Professional Certificate in Analytics for Supply Chain Performance Improvement
-- ViewingNowThe Professional Certificate in Analytics for Supply Chain Performance Improvement is a comprehensive course designed to empower learners with the essential skills needed to drive data-driven decision-making in supply chain management. This certificate course is of paramount importance due to the increasing demand for analytics in optimizing supply chain performance, reducing costs, and improving operational efficiency.
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⢠Introduction to Supply Chain Analytics: Fundamentals of data-driven decision making, supply chain analytics tools and techniques, and their impact on performance improvement.
⢠Data Management for Supply Chain: Data collection, cleaning, and validation; data integration and warehousing; data security and privacy in the supply chain context.
⢠Descriptive Analytics for Supply Chain: Data visualization, exploratory data analysis, and reporting; identifying trends, patterns, and exceptions in supply chain data.
⢠Predictive Analytics in Supply Chain: Statistical modeling, machine learning, and simulation; demand forecasting, inventory management, and supply chain risk analysis.
⢠Prescriptive Analytics for Supply Chain: Optimization models, decision trees, and heuristics; supply chain network design, logistics optimization, and supplier relationship management.
⢠Implementing Analytics in Supply Chain: Change management, communication, and collaboration; integrating analytics into supply chain processes, systems, and culture.
⢠Performance Metrics for Supply Chain Analytics: Key performance indicators (KPIs), balanced scorecards, and dashboards; measuring and monitoring supply chain efficiency, effectiveness, and flexibility.
⢠Ethics and Legal Issues in Supply Chain Analytics: Data ownership, privacy, and security; ethical use of algorithms and models; legal and regulatory compliance in supply chain analytics.
⢠Emerging Trends in Supply Chain Analytics: Artificial intelligence, internet of things (IoT), and blockchain; their potential impact on supply chain analytics and performance improvement.
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