Understanding Supply Chain Analytics is a practitioner's guide to both the fundamentals of supply chain management and the analytical tools that make those fundamentals intelligent. The book covers the full operational landscape - demand planning, sourcing, production, inventory, warehousing, order fulfillment, master data, and customer management - and then layers on the analytics methods that turn operational data into decisions: time series forecasting, Monte Carlo simulation, optimization models, and advanced statistical techniques.
What makes this book timely is its treatment of generative AI - not as a replacement for quantitative methods, but as a complementary layer that can explain forecasts in plain language, surface insights from unstructured data like emails and contracts, and make advanced analytics accessible to non-specialists.
Written by two practitioners with excellent supply chain experience, the book is designed for professionals who want enough analytical intuition to ask better questions, challenge black-box outputs, and build supply chains that are not just efficient on paper, but genuinely resilient in practice.
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