Next Gen Supply Chain Prediction: Increased “Operationalization” of AI/ML Yields Business Value
AI can help harness the power of external causal data such as weather, GDP, CPI, employment levels, and industrial production.
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The data explosion is at its peak and becoming more mainstream across all industries – the supply chain is no exception, maintains Dr. Madhav Durbha, Group Vice President of Industry Strategy at LLamasoft, a leading provider of enterprise supply chain design technology.
He predicts that Artificial Intelligence (AI) and Machine Learning (ML) will move beyond its current “hype cycle” next year to offer more tangible use cases that deliver real business value.
Below are a few examples of AI applications that will take off in 2020:
- Predicting Volatile Order Patterns: AI and ML will give companies the ability to predict less stable, highly volatile order patterns from customers. The supplier community is seeing increased volatility in demand signal due to an uptick in order volumes from leading online retailers. Predictability with the ordering is a challenge a significant challenge and AI models perform at much more optimal levels in these situations.
- Market Sensing: AI can help harness the power of external causal data such as weather, GDP, CPI, employment levels, and industrial production. Furthermore, it can serve as a better predictor of markets shifts and demand drivers, bringing better sensory capabilities into the supply chain, product portfolio, capital expenditure decisions, and long term strategic and capacity planning.
- Chargeback Reduction: Retailers charge hefty penalties to brand owners for missed OTIF (On Time in Full) deliveries. Deep learning algorithms allow sifting through key shipment data including order types, times, quantities, locations and transportation modes to identify root causes for chargebacks and predict points of failure.
Rise of Digital Twin to Tackle the “Never Normal”
With the rise of cloud and algorithmic intelligence, digital representations of a supply chain no longer needs to be a patchwork of models for sourcing, manufacturing, distribution, etc. Instead, a living model of a supply chain can be digitally rendered and real world events can be simulated to predict outcomes and actions for decisioning. A new breed of digital platforms capable of this virtual representation has emerged to help organizations cope with the “never normal” business environment.
“Built with cloud computing and marketing sensing capabilities, these platforms offer unprecedented speed and scale coupled with the power of advanced algorithms to help companies predict and plan for rapid market shifts,” contends Dr. Durbha.
About the Author
Patrick Burnson, Executive Editor Mr. Burnson is a widely-published writer and editor specializing in international trade, global logistics, and supply chain management. He is based in San Francisco, where he provides a Pacific Rim perspective on industry trends and forecasts. He may be reached at his downtown office: [email protected].Subscribe to Supply Chain Management Review Magazine!
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Article Topics
Artificial Intelligence · Management · Supply Chain Management ·It’s high time to go beyond visibility Driving supply chain flexibility in an uncertain and volatile world View More From this Issue