In 2016, e-commerce sales accounted for roughly 8% of total retail sales, growing from a measly 0.6% in 1999. It is estimated that by 2020, U.S. e-commerce sales will approach $500 billion dollars, growing at a 5-year compound annual growth rate (CAGR) of 10%. Given the lower barriers to entry and execution in e-commerce, a number of industries are being disrupted and reinvented as a result. As retailers and consumer goods companies grapple with these changes, they are shifting their focus to growing their digital offerings, while balancing the deployment of inventory across all their channels—wholesale, owned brick-and-mortar retail, and e-commerce. Here we will discuss how to successfully deploy inventory in an omnichannel environment to maximize profit and improve customer service.

1. Strategic Inventory
Management in an
OmnichannelEnvironment
By Rene Saroukhanoff, CPF and Manik Aryapadi
Rene Saroukhanoff | Rene is the Senior Director of Merchandising Reporting Analytics at Levi Strauss
Company. He is responsible for merchandise planning and forecasting analytics, including executing special
projects related to targeted growth initiatives, enhancing inventory and sizing optimization, and delivering
advanced visualization capabilities. He has over 15 years of experience in the Apparel Industry—in multiple
leadership roles and functions. He has a degree in business from University of Southern California and is a certified
professional forecaster (CPF).
Manik Aryapadi | Manik is a Principal in A. T. Kearney’s retail practice with experience in Strategic
Operations and Digital Transformation initiatives. He has led and delivered multiple engagements in consumer
facing industries at the intersection of Planning/Forecasting, Systems Enablement, Organization, and Big Data
Analytics. He holds a graduate degree in engineering management from Northwestern University and a degree in
electrical engineering from Texas AM University. He is a certified Supply Chain professional.
E x e c u t i v e S u m m a r y | In 2016, e-commerce sales accounted for roughly 8% of total retail sales, growing from a
measly 0.6% in 1999. It is estimated that by 2020, U.S. e-commerce sales will approach $500 billion dollars, growing at a 5-year
compound annual growth rate (CAGR) of 10%. Given the lower barriers to entry and execution in e-commerce, a number of
industries are being disrupted and reinvented as a result. As retailers and consumer goods companies grapple with these
changes, they are shifting their focus to growing their digital offerings, while balancing the deployment of inventory across all
their channels—wholesale, owned brick-and-mortar retail, and e-commerce. Here we will discuss how to successfully deploy
inventory in an omnichannel environment to maximize profit and improve customer service. Please note that in this article,
“consumer” refers to the end consumer (those who are directly consuming or purchasing the product); whereas, “customer”
refers to channel partners (wholesalers, department stores, distributors etc.).
I
nearlyAugust2016,Macy’sannounced
that they will be optimizing their store
footprint by shuttering 15% of their
department stores. In the same call, it
also elaborated on how its e-commerce
sales have doubled over the past year
with increased traffic and conversion.
This is the classic predicament for
today’s retailers—how to be relevant in
an increasingly digital world? The silver
lining for brick-and-mortar retailers in
the blockbuster story of e-commerce
growth is that though more and more
consumers are buying products online,
they also prefer the convenience of a
physical store to try on a product, pick up
an item or return an item, or order in store
for direct shipments. (Consumers are here
Copyright © 2017 Journal of Business Forecasting | All Rights Reserved | Winter 2016-2017 | www.ibf.org 37

2. referred to as the end consumers—those
who directly consume or purchase the
product). This means that retailers need
to rapidly evolve to meet the changing
needs of the consumer and get adept
at inventory placement—where they
have the highest likelihood of making a
sale—irrespective of location or channel
preferences.
For global consumer companies
like Levi’s and others, whose products
are sold in several department stores
across the United States, this situation
presents a dilemma and an opportunity.
As we look ahead, we need to learn to
continue to successfully partner with
department stores and other wholesale
retailers, while also ensuring that we have
enough products to continue to grow
our own brick-and-mortar business, and
clicks operations (i.e., physical retail and
e-commerce). The ultimate goal is to
ensure that consumer expectations are
met and fulfilled, no matter what channel
they use to buy our products.
In our experience, there are four key
steps to achieving breakthrough product
profitability across all channels:
1. Effectively Segment Product
Assortment,
2. Proactively Manage Channel Conflict,
3. Enforce Rules-Based Inventory
Allocation, and
4. Engage in Continuous Improvement.
EFFECTIVE PRODUCT
SEGMENTATION
When Michelle Obama wore a J. Crew
dress for the president’s inauguration in
2012,thedressandassociatedaccessories
were sold out within 24 hours. Welcome
to the fashion business! It’s a finicky
world, and what’s hot today may fade out
in a few months, a few weeks, or a few
days. Though we cannot always foresee
exceptional events, we can still use past
performance data, consumer insights,
and strategic guidance to build a product
segmentation model that can be used to
build a consumer focused assortment.
To effectively segment a product
withinmerchandising,weneedtoanalyze
various performance criteria across four
key dimensions. (See Figure 1 for details)
1. Ability to predict (forecastability):
How can we effectively predict a
product based on past per­formance?
For apparel, footwear, and consumer
companies,itiseasiertopredictba­sic
products such as men’s bottoms
(jeans) as opposed to more fashion­
able items such as women’s tops.
2. Ability to fulfill demand (agility):
In addition to evaluating the fore­
castability of an item, it is also
important to analyze how quickly
we can fulfill demand for a particular
product. This will determine the
appropriate supply chain strategies
for getting the product from factory
to store, and eventually to the
consumer.
3. Length of product life (product
life cycle): Active product life cycle
management is critical to ensure
seamless product introduction and
eventual product retirement. Pro­
ducts that are on the shelves for a
few weeks would require different
forecasting, buying, and inventory
management strategies vis-à-vis
those that live for a few months. In
our experience, products with longer
life cycles have more forecastability
versus those with shorter life cycles.
4. Dimension (SKU-location): Within
the apparel and footwear industries,
it is very difficult to predict item
sales and performance at the stock
keeping unit (SKU) level (style, color,
and size) and at the location level.
Setting up various strategies for each
dimensionoftheproducthierarchyis
important to ensure that we capture
information at the lowest common
denominator.
PROACTIVE
CHANNEL CONFLICT
MANAGEMENT
Given the explosion in consumer
shopping choices across multiple chan-
nels, it is important for consumers to
have a seamless experience, no matter
where they shop. Channel proliferation
has led to the same product being avail-
able for purchase through distributors,
wholesalers, independent retailers, and
online players. As an example, we can
purchase men’s jeans on amazon.com,
macys.com, levis.com, kohls.com, local
mom-and-pop shops, and at the physi-
cal locations of department store retailers
(locations are non-exhaustive). Therefore,
it is important for companies like Levi’s to
make sure that there is enough inventory
in stock at various nodes in the supply
chaintofulfilldemandacrossallchannels.
Given that multi-channel merchants
often use varying pricing strategies at
different channels, their product profit­
ability is impacted by when and where
the product is sold, thereby creating a
potential conflict in product placement—
1
gure 1 | Product Segmentation Framework for Apparel and Footwear
ource: A. T. Kearney
Basics
Women’s
Tops
Fast
Fashion
Style
Color
Size
LO
NG
Handbags
PRO
DUCT
LIFE
CYCLE
SHO
RT
LOW HIGH
ABILITYTOPREDICT
LOWHIGH
ABILITY TO FULLFILL DEMAND
Figure 1 | Product Segmentation
Framework for Apparel
and Footwear
Source: A.T. Kearney Analyses
38 Copyright © 2017 Journal of Business Forecasting | All Rights Reserved | Winter 2016-2017 | www.ibf.org

3. especially when an item goes out of stock.
In the event that lack of product becomes
an issue, multi-channel merchants need
to be strategic about how they deploy
inventory to maximize revenue and
profitability (short-term and long-term),
while also balancing customer require­
ments (wholesale, franchise, distributors)
and stay focused on growing owned and
operated channels (bricks and clicks).
In our experience, effective customer
segmentation can help mitigate conflicts
among channels. Unfortunately, many
multi-channel merchants often allocate
inventory on an ad hoc basis to meet
short-term sales targets or to balance
their books. This view of managing
inventory is shortsighted, negatively
impacts brand equity, and erodes trust
with customers (wholesalers, department
stores, distributors etc.) and consumers.
A cohesive customer segmentation
process driven by strategic objectives
can help uncover revenue and margin
opportunities, address weaknesses in the
business, and formalize the process of
inventory allocation.
As outlined in Figure 2, we have seen
successful multi-channel merchants a­dopt
a holistic process for segmenting their
customers based on multiple dimensions
and criteria. As an example, strategic
intensity and customer requirements are
the two key dimensions (as illustrated on
the X-axis and Y-axis), with each of them,
in turn, having four associated criteria.
Each criterion is assigned a weight in
scoring, and is then individually scored on
a range from 1 to 10 (1 being the lowest
score and 10 being the highest score).
The scores are then averaged across the
four criteria and placed on a 2x2 matrix to
segment the appropriate customer.
For instance, if you are a merchant
with saturated market share with a high-
volume customer (i.e., you are one of
their top suppliers), then your focus is not
on growth expectations; rather, it is on
maintaining revenue and margin. Such
a customer would typically rank high in
strategic intensity and high on customer
requirements, thereby qualifying for
being a“key account.”
RULES-BASED
INVENTORY
DEPLOYMENT
Customer Segmentation is easier said
than done, and it is often the first step
towards building a robust rule-based
inventory management solution. In
addition to using customer segmentation
as a foundation, additional dimensions
such as region, demand class, and time
are used to further refine inventory
deployment decisions. These decisions
can be made on a pre-season basis (i.e.,
before a product hits the distribution
center) or on an in-season basis (i.e., after
a product hits the distribution center). For
more details, see Figure 3.
Most apparel and fashion retailers
are concentrated in urban and suburban
locations. This stands in stark contrast
to mass and big box stores, which tend
to be skewed more towards suburban
and semi-urban/rural locations. Why
are store locations important? Because
2
CustomerRequirements
Strategic Intensity
Low
High
HighLow
Support for
promotion, marketing
and branding
Sophistication of
customer-buyer
Service level
expectations
Upside / downside
flexibility
Strategic importance
Margin
Growth expectations
Revenue
Brand X
.com
Brand Y
Boutiques
Independ-
ent Retail
“Key Accounts”
“Retail Other”
“Consumer Direct”
Figure 2 | Customer Segmentation Framework for Inventory Management
Source: A.T. Kearney
Figure 2 | Customer Segmentation Framework for Inventory Management
Figure 3 | Framework for Inventory Management Allocation Logic
Source: A.T. Kearney Analyses
Source: A.T. Kearney Analyses
Description Design Choices
• Prioritization based on
customer segments and
individual customers
• Prioritization based on
geographic regions
• Prioritization based on
store type (e.g.: flagship,
mainline, outlet, etc.)
• Prioritization based on
demand classes: orders,
firm forecasts, forecasts
• Time-period of allocation
Key Dimensions
Customer
Segment
Period
Demand Class
Region
All
segments
are equal
Some
demand
classes have
higher
priority
All demand
classes are
equal
Source: A.T. Kearney
Some
segments
have higher
priority
Each
segment is
ranked
Each
customer
within a
segment is
ranked
Some
customers
have higher
priority
All
customers
within a
segment are
equal
All regions
are equal
Some
regions have
higher
priority
Each region
is ranked
Each
country
within
region is
ranked
Some
countries
have higher
priority
All countries
within a
region are
equal
Each
demand
class is
ranked
Allocation
by
month
Allocation
by quarter
Allocation
by
week
Increasing level of aggregation
Within a segmentAcross segments
Preferred Method for Product X
Store Type
All stores
are equal
Some stores
have higher
priority
Each store
is ranked
Each store
within a
store type is
ranked
Some store
types have
higher
priority
All stores
within a
store type
are equal
Figure 3 | Framework for Inventory Management Allocation Logic
Copyright © 2017 Journal of Business Forecasting | All Rights Reserved | Winter 2016-2017 | www.ibf.org 39

4. the locations of the stores impact the
supply chain strategy and associated in-
store inventory levels. As an example,
higher-traffic urban stores have smaller
back rooms and typically carry far less
inventory than suburban stores. Stores in
urban regions also go through frequent
floor-set updates and assortment changes
to drive variety and improve foot-traffic.
Given these constraints, they need to
be replenished more frequently with a
broader assortment. Factoring in regional
criteria for inventory rules deployment
is essential to maintaining a strong
presentation at the store, and ensuring
that sales are not lost due to stock outs.
Not all store types are created
equal. For instance, flagship stores
are considered marquee stores and
typically carry a broader assortment than
suburban retail stores. Given that most
flagships are in prime tourist locations
(e.g., Times Square in NYC or South Beach
inFlorida’sMiamiBeach),theyaretypically
given higher priority from an inventory
allocation perspective, even if stores in
the suburbs are running lean on an in-
demand product. By segmenting our
storesintoflagships,mainline,outlets,and
anchor stores, we can better account for
fluctuationsinsalespersquarefoot,traffic,
assortment breadth, and conversion.
Lastly, order management and timing
are also vital components of a robust
inventory management process. The
saying “a bird in hand is worth two in the
bush” is an apt analogy for managing
customer orders. A firm order from the
customer typically outweighs a soft order
(i.e., an order without commitment) or
a customer forecast. Though soft orders
and customer forecasts can be used to
manage in-stock levels, it is not best
practice to hold inventory for customers
who do not have a firm order in place
(though there are always exceptions,
which can be handled on an ad hoc
basis). The retail business is seasonal and
a vast majority of retail sales happen in
the back half of the year (back to school
and holidays). The timing of orders and
allocationofinventorybasedonshipment
and on-floor dates are critical to ensuring
that customer orders are fulfilled on-time
and at the agreed-upon service levels.
CULTURE OF
CONTINUOUS
IMPROVEMENT
Resistance to change and siloed ways
of working are the biggest impediments
to successful deployment of an om-
nichannel inventory deployment strategy.
For transformational initiatives to succeed,
implementing data-driven decision mak-
ing processes and building systemic rules
can only take an organization so far. For
any large-scale transformation to stick, it
is important to account for organizational
and people implications.
As an example, at Levi’s we have
created an Omnichannel Inventory Man­
agement Group that reports directly
to the SVP of Merchandise Planning to
drive insights and make tough calls on
allocating product within and across
channels in the event of an inventory
constraint. We also created dashboards
in tableau to push information out to
planners and allocators, who could now
make more informed decisions based on
real-time availability of data, instead of
waiting for weekly reports. (See Figure 4,
for example.)
Based on our experience, there are a
fewcriticalsuccessfactorsthatwillembed
and sustain change in the organization:
• Empower employees to make data-
driven decisions,
• Encourage respectful dissension to
prevent group thinking,
• Adopt a culture of “Why Not” and
“Challenge Assumptions,” and
• Collaborate across functions and si-
loes to achieve breakthrough perfor-
mance.
By adopting these approaches,
we believe many consumer and retail
organizations can accelerate adoption
of omnichannel inventory management
strategies.
—Send Comments to: JBF@ibf.org
References
1. http://www.practicalecommerce.com/
articles/1373-Chart-of-the -Week-
Online-Holiday-Shopping-1999-2009
2. https://www.internetretailer.com/2016/
01/29/online-sales-will-reach-523-
billion-2020-us
Figure 4 | Sample Dashboards to Drive Productive Decision Making
4
Figure 4 | Sample Dashboards to Drive Productive Decision
Making
Drill Down Dashboard 2x2 Dashboard and Time Series SKU / Store Dashboard
Purpose
Quickly and visually highlight the areas
of opportunity across store clusters,
stores, sizes, styles and geography.
Identify concentration of opportunity
across SKU-Door productivity to inform
investment and allocation decisions
Quantify and detail opportunity across
SKU-Doors by various filters and cuts –
issues goods request or drop into SAP
Key Feature
Dynamic drill-down interface to view
opportunity across multiple dimensions
YoY view of quadrant performance over
time and weekly snapshots as needed
Detail behind analytics driving
dashboards of the report
Source. A.T. Kearney
Source: A.T. Kearney Analyses
40 Copyright © 2017 Journal of Business Forecasting | All Rights Reserved | Winter 2016-2017 | www.ibf.org