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Omnichannel’s Biggest Challenge – Leadership & Corporate Culture
Anoop KulshreshthaVice President, Digital Technology
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Omnichannel by numbers:
• E-Retail sales are forecast to increase by 62% to $327 billion in 2016 from $202 billion in 2012.
• Sales on ‘smartphones’ will touch $27 billion.• 2014 Cyber Monday had a peak traffic of 13
million V/PM. In 2012 it was 8.5 million V/PM.• 63% of searchers use multiple devices to find
local business.• 80% of local searches on mobile phone
converts.
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Omnichannel goes beyond fulfillment
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Omnichannel Framework• Synchronized operating model in which all of
company’s channels are aligned and present a single face to the customer.
• Brand effectively operates as a single channel, orchestrating high value customer experience across all touch points.
• Customer’s each interaction becomes seamless extension of the previous interaction.
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Omnichannel Framework• Omnichannel retailers are nimble enough to
respond to customer’s increasingly dynamic, accessible and continuous decision making.
• Customer’s expectations: Know Me, Show Me You Know Me, Enable Me & Value Me.
• Multi-channel is NOT omnichannel.
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Omnichannel Opportunities
• Cohesive & collaborative internal processes.• Designing omnichannel capable fulfillment
operations.• Customer centricity• Data driven decision management.
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Cohesive & collaborative internal processes – Failure points
• Technology infrastructure investments before equipping internal processes.
• Lack of visibility in any given team’s working.• Structural constraints such as
disproportionately sized business within a brand.
• Not all channels are owned by the same organization within the company.
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Cohesive & collaborative internal processes - Solutions
• Every department needs to be in complete alignment.
• Create synchronized channel SLA, goals and targets.
• Creating omnichannel organization models should be a priority.
• Move beyond traditional business KPI to measure success.
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Cohesive & collaborative internal processes - Solutions
• Promote cross functional teams– Leader is an enabler– Managing diversity of culture and thoughts– Trust is even more crucial for success– Clear goals are drivers of autonomy– Early “wins” are important– Constant communication is the glue
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Designing Omnichannel Capable Fulfillment Operations
• Buy online and pick it up in the store.• Walk to a store, try it on & then get it
delivered to your home.• Know exact shipping costs & delivery time
before placing an order.• Buy online and then return it at the store.• Get your order fulfilled from multiple
locations.
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Designing Omnichannel Capable Fulfillment Operations
• Evaluate synergies across channels.
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Designing Omnichannel Capable Fulfillment Operations
• Find the best operating methods.
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Designing Omnichannel Capable Fulfillment Operations
• Optimal technology stack for each operating method
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Designing Omnichannel Capable Fulfillment Operations
• Define optimal flow path
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Designing Omnichannel Capable Fulfillment Operations
• Choose specific technology– Pick by paper/RF / by voice / by light– Balance between performance, flexibility and cost.
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Customer vs Product Centricity
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Customer Centricity – Building Blocks
• Customer Life-Cycle View– Reorient entire business model around customer.– Clear articulation of the value that customer
represents to the bottomline.– Defined and quantified customer segmentation
strategy.– Business streams deliver maximum value to the
best customer for the least cost.
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Customer Centricity – Building Blocks
• Solution Mindset– Solutions replace products as basic customer
value preposition.– Work with competitors and partners to fulfill
customer needs.– Go beyond off-the-self solutions to customized
products.
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Customer Centricity – Building Blocks
• Can-Do Customer Interface– Deploy skills and authority to tailor solutions at
point of contact.– Develop more self service options for the
customers.
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Customer Centricity – Building Blocks
• Fit-For-Purpose Business Processes– Reduce organizational complexities for your most
profitable and lucrative products.– Minimize one off workarounds.
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Data-Driven Decision Management
–DDDM is an approach to business governance that values decisions that
can be backed up with data that can be verified.
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Data-Driven Decision Management
• Google Project Oxygen
– 8 simple rules for being a better manager.
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Data-Driven Decision Management- Project Oxygen
• Step 1- Collect Data– Start with a question and define what information
is required. “Do managers actually matters?”• Step 2 – What data to use– Existing data ( reviews) – New data (Segmentation into top and bottom
quartile)
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Data-Driven Decision Management- Project Oxygen
• Step 3- Analytics– Regression analysis reveals big difference in team
productivity, happiness and turnover.• Step 4 – New data collection. – HR instituted a great manager award.– Additional data used for text analysis.
• Step 5 – Using the insights– 8 point recommendation on how to be a better
manager.
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Data-Driven Decision Management – Applications in Retail – Data Science
• Advanced Data Modeling Perquisites
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Data-Driven Decision Management – Applications in Retail
• “Past results do not guarantee future performance ” – Modeling future based upon learning from past is not enough.
• Clear & diversified data strategy - prepare multiple data sources including external data.
• Use multiple models:– RFM model (recent – frequency – monetary value)– Advanced model to predict customer reaction to
product / price points / brands.
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Data-Driven Decision Management – Applications in Retail
• Point of Sale– Are there more efficient ways to market?• Email/Text based targeted marketing through POS• Ability to ‘flash sale’ to the customer based upon past
purchase history.
– Do I have the right amount of store inventory?• Past order history can provide an insight into strong
and lean periods for seasonal and cyclic products.
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Data-Driven Decision Management – Applications in Retail
• Price Optimization– Retail inventory, pricing and POS data spread across
multiple systems– Faster processing time to answer questions like:
• Are higher price products selling in select markets?• Should we have geography based inventory/pricing
optimization?
– Leverage big data to migrate all required data to centralized hub.
– Use techniques such as MapReduce to present daily intelligence in a consolidated pricing portal.
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Questions…..