ARTICLES & WEBSITES
HARVARD BUSINESS REVIEW
How Machine Learning Will Transform Supply Chain Management
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The article from Harvard Business Review discusses the transformation of supply chain management through Optimal Machine Learning (OML), developed by the authors. Traditional planning methods, which rely heavily on forecasts, have proven inadequate, especially in the face of disruptions like the COVID-19 pandemic and geopolitical conflicts. These methods often result in misaligned objectives, poor inventory decisions, and financial losses. The authors present OML as a solution, focusing on decision-making rather than just prediction. OML leverages historical data, AI, and a digital twin of the supply chain to optimize key decisions, enhancing agility, resilience, and performance. It also addresses data challenges by creating an end-to-end architecture for real-time updates and improved scenario planning. The approach has shown success in real-world applications, leading to better inventory management, cost reduction, and increased service levels. OML’s effectiveness lies in its ability to align stakeholder goals, integrate business constraints, and adapt rapidly to changes.
HARVARD BUSINESS REVIEW
How Global Companies Use AI to Prevent Supply Chain Disruptions
by Remko Van Hoek and Mary Lacity
As they strive to make their supply chains more resilient, global companies are grappling with two challenges: the difficulty in discerning potential sources and the extended time required to find, vet, and onboard new suppliers. Companies such as Walmart, Tyson Foods, Koch Industries, Maersk, Siemens, and Unilever are using AI tools to swiftly find and engage with alternative suppliers during unexpected disruptions. They are also employing AI tools to pre-qualify suppliers ahead of time. These AI tools provide buyers with enhanced information that allows them to beat their competitors in securing alternate sources of supplies.
Forbes
Companies Improve Their Supply Chains With Artificial Intelligence
The Forbes article by Steve Banker discusses how artificial intelligence (AI) is transforming supply chain management. AI, particularly machine learning, is increasingly being adopted to enhance demand forecasting, optimize inventory, and improve overall supply chain efficiency. However, the effectiveness of AI depends on the quality of input data, and "garbage in, garbage out" remains a significant challenge. AI's ability to adapt quickly to real-time data has proven beneficial, especially during disruptions like the COVID-19 pandemic. Companies are also leveraging AI for sustainability goals, predictive maintenance, and autonomous decision-making, making supply chains more resilient and responsive.
MARS
12 Canadian companies solving our supply chain woes
By Max Zimmerman
The Supply AI program, a collaborative initiative involving the federal government, the Government of Quebec, MaRS, and Scale AI, supports Canadian ventures using artificial intelligence (AI) to enhance supply chain resilience and efficiency. The program addresses the challenges exacerbated by the pandemic and geopolitical conflicts, offering AI-driven solutions for improved demand forecasting, inventory management, and operational streamlining. AI's role in supply chain management is emphasized for its ability to automate routine tasks, forecast demand, and optimize decision-making processes. The program's six-month coaching aims to scale products, create jobs, and attract investment. Key participants include startups leveraging AI for various sectors, such as biopharma, foodservice, agriculture, and logistics, each working on innovative solutions to strengthen supply chains. The initiative also fosters collaboration among participants, enhancing their ability to tackle shared challenges, ultimately contributing to the creation of more adaptive and robust supply chains.
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NVDIA
AI-Powered Supply Chain Management
This page provides an overview of NVIDIA’s AI-powered supply chain management solutions, highlighting their role in enhancing efficiency and intelligence for retailers and consumer packaged goods (CPG) companies. It features use cases like warehouse simulation, demand forecasting, and last-mile delivery optimization, all powered by AI and simulation technologies like NVIDIA Omniverse and intelligent video analytics (IVA). The page also includes resources such as videos, training, and blogs to help users dive deeper into AI in retail. Additionally, it promotes NVIDIA's partnerships, hardware, software solutions, and consultation services aimed at building intelligent supply chains.
ERNST & YOUNG (EY)
How supply chains benefit from using generative AI
by Glenn Steinberg​, Matthew Burton, Ayoub Abielmona
The EY article explores the transformative impact of generative AI (GenAI) on supply chain management, highlighting its potential to enhance resilience, sustainability, and efficiency across various stages, including planning, sourcing, manufacturing, and logistics. GenAI, which generates new content based on existing data, is being rapidly adopted, with around 40% of supply chain organizations already investing in it. It offers significant advantages, such as improved demand forecasting, risk management, and logistics optimization, while automating complex tasks and enabling faster decision-making. However, the article emphasizes the importance of high-quality data, cautious implementation, and strong governance to mitigate risks and maximize GenAI's benefits
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DELOITTE
Managing a modern supply chain: Utilizing AI to combat complexity
The article discusses how artificial intelligence (AI) is transforming supply chain management by addressing the increasing complexity and disruptions in global supply chains. Companies that effectively manage "entropy"—the natural decline from order to disorder—are turning to AI to maintain order and optimize operations. AI applications, such as predictive maintenance, risk management, and computer vision, help organizations preempt disruptions, improve safety, and enhance efficiency. The article highlights successful AI implementations in various industries, showcasing significant cost savings and operational improvements. To successfully adopt AI, companies should develop a strategic approach, ensure employee adoption, and focus on high-impact use cases. AI is positioned as a critical tool for modern supply chain managers, enabling them to navigate challenges like geopolitical shifts, natural disasters, and evolving labor dynamics, ultimately providing a competitive edge.
AIMultiple
Top 12 Supply Chain AI Use Cases in 2024
Written by Shehmir Javaid
The article from AIMultiple explores the top 12 use cases of AI in supply chain management for 2024, emphasizing how AI is transforming this critical business function. AI-driven automation is highlighted as essential for modern supply chain operations, enabling the automation of back-office tasks, logistics, warehouse management, quality checks, and inventory management. Predictive analytics powered by AI enhances demand forecasting, inventory optimization, and region-specific forecasts while mitigating the bullwhip effect. The article also underscores the importance of AI in improving supplier relationship management by optimizing supplier selection, communication, and performance tracking. Additionally, AI contributes to sustainability by optimizing transportation routes and reducing warehouse emissions. Overall, the article stresses that while AI offers significant benefits in managing supply chain complexity, its success depends on how and where it is applied, urging supply chain leaders to develop strong use cases to fully harness AI's potential.
GRAMENER
Ace Your Supply Chain Game With AI In Supply Chain Use Cases
The article by Sudha N Bharadwaj explores the significant role of Artificial Intelligence (AI) and Machine Learning (ML) in transforming supply chain management, particularly in response to disruptions like the COVID-19 pandemic and the war in Ukraine. It highlights the top 10 AI and ML use cases in supply chain management, including demand forecasting, supply forecasting, inventory planning, production planning, warehouse management, logistics management, pricing management, text analytics, customer management, and workforce management. The article underscores the importance of AI in automating processes, improving efficiency, and enhancing decision-making across these areas. Additionally, it addresses the challenges faced by the logistics and supply chain industry, such as cost inefficiencies, technical downtimes, and poor customer experiences, and how AI can mitigate these issues. The piece also showcases case studies from companies like Pfizer, Audi, Boeing, and Bosch, illustrating the practical benefits of AI in optimizing supply chain operations and achieving sustainability goals.
INBOUND LOGISTICS
Top 20 AI Applications in the Supply Chain
By Katrina Arabe
The article by Katrina Arabe highlights the top 20 applications of Artificial Intelligence (AI) in supply chain management, showcasing how AI is transforming various aspects of the industry. AI is instrumental in enhancing supply chain visibility, optimizing sourcing and inventory management, and improving demand forecasting. It also aids in predicting production bottlenecks, managing suppliers, streamlining inbound logistics, and load planning. AI's role extends to improving customer service, automating customs clearance, handling e-commerce returns, and supporting sustainability initiatives. Additionally, AI enhances last-mile delivery efficiencies and ensures worker safety by flagging dangerous situations. The article underscores AI's capability to process vast amounts of data, provide predictive insights, and automate complex tasks, thereby enabling companies to achieve greater operational efficiency and responsiveness in an increasingly complex global supply chain environment.
builtin
27 Top Supply Chain Companies to Know
Written by Ellen Glover
The article by Ellen Glover highlights 27 top supply chain companies that are revolutionizing the industry with advanced technologies like AI, IoT, blockchain, and robotics. These companies play a crucial role in optimizing every aspect of the supply chain, from procurement to delivery. Notable companies include Amazon and Walmart, which leverage extensive data analytics and automation to streamline operations. Companies like DHL and FedEx are pioneers in logistics, using IoT sensors and blockchain for smarter routing and shipment tracking. Others like Blue Yonder and C.H. Robinson use AI to enhance demand forecasting and supply chain visibility. These companies are at the forefront of an industry that was valued at $27 billion in 2022, projected to reach $75 billion within the decade.
ORACLE
Benefits of AI in the Supply Chain
The article highlights the transformative impact of AI on supply chain management, emphasizing its ability to enhance efficiency and resilience. AI is being employed to optimize various supply chain functions such as inventory management, demand forecasting, warehouse operations, and transportation logistics. The technology helps identify patterns in large data sets that are often missed by traditional systems, enabling more accurate predictions and decision-making. AI also improves supply chain transparency and sustainability by monitoring ethical sourcing and reducing environmental impact. Despite the significant benefits, the implementation of AI in supply chains presents challenges, including high costs, complex integration, and the need for robust data management. However, with careful planning and execution, businesses can leverage AI to significantly improve their supply chain operations, making them more agile and competitive in a globalized economy.
SFS
The Role of AI in Developing Resilient Supply Chains
by Maxime C. Cohen & Christopher S. Tang
The article "The Role of AI in Developing Resilient Supply Chains" by Maxime C. Cohen and Christopher S. Tang explores the transformative impact of AI on global supply chain management. As supply chains become more complex due to global disruptions, AI offers significant potential to enhance resilience, efficiency, and visibility. The authors discuss the Biden administration's focus on AI and supply chain resilience through executive orders, highlighting the need to integrate these efforts. AI can revolutionize supply chain planning, mapping, and response strategies by optimizing logistics, forecasting demand, and detecting disruptions in real time. However, the authors emphasize that AI's integration should not result in job losses; instead, it should create new opportunities while requiring human oversight to mitigate risks like bias and ethical concerns. The article concludes by stressing the importance of responsible AI development and the critical role of supply chain managers in navigating the evolving landscape.
