AWS for Industries

Five Benefits of Building Intelligent Supply Chains (Part 2)

In my previous blog, How to Build Supply Chain Intelligence as a Retailer (Part 1), I discussed the four disruptions retailers must overcome to improve their supply chain intelligence and meet customers’ fulfillment demands. To recap, intelligent retail supply chains are automated in order to increase efficiency, speed, and adaptability to disruption. Retailers have prioritized building intelligent supply chains because small improvements can significantly benefit the business and end customer. According to recent studies from McKinsey, the benefits of an intelligent supply chain are:

  • Better product allocation from improved forecasting—This can generate 4-6% uplifts in addressed demand. One of the most common challenges for retailers is providing optimal product availability, while maintaining healthy product coverage levels—that is, the amount of product allocated to the store network versus how much remains in central warehouses to restock the higher sales channels. Incorrect initial product allocation of new product launches or releases will result in product sitting in stores where it is not selling, and stores running out where it is selling well. Moreover, this misplaced stock will result in lost sales, write downs, unplanned transportation costs to redistribute stock, and worse—unhappy customers. River Island, a major UK fashion retailer, reduced in-store stock-outs, thus reducing lost sales by 28.3% for continuity products and 14.8% for fast fashion products via AWS.
  • Better demand planning—This can generate stock-out and waste reduction of between 10-30%. Without the proper forecasting tools and processes, retailers constantly see their most important SKUs go out of stock in certain locations while excess inventory sits in others. Furthermore, if the retailer doesn’t have the correct processes and tools for sensing and planning demand and ordering optimal quantities, store managers making buying decisions will be less confident when placing orders, trying to avoid under- and over-forecasting costs. Buyers end up repeating orders from the previous day or ordering three to five times more for promotional periods without any data-based guidance regarding the correct demand levels. This creates a vicious circle of both out-of-stock and overstock items. More Retail reduced waste by up to 30% and improved in-stock items by 80-90% via Amazon Forecast, which provided a forecast distribution that ultimately helped More Retail minimize under- and over-forecasting costs.
  • Better allocation of products to channels and markdown reductions—This can increase profitability by 2-4%. When retailers miss demand and product allocation not only across their store network, but also between their online and physical stores’ sales channels, they incur unplanned costs, mainly in the forms of inventory holding, write downs, and transportation costs from transferring inventory across the network, whenever feasible. For fresh produce inventory, transfer is mostly not viable. Waste is a key driver of food retail cost, while write downs, dead inventory, and inventory that must be disposed of are the key drivers in non-food retail. Building and deploying a demand forecasting and automated ordering system around Amazon Forecast also allowed More Retail to increase gross profits by 25% through reducing waste and improving supply chain efficiency.
  • Greater automation, higher labor productivity in warehousing, and better transport analytics—This can lead to 10-20% reduction in warehousing and distribution costs. Warehouse operations are among the biggest supply chain challenges retailers face, including managing inter-dependent processes like picking, packing, put-away, real-time inventory locating, and tracking within the warehouse; synchronizing workforce capacity and tasks; managing space utilization; and interlocking warehouse operations with inbound and outbound logistics. Automation is essential to achieving warehouse operations scale, speed, and efficiency. Automation via robotics and computer vision technologies is becoming more and more table stakes in modern warehouse management. For example, computer vision assists fulfillment center associates in placing items in bins and racks to achieve better inventory visibility in the warehouse and reduce decision process variation regarding where to stow, all while decreasing the cognitive load on associates. Utilizing in-store, the cloud-based fulfillment solutions, Co-op, a major UK grocer, fulfills online orders from their stores in less than two hours from click to delivery.
  • Agility, faster reaction times, and proximity to customers—This can offer a competitive advantage. During supply chain disruptions, the ability to react fast to demand fluctuations and unforeseen events, like a pandemic and subsequent border and route closures, becomes more critical than ever. Agile supply chains begin with real-time, end-to-end visibility, utilizing data to produce actionable insights and installing decision support platforms that allow for predictive and prescriptive recommendations to mitigate risks and pivot when necessary. Moreover, connecting your supply chain and trading partners brings coordination and agility to the ecosystem. Working on these dimensions provides retailers with truly demand-driven supply chains, as well as sense and respond capabilities that mitigate issues even before they happen and build competitive advantage throughout the supply chain. For example, DoorDash can reach 90% of the US population within 35 minutes. Nu Skin is shipping products 34% faster while achieving a 43% reduction in TCO by utilizing AWS cloud technologies.

Cloud Technology: the Vehicle to Build Intelligent Supply Chains

A simple AWS framework for building intelligent retail supply chains requires only five steps:

  1. Always start with a clear customer question you want to answer. Ask, “where is the friction I want to solve?”
  2. Identify what data is needed to establish potential solutions.
  3. Integrate all of your data in a single platform in order to enable advanced analytics, experimentation, and prototyping.
  4. Utilize AI/ML to optimize your solutions, deliver a differentiated impact, and ensure predictive capabilities in the model.
  5. Automate the process so that it can deliver non-linear scaling.

AWS Is Your Supply Chain Partner

If you want to achieve greater flexibility and product availability across channels, especially during peak seasons and big promotion events, AWS can help. Contact your account team today or visit our AWS Retail webpage to get started.

Alejandro Mondragon

Alejandro Mondragon

Alejandro Mondragon joined AWS in 2020 as the Head for Business Development Retail for Germany, Austria, and Switzerland. With the goal of helping retailers in his region grow their businesses, he leads the development and go-to-market strategy for the retail vertical in the region, including channel development and sales enablement. With deep domain expertise in retail industry data, marketing strategies, and customer experiences, prior to joining AWS, Alejandro held leadership positions at GfK, WPP, Roland Berger, A.T. Kearney, and French retailer Carrefour. He has a BSc in Mechanical & Industrial Engineering and an MBA from Georgetown University.