This document discusses the challenges that retailers face in the digital commerce space. It notes that retailers often make decisions at too aggregate a level without understanding trade-offs, apply flawed logic, and have poor execution due to issues like speed, volume, granularity, and siloed systems. This results in a "ghost economy" where 25% of sales occur at a loss. However, companies like Amazon have found success by focusing on controllable inputs rather than just financial outputs. The document advocates repurposing all customer data through integration and algorithms to provide prioritized action lists that can increase profitability.

1. 1
Making
sense
of
digital
commerce
Michael
Ross
NOAH
conference
2014
13
November
2014

3. 2
Retail
revolution
The
challenges
• Not
making
decisions
• Accepting
default
decisions
• Decisions
made
at
too
aggregate
a
level
• Failure
to
understand
trade-­‐offs
[optimise
in
silo]
• Apply
traditional
–
or
flawed
–
logic
• Poor
execution
• Speed
• Volume
• Granularity
• Digital
exhaust
• Volume
• Granularity
• Variable
costs
• Marketing
economics
• Black
boxes
• Siloed
systems
Atomisation
of
actions
Atomisation
of
data
Explosion
of
complexity
Lack
of
visibility

4. 3
The
ghost
economy
A
€600
billion
data
disconnect
haunting
retail
" Products
marketed
and
orders
taken
for
products
that
‘don’t
exist’
" 25%
of
retail
sales
happening
at
low
or
negative
margin
" Disconnects
in
inventory
and
stock
data,
marketing
and
operations,
shipping
and
delivery-­‐on-­‐
promise
" Not
enough
hands,
eyes
and
analysts
to
manage
the
business

5. 4
The
genius
of
Amazon
Senior
leaders
that
are
new
to
Amazon
are
often
surprised
by
how
little
time
we
spend
discussing
actual
financial
results
or
debating
projected
financial
outputs.
To
be
clear,
we
take
these
financial
outputs
seriously,
but
we
believe
that
focusing
our
energy
on
the
controllable
inputs
to
our
business
is
the
most
effective
way
to
maximize
financial
outputs
over
time.
“
” Extract
from
Jeff
Bezos,
Amazon
CEO,
Letter
to
shareholders
2010

6. 5
Repurposing
all
data
to
drive
proBit

7. 6
Big
Data
Integration
££££
‘Increase
stock
intake
for
high
view,
high
conversion,
low
availability,
core
line
products’
£££
‘Pause
paid
search
spend
on
zero-­‐inventory
products’
££
‘Initiate
Win-­‐Back
program
for
customers
where
we
missed
shipping
on
promise’
£
Identify
high
value
customers
rejected
by
fraud
system
DIGEST
Is
the
business
good
or
bad?
Single
view
of
profit
Decision
Science
Operationalized
Insight
DIAGNOSE
What
is
driving
performance?
De-­‐averaging
and
disaggregation
algorithms
DO
What
actions
should
I
take?
100’s
of
prioritised
action
lists
based
on
predicted
impact
on
profit

8. 7

9. 8

10. 9
Our
clients
DynamicAction
is
not
something
we
had
planned
or
budgeted
for,
but
we
quickly
shifted
gears
when
we
understood
that
it
is
not
just
another
big
data
or
analytics
player,
but
has
the
ability
to
make
our
data
truly
actionable
and
provide
specific
direction
for
increased
profitability.
Kevin
Ertell
VP
eCommerce,
Sur
la
table
“
”

11. 10
The
future