11:08 - 11:11for the privilege of working
in the KIVA zone that day. -
11:11 - 11:14And sometimes we'll catch
them on testimonial videos -
11:14 - 11:16saying such things as,
-
11:16 - 11:20they have more energy after the
day to play with their grandchildren, -
11:20 - 11:25or in one case a guy said, "the
KIVA zone is so stress-free -
11:25 - 11:28that I've actually stopped taking
my blood pressure medication." -
11:28 - 11:30(Laughter)
-
11:30 - 11:34That was at a pharmaceutical distributor.
So they told us not to use that video. -
11:34 - 11:37(Laughter)
-
11:37 - 11:40So what I wanted to leave you
with today is the notion that -
11:40 - 11:43when you let things start
to kind of think and walk -
11:43 - 11:48and talk on their own, interesting
processes and productivities can emerge. -
11:48 - 11:51And now I think next time
you go to your front step -
11:51 - 11:54and pick up that box that
you just ordered online, -
11:54 - 11:56you break it open and
the goo is in there, -
11:56 - 11:59you'll have some wonderment
as to whether a robot -
11:59 - 12:01assisted in the picking
and packing of that order. -
12:01 - 12:03Thank you
-
12:03 - 12:08(Applause)
- Title:
- Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston
- Description:
-
Mick Mountz revolutionized the way warehouses pack and ship their inventory by using robots, mobile shelving, and algorithms based on complexity theory. What used to take hours of tedious tasks is transformed into fun, 15-minute, click-to-ship order processing.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDxTalks
- Duration:
- 12:10
Elisabeth Buffard approved English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Elisabeth Buffard edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Elisabeth Buffard edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Elisabeth Buffard edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Nhu PHAM accepted English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Nhu PHAM edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Bob Prottas edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston | ||
Bob Prottas edited English subtitles for Let The Inventory Walk and Talk: Mick Mountz @ TEDxBoston |