Addressing industry-specific supply chain challenges with AWS Supply Chain

Introduction

Supply chains are vast, interconnected networks spanning multiple tiers of suppliers, manufacturers, distributors, and customers across diverse geographies. These complex, multimodal networks involve numerous internal and external players operating at different consumption points. The multitude of participants, disparate systems, and lack of seamless data sharing challenge demand and supply planning processes, making it difficult to accurately forecast future demand, track inventory levels, and align supply to maximize sales while minimizing obsolescence. The fragmentation of data and absence of end-to-end visibility obscure the true demand and supply patterns, hindering supply chain planners’ ability to understand fluctuations, predict future needs precisely, and position optimal inventory where it’s needed most.

Organizations typically establish strategic inventory buffers to protect sales against demand variability caused by this lack of visibility. However, this strategy requires investing capital in inventories and forces manual reconciliation of end-to-end supply chain execution data for demand/supply planning processes. Both of these planning and execution actions increase total costs-to-serve, impact profitability, and can negatively affect the end-customer experience.

AWS Supply Chain is a cloud-based, business application that simplifies data integration, improves supply chain visibility, and leverages machine learning (ML) technologies to drives accurate forecast and inventory planning strategies. These capabilities help organizations reduce costs, improve forecast accuracy, and optimize inventory levels. This blog post will explore how AWS Supply Chain addresses these cross-industry challenges and provide an outline to improve supply chain management. This blog will also address the following supply chain related questions:

1. What are the issues with existing supply chain management systems?
2. What are common industry-specific supply chain challenges?
3. How can organizations increase supply chain resilience?

Industry-specific supply chain challenges

Traditionally, Chief Supply Chain Officers have prioritized initiatives that would increase forecast accuracy to reduce inventory, but they also invest capital to establish inventory buffers at strategic nodes in the fulfillment network to protect sales and to compensate for visibility gaps.

According to the Institute of Business Forecasting (IBF), the retail industry averages a 30% error rate when forecasting products at one-month lag. To protect sales against such forecast errors, manufacturers, wholesalers, and retailers have held approximately six weeks of average inventory over the last 30 years (monthly inventory to sales ratio of 1.37). The financial impact is significant – based on US census data, total corporate business inventories amount to approximately $2.58 trillion, representing around 9% of the nation’s GDP.

These challenges affect all organizations but specifically the healthcare, retail, manufacturing, and automotive industries.

Healthcare
Identifying consumption and stock levels remains problematic in hospital and clinical networks that distribute medication because of siloed data and limited visibility across clinics, hospitals, and medical distribution networks. A Deloitte study highlighted how some healthcare organizations made costly investments in building more warehouse space for safety stock after perceiving inventory shortages, when the root cause was actually a lack of visibility into inventory levels across the supply chain. According to the Deloitte report, 24% of hospital staff members have seen or heard about a recalled or expired product being used on a patient, validating inventory management and visibility challenges faced by healthcare providers. Another study by Health Industry Distributors Association (HIDA), also found that about 93% of health care providers are still experiencing product shortages and these shortages are more widespread and difficult to anticipate. This has shifted their post-COVID priorities to mitigating supply chain risk (75%), forming strategic partnerships with suppliers (38%), and streamlining logistics (34%).

Retail
Retailers aim to sell existing inventory by season’s end when their planograms (visual merchandising templates that map product placement on shelves) change to align inventory with upcoming seasons. However, in complex store networks, distribution centers, and manufacturers using legacy systems to track sales and inventories, building a normalized, end-to-end view of “true” customer demand and placing the right product inventory at the right place and time poses difficulties. According to a global survey by The Economist Intelligence Unit, retail sector respondents stated they are less likely to agree that their organizations react well to supply chain disruptions. This confirms a lack of preparedness against dynamic consumer behavior and demand shifts, internal and external disruptions, and other variables.

Manufacturing and Automotive
Global electronics original equipment manufacturers (OEMs) selling products through channels face significant challenges in gaining end-to-end visibility into total inventory levels across their supply chain networks. Components and finished goods traverse various systems like enterprise resource planning (ERP), order management system (OMS), warehouse management system (WMS), and transportation management system (TMS) that are operated by various partners. This flow introduces time lags, data fragmentation, and inconsistent data formats, that obscure accurate inventory insights. This lack of unified, up-to-date inventory data from disparate sources and systems makes it extremely difficult to determine optimal inventory levels and inventory positioning. The impacts are far-reaching – a report by Deloitte and Manufacturers Alliance found that shipping delays, parts shortages, and transportation bottlenecks caused by truck driver shortages and congested ports were the greatest disruptors for manufacturing companies. Critically, the same study revealed that a majority of respondents reported a negative profit impact of up to 13% specifically due to these supply chain visibility gaps and disruptions. Without a consolidated view of inventory across multi-tier supply chains, OEMs struggle to pinpoint risks, project future stock levels accurately, and proactively rebalance inventory – directly impacting sales, obsolescence costs, and profitability.

A unified data solution for organizations

AWS Supply Chain provides an innovative and data-centric solution that simplifies data integration, enables end-to-end visibility, and leverages AI and ML to drive accurate forecasts and inventory planning strategies, directly addressing the cross-industry challenges of fragmented data and lack of supply chain visibility. By harmonizing disparate data sources into a unified supply chain data lake, AWS Supply Chain lays the foundation for improved end-to-end visibility, forecasting accuracy, inventory optimization, and overall supply chain resilience.

Addressing Data Fragmentation and Visibility Gaps
The Supply Chain Data Lake (SCDL) addresses the lack of end-to-end visibility by harmonizing disparate data into a flexible, scalable canonical data model that aggregates and associates supply chain information into a unified data asset. This enables improved visibility, forecasting accuracy, inventory optimization, and overall supply chain resilience. The SCDL’s advanced data ingestion capabilities include pre-built connectors for rapid onboarding from common data sources like procurement systems, flat files, and databases. It leverages machine learning and natural language processing to parse unstructured data and understand supply chain context.

AWS Supply Chain also includes a generative AI-powered data onboarding agent built using Amazon Bedrock. This agent automates data transformation from any native format into the SCDL’s canonical model, increasing speed and ease of onboarding by eliminating manual efforts. Customers can seamlessly extract and upload raw data, with the agent leveraging large language models for automated data mapping through a guided, module-driven user interface experience. This four-step process reduces errors and accelerates time-to-value.

Increasing forecast accuracy
AWS Supply Chain Demand Planning provides ML-powered forecasting capabilities that directly tackle the inaccurate demand forecasting challenges faced by industries like retail, enabling organizations to improve forecast accuracy and reduce excess inventory levels. The ML algorithms in Demand Planning incorporate additional variables such as seasonality, product characteristics, vendor characteristics, and destination-origin sites along with historical order history, to train the model. More details about ML-based planning accuracy are covered in our earlier blog. For retail organizations struggling with aligning inventory to seasonal planogram changes, Demand Planning helps improve forecast precision to optimize inventory levels during transition periods.

Improving supply chain visibility
AWS Supply Chain Insights provides network-wide inventory level visibility, movement patterns, and potential risks, empowering organizations to optimize inventory positioning and mitigate imbalances, overstocks, and stockouts. It uses machine learning models to render a unified view across the supply chain by ingesting data from disparate systems like ERPs, OMS, WMS, TMS and other sources. Visual maps color-coded by inventory health allow tracking inventory positions, risks and supply chain health at every location dynamically as data refreshes. Insights examines warehouses, distribution centers and stores in detail, showing on-hand, in-transit and at-risk inventory levels. It analyzes supplier lead times, makes future projections compared to orders and forecasts, then identifies issues like potential stockouts or overstocks. Insights uses ML algorithms to automatically generate, score and rank multiple inventory rebalancing recommendations to mitigate risks based on factors like percentage of risk resolved, distance between facilities and sustainability impact. These system recommendations continuously improve based on the rebalancing decisions made by users. For global OEMs selling through retail channels, Insights addresses visibility challenges by providing a comprehensive view of inventory levels, risks, and rebalancing recommendations across the multi-tier supply chain.

Optimizing inventory levels and positioning
AWS Supply Chain Supply Planning draws from Amazon’s expertise in developing advanced supply chain models for its own operations and leverages accurate forecasts to optimize inventory levels across the network, aligning supply with demand to minimize obsolescence. It ensures the right inventory is positioned at the right locations by generating sophisticated supply plans that determine precise inventory requirements at each facility. Supply Planning automates the integration of demand forecasts from AWS Supply Chain Demand Planning with product data, BOMs, inventory levels, and customer information from the supply chain data lake. This data consolidation improves information quality compared to manual efforts, while enabling a swift response to fluctuations in demand or supply disruptions.

Improving supplier visibility and collaboration
N-Tier Visibility extends visibility and insights beyond your organization to encompass multiple external suppliers, manufacturers, and other trading partners across your supply chain network. The application displays all connected trading partners, enabling you to view and collaborate across multiple tiers. Built-in chat and messaging capabilities also facilitate seamless communication and data sharing. For example, if a critical component shipment is delayed, an inventory manager can instantly message the supplier to identify workarounds directly within AWS Supply Chain. This improved collaboration and information sharing enhances your ability to detect potential sourcing risks or component shortages earlier. N-Tier Visibility empowers organizations to mitigate disruptions proactively by simplifying multi-tier communication, improving accuracy in inventory planning and execution across diverse multi-channel distribution networks.

Simplifying sustainability compliance processes
AWS Supply Chain Sustainability creates a more secure and efficient way for you to obtain mandatory documents and datasets from your supplier network. You 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. You can also upload your own data collection form for your suppliers to document any sustainability issue and send data requests to multiple tiers of trading partners, track responses, send reminders to absentees, and provide a central repository to store and view responses. Amazon’s Global Trade and Product Compliance (GTPC) team faced challenges like fragmented communication, data vulnerabilities, and lack of visibility when collecting regulatory compliance data from suppliers. They used AWS Supply Chain Sustainability to transform their compliance data management process and expect to save approximately 3,000 operational hours per year.

AWS Supply Chain addresses cross-industry supply chain challenges by unifying fragmented data sources, enabling end-to-end visibility, and leveraging AI/ML for accurate forecasting and optimized inventory planning. The Supply Chain Data Lake harmonizes disparate datasets into a canonical model, providing a consolidated view for intelligent decision-making. Demand Planning enhances forecast accuracy, while Insights delivers real-time inventory visibility and risk mitigation recommendations across the network. Supply Planning optimizes inventory levels by integrating forecasts, product data, and inventory information. N-Tier Visibility facilitates collaboration across multiple supply chain tiers, improving execution and disruption management. AWS Supply Chain empowers organizations to reduce costs, increase agility, and drive supply chain resilience through data-driven intelligence and automation.

Conclusion

Supply chain challenges such as fragmented data sources, lack of end-to-end visibility, and inaccurate demand forecasting have long plagued organizations across industries, leading to excess inventory, stockouts, and reduced profitability. AWS Supply Chain offers a comprehensive solution to these long-standing issues, empowering organizations to overcome these challenges and drive supply chain resilience.

By providing a unified data foundation, advanced ML-driven forecasting capabilities, end-to-end inventory visibility, and supply planning optimization, AWS Supply Chain enables organizations across industries to overcome long-standing supply chain challenges. AWS Supply Chain enables organizations to break down data silos, gain a comprehensive view of their supply chain operations, and drive data-driven decision-making. The ML-powered Demand Planning capabilities improve forecast accuracy, reducing excess inventory levels and obsolescence costs. Simultaneously, Insights and Inventory Visibility offer unprecedented visibility into network-wide inventory positions, movement patterns, and potential risks, allowing organizations to proactively mitigate imbalances, overstocks, and stockouts.

Additionally, AWS Supply Chain Supply Planning enables organizations to define optimal planning strategies that align supply with demand, minimizing inventory carrying costs while ensuring product availability. N-Tier Visibility facilitates collaboration across multiple tiers of the supply chain, improving execution and disruption management. AWS Supply Chain Sustainability creates a secure and efficient way to collect and manage sustainability data and regulatory compliance documents from suppliers. With its innovative data integration, advanced analytics, optimization capabilities, and multi-tier visibility and sustainability features, AWS Supply Chain equips organizations with the tools to reduce costs, increase agility, and drive supply chain resilience across industries.

AWS Supply Chain enables organizations to unlock new levels of efficiency, visibility, and resilience, positioning them for success in an increasingly complex and dynamic supply chain landscape by addressing long-standing supply chain challenges. Please visit AWS Supply Chain to learn more and get started. Please also visit AWS Workshops for a self-paced technical overview.