AWS Supply Chain Supply Planning offers specialized models to accurately forecast and plan purchase of raw materials, components, and finished goods to improve in-stock rates across customers’ supply chains

AWS Supply Chain N-Tier Visibility helps customers publish forecasts and confirm orders with multiple tiers of suppliers, improving the accuracy of planning and execution of processes

AWS Supply Chain Sustainability provides a single, auditable way to request and collect carbon emissions and other compliance data from suppliers

Amazon Q, a generative AI-powered assistant in AWS Supply Chain that can summarize and highlight key risks, and visualize “what if” scenarios to optimize supply chain decisions

Boston Consulting Group, Equipment Depot, and Woodside Energy among customers using new AWS Supply Chain capabilities

At AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), today announced four new capabilities for AWS Supply Chain—combining Amazon’s nearly 30 years of supply chain experience with the resilience, security, and business continuity of an AWS managed service to help customers optimize their supply chains. These new capabilities, which will be available in 2024, expand existing data lake, demand planning, and machine learning (ML)-powered insights. With new supply planning, collaboration, sustainability, and generative AI capabilities to support upstream supply chain processes, such as supplier orders, AWS Supply Chain is making it possible for an entirely new set of customers, including manufacturers, to benefit from the service. First, AWS Supply Chain Supply Planning will help customers forecast, plan, position, and replenish components and finished goods to reduce inventory costs and respond more quickly to demand variations and supply disruptions. Second, AWS Supply Chain N-Tier Visibility streamlines communication between customers and multiple tiers of suppliers, improving their ability to more accurately respond to supply plans, as well as manage demand or supply changes during the execution window. With this capability, customers can collaborate securely with their trading partners in just a few clicks. Third, AWS Supply Chain Sustainability will provide a central repository, enabling customers to request, collect, and audit sustainability data. Finally, Amazon Q in AWS Supply Chain provides supply chain professionals with a generative AI assistant to provide a summarized view of key risks around inventory levels, demand variability, and visualizes the tradeoffs between different possible scenarios. To learn more about AWS Supply Chain, visit aws.amazon.com/aws-supply-chain.

Today, customers are using AWS Supply Chain to improve inventory visibility, help prevent stock-outs that can erode consumer trust, and reduce overstock events that can increase carrying costs. The existing Demand Planning capability of AWS Supply Chain applies Amazon’s deep supply chain and ML expertise to increase the speed and accuracy of demand forecasts. Customers can also use AWS Supply Chain Insights, which provides a unified view of customer supply chain data, to receive machine learning-powered recommendations to help them mitigate inventory and lead-time risks. AWS Supply Chain makes this possible by aggregating relevant customer data from Enterprise Resource Planning (ERP) systems and normalizing them to a common format. The data consolidated by AWS Supply Chain serves as the foundation of the application’s current capabilities—Demand Planning and Insights—but customers are asking for more support on their upstream supply chain processes. The four new capabilities announced today were born from that customer need.

“Customers are excited that we're making our extensive supply chain experience available to them as a managed service. That, combined with our industry leading analytics and ML means customers can now track and plan for products more predictably, from manufacturing facilities to final points of distribution,” said Diego Pantoja-Navajas, vice president of AWS Supply Chain. “With AWS Supply Chain, our customers have been able to increase inventory visibility and execute on insights to mitigate supply chain risks, reduce cost, and improve customer satisfaction. And thanks to the power of generative AI, customers can ask Amazon Q in AWS Supply Chain what is happening across their supply chains and receive intelligent, conversational answers to complex questions.”

New capabilities extend AWS Supply Chain upstream, enhancing visibility and insights

Supply chain leaders continuously face the challenge of coordinating with many different layers of trading partners, such as suppliers, manufacturers, distributors, and retailers. Each trading partner often has their own data stores that require expensive customizations and long development cycles or manual work-arounds to integrate. As a result, supply planners spend a lot of time reconciling forecasts, order confirmations, shipment quantities, and more. Siloed data—coupled with demand variations, supply disruptions, and vendor lead-time uncertainty—makes it difficult for many companies to accurately forecast demand and determine optimal inventory levels. Manufacturers face additional complexities associated with raw materials and components, which are prone to variable pricing and availability. Furthermore, trading partner responses to customer requests for data vary in quality, frequency, timeliness, and structure, and are not always systematically tracked or audited. Managing compliance artifacts like carbon emissions and hazardous material disclosures at scale is similarly challenging, and has traditionally been done via email, fax, and messaging apps, without formal tracking and auditing mechanisms. As a result, many organizations struggle to ensure appropriate quantities of goods are in the right place at the right time to efficiently meet demand or to meet increasingly stringent regulatory requirements. With the new AWS Supply Chain capabilities announced today, customers can more easily manage their upstream supply chain, more accurately forecast needed materials and inventory, communicate with suppliers to confirm supply plans and obtain commitments, and get accurate data about key environmental factors.

• AWS Supply Chain Supply Planning draws on Amazon’s expertise in developing ML for its own operations and applies this knowledge to create sophisticated supply planning models that can accurately predict the right levels of inventory needed across facilities. Supply Planning uses the demand forecasts created by AWS Supply Chain Demand Planning, along with data about product, facility, bill of materials (BOM), and inventory. This helps customers determine how many units to order, when to place the order, and where to position inventory, by recommending actions such as the creation of purchase orders or inventory transfer requests.

• AWS Supply Chain N-Tier Visibility extends customers’ visibility and insights not only to their direct relationships, but also to multiple tiers of external trading partners. Customers can invite and onboard trading partners in just a few clicks. Trading partners can then automate communication and improve their own forecasts. For example, customers can share purchase orders and demand forecasts with their trading partners, and then track the status of those purchase orders or changing inventory levels, all from within AWS Supply Chain N-Tier Visibility. The updated supply plans and purchase orders are exported to Amazon Simple Storage Service (S3), so customers can integrate them with their ERP systems. AWS Supply Chain chat and messaging capabilities make collaboration even easier across the entire supply chain. For example, if a component shipment is delayed, an inventory manager can message a supplier to identify a work-around within the AWS Supply Chain application. Improved collaboration and information sharing with suppliers and manufacturers enhances the ability to detect sourcing risks and component shortages, and enables customers to mitigate disruptions.

• AWS Supply Chain Sustainability creates a more secure and efficient way for sustainability professionals to obtain documents and datasets from their supplier network. These customers can request, collect, and export artifacts, such as product life cycle assessments, certificates on product safety, or reports on hazardous substances used, at any point in the supply chain. Customers can also upload their own data collection form for their suppliers to document any sustainability issue, utilize a standard workflow process to send their suppliers reminders to answer data requests, and communicate necessary changes based on supplier responses. These capabilities will help customers provide compliance information for environmental and social governance (ESG) regulations with a single, auditable record of the data.

Generative AI enables customers to query supply chain data

Customers want to be able to easily identify causal relationships between factors that impact their supply chain decisions, such as fluctuations in demand and disruptions in supply, but doing so is challenging because it requires gathering and analyzing disparate data across many different sources, which is both tedious and time consuming. Gauging tradeoffs or visualizing outcomes to complex scenarios in their supply chain can also be challenging. As a result, supply chain leaders often have to make decisions in the planning and positioning of materials and inventory without the most accurate insights to inform decision-making. Amazon Q in AWS Supply Chain helps solve these challenges and improves customer productivity by providing an easy-to-use, natural language interface that intelligently responds to data analysis queries and questions about supply chain decisions.

• Amazon Q in AWS Supply Chain is a generative AI assistant powered by Amazon Bedrock that provides a natural language interface in the AWS Supply Chain application so that customers can query data within the AWS Supply Chain Data Lake, and receive intelligent answers to “what?” and “why?” and “what if?” questions. Amazon Q can be tailored to a customer’s business and can also visualize outcomes of complex scenarios and the tradeoffs between different supply chain decisions. For example, via a conversational prompt within the AWS Supply Chain application, a customer may ask, “What is the financial impact of delayed replenishment orders in the Southeast region?” Amazon Q would respond, "There are currently 8 delayed replenishment orders that could cause an out-of-stock situation for 20 of your fast-moving products in that region. The delay will have a revenue impact of $150K." A customer may further ask, “Why are we not moving product from other regions to account for this shortfall?" Amazon Q would then respond, “Because you have less than optimal inventory across your entire network for the next 7 days." The customer could then ask, “What if I expedite the orders through air freight?” Amazon Q would respond, “Air freight typically arrives in 2 days and could reduce the revenue impact by $95K, but adds $2.4K in expedite costs.” The speed and accuracy of Amazon Q’s responses can help customers gain actionable insights to improve every aspect of their supply chain.

Boston Consulting Group (BCG), a global management consulting firm, is a strategic alliance partner to AWS. The partnership between BCG and AWS helps organizations transform and enhance their supply chains to enable advantaged growth, optimally balancing agility, resilience, service, cost and sustainability. “Our partnership provides a compelling and tangible business benefit to customers, as BCG brings expertise in strategy, organizational transformation and business integration to help deploy, scale and drive adoption of AWS supply chain solutions at our customers,” said Drake Watten, managing director and partner at BCG. “We are currently supporting projects with the generally available capabilities and preparing customers for the upcoming AWS Supply Chain releases that will improve material, component, and finished goods planning, improve partner management, and introduce generative AI as a solution for supply chain management.”

Equipment Depot is a leading independent material-handling equipment supplier and rental source with more than 50 branch locations supporting 850 technicians. “Equipment Depot is implementing an expansive digital transformation strategy to support our rapid growth, and we’re excited to work with AWS to support this strategy,” said Joakim Langkaas, director of Operations at Equipment Depot. “AWS Supply Chain will transform our planning process, improve inventory levels, and increase our ability to make data-driven supply decisions. Demand Planning, Supply Planning, and Insights will anticipate low inventory and original equipment manufacturer delays, and provide real-time recommendations to increase speed of service, improve customer experience, and decrease equipment downtime. As an early adopter of this technology, we expect these new capabilities will enable our teams to put the right parts in the right place at the right time.”

Woodside is a global energy company, founded in Australia with a spirit of innovation and determination. Woodside provides energy the world needs to heat and cool homes, keep lights on and enable industry with a global footprint ranging from operations in Western Australia to the Gulf of Mexico and beyond. “The remoteness of our locations prohibits us from utilizing supply chain processes like overnight shipment of spare parts, so we rely on stocking the right parts across our warehouse network and leveraging multiple modes of transport to ensure we support our operated facilities,” said Tracey Simpson, vice president of Supply Chain at Woodside Energy. “Our business needed a way to improve end-to-end supply chain visibility, so we worked with AWS Supply Chain knowing their vision for solving the problem aligned with ours. If fully scaled, we expect the proactive visibility of order status, delivery issues, and recommendations enabled by Order Insights will improve the efficiency of our system and ways of working. We anticipate there may be tangible business benefit for example a reduction in material expedites and re-planning of maintenance. We are also excited about the next phase of AWS Supply Chain, including advanced supply planning, enriched partner collaboration, and the integration of generative AI, to further improve supply chain performance.”

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