Why SCM Teams Are Finally Paying Attention to AI?
A recent study conducted by Gartner revealed that all the top supply chain organizations are investing in AI and ML at more than twice the rate of their competitors, showcasing AI’s crucial role in modern supply management. Why are they doing this? It’s mainly because AI systems can learn from data autonomously, they can discover patterns that are often overlooked.
But the real question is: are these companies seeing results? Is the ROI worth the hype?
So, how can AI improve supply chain?
Let’s take the example of the Red Sea crisis. Shipping routes have been disrupted, forcing companies to reroute their shipments, through longer, more expensive routes, leading to longer delivery timelines, unsatisfied customers, and increased costs. Meanwhile, companies that had AI systems in place were able to act far more quickly. They optimized shipment routes for quicker delivery, updated customers, and in turn dodged heavy losses.
While we’re certain that AI for supply management is the key to uncovering potential goldmines within the supply chain industry, let’s break down exactly why SCM teams are finally paying attention.
Cost Reduction
Forget endless spreadsheets - AI dives into complex data streams to spot cost-cutting opportunities in real time. AI-powered analytics help teams allocate resources better, streamline budgets, and cut unnecessary spending.
Enhanced Decision Making with Predictive Analytics
Supply chain leaders can make quick decisions with AI-powered predictive analytics. With AI models, the SCM team can anticipate future trends, demand fluctuations, and disruptions. AI can analyze historical data and other factors like weather patterns and market trends. It gives real-time end-to-end visibility from inventory levels to supplier delays. Therefore, no more inefficient decision-making with outdated data.
Project Visibility and Inventory Management
When visibility improves, so does accountability. AI-driven models offer real-time project updates and performance metrics, ensuring accountability. AI-enhanced applications can streamline inventory management by using predictive analytics for end-to-end visibility to determine optimal stock levels, minimizing stockouts and overstocking.
Optimized Logistics
AI-powered business applications can spot risks before they become a problem. AI can predict potential issues like delays and supply shortages. With AI, advanced route optimization and real-time tracking are possible for faster deliveries and fewer delays.
Enhanced Sustainability
AI-enabled sustainability trackers can determine efficient delivery routes, reducing fuel consumption and lowering carbon emissions. For example, Unilever has integrated AI to track environmental changes and improve traceability, to contribute to its sustainability goals.
Real AI Use Cases in Supply Management
Demand Forecasting
According to a report by McKinsey, AI is not only predicting trends but also reducing errors by 20 to 50%. AI models deliver sharper, simulation-driven forecasts by analyzing both historical and external data.
Inventory Optimization
AI-powered inventory optimization models can analyze sales data, trends, and lead times to recommend accurate inventory levels as well as minimize costs while preventing stockouts or excess stocks.
Risk Management
AI assists in mitigating risks in cases of sudden mishappenings, geopolitical events, regulatory changes, and market trends by identifying potential risks.
Procurement Strategy
AI algorithms assess and find the right procurement strategy by considering factors like supplier performance, economic indicators, and pricing trends.
Sustainability and Waste Reduction
AI-powered predictive analytics can predict production and consumption based on real-time data monitoring. With the deployment of sustainability trackers companies can direct their supply chain to zero in the areas for waste elimination, enhanced resource utilization, and ultimately cost savings.
Supplier Selection
For a resilient supply chain, supplier diversification and supplier management are crucial. AI can automate supplier onboarding processes, evaluate performance metrics and compliance requirements, and build a reliable supplier network without disruptions.
Route Optimization
AI can optimize truck routes and strategically place distribution centers, considering factors like traffic and fuel costs for increased efficiency and customer satisfaction.
Real World Cases
- FedEx utilizes AI-powered FedEx Surround to monitor shipments in real-time, reducing delays and enhancing supply chain reliability
- Walmart has integrated AI into its supply chain to improve its online pickup and delivery resulting in improved efficiency and customer satisfaction.
Conclusion
The future of AI for supply management is certainly remarkable. Integrating AI into your supply chain is no longer a choice but the faster it’s adapted the easier it is for businesses to stay competitive and build a healthy, and future-ready supply chain. Yes, there is an upfront investment while implementing AI into your systems, but it pays off quickly. And, what you get in return—fewer disruptions, fewer losses, better decisions, and happier customers—makes the payoff more than worth it.
Syren is at the forefront of revolutionizing supply chain management with AI, Data, and Analytics. With our AI-powered tools, we bring in real business impact. We understand every business’s unique challenges and we help them develop a resilient and robust supply chain.
Want to know how? Contact us today to get started!
