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How Retailers Can Compete With Amazon At Its Own Supply Chain Game

  • Written by  Andrea Morgan-Vandome, Celect

0aaaAndrea Morgan-Vandome CelectWhile few things remain constant in retail, the customer always comes first. And in today’s Amazon Prime world, customers demand faster, cheaper and more convenient fulfillment options than ever before. Retailers are scrambling to keep pace, offering everything from pre-selected delivery slots and buy online, pick up-in-store (BOPIS) to two-hour delivery windows in an effort to provide the seamless, channel-less experience customers expect.

Yet retailers are struggling to accurately determine what, when, where and how much customers will buy. To beat this real-time “last mile” supply chain challenge and successfully compete with Amazon, retailers must take a page from the retail giant’s own playbook and leverage their stores as one unified distribution center to achieve massive margin gains. 

The Evolution Of Fulfillment And The New Ship-From-Store Model

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Historically, online order fulfillment has been accomplished through either large fulfillment centers or store-based fulfillment via stiff, rules-based order management systems, where inventory was either pulled from the store closest to the customer or a store with the lowest shipping costs.

While this approach works in theory, the reality is that the retailer often suffers as costs escalate. Either additional inventory is stockpiled or stores must manage resulting inventory dilemmas. For example, stores with high inventory turnover become under stocked and cannot cover walk-in demand, while stores with slower inventory turnover become overstocked and vulnerable to unplanned markdowns. Last year alone, U.S. non-grocery retailers lost $300 billion in revenues due to markdowns — which were primarily driven by inventory misjudgments. 

With the success of Amazon and the need for faster, more cost-effective order fulfillment, many traditional retailers have turned to “ship-from-store” methods using store inventory to fulfill online orders. The majority of these companies are adopting a combination approach leveraging distribution centers (DC) and stores. While this approach enables more flexible delivery capabilities and considers cost, it has also introduced two new challenges:

Inventory Uncertainty: With more ways for customers to buy, receive and return goods, demand prediction and inventory management can seem like voodoo science. Retailers struggle to understand if a particular store will have enough inventory to satisfy in-store demand first, let alone accurately pinpoint which store locations will have too much inventory of a particular item that won’t sell in-store and instead should be fulfilled for online orders.

In-Store Sales Cannibalization: By fulfilling online orders using in-store inventory, retailers run the risk of negatively impacting in-store sales. Without an accurate, real-time view of demand across channels, it is incredibly hard to predict if an item will sell well in a physical store vs. online — and when this could change or reverse.

Demystifying Demand With Artificial Intelligence And Machine Learning

Retailers need to clearly understand how to best use store inventory and take advantage of location to maintain the edge they need to compete in today’s retail environment. If done correctly, ship-from-store fulfillment not only addresses customer expectations, but also helps retailers avoid markdowns and lost sales, decrease fulfillment costs and increase full-price sales.

Retailers can gain a more accurate view of demand across stores and exceed customer expectations by harnessing the power of artificial intelligence (AI) and machine learning (ML).While 86% of retailers see the value in advanced analytics, retailers have long struggled to effectively use analytics. It is difficult to predict true demand based on sparse or incomplete data and lack of real-time context (such as available assortment and upsell and market trends) — especially at scale.

However, thanks to recent technology advancements in AI and ML, retailers now have ways to evaluate millions of data points at once to help quickly identify the overall opportunity cost of each potential fulfillment scenario. With this, retailers gain critical insight about where to ship from in order to best utilize the inventory — helping them maximize gross margins and sell-through.

In addition, technology advancements now also enable robust optimization capabilities that can help retailers solve a wide range of critical merchandise, planning, allocation and fulfillment challenges. With the ability to optimize across multiple (and often competing) objectives, retailers can better predict the best fulfillment strategy based on product availability, likely demand, capacity constraints, shipping costs, delivery timing and more. 

For each fulfillment decision that needs to be made, advanced optimization can account for the overall margin profitability and customer satisfaction by identifying the immediate payoff versus the long-term opportunity cost — instantly. Not only has effective fulfillment become a scientific game of advanced analytics, but it also must now play by the rules of the Amazon-driven era of urgency. 

Winning The Supply Chain Game

Inventory continues to be both retailers’ largest liability and greatest asset. In today’s volatile retail market, there is absolutely no room for guesswork or reliance on backwards looking data. By embracing the predictive analytics afforded by the AI/ML technology era, retailers can optimize inventory and modernize supply chains. In fact, omnichannel retailers can successfully meet consumer demand across ALL channels and stores — and beat Amazon at its own game. 


 

A seasoned retail tech leader, Andrea Morgan-Vandome’s experience across marketing, product, sales, customer relationships and market strategy has driven the success of both industry giants and innovative startups. As the CMO of Celect, she leads the development of strategic marketing efforts to expand the company’s product suite in the retail space. In her recent role as global vice president Cognitive Solutions at IBM Watson, she led the delivery of the first repeatable artificial intelligence and machine learning offerings and drove the product strategy, user experience and go-to-market approach for Watson solutions. Before joining IBM, Morgan-Vandome served as global vice president of cloud and global vice president of strategy and solution management at Oracle Retail, where she worked with retailers around the globe on merchandising, planning, inventory, supply chain, omnichannel and store challenges. Earlier in her career, she led strategic product and marketing initiatives at various startups including Retek, Connect3 Systems and StorePerform Technologies.

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