Visualize a future where technology ensures openness for transactions or can forecast demand and supply planning with extreme precision. These are not just fancy delusions but the supply chain environment of today blends with ease to this.
According to PRNewswire, with a projected value of USD 1713 million in 2023, the global artificial intelligence (AI) supply chain and logistics market is expected to grow at a compound annual growth rate (CAGR) of 10.1% from 2024 to 2030, reaching USD 3377.2 million.
Being the foundation of modern commerce where accuracy and efficiency can either help or hinder a company, Supply Chain Solutions ensures that every part runs well, from the efficient flow of raw materials to the prompt delivery of completed goods. Though the whole process flow in SCM is important, it’s the cutting-edge applications that propel industries forward that make SCM in logistics stand out for itself.
Join us to delve into diverse AI use cases that demonstrate SCM’s revolutionary potential in various fields.
Real-time use cases of SCM
- Predictive Demand Forecasting
Walmart is a renowned Retailer with franchises around the globe. Though it is possible to predict customer behavior, there can be additional hurdles due to unanticipated occurrences and their impact on typical purchasing habits.
However, to account for anomalies—like a Florida snowstorm that happens just once in a lifetime—in their inventory management procedure, Walmart attempts to match demand as nearly as possible to past customer trends and modifications.
AI/ML engines’ ability to withstand abnormalities, preventing the introduction of one-time deviations into subsequent inventory management procedures, gives them such immense strength.
AI (1)-driven systems ascertain the amount and timing of inventory flow and pinpoint the precise location of distribution. It helps to better understand clients’ needs by differentiating them based on zip codes owing to increased precision in regional distribution zones.
Walmart systems are optimizing Spark delivery routes to save clients time from the point of purchase to their front door so they may enjoy at-home delivery.
- Optimized Inventory levels
Managing ideal inventory levels was challenging for a Fortune 500 telecom firm due to its extensive global warehouse network and diverse SKU usage patterns. It resulted in high CAPEX.
GeakMinds approach involved analyzing previous consumption trends to determine the demand for each part. Any sizable new order that might be placed in advance and was taken into consideration also had an impact on demand.
The application’s react web UI and AI/ML model were developed with network planners enabling them to examine daily stock levels and all inventory-related KPIs. This reduced overstocking and enabled proactive measures to prevent understocking through effective monitoring and recommendations, achieving a Just-In-Time (JIT)Inventory.
- Improved Supplier Management
A major US retailer and a European container shipping company are utilizing GenAI-powered bots to speed up the process of negotiating purchase terms and costs with vendors.
When asked how the bot performed, more than 65% of vendors said they would rather negotiate with it than with a human employee, demonstrating how the technology allows them to accomplish more with less. Additionally, there have been cases when businesses have used GenAI tools to bargain with one another.
In addition to offering advice on what to do next, GenAI offers recommendations to enhance supplier relationships and management outside of discussions.
- Efficient Logistics and Route Planning
Using a proprietary AI platform, one of the largest logistics companies in the US is optimizing picking routes within its warehouses, increasing worker productivity by over 30% and reducing operating costs through better use of space and materials handling.
With the application of AI, the generative component adds new levels of customization, such as optimizing using less fuel, giving specific deliveries priority, or taking into account a variety of other parameters in a user-friendly application.
The organization was able to determine whether its trade network was optimized and receive suggestions for development by chatting with its tailored tool.
- Risk Mitigation
An Automotive Company wanted to detect and assess possible risks in its supply chain, such as interruptions brought on by catastrophes or global crises.
The generative AI model finds weak points in the supply chain by examining past supply chain data and other external factors. This helps the Automotive company create backup plans or strategic action plans to reduce the effect of possible risks.
- Automated Quality Assurance
By designating an end-to-end strategy that enables scalable technology adoption, Colgate has included AI in its supply chain. This strategic position promotes an overall perspective of the supply chain, enhancing efficiency and coordination at every turn.
Colgate makes sure that AI-driven automation improves operational effectiveness and overall business performance. Colgate’s supply chain resilience and efficacy have increased as a result of this deliberate and continuous application of AI, which has supported the company’s long-term growth and steady financial performance.
Conclusion
There has been a wide-ranging impact of SCM in manufacturing, e-commerce, retail, and technology. Through the utilization of cutting-edge technologies, businesses may optimize their supply chains to boost productivity, cut expenses, and boost customer satisfaction.
GeakMinds solutions are aimed at improving the productivity of your supply chain management operations. Get in touch with us and we will help you enhance your company’s growth by achieving flawless supply chain performance.
Reference:
- https://tech.walmart.com/content/walmart-global-tech/en_us/blog/post/walmarts-ai-powered-inventory-system-brightens-the-holidays.html