AI Machine Learning for the Supply Chain How Do We Use It? Practical and Visionary Use Cases

A well-functioning SCM system requires efficient management of each of these components in order to successfully deliver goods and services on schedule. Supply chain management comes with a great deal of detail-oriented analysis, including how shipments and goods are loaded and unloaded from the shipping containers. Both data modeling and AI precision are needed to determine the most efficient ways to get the goods on and off the containers.

For instance, Nike uses AI to predict demand for new running shoes even before they are released. Back in 2018, Nike precisely predicted demand for the Air Jordan 11, which were the most popular running shoes of the year. Artificial intelligence (AI) is a game-changer for supply chains, becoming a need rather than a luxury. A 2023 Meticulous Research study reports the market for AI in supply chain is expected to reach $41 billion by 2030, growing 39% yearly from 2023. Envision a world where supply chains are self-aware, can forecast tomorrow’s customer demand, and can analyze their own inefficiencies and re-route shipments in real time based on rapid weather changes. The 2020 pandemic and other geopolitical disruptions have demonstrated how weak supply chains can bring down entire organizations.

Use Case 2: Substitution Solution by Walmart

If any issues arise, the customer can directly speak with the customer service team, which is very beneficial to resolving the issue in less span. The items that could not move for a long time in the warehouse are pushed backwards and then replaced with fast-moving materials. It will be really a big task for retailers to move old items out of the warehouse if there is no proper planning and implementation.

The forecasting engine let ATD move from fixed forecast intervals to dynamic planning. The solution increases forecast collaboration with its suppliers and end retailers so the ATD team can make more demand-responsive decisions. One shipper reporting benefits from AI is American Tire Distributors (ATD), which supplies tires, wheels, and tools to the automotive market. The company deployed ToolsGroup Service Optimizer 99+ (SO99+), which has an AI-powered probabilistic forecasting engine, to gain insights into demand behavior.

Sales and operations planning

However, the complexity and volatility across global supply chains present new problems every day. Innovative AI in supply chain use cases tackles these issues at the micro and macro levels. The benefits of AI in supply chain mean consumer goods companies can optimize their route planning and warehouse fulfillment operations. In doing so, companies can decrease their emissions to advance their sustainability goals, as well as reduce labor costs and improve customer service levels. AI in Logistics is the incorporation of Artificial Intelligence to improve efficiency and accuracy in the management of the products and services that make up a supply chain. AI can be used to facilitate numerous processes such as process mining, customer service, data collection, supply chain optimization, and service providers.

• For example, UPS has developed an Orion AI algorithm for last-mile tracking to make sure goods are delivered to shoppers in the most efficient way.
• AI-powered with big data can help the supply chain become not only sustainable but resilient at the same time.
• And, the effectiveness of the response increases proportionally to how fast the business can respond to problems.
• Companies are training models on their own data sets, and then asking AI to find ways to improve productivity and efficiency.

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