Cracking the 'Last Mile' Supply Chain Challenge

As Amazon.com rewrites the rules of retail, retailers are struggling to adapt and stay relevant. And it’s only getting harder to compete as the online retail giant continues to up the ante — most recently introducing one-day free shipping to Amazon Prime customers. Instead of forging new and uncharted paths, retailers can succeed by taking a page from Amazon’s own playbook and beating it at its own supply chain game.

This approach starts by moving away from traditional fulfillment centers and rules-based order management systems to an Amazon-inspired “ship from store” model, essentially transforming disparate store locations into one unified distribution center to enable faster, more cost-effective order fulfillment. But it doesn’t end there. To truly crack the “last mile” supply chain challenge, retailers must also employ advanced analytics and optimization technologies to connect the dots between available data points and provide real-time context into what, when, where and how much customers will buy.

This enables retailers to match inventory to the best view of demand. For many retailers, online order fulfillment is accomplished by pulling merchandise from the closest stocked location to the customer without an eye to inventory coverage. This can result in both understocked stores with high inventory turnover and piles of extra inventory that end up being sold at significant markdown. In fact, U.S. non-grocery retailers lost $300 billion last year in revenues due to markdowns caused largely by poor inventory planning and misalignment. This major challenge persists, as many retailers continue to rely on historical analysis, gut instinct and averages to run their businesses.

Leveraging artificial intelligence (AI) and machine learning (ML) makes the once-impossible job of matching inventory to the best view of demand possible. These advancements can provide retailers with a comprehensive view of every fulfillment scenario possible — taking product availability, likely demand, capacity constraints, shipping costs, delivery timing and more into account instantly — and enabling them to make real-time decisions on where inventory should come from. This holistic, data-driven insight also helps retailers effectively weigh short- and long-term opportunity costs, maximize gross margins and increase sell-through.

Deliver on Heightened Customer Expectations

Today’s customers expect it all. They expect that when they walk into a store, they can get exactly what they want immediately — in their size, their preferred color/model, etc. — and also be able to browse comparable products in-store. They also want to be able to search for products online — any day and at any time — hit “buy” and be able to have the product in their hands within a day or even less.

Advanced analytics and optimization through AI and ML can help retailers accurately anticipate inventory purchasing spikes and dips, and dynamically map to demand patterns to deliver on these ever-increasing customer demands across all channels. By connecting millions of pieces of data from numerous sources, retailers can more intelligently leverage store inventories to fulfill online orders, without negatively impacting in-store inventories for foot traffic. Retailers can now extend and enhance their traditional rules-based order management systems with advanced analytics and real-time optimization capabilities to help avoid markdowns and lost sales, decrease fulfillment costs, and increase full-price sales.

By harnessing the power of AI and ML, retailers can match inventory to the best view of demand, enhance stakeholder value, and deliver the fast, seamless (and instantly gratifying) experience today’s consumers expect in the Amazon age.

Andrea Morgan-Vandome is chief marketing officer at Celect, an inventory optimization technology solution.