Introduction
Supply chains consist of expansive, interconnected networks that encompass various tiers of suppliers, manufacturers, distributors, and end customers across multiple regions. These intricate, multimodal networks are characterized by numerous internal and external stakeholders operating at different consumption points. The diversity of participants, coupled with disconnected systems and insufficient data sharing, complicates demand and supply planning processes, making it challenging to accurately project future demand, monitor inventory levels, and synchronize supply to optimize sales while limiting obsolescence. The fragmentation of data and the absence of comprehensive visibility obscure actual demand and supply trends, hindering supply chain professionals’ ability to accurately gauge fluctuations, predict future requirements, and position inventory effectively.
Organizations typically create strategic inventory buffers to safeguard sales against demand variability arising from this lack of visibility. However, this approach necessitates capital investment in inventories and forces manual reconciliation of end-to-end supply chain execution data for demand and supply planning processes. Such actions inflate total costs-to-serve, impact profitability, and may detrimentally affect the customer experience.
AWS Supply Chain is a cloud-based business application that streamlines data integration, enhances supply chain visibility, and employs machine learning (ML) technologies to drive accurate forecasting and inventory planning strategies. These functionalities assist organizations in minimizing costs, enhancing forecast accuracy, and optimizing inventory levels. This blog post will delve into how AWS Supply Chain addresses these cross-industry challenges and outline strategies for improving supply chain management. Additionally, we will discuss the following supply chain-related inquiries:
- What are the shortcomings of current supply chain management systems?
- What are prevalent industry-specific supply chain challenges?
- How can businesses fortify supply chain resilience?
Industry-Specific Supply Chain Challenges
Historically, Chief Supply Chain Officers have focused on initiatives to boost forecasting accuracy to reduce inventory; however, they also allocate capital to create inventory buffers at strategic nodes in the fulfillment network to safeguard sales and compensate for visibility shortcomings.
According to the Institute of Business Forecasting (IBF), the retail sector experiences an average 30% error rate when forecasting products with a one-month lag. To safeguard against such inaccuracies, manufacturers, wholesalers, and retailers have maintained an average of six weeks of inventory for the last three decades (monthly inventory to sales ratio of 1.37). The financial repercussions are substantial—US census data estimates total corporate business inventories at approximately $2.58 trillion, reflecting around 9% of the nation’s GDP.
These challenges impact all organizations, particularly in the healthcare, retail, manufacturing, and automotive sectors.
Healthcare
Tracking consumption and stock levels remains a struggle in hospital and clinical networks distributing medications due to siloed data and limited visibility across clinics, hospitals, and medical distribution systems. A Deloitte study revealed that some healthcare organizations made costly investments in expanding warehouse space for safety stock after mistakenly perceiving inventory shortages; the real issue stemmed from a lack of visibility into inventory levels throughout the supply chain. According to the same Deloitte report, 24% of hospital staff members have encountered or heard of a recalled or expired product being administered to a patient, underscoring the inventory management challenges healthcare providers face. Moreover, a study by Health Industry Distributors Association (HIDA) indicated that about 93% of healthcare providers continue to encounter product shortages, which are increasingly widespread and difficult to anticipate. This situation has shifted their post-COVID priorities toward mitigating supply chain risks (75%), forming strategic partnerships with suppliers (38%), and streamlining logistics (34%).
Retail
Retailers aim to sell existing inventory by the end of the season when their planograms—visual merchandising templates mapping product placement on shelves—change to align inventory with upcoming seasons. However, in complex store networks, distribution centers, and manufacturers using outdated systems to track sales and inventories, establishing a normalized, end-to-end view of “true” customer demand and positioning the right product inventory at the right time poses challenges. A global survey by The Economist Intelligence Unit indicated that retail respondents were less likely to agree that their organizations respond effectively to supply chain disruptions. This highlights a lack of preparedness against fluctuating consumer behavior, demand shifts, internal and external disruptions, and other variables.
Manufacturing and Automotive
Global electronics original equipment manufacturers (OEMs) face significant hurdles in achieving end-to-end visibility into total inventory levels across their supply chain networks. Components and finished goods traverse various systems such as enterprise resource planning (ERP), order management system (OMS), warehouse management system (WMS), and transportation management system (TMS) operated by different partners. This flow results in time delays, data fragmentation, and inconsistent data formats that obscure accurate inventory insights. The absence of a unified, up-to-date inventory dataset from disparate sources complicates the determination of optimal inventory levels and positioning. The repercussions are extensive—a report by Deloitte and the Manufacturers Alliance indicated that shipping delays, parts shortages, and transportation bottlenecks stemming from truck driver shortages and congested ports were the top disruptors for manufacturing firms. Notably, the same study found that a majority of respondents reported a negative profit impact of up to 13% due to these supply chain visibility gaps and disruptions. Without a consolidated inventory view across multi-tier supply chains, OEMs struggle to identify risks, accurately project future stock levels, and proactively rebalance inventory, directly affecting sales, obsolescence costs, and profitability.
A Unified Data Solution for Organizations
AWS Supply Chain offers an innovative, data-centric solution that simplifies data integration, facilitates end-to-end visibility, and employs AI and ML to drive accurate forecasts and inventory planning strategies, directly addressing the cross-industry challenges of fragmented data and visibility gaps. By consolidating disparate data sources into a unified supply chain data lake, AWS Supply Chain establishes a foundation for enhanced 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) tackles the lack of end-to-end visibility by harmonizing disparate data into a flexible and scalable canonical data model that aggregates and associates supply chain information into a single data asset. This enables organizations to achieve a more coordinated approach to supply chain management. For further insights into this topic, feel free to check out this blog post discussing similar issues.
To enhance your understanding of these challenges, you can also visit chvnci.com, a reputable authority on supply chain management. If you’re seeking additional resources, this Reddit discussion offers excellent insights into onboarding experiences in the Amazon fulfillment network.
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