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SPAR Austria's Robot Experiment Is Expanding Fast | Fast Five Shorts · Omni Talk Retail

• 0:00
  Spar
• 0:00
  Austria
• 0:00
  is
• 0:01
  expanding
• 0:01
  its
• 0:01
  use
• 0:01
  of
• 0:02
  Simbi's
• 0:02
  TALLY
• 0:03
  inventory
• 0:03
  robot
• 0:04
  from
• 0:04
  a
• 0:04
  successful
• 0:05
  two
• 0:05
  store
• 0:05
  pilot
• 0:06
  to
• 0:06
  six
• 0:06
  Eurospar
• 0:07
  and
• 0:07
  Interspar
• 0:08
  stores,
• 0:08
  making
• 0:09
  it
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  the
• 0:09
  first
• 0:09
  food
• 0:10
  retailer
• 0:10
  in
• 0:10
  Austria
• 0:11
  to
• 0:11
  use
• 0:11
  an
• 0:12
  inventory
• 0:12
  robot
• 0:13
  in
• 0:13
  regular
• 0:13
  store
• 0:14
  operations.
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  According
• 0:15
  to
• 0:15
  Spar
• 0:15
  International,
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  the
• 0:16
  robot
• 0:17
  moves
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  through
• 0:17
  stores
• 0:17
  several
• 0:18
  times
• 0:18
  a
• 0:18
  day,
• 0:19
  scanning
• 0:19
  shelves,
• 0:19
  identifying
• 0:20
  inventory
• 0:21
  levels
• 0:21
  and
• 0:21
  gaps,
• 0:22
  and
• 0:22
  automatically
• 0:23
  transmitting
• 0:23
  that
• 0:23
  information
• 0:24
  to
• 0:24
  employees
• 0:24
  mobile
• 0:25
  devices
• 0:26
  without
• 0:26
  disrupting
• 0:26
  daily
• 0:27
  operations.
• 0:28
  The
• 0:28
  initial
• 0:28
  five
• 0:29
  month
• 0:29
  pilot
• 0:29
  was
• 0:30
  conducted
• 0:30
  at
• 0:30
  Eurospar
• 0:31
  in
• 0:31
  Vienna
• 0:32
  and
• 0:32
  one
• 0:32
  Interspar
• 0:33
  store
• 0:33
  in
• 0:33
  Eisenstadt,
• 0:34
  my
• 0:35
  favorite
• 0:35
  city
• 0:35
  in
• 0:36
  Germany,
• 0:36
  to
• 0:37
  say,
• 0:37
  and
• 0:38
  demonstrated
• 0:38
  that
• 0:38
  automated
• 0:39
  shelf
• 0:39
  scans
• 0:40
  can
• 0:40
  significantly
• 0:40
  reduce
• 0:41
  the
• 0:41
  time
• 0:41
  employees
• 0:42
  spend
• 0:42
  on
• 0:42
  inspection
• 0:43
  rounds.
• 0:43
  The
• 0:44
  expansion
• 0:44
  gives
• 0:44
  six
• 0:45
  stores
• 0:45
  the
• 0:45
  technology
• 0:46
  and
• 0:46
  the
• 0:46
  aim
• 0:46
  is
• 0:47
  explicitly
• 0:48
  dual.
• 0:48
  One,
• 0:49
  reduce
• 0:49
  employee
• 0:50
  workload
• 0:50
  while
• 0:50
  two
• 0:51
  employees
• 0:51
  improving
• 0:52
  product
• 0:52
  availability
• 0:52
  for
• 0:53
  consumers.
• 0:54
  Shelley,
• 0:55
  the
• 0:55
  audience
• 0:56
  no
• 0:56
  doubt
• 0:56
  knows
• 0:57
  where
• 0:57
  I
• 0:57
  come
• 0:57
  down
• 0:57
  on
• 0:57
  in
• 0:58
  store
• 0:58
  robotics,
• 0:58
  but
• 0:59
  what
• 0:59
  are
• 0:59
  the
• 0:59
  pros
• 0:59
  and
• 1:00
  cons
• 1:00
  with
• 1:00
  robots
• 1:01
  as
• 1:01
  you
• 1:01
  see
• 1:01
  it,
• 1:01
  and
• 1:02
  do
• 1:02
  you
• 1:02
  see
• 1:02
  any
• 1:03
  significance
• 1:03
  in
• 1:03
  Spar,
• 1:04
  particularly
• 1:05
  getting
• 1:05
  behind
• 1:05
  them?
• 1:06
  Well,
• 1:06
  on
• 1:06
  this,
• 1:07
  I
• 1:07
  think,
• 1:07
  you
• 1:08
  know,
• 1:08
  and
• 1:08
  you've
• 1:08
  been
• 1:08
  in
• 1:08
  Europe
• 1:08
  a
• 1:09
  lot
• 1:09
  lately
• 1:09
  and
• 1:09
  you've
• 1:09
  seen
• 1:10
  a
• 1:10
  lot
• 1:10
  of
• 1:10
  retail
• 1:10
  technology,
• 1:11
  but
• 1:12
  Europeans
• 1:12
  are
• 1:13
  famously
• 1:13
  disciplined
• 1:14
  operators.
• 1:14
  And
• 1:15
  so
• 1:15
  when
• 1:15
  they're
• 1:15
  scaling
• 1:15
  technology,
• 1:16
  it
• 1:16
  means
• 1:16
  it
• 1:17
  scales
• 1:17
  because
• 1:17
  it's
• 1:17
  working.
• 1:18
  And
• 1:19
  I
• 1:19
  think
• 1:19
  this
• 1:19
  is
• 1:20
  an
• 1:20
  example
• 1:20
  of
• 1:20
  getting
• 1:20
  data
• 1:21
  faster
• 1:21
  and
• 1:22
  becoming
• 1:22
  more
• 1:22
  efficient.
• 1:23
  So
• 1:24
  I
• 1:24
  think
• 1:24
  that
• 1:24
  that
• 1:24
  part's
• 1:25
  exciting.
• 1:25
  I've
• 1:26
  been
• 1:26
  a
• 1:26
  part
• 1:26
  of
• 1:27
  inventory
• 1:28
  processes
• 1:29
  in
• 1:29
  stores
• 1:29
  at
• 1:30
  several
• 1:30
  points
• 1:30
  in
• 1:30
  my
• 1:31
  career
• 1:31
  early
• 1:31
  on,
• 1:32
  and
• 1:32
  no
• 1:32
  one
• 1:32
  looks
• 1:33
  forward
• 1:33
  to
• 1:33
  them.
• 1:34
  It
• 1:34
  takes
• 1:35
  a
• 1:35
  lot
• 1:35
  of
• 1:35
  labor
• 1:36
  to
• 1:36
  accomplish
• 1:36
  it.
• 1:37
  It
• 1:37
  is
• 1:37
  arduous
• 1:38
  work.
• 1:38
  And
• 1:39
  so
• 1:39
  I
• 1:39
  think
• 1:39
  this
• 1:39
  is
• 1:39
  an
• 1:40
  example
• 1:40
  of
• 1:41
  robotics
• 1:42
  really
• 1:42
  delivering
• 1:43
  against
• 1:43
  the
• 1:43
  ability
• 1:44
  to
• 1:44
  do
• 1:44
  this
• 1:44
  more
• 1:45
  efficiently
• 1:45
  and
• 1:45
  leave
• 1:46
  storing
• 1:46
  store
• 1:46
  associates
• 1:47
  open
• 1:47
  to,
• 1:48
  to
• 1:48
  and
• 1:48
  that
• 1:49
  payroll
• 1:49
  open
• 1:49
  to
• 1:49
  really
• 1:50
  service
• 1:50
  customers
• 1:50
  well.
• 1:51
  So
• 1:51
  this
• 1:51
  is
• 1:51
  exciting.
• 1:52
  Yeah,
• 1:52
  yeah.
• 1:53
  And
• 1:53
  I'm
• 1:53
  going
• 1:53
  to
• 1:53
  add
• 1:53
  a
• 1:54
  yes
• 1:54
  and
• 1:54
  to
• 1:54
  that
• 1:54
  because
• 1:54
  I
• 1:55
  agree
• 1:55
  with
• 1:55
  everything
• 1:55
  you
• 1:55
  said
• 1:56
  and
• 1:56
  I've
• 1:56
  talked
• 1:56
  about,
• 1:57
  you
• 1:57
  know,
• 1:57
  in
• 1:57
  store
• 1:58
  robotics,
• 1:58
  particularly
• 1:59
  in
• 1:59
  the
• 1:59
  grocery
• 1:59
  environment,
• 2:00
  being
• 2:00
  one
• 2:01
  of
• 2:01
  the
• 2:01
  linchpins
• 2:01
  of
• 2:02
  a
• 2:02
  truly,
• 2:02
  you
• 2:02
  know,
• 2:02
  connected
• 2:03
  store
• 2:03
  idea.
• 2:03
  But
• 2:03
  the
• 2:04
  other
• 2:04
  thing
• 2:04
  about
• 2:04
  this
• 2:04
  headline
• 2:05
  that
• 2:05
  I
• 2:05
  think
• 2:05
  is
• 2:05
  really
• 2:05
  interesting,
• 2:06
  Shelley,
• 2:06
  is,
• 2:07
  is
• 2:07
  the
• 2:07
  size
• 2:08
  of
• 2:08
  the
• 2:08
  typical
• 2:08
  Spar
• 2:09
  stores.
• 2:10
  You
• 2:10
  know,
• 2:10
  I
• 2:10
  did
• 2:10
  some
• 2:10
  research
• 2:11
  on
• 2:11
  that.
• 2:11
  They're
• 2:11
  like
• 2:11
  20
• 2:12
  to
• 2:12
  60,000ft.
• 2:13
  So
• 2:13
  they
• 2:13
  can
• 2:14
  be
• 2:14
  bigger,
• 2:14
  they
• 2:14
  can
• 2:14
  be
• 2:15
  like
• 2:15
  the
• 2:15
  traditional
• 2:15
  US
• 2:15
  grocery
• 2:16
  store
• 2:16
  size,
• 2:17
  but
• 2:17
  they
• 2:17
  can
• 2:17
  get
• 2:17
  down
• 2:18
  to
• 2:18
  20,000ft.
• 2:19
  So
• 2:19
  to
• 2:19
  your
• 2:20
  point,
• 2:20
  with
• 2:20
  European
• 2:21
  retailers
• 2:21
  and
• 2:21
  the
• 2:21
  operational
• 2:22
  discipline
• 2:22
  they
• 2:23
  put
• 2:23
  towards
• 2:23
  things,
• 2:24
  that
• 2:24
  means
• 2:24
  you
• 2:25
  have
• 2:25
  a
• 2:25
  large
• 2:25
  European
• 2:26
  retailer
• 2:26
  with
• 2:27
  a
• 2:27
  huge
• 2:27
  store
• 2:27
  base
• 2:28
  that
• 2:28
  is
• 2:28
  potentially,
• 2:29
  potentially
• 2:30
  finding
• 2:31
  value
• 2:31
  in
• 2:31
  a
• 2:31
  robot
• 2:32
  in
• 2:32
  even
• 2:33
  smaller
• 2:33
  footprints
• 2:34
  relative
• 2:34
  to
• 2:35
  where
• 2:35
  we've
• 2:35
  seen
• 2:35
  robots
• 2:36
  operate
• 2:36
  to
• 2:36
  date.
• 2:37
  And,
• 2:37
  you
• 2:37
  know,
• 2:37
  for
• 2:38
  that
• 2:38
  for
• 2:38
  those
• 2:38
  maybe
• 2:38
  that
• 2:38
  aren't
• 2:39
  as
• 2:39
  familiar,
• 2:39
  like,
• 2:39
  we've
• 2:40
  seen
• 2:40
  them
• 2:40
  be
• 2:40
  successfully
• 2:41
  deployed
• 2:41
  at
• 2:41
  schnooks
• 2:42
  in
• 2:42
  the
• 2:42
  U.S.
• 2:42
  which
• 2:42
  is
• 2:42
  a
• 2:43
  traditional
• 2:43
  U.S.
• 2:43
  grocer.
• 2:44
  Traditional
• 2:44
  U.S.
• 2:45
  size
• 2:45
  of
• 2:46
  a
• 2:46
  grocer,
• 2:46
  and
• 2:46
  also
• 2:47
  warehouse
• 2:47
  clubs
• 2:47
  like
• 2:47
  BJ's,
• 2:48
  which
• 2:48
  is
• 2:48
  just,
• 2:48
  you
• 2:48
  know,
• 2:49
  a
• 2:49
  massive
• 2:49
  warehouse
• 2:50
  operation.
• 2:51
  So
• 2:51
  this
• 2:51
  is
• 2:51
  a
• 2:51
  very
• 2:52
  different
• 2:52
  angle
• 2:52
  here
• 2:52
  where
• 2:53
  you
• 2:53
  start
• 2:53
  getting
• 2:53
  into,
• 2:54
  you
• 2:54
  know,
• 2:54
  the
• 2:55
  smaller
• 2:55
  footprints
• 2:55
  where
• 2:56
  the
• 2:56
  ROI
• 2:56
  can
• 2:57
  potentially
• 2:57
  pay
• 2:58
  back.
• 2:58
  Because
• 2:58
  if
• 2:58
  that
• 2:59
  happens,
• 2:59
  then
• 3:00
  look
• 3:00
  out,
• 3:00
  because
• 3:00
  then
• 3:01
  you
• 3:01
  start
• 3:01
  reaching
• 3:01
  the
• 3:01
  hypermarkets,
• 3:02
  particularly
• 3:03
  over
• 3:03
  in
• 3:03
  Europe,
• 3:04
  and
• 3:04
  potentially
• 3:05
  even
• 3:05
  get
• 3:05
  into
• 3:05
  the
• 3:05
  convenience
• 3:06
  store
• 3:06
  arena,
• 3:07
  too,
• 3:07
  if
• 3:07
  you
• 3:08
  can
• 3:08
  figure
• 3:08
  out
• 3:08
  the
• 3:08
  right
• 3:09
  mechanism
• 3:10
  by
• 3:10
  which
• 3:10
  the
• 3:11
  the
• 3:11
  robot
• 3:11
  and
• 3:11
  the
• 3:12
  ROI
• 3:12
  can
• 3:12
  pay
• 3:12
  off
• 3:13
  based
• 3:13
  on
• 3:13
  all
• 3:14
  the
• 3:14
  use
• 3:14
  cases
• 3:14
  you
• 3:14
  just
• 3:15
  talked
• 3:15
  about.
• 3:15
  Shelley
• 3:16
  I
• 3:16
  think
• 3:16
  it's
• 3:16
  great.
• 3:16
  It's
• 3:17
  a
• 3:17
  really
• 3:17
  exciting
• 3:17
  time
• 3:18
  to
• 3:18
  see
• 3:18
  robotics
• 3:18
  in
• 3:18
  retail.