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Starbucks Just Killed Its AI Inventory Tool | Fast Five Shorts · Omni Talk Retail

• 0:00
  Starbucks
• 0:00
  has
• 0:00
  scrapped
• 0:01
  its
• 0:01
  AI
• 0:01
  powered
• 0:02
  inventory
• 0:02
  counting
• 0:02
  tool
• 0:03
  just
• 0:03
  nine
• 0:04
  months
• 0:04
  after
• 0:04
  rolling
• 0:05
  it
• 0:05
  out
• 0:05
  across
• 0:05
  its
• 0:06
  North
• 0:06
  American
• 0:06
  stores
• 0:07
  after
• 0:07
  the
• 0:07
  system
• 0:08
  repeatedly
• 0:09
  miscounted
• 0:09
  and
• 0:09
  mislabeled
• 0:10
  products,
• 0:11
  including
• 0:12
  confusing
• 0:12
  similar
• 0:13
  milk
• 0:13
  types
• 0:13
  and
• 0:14
  missing
• 0:14
  items
• 0:15
  altogether,
• 0:16
  according
• 0:16
  to
• 0:17
  the
• 0:17
  must
• 0:17
  read
• 0:18
  retail
• 0:18
  coverage
• 0:19
  in
• 0:19
  the
• 0:19
  Huff
• 0:19
  post.
• 0:20
  Of
• 0:20
  course
• 0:20
  I'm
• 0:21
  joking,
• 0:21
  but
• 0:21
  that
• 0:21
  tells
• 0:21
  you
• 0:22
  something
• 0:22
  about
• 0:22
  this
• 0:22
  story.
• 0:23
  Starbucks
• 0:23
  has
• 0:24
  terminated
• 0:24
  what
• 0:24
  it
• 0:24
  called
• 0:24
  its
• 0:25
  automated
• 0:25
  counting
• 0:26
  program
• 0:26
  this
• 0:26
  week
• 0:27
  with
• 0:27
  an
• 0:27
  internal
• 0:27
  company
• 0:28
  newsletter
• 0:28
  confirming
• 0:29
  the
• 0:29
  shutdown.
• 0:30
  The
• 0:30
  tool
• 0:30
  provided
• 0:31
  by
• 0:31
  Nomad
• 0:31
  Go
• 0:32
  was
• 0:32
  deployed
• 0:32
  in
• 0:32
  September
• 0:33
  2025
• 0:33
  across
• 0:35
  more
• 0:35
  than
• 0:36
  11,000
• 0:36
  North
• 0:37
  American
• 0:37
  locations
• 0:38
  as
• 0:38
  part
• 0:39
  of
• 0:39
  CEO
• 0:39
  Brian
• 0:40
  Nichols
• 0:40
  back
• 0:40
  to
• 0:40
  Starbucks
• 0:41
  turnaround
• 0:41
  strategy.
• 0:42
  Nomad
• 0:43
  Go
• 0:43
  had
• 0:43
  claimed
• 0:43
  the
• 0:43
  system
• 0:44
  could
• 0:44
  count
• 0:44
  inventory
• 0:44
  up
• 0:45
  to
• 0:45
  eight
• 0:45
  times
• 0:45
  faster
• 0:46
  than
• 0:46
  manual
• 0:46
  efforts
• 0:46
  and
• 0:47
  with
• 0:47
  99%
• 0:48
  accuracy.
• 0:49
  In
• 0:49
  a
• 0:49
  slight
• 0:50
  bit
• 0:50
  of
• 0:50
  irony
• 0:50
  too,
• 0:50
  Laura
• 0:51
  Starbucks
• 0:51
  had
• 0:51
  previously
• 0:52
  told
• 0:52
  Reuters
• 0:53
  and
• 0:53
  as
• 0:53
  recently
• 0:53
  as
• 0:54
  February
• 0:55
  so
• 0:55
  just
• 0:55
  three
• 0:56
  months
• 0:56
  ago,
• 0:56
  that
• 0:57
  the
• 0:57
  adoption
• 0:57
  of
• 0:57
  the
• 0:57
  tool
• 0:58
  had
• 0:58
  improved
• 0:58
  product
• 0:58
  availability
• 0:59
  in
• 0:59
  stores.
• 1:00
  The
• 1:01
  company
• 1:01
  has
• 1:01
  since
• 1:01
  deleted
• 1:02
  the
• 1:02
  original
• 1:02
  September
• 1:03
  2025
• 1:04
  blog
• 1:04
  post
• 1:05
  announcing
• 1:05
  the
• 1:05
  rollout.
• 1:06
  Laura
• 1:07
  Starbucks
• 1:07
  just
• 1:08
  pulled
• 1:08
  the
• 1:08
  plug
• 1:08
  on
• 1:08
  an
• 1:08
  AI
• 1:09
  inventory
• 1:09
  tool
• 1:10
  that
• 1:10
  couldn't
• 1:10
  count
• 1:11
  milk.
• 1:11
  What
• 1:12
  does
• 1:12
  this
• 1:12
  story
• 1:12
  tell
• 1:12
  us
• 1:13
  about
• 1:13
  the
• 1:13
  state
• 1:13
  of
• 1:13
  AI
• 1:14
  deployment
• 1:14
  in
• 1:14
  retail
• 1:15
  operations
• 1:15
  right
• 1:15
  now?
• 1:16
  And
• 1:16
  do
• 1:16
  you
• 1:16
  think
• 1:17
  this
• 1:17
  is
• 1:17
  a
• 1:17
  one
• 1:17
  off
• 1:17
  stumble
• 1:18
  or
• 1:18
  a
• 1:19
  warning
• 1:19
  sign
• 1:19
  for
• 1:19
  the
• 1:19
  industry?
• 1:21
  I
• 1:21
  think
• 1:21
  the
• 1:22
  simple
• 1:22
  answer
• 1:22
  is
• 1:22
  I
• 1:22
  think
• 1:23
  it's
• 1:23
  a
• 1:23
  stumble.
• 1:24
  But
• 1:25
  with
• 1:25
  any
• 1:26
  activity
• 1:26
  in
• 1:27
  this
• 1:27
  space
• 1:27
  it's
• 1:27
  always
• 1:28
  going
• 1:28
  to
• 1:28
  give
• 1:28
  us
• 1:28
  a
• 1:29
  useful
• 1:29
  data
• 1:29
  point
• 1:30
  of
• 1:30
  some
• 1:30
  kind
• 1:32
  just
• 1:32
  in
• 1:32
  case
• 1:32
  people
• 1:33
  don't
• 1:33
  know.
• 1:33
  Nomad
• 1:34
  goes
• 1:34
  technology.
• 1:36
  It
• 1:36
  uses
• 1:36
  devices
• 1:37
  with
• 1:37
  spatial
• 1:38
  vision,
• 1:38
  a
• 1:39
  form
• 1:39
  of
• 1:39
  computer
• 1:39
  vision,
• 1:40
  to
• 1:41
  count
• 1:41
  what's
• 1:41
  on
• 1:41
  a
• 1:41
  shelf
• 1:42
  and
• 1:42
  see
• 1:42
  what's
• 1:42
  missing.
• 1:44
  An
• 1:44
  associate
• 1:45
  does
• 1:45
  interact
• 1:46
  with
• 1:46
  the
• 1:46
  device.
• 1:46
  It's
• 1:47
  not
• 1:47
  a
• 1:47
  fixed
• 1:48
  camera
• 1:48
  like
• 1:48
  so
• 1:49
  much
• 1:49
  of
• 1:49
  what
• 1:49
  we
• 1:49
  know
• 1:49
  with
• 1:50
  computer
• 1:50
  vision
• 1:51
  for
• 1:51
  inventory.
• 1:52
  And
• 1:53
  the
• 1:53
  part
• 1:53
  about
• 1:53
  a
• 1:53
  human
• 1:54
  being
• 1:54
  involved
• 1:54
  is
• 1:55
  probably
• 1:56
  the
• 1:56
  main
• 1:56
  issue
• 1:56
  and
• 1:57
  just
• 1:57
  highlights
• 1:58
  the
• 1:58
  variability
• 2:00
  and
• 2:00
  challenge
• 2:01
  and
• 2:01
  how
• 2:01
  all
• 2:01
  of
• 2:01
  these
• 2:01
  tools
• 2:02
  work.
• 2:03
  You
• 2:03
  know,
• 2:04
  I
• 2:04
  feel
• 2:04
  like
• 2:04
  every
• 2:05
  example
• 2:06
  of
• 2:06
  AI
• 2:07
  inventory
• 2:07
  tracking,
• 2:08
  often
• 2:08
  computer
• 2:09
  vision
• 2:09
  and
• 2:10
  the
• 2:10
  use
• 2:10
  of
• 2:10
  it
• 2:10
  as
• 2:10
  shelf
• 2:11
  has
• 2:11
  taught
• 2:11
  us
• 2:11
  that
• 2:12
  there
• 2:12
  are
• 2:12
  very
• 2:12
  specific
• 2:13
  and
• 2:13
  narrow
• 2:14
  circumstances
• 2:15
  where
• 2:15
  it
• 2:15
  does
• 2:16
  work.
• 2:17
  You,
• 2:17
  you
• 2:17
  need
• 2:17
  things
• 2:17
  to
• 2:18
  be
• 2:18
  very
• 2:18
  predictable
• 2:18
  as
• 2:19
  the
• 2:19
  oversimplified
• 2:20
  version
• 2:20
  of
• 2:20
  it.
• 2:21
  And
• 2:22
  a
• 2:22
  restaurant
• 2:23
  and
• 2:23
  a
• 2:23
  business
• 2:23
  like
• 2:24
  Starbucks
• 2:24
  is
• 2:25
  not
• 2:25
  predictable.
• 2:26
  It's
• 2:26
  very
• 2:26
  high
• 2:27
  turn.
• 2:28
  There's
• 2:28
  seasonal
• 2:29
  drinks
• 2:29
  coming
• 2:30
  in,
• 2:31
  you
• 2:31
  know,
• 2:31
  in
• 2:31
  the
• 2:31
  tools
• 2:32
  defense.
• 2:32
  All
• 2:33
  milk,
• 2:33
  whether
• 2:34
  it's
• 2:34
  a
• 2:34
  milk
• 2:34
  product
• 2:35
  or
• 2:35
  dairy
• 2:36
  milk
• 2:36
  looks
• 2:37
  the
• 2:37
  same.
• 2:38
  And
• 2:39
  so
• 2:39
  then
• 2:39
  you
• 2:39
  mentioned
• 2:40
  11,000
• 2:40
  locations
• 2:41
  that
• 2:42
  multiply
• 2:42
  that
• 2:42
  by
• 2:43
  number
• 2:43
  of
• 2:43
  associates
• 2:45
  and
• 2:45
  then
• 2:45
  you've
• 2:46
  got
• 2:46
  an
• 2:46
  associate
• 2:46
  who
• 2:46
  is
• 2:47
  looking
• 2:47
  at
• 2:48
  the
• 2:48
  screen
• 2:49
  based
• 2:49
  on
• 2:49
  Nomad
• 2:49
  goes
• 2:50
  on
• 2:50
  Videos
• 2:50
  and
• 2:51
  kind
• 2:51
  of
• 2:51
  checking
• 2:52
  it.
• 2:52
  And
• 2:52
  so
• 2:53
  the
• 2:54
  tough
• 2:54
  thing
• 2:54
  for
• 2:54
  Nomad
• 2:55
  is
• 2:55
  that
• 2:56
  restaurants
• 2:56
  and
• 2:57
  food
• 2:57
  service
• 2:57
  are
• 2:57
  listed
• 2:58
  as
• 2:58
  its
• 2:58
  top
• 2:58
  capabilities.
• 2:59
  And
• 2:59
  so
• 3:00
  that's
• 3:01
  unfortunate
• 3:01
  for
• 3:01
  them.
• 3:02
  You
• 3:02
  know,
• 3:02
  if
• 3:02
  it
• 3:02
  was
• 3:02
  further
• 3:03
  down
• 3:03
  their
• 3:03
  list
• 3:04
  of
• 3:04
  capabilities,
• 3:05
  that
• 3:05
  might
• 3:05
  be
• 3:06
  better.
• 3:07
  But,
• 3:09
  yeah,
• 3:09
  I
• 3:09
  would
• 3:10
  also
• 3:10
  have
• 3:10
  to
• 3:10
  imagine,
• 3:11
  you
• 3:11
  know,
• 3:11
  that
• 3:12
  I
• 3:12
  would
• 3:13
  have
• 3:13
  thought
• 3:13
  that
• 3:13
  there'd
• 3:13
  be
• 3:13
  someone
• 3:14
  who'd
• 3:14
  recognize
• 3:14
  some
• 3:14
  of
• 3:15
  these
• 3:15
  errors.
• 3:15
  And
• 3:15
  so
• 3:15
  it
• 3:16
  really
• 3:16
  shows
• 3:16
  you
• 3:17
  how
• 3:18
  when
• 3:18
  you
• 3:18
  get
• 3:18
  these
• 3:19
  tools
• 3:19
  into
• 3:20
  a
• 3:20
  store
• 3:20
  and
• 3:21
  into
• 3:21
  operation,
• 3:21
  store,
• 3:22
  restaurant,
• 3:22
  what
• 3:23
  have
• 3:23
  you,
• 3:24
  you're
• 3:24
  relying
• 3:25
  on
• 3:25
  so
• 3:26
  many
• 3:26
  different
• 3:26
  factors
• 3:27
  that
• 3:27
  you
• 3:27
  can
• 3:27
  control
• 3:28
  for
• 3:28
  when
• 3:28
  you're
• 3:28
  testing
• 3:29
  them.
• 3:31
  The
• 3:31
  other
• 3:31
  thing
• 3:31
  that
• 3:31
  I
• 3:32
  do
• 3:32
  think
• 3:32
  is
• 3:32
  important
• 3:32
  to
• 3:32
  note
• 3:33
  is
• 3:33
  that
• 3:33
  this
• 3:34
  is
• 3:34
  a
• 3:34
  type
• 3:34
  of
• 3:34
  AI
• 3:35
  solution
• 3:35
  that
• 3:35
  has
• 3:35
  existed
• 3:36
  much
• 3:36
  longer
• 3:37
  than
• 3:37
  what
• 3:37
  we
• 3:37
  think
• 3:38
  of
• 3:38
  in
• 3:38
  2026
• 3:39
  as
• 3:39
  AI
• 3:40
  deployment
• 3:40
  and
• 3:40
  retail
• 3:41
  operations.
• 3:42
  Definitively.
• 3:44
  Yeah.
• 3:44
  And
• 3:44
  so,
• 3:45
  you
• 3:45
  know,
• 3:46
  maybe
• 3:46
  this
• 3:46
  just
• 3:46
  reminds
• 3:47
  us
• 3:47
  of
• 3:47
  how
• 3:47
  much
• 3:48
  refinement
• 3:48
  there's
• 3:48
  going
• 3:49
  to
• 3:49
  be
• 3:49
  for
• 3:49
  every
• 3:50
  type
• 3:50
  of
• 3:50
  AI
• 3:51
  in
• 3:51
  retail
• 3:52
  that
• 3:52
  we
• 3:52
  think
• 3:53
  of
• 3:53
  going
• 3:54
  into
• 3:54
  the
• 3:54
  next,
• 3:55
  you
• 3:56
  know,
• 3:56
  decade.
• 3:56
  Who
• 3:57
  knows?
• 3:58
  You
• 3:58
  know,
• 3:59
  going
• 3:59
  back
• 3:59
  to
• 3:59
  what
• 3:59
  I
• 4:00
  heard
• 4:00
  at
• 4:00
  the
• 4:00
  lead,
• 4:00
  though,
• 4:00
  was
• 4:01
  a
• 4:01
  lot
• 4:01
  of
• 4:01
  enthusiasm
• 4:02
  for
• 4:02
  test
• 4:02
  and
• 4:03
  learn
• 4:03
  culture
• 4:04
  being
• 4:05
  first
• 4:05
  instead
• 4:06
  of
• 4:06
  just
• 4:06
  a
• 4:06
  fast
• 4:06
  follower
• 4:07
  and
• 4:07
  then
• 4:07
  learn,
• 4:08
  you
• 4:08
  know,
• 4:08
  iterating
• 4:08
  fast
• 4:09
  from
• 4:09
  there.
• 4:09
  And
• 4:09
  so
• 4:10
  you
• 4:11
  hope
• 4:11
  that
• 4:11
  Nomad
• 4:12
  learns.
• 4:13
  Starbucks
• 4:13
  has
• 4:13
  shown
• 4:14
  an
• 4:14
  affinity
• 4:14
  for
• 4:14
  that.
• 4:15
  And
• 4:15
  so
• 4:15
  I
• 4:15
  don't
• 4:15
  think
• 4:15
  we
• 4:16
  have
• 4:16
  to
• 4:16
  be
• 4:16
  worried
• 4:16
  about
• 4:17
  Starbucks
• 4:17
  on
• 4:17
  that
• 4:18
  front
• 4:18
  specifically.
• 4:20
  So,
• 4:20
  yeah,
• 4:21
  that's
• 4:21
  my
• 4:21
  take.
• 4:21
  I
• 4:21
  think
• 4:22
  there's
• 4:22
  a
• 4:22
  lot
• 4:22
  to
• 4:22
  learn
• 4:22
  from
• 4:23
  it.
• 4:24
  Yeah,
• 4:24
  I
• 4:24
  think.
• 4:24
  I
• 4:25
  think
• 4:25
  100%
• 4:26
  it's.
• 4:26
  I
• 4:26
  think
• 4:26
  it's
• 4:27
  definitively
• 4:27
  a
• 4:27
  stumble.
• 4:28
  You
• 4:28
  know,
• 4:28
  I
• 4:28
  think
• 4:28
  the
• 4:28
  interesting
• 4:29
  part
• 4:29
  about
• 4:29
  this,
• 4:29
  I
• 4:29
  think
• 4:30
  there's
• 4:30
  two
• 4:30
  things
• 4:30
  I'd
• 4:30
  say
• 4:30
  off
• 4:31
  what
• 4:31
  you
• 4:31
  said.
• 4:31
  I
• 4:31
  think
• 4:31
  one
• 4:31
  is,
• 4:32
  what
• 4:32
  is
• 4:32
  the
• 4:32
  interesting
• 4:33
  point
• 4:33
  is
• 4:33
  the
• 4:33
  egg
• 4:33
  on
• 4:33
  the
• 4:33
  face.
• 4:34
  Like,
• 4:34
  when
• 4:34
  you're
• 4:34
  talking
• 4:34
  about
• 4:35
  this
• 4:35
  being
• 4:35
  like
• 4:35
  a
• 4:35
  significant
• 4:36
  part
• 4:36
  of
• 4:36
  your
• 4:36
  operational
• 4:37
  improvements
• 4:37
  in
• 4:37
  February,
• 4:38
  it's
• 4:38
  kind
• 4:39
  of
• 4:39
  like,
• 4:39
  oh,
• 4:39
  you
• 4:39
  got
• 4:39
  to
• 4:39
  make
• 4:40
  an
• 4:40
  about
• 4:40
  face
• 4:40
  on
• 4:40
  that.
• 4:40
  That's
• 4:41
  not
• 4:41
  good
• 4:41
  for
• 4:41
  Starbucks.
• 4:41
  It's
• 4:42
  definitely
• 4:42
  not
• 4:42
  good
• 4:42
  for
• 4:42
  Nomad.
• 4:43
  Go
• 4:43
  for
• 4:43
  the
• 4:43
  reasons
• 4:44
  you
• 4:44
  said,
• 4:44
  too.
• 4:46
  And
• 4:46
  so,
• 4:47
  you
• 4:47
  know,
• 4:47
  I
• 4:47
  think
• 4:47
  that
• 4:47
  tells
• 4:48
  me
• 4:48
  too,
• 4:48
  you
• 4:48
  can't
• 4:48
  always
• 4:48
  buy
• 4:49
  into
• 4:49
  the
• 4:49
  hype
• 4:49
  cycle.
• 4:50
  You
• 4:50
  got
• 4:50
  to
• 4:50
  give
• 4:50
  it
• 4:50
  time
• 4:51
  and
• 4:52
  to
• 4:52
  do
• 4:52
  this
• 4:52
  effectively.
• 4:53
  My
• 4:53
  first
• 4:54
  takeaway
• 4:54
  is,
• 4:55
  my
• 4:55
  first
• 4:55
  takeaway
• 4:56
  is
• 4:56
  you
• 4:56
  have
• 4:56
  to
• 4:57
  have
• 4:57
  continuous
• 4:57
  learning.
• 4:58
  It's
• 4:58
  not
• 4:58
  just
• 4:59
  jumping
• 4:59
  be
• 5:00
  first
• 5:00
  to
• 5:01
  try
• 5:01
  new
• 5:01
  technologies
• 5:01
  or
• 5:02
  experiment,
• 5:02
  but
• 5:02
  you
• 5:02
  have
• 5:02
  to
• 5:03
  be
• 5:03
  continuously
• 5:03
  learning
• 5:04
  and
• 5:04
  basically
• 5:05
  coming
• 5:05
  at
• 5:05
  it
• 5:05
  with
• 5:05
  the
• 5:05
  mindset
• 5:06
  of
• 5:06
  you're
• 5:06
  never
• 5:07
  going
• 5:07
  to
• 5:07
  get
• 5:07
  this
• 5:07
  right,
• 5:08
  and
• 5:08
  so
• 5:08
  you
• 5:08
  almost
• 5:08
  don't
• 5:09
  even
• 5:09
  want
• 5:09
  to
• 5:09
  talk
• 5:09
  about
• 5:10
  these
• 5:10
  things
• 5:10
  publicly
• 5:10
  because
• 5:11
  you're
• 5:11
  kind
• 5:11
  of
• 5:11
  setting
• 5:11
  yourself
• 5:12
  up
• 5:12
  for
• 5:12
  failure
• 5:13
  when
• 5:13
  you
• 5:13
  start
• 5:14
  to
• 5:14
  do
• 5:14
  that,
• 5:14
  especially
• 5:14
  when
• 5:15
  they're
• 5:15
  just
• 5:15
  at
• 5:15
  the
• 5:15
  early
• 5:15
  stages
• 5:16
  of
• 5:16
  implementation.
• 5:17
  The
• 5:17
  other
• 5:17
  part,
• 5:17
  the
• 5:18
  word
• 5:18
  you
• 5:18
  said
• 5:18
  predictability,
• 5:19
  Laura.
• 5:20
  For
• 5:20
  me,
• 5:20
  the
• 5:20
  reason
• 5:20
  I
• 5:21
  think
• 5:21
  that's
• 5:21
  the
• 5:21
  number
• 5:22
  one
• 5:22
  reason
• 5:22
  it's
• 5:22
  a
• 5:22
  stumble
• 5:23
  is
• 5:23
  it's
• 5:24
  predictability.
• 5:24
  But
• 5:24
  it
• 5:24
  comes
• 5:25
  down
• 5:25
  to
• 5:25
  also
• 5:25
  the
• 5:25
  predictability
• 5:26
  angle,
• 5:26
  I
• 5:26
  would
• 5:26
  say
• 5:26
  too,
• 5:27
  is
• 5:27
  it
• 5:27
  comes
• 5:27
  down
• 5:27
  to
• 5:27
  the
• 5:27
  predictability
• 5:28
  of
• 5:28
  who's
• 5:29
  using
• 5:29
  the
• 5:29
  technology
• 5:30
  when
• 5:31
  your
• 5:31
  technology
• 5:32
  requires
• 5:32
  an
• 5:32
  employee
• 5:33
  to
• 5:33
  use
• 5:33
  it.
• 5:35
  With
• 5:35
  the
• 5:35
  turnover
• 5:35
  in
• 5:36
  the
• 5:36
  retail
• 5:36
  industry,
• 5:37
  that
• 5:37
  just,
• 5:38
  that
• 5:38
  just
• 5:38
  is
• 5:38
  a
• 5:38
  massive
• 5:39
  issue.
• 5:39
  And
• 5:40
  so
• 5:40
  whenever
• 5:41
  that
• 5:42
  fact
• 5:42
  is
• 5:42
  in
• 5:42
  play,
• 5:43
  it's
• 5:43
  hard
• 5:43
  to
• 5:43
  deploy
• 5:44
  a
• 5:44
  system
• 5:44
  that
• 5:45
  works
• 5:45
  consistently
• 5:46
  the
• 5:46
  same
• 5:46
  way
• 5:46
  every
• 5:46
  time.
• 5:47
  And
• 5:47
  that's
• 5:48
  where
• 5:48
  automation
• 5:48
  works
• 5:49
  best.
• 5:49
  Whether
• 5:49
  it's
• 5:49
  AI,
• 5:50
  computer
• 5:51
  vision,
• 5:51
  whatever.
• 5:51
  You
• 5:52
  want
• 5:52
  to
• 5:52
  be
• 5:52
  doing
• 5:52
  the
• 5:52
  same
• 5:53
  thing
• 5:53
  the
• 5:53
  same
• 5:53
  way
• 5:54
  every
• 5:54
  time.
• 5:55
  That's
• 5:55
  why
• 5:55
  things
• 5:56
  like
• 5:56
  robotics,
• 5:57
  fixed
• 5:57
  position
• 5:57
  cameras
• 5:58
  like
• 5:58
  you
• 5:58
  mentioned,
• 5:58
  or
• 5:59
  robotics
• 5:59
  that
• 6:00
  always
• 6:00
  do
• 6:00
  it
• 6:00
  the
• 6:01
  same
• 6:01
  way,
• 6:01
  because
• 6:01
  it's
• 6:02
  a
• 6:02
  frickin
• 6:03
  robot,
• 6:03
  not
• 6:03
  a
• 6:03
  person
• 6:04
  that
• 6:04
  you
• 6:04
  have
• 6:04
  to
• 6:05
  train
• 6:05
  each
• 6:06
  time,
• 6:06
  or
• 6:06
  even
• 6:06
  overhead
• 6:07
  rfid,
• 6:08
  which
• 6:08
  we're
• 6:08
  going
• 6:08
  to
• 6:08
  talk
• 6:09
  about
• 6:09
  as
• 6:10
  well.
• 6:10
  So
• 6:12
  those
• 6:13
  are
• 6:13
  where
• 6:13
  I
• 6:13
  see
• 6:13
  things
• 6:13
  going
• 6:14
  in
• 6:14
  the
• 6:14
  long
• 6:15
  run.
• 6:15
  And
• 6:15
  that's
• 6:15
  why
• 6:15
  I
• 6:16
  think
• 6:16
  this
• 6:16
  is,
• 6:16
  it's
• 6:17
  a
• 6:17
  much
• 6:17
  harder
• 6:18
  technology
• 6:18
  to
• 6:18
  implement
• 6:19
  than
• 6:19
  people
• 6:19
  think.
• 6:19
  Even
• 6:20
  though
• 6:20
  to
• 6:20
  your
• 6:20
  point,
• 6:21
  it's
• 6:22
  been
• 6:22
  around
• 6:22
  for
• 6:22
  a
• 6:23
  really
• 6:23
  long
• 6:23
  time.
• 6:24
  Like
• 6:24
  self
• 6:24
  scanning
• 6:25
  with
• 6:25
  a,
• 6:25
  with
• 6:25
  the
• 6:26
  employee
• 6:26
  device
• 6:26
  or
• 6:27
  an
• 6:27
  iPad
• 6:27
  is
• 6:27
  not
• 6:27
  new,
• 6:28
  but
• 6:28
  it's
• 6:29
  really
• 6:29
  hard
• 6:29
  to
• 6:29
  do
• 6:29
  it
• 6:29
  well
• 6:30
  for
• 6:30
  the
• 6:30
  reasons
• 6:30
  we.
• 6:31
  Yeah,
• 6:31
  I
• 6:31
  mean,
• 6:32
  and
• 6:32
  I
• 6:32
  think
• 6:32
  from
• 6:32
  the
• 6:32
  tech
• 6:33
  company
• 6:33
  perspective,
• 6:34
  maybe
• 6:34
  that
• 6:35
  it
• 6:35
  elevates
• 6:36
  the
• 6:37
  need
• 6:37
  to
• 6:38
  emphasize
• 6:39
  employee
• 6:39
  training
• 6:40
  as
• 6:40
  part
• 6:40
  of
• 6:40
  the
• 6:40
  solution.
• 6:41
  Like
• 6:41
  we're
• 6:42
  going
• 6:42
  to
• 6:42
  help,
• 6:42
  this
• 6:43
  is
• 6:43
  how
• 6:43
  we're
• 6:43
  going
• 6:43
  to
• 6:43
  help
• 6:44
  your
• 6:44
  employees
• 6:44
  learn.
• 6:44
  Because
• 6:45
  like
• 6:45
  you
• 6:45
  said,
• 6:45
  they
• 6:45
  have
• 6:45
  to,
• 6:46
  they
• 6:47
  have
• 6:47
  to
• 6:47
  train
• 6:47
  people
• 6:48
  quickly
• 6:48
  and
• 6:49
  you
• 6:49
  know,
• 6:49
  a
• 6:49
  new
• 6:50
  person
• 6:50
  every
• 6:50
  day.
• 6:51
  And
• 6:51
  if
• 6:52
  that's
• 6:52
  going
• 6:52
  to
• 6:52
  be
• 6:52
  a
• 6:52
  huge
• 6:53
  part
• 6:53
  of
• 6:53
  it,
• 6:53
  and
• 6:53
  if
• 6:53
  you're
• 6:54
  going
• 6:54
  to
• 6:54
  promise
• 6:54
  that
• 6:54
  the
• 6:54
  human
• 6:55
  in
• 6:55
  the
• 6:55
  loop
• 6:55
  is
• 6:56
  a
• 6:56
  big
• 6:56
  part
• 6:56
  of
• 6:56
  the
• 6:56
  solution,
• 6:58
  then
• 6:58
  maybe
• 6:59
  employee
• 7:00
  training
• 7:00
  needs
• 7:01
  to
• 7:01
  be
• 7:01
  a
• 7:01
  higher
• 7:01
  priority.
• 7:02
  Yeah,
• 7:03
  and
• 7:04
  when
• 7:04
  I
• 7:04
  hear
• 7:04
  you
• 7:04
  say
• 7:04
  that,
• 7:04
  I'm
• 7:05
  already
• 7:05
  like,
• 7:05
  yeah,
• 7:06
  not
• 7:06
  for
• 7:06
  me,
• 7:06
  like
• 7:07
  as
• 7:07
  a
• 7:07
  former
• 7:07
  executive,
• 7:08
  I'm
• 7:08
  like,
• 7:08
  no,
• 7:08
  not
• 7:09
  for
• 7:09
  me.
• 7:09
  Then
• 7:10
  we're
• 7:10
  going
• 7:10
  to
• 7:10
  look
• 7:10
  for
• 7:10
  a
• 7:10
  different
• 7:11
  answer
• 7:11
  that
• 7:12
  provides
• 7:12
  an
• 7:13
  easier
• 7:13
  path
• 7:13
  to
• 7:14
  what
• 7:14
  we're
• 7:14
  trying
• 7:14
  to
• 7:14
  accomplish
• 7:15
  or
• 7:15
  what
• 7:15
  our
• 7:15
  objective
• 7:16
  is.
• 7:16
  That's
• 7:16
  how
• 7:16
  I
• 7:16
  think
• 7:16
  about
• 7:16
  what
• 7:17
  you
• 7:17
  just
• 7:17
  said,
• 7:17
  Laura.