Rick Morris is the CEO of Thrive Technologies, a provider of digital supply chain planning to SKU-intensive companies.
Managing supply chains would be simple if demand and supply remained constant. However, in reality, they fluctuate continuously—often unpredictably—creating challenges for businesses trying to maintain optimal inventory levels. The disruptions caused by events like the COVID-19 pandemic highlighted just how quickly supply chain dynamics can shift, leading to costly stockouts or excess inventory.
AI is transforming supply chain management by providing real-time insights that traditional methods often miss. By detecting subtle changes in demand patterns, supplier performance and logistics bottlenecks, AI helps businesses stay ahead of disruptions, optimize inventory and improve overall efficiency.
To help leaders take advantage of new opportunities for business resilience, I asked members of the Supply Chain group, a community I lead through Forbes Business Council, to share insight into one area in supply chain management that they think has tremendous room for AI.
1. Allowing Healthcare Professionals To Focus On Patients Rather Than Logistics
AI has huge potential in optimizing inventory management within healthcare supply chains. By accurately predicting demand, AI ensures that essential medications and supplies are always available, reducing waste and preventing shortages. Implementing AI can streamline operations, enhance efficiency, and allow healthcare professionals to focus more on patient care rather than logistics. – Dr. Christina Carter, Her Practice®
2. Combating Cargo Theft
AI will play a huge role in fighting cargo theft. It can be employed to analyze large amounts of information to identify potential risks for cargo shipments. This helps predict where and when thefts might happen, allowing for better protection. AI can also spot unusual activity, like sudden stops or unauthorized access, and quickly alert people to potential problems. By planning safer routes and automating tasks after a theft, AI can improve security and reduce the time it takes to respond. – Sabeer Nelliparamban, Tyler Petroleum Inc
3. Improving Truck Driver Recruiting
AI has significant potential in truck driver recruiting within supply chain management. By analyzing data on driver performance and retention, AI can predict which candidates will perform well and stay long-term. This optimizes the recruitment process, improves hire quality, and ensures a reliable transportation network, which is crucial for efficient supply chain operations. – Kameel Gaines, Rig On Wheels Broker & Recruitment Services
4. Avoiding Stockouts
Inventory management is an area of supply chain with a great opportunity for AI to enhance accuracy and efficiency in stock control. It analyzes historical data and current trends and helps optimize inventory levels. With predictive analytics, AI forecasts future demand, helping companies keep the right inventory level to meet customer needs and ensuring timely restocking and no stockouts. It can improve operational efficiency, customer satisfaction and reduce costs. – Abhishek Jajoo, AJMS Global Consulting LLC
5. Optimizing Transportation Management Systems
By leveraging AI, transportation management systems (TMS) can analyze vast amounts of real-time and historical data, such as traffic patterns, weather conditions, fuel costs and driver availability, to optimize route suggestions and scheduling in real time. AI-driven predictive analytics allows TMS to adjust routes proactively, reduce delays, improve fuel efficiency, and enhance load utilization. – Emmanuel Carrillo, Talon Logistics Inc
6. Providing Predictive Analytics
There’s a significant buzz surrounding the opportunities that AI brings to supply chains. However, it all boils down to data. Predictive analytics uses data to enhance demand forecasting, optimize supply chain operations, and manage risks. AI can analyze historical data and external factors to predict demand, identify inefficiencies, and anticipate disruptions, enabling companies to optimize inventory levels, reduce costs, and mitigate risks, leading to more efficient and resilient supply chains. – Ioana Dragomir, Tulipr
7. Forecasting Customer Demand
Demand forecasting in supply chain management is one area with great AI potential. Already, AI has remarkable accuracy in analyzing real-time data to forecast customer demand. As a result, companies may better control inventory, cut expenses and guarantee that goods are available when clients need them, improving overall process efficiency and responsiveness. – Waleed Najam, NEO Innovations
8. Providing End-To-End Visibility
AI can enable end-to-end visibility and predictive capabilities in supply chains. For instance, if a copper mine shuts down in China, AI can predict the impact on the production of OEMs in North America, suggest alternative suppliers, and adjust logistics to mitigate disruptions, ensuring business continuity and resilience. – Raghunandan Gurumurthy, Crossover Solutions
9. Predicting Demand In A Variety Of Industries
Demand prediction, based on previous data, is one of AI’s strong suits. Having inventory as close to the demand as possible would help supply chain managers tremendously. You don’t want to run the risk of having too few items for it will hit your top line. But you also don’t want a surplus, since that will create waste and hamper your bottom line. AI can sift through past data and help you keep just the right amount. – Vikram Joshi, pulsd
Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Read the full article here
