Bloomberg Businessweek - USA (2019-07-22)

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Bloomberg Businessweek July 22, 2019

reporterforGeekWireuseda pole

witha cameraattachedtoit topeek

inside.Aroundthesametime,Bezos

sneakedinthrougha backdoortosee

it forthefirsttimeandwasdelighted.

HesaidhefeltasifAmazon’sbusiness

wascomingfullcircle.

TolongtimemembersoftheIHMproj-

ect,watchingAmazonBooksformand

takeoffwithinthespanofa fewmonths

wasdizzying.They’dbeenworkingforthree

years,andtheirprojectdidn’tevenhavea for-

malnameyet.Togetone,inearly2016,Puerini’steamcame

upwiththeGobrandtoconveyspeed.“Eventheworditselfis

onlytwocharacters,”shesays.“Youcanliterallygrabandgo.”

Tocontinuedevelopingthetechnology,Kumar’sengineers

setupa top-secretlabstoreonthegroundflooroftheteam’s

newbuilding,dubbedOtter,onthecornerofFifthAvenue

andBellStreetindowntownSeattle.ThelabinOtterwas

accessibleonlyfrominsideviaa pairoflockeddoors.Atfirst,

shelveswerepackedwithfakefoodfashionedfromclayand

Styrofoam;shreddedgreenconstructionpaperstoodinfor

lettuce.Employeeswerefrequentlyaskedtovisitandtotry

tofoolthetechnology.Theyworeheavycoats,walkedwith

crutches,orpushedwheelchairs.Theyputitemsbackinthe

wrongplace,generatinganautomatic“untidyitem”alertthat

directeda storeclerktorestocktheitemonthepropershelf.

Oneday,everyonewasaskedtobringinumbrellastoseeif

they’dobscurethecameras’view;onanother,employeesall

woreSeattleSeahawksjerseystoconfusealgorithmsthatdistin-

guishedamongshoppersbasedonthecoloroftheirclothing.

Whenthefakefoodwaseventuallyreplacedwithrealitems,

employeeswereaskedtoshop

butunderspecificscenarios:

forexample,Puerinirecalls,

“You’rerunningtoa meeting:

Buya saladanda drinkfor

lunch,”or“You’reina rushto

pickupthekidsfromdaycare:

Grabmilk,strawberries,and

cerealfortomorrowmorning.”

Onanotherday,parentswere

askedtobringintheiryoung

kids,whofidgeted,ranaround,

andgrabbed things,further

stress-testingthesystem.To

augmentthesereal-lifeexperi-

ments,thecompanyalsodevel-

opeda digitalsimulationofthe

storeand populatedit with

computer-generatedshoppers.

Kumar’s engineerswere

trying tosolve one of the

trickiestproblems in the his-

tory of retail: how to figure

outwhatpeoplearegrabbingwithout

going through the items one by one

at checkout. After years of work,

the team had concluded that visual

identification of products solely

with overhead cameras wasn’t possible.

Changesinlightingconditionsoverthe

courseofa day,thedepthofa product’s

placementonshelves,handsandbodies

thatconcealedthecustomizedproduct

stickers,orout-of-control toddlers could

easily confuse the system.

Eventually they decided to add scales and place more

cameras inside shelves. (“Weight provides an additional sig-

nal we can use, but most of the heavy lifting is done by the

cameras and the vision algorithms,” Kumar says.) Amazon

then combined the data to decide who was buying what.

But humans were still needed to supervise these judg-

ments.Separateteamswereformedtoreviewfootagewhen

thesystemwasn’tsureabouta purchase,a so-calledlow-

confidence event. The creation of the groups led at least

some employees to question the entire effort. It “was a tricky

thing,” one former participant says. “If we have an army of

people looking at footage, is that scaling properly?” (Amazon

says human intervention is rare.)

People had another role to play as well: They had to

develop meal kit recipes and prepare the daily lunch fare

(lamb sandwiches, chicken banh mi, caprese salads).

To get ready for the opening of a scaled-down prototype

store on Amazon’s new downtown Seattle campus in late

2016, the companyhiredchefsandstafffromchainrestau-

rants. It openedbotha kitcheninsidetheprototypestore

and a commercial-grade test kitchen

neartheoldwarehouseinsouthSeattle.

Uncharacteristically,Amazonsplurged.

It boughtGermancommercialovensthat

costtensofthousandsofdollarseach.

Whensomethingsmelledoffinthepilot

kitchen,Amazonhireda pairofprofes-

sionalsmellerstosolvethemystery.(The

culprit:pickled daikon.)

The kitchens, along with Amazon’s

penchant for pursuing rigorous and

sometimes inhumane efficiencies in its

operations, brought with them another

set of unexpected challenges. Because

food safety was a top priority, the com-

mercial kitchen was kept bitterly cold, and

Amazon initially refused requests from

the staff, who had to stand on their feet

during shifts, to install mats on the facil-

ity’s chilly concrete floor, one employee

recalls. After a senior manager from head-

quarters spent a day observing operations

at the cookhouse, the company issued

A CUSTOMER SCANS IN