The Building Blocks Are Evolving
The modern supply chain has always been a mixture of Makers, Movers, and Sellers. These functions are the basic building blocks of our modern supply chain.
Makers produce goods to be sold. This may mean taking raw materials, possibly combining them with other ingredients, even adding assembled components, and building a finished good that will then make its way through the supply chain via Movers and to the end consumer via Sellers.
Once these goods are produced, Movers must transport the goods to the location in which they will be sold. Movers are responsible for picking up these goods from the Makers, managing the goods in transit, and delivering them to the proper destination at the appropriate time.
Sellers must now receive the ready-to-sell product from Movers and ensure it is available to be sold to the end consumer.
Failure at any function can ultimately prevent the product from ever reaching the end consumer.
To combat failure and promote efficient handoffs between functions, the modern supply chain has evolved. We can now analyze every aspect of what is happening across the supply chain, compared to what we want to happen, and use micro-levers to adjust and pivot in real time. This gives each function a better chance at being successful at moving the final product into the hands of the consumer.
How well a supply chain can recognize potential issues and set resolutions in motion is now a competitive and strategic advantage for many businesses regardless of which function they perform. This advantage has been enabled by the deployment of leading-edge automation, operations research (OR), and artificial intelligence (AI) both within each function and across functions.
New Ways to Manage Old Problems
Used in combination, advanced automation, operations research (OR), and AI can provide powerful insights and autonomous resolution across the modern supply chain making it more intelligent.
Makers, Movers, and Sellers can individually and collectively benefit from the insights gained by deploying the latest advanced capabilities. In fact, the insights and increased value can be exponential when techniques such as deterministic heuristics, stochastic optimization, and AI algorithms including machine learning, deep learning, and natural language processing are used in collaborating across all functions.
Makers encounter challenges to operating in an agile and resilient manner. They need to manage parts, ingredients, and raw materials shortages and excesses and they need to know what is happening on the supplier side to better predict supply shortages and meet buyer demand.
Supports alerting and autonomous resolution to future supply shortages and minimizes expedites by optimizing safety stock for random demand via real-time supply signals and events.
Multi-echelon Inventory Optimization
Optimizes inventory levels across internal operations, external suppliers, and the channel ecosystem with nonlinear stochastic optimization and intelligent clustering of products to manage constraints like products with a limited shelf life.
Movers have their own set of challenges. To effectively move the goods, Movers must do everything they can to know when transportation issues may occur. They are constantly assessing how they can accurately know when a shipment will arrive and making improvements to the calculation. Additional challenges arise when managing the many aspects of cross-border trade compliance.
Movers can use advanced automation and OR to manage the process but must supplement this with the advantages of artificial intelligence and advanced learning techniques.
Predictive Shipment Arrival
Increases estimated arrival accuracy by using machine learning to identify shipment port and route clusters and generates its own models to assess arrival times in real-time and with the latest information updates.
Proactive Trade compliance
Increases compliance for cross-border trade regulations by proactively assessing countries of origin and destination and learning a classification system that drives proper licensing and documentation to significantly reduce manual compliance efforts.
Sellers are frequently operating blind when it comes to how much data and signals they are actually utilizing compared to all the information available to optimize their selling efforts. Typical solutions to increase visibility and insights when running promotions and understanding true and immediate fluctuations in demand are falling short if they are not utilizing the advanced learning techniques and algorithms available.
Enhances near-term demand accuracy with real-time data, automation, and learning algorithms by systematically processing and utilizing the predictive power of each demand signal.
Increases the predictability of the promotional impact from demand shifts and provides insights related to the cannibalization of related products by simulating the promotional lift.
Kickstart Your AI Journey
The roadmap to a resilient supply chain requires artificial intelligence. By consuming signals and events occurring within and outside your four walls and processing them with the power of AI and machine learning, each supply chain function can drive an effective roadmap through event and performance analysis, analytics-driven optimization, and achieve an autonomous supply chain.
To learn more about how you can gain AI-driven, end-to-end collaboration and insights across your multi-tier supply chain, please visit our latest infographic experience.
Jeff Eckel is Director of Product Marketing at e2open.