
Supply Chain Analytics and Data-Driven Decision-Making Training Program
Preamble
In today’s fast-paced business environment, Supply Chain Analytics plays a crucial role in enhancing efficiency, reducing costs, and improving overall performance. Organizations are increasingly leveraging data-driven decision-making to optimize procurement, inventory management, logistics, and demand forecasting.
This training program is designed to equip participants with the skills and tools needed to collect, analyze, and interpret supply chain data, enabling them to make informed, strategic decisions. By incorporating predictive analytics, AI, machine learning, and real-time data insights, this program empowers professionals to drive operational excellence and business growth.
Training Objectives
By the end of this training, participants will be able to:
✅ Understand the role of data analytics in supply chain management.
✅ Apply descriptive, predictive, and prescriptive analytics to optimize supply chains.
✅ Use big data, AI, and machine learning for demand forecasting and inventory optimization.
✅ Implement data visualization techniques for actionable insights.
✅ Improve supply chain efficiency using real-time tracking and IoT analytics.
✅ Develop data-driven strategies for cost reduction and risk management.
✅ Enhance decision-making processes using analytics tools and dashboards.
Training Content
Module 1: Introduction to Supply Chain Analytics
📌 What is Supply Chain Analytics and why does it matter?
📌 The role of data-driven decision-making in modern supply chains
📌 Overview of analytics types: Descriptive, Predictive, and Prescriptive Analytics
📌 Case studies on data-driven supply chain improvements
Module 2: Data Collection & Integration in Supply Chains
📌 Sources of supply chain data – ERP, IoT, RFID, sensors, and logistics data
📌 Big Data in Supply Chains – Handling large datasets for decision-making
📌 Data accuracy & quality control – Ensuring reliable analytics
📌 Data integration across suppliers, warehouses, and logistics partners
Module 3: Demand Forecasting & Inventory Optimization
📌 Predictive analytics for demand forecasting
📌 Machine learning models for inventory optimization
📌 Real-time inventory tracking using IoT and cloud solutions
📌 Reducing waste and stockouts with smart inventory management
Module 4: Logistics & Transportation Analytics
📌 Route optimization using AI and geospatial analytics
📌 Cost reduction strategies through real-time tracking & fleet analytics
📌 Warehouse automation & robotics for supply chain efficiency
📌 Enhancing delivery performance with blockchain & smart contracts
Module 5: Risk Management & Decision Science
📌 Identifying supply chain disruptions through predictive analytics
📌 AI-driven decision models for crisis response and risk mitigation
📌 Cybersecurity risks in data-driven supply chains
📌 Real-world applications of prescriptive analytics in risk management
Module 6: Tools & Technologies in Supply Chain Analytics
📌 Overview of analytics tools: Tableau, Power BI, Python, R, SAP Analytics
📌 Using dashboards & visualization techniques for actionable insights
📌 How blockchain, AI, and IoT enhance supply chain analytics
📌 Future trends: Autonomous supply chains and AI-driven decision-making
Final Assessment & Certification
📌 Case study analysis on data-driven decision-making
📌 Certification awarded upon successful completion
Target Market
This training is designed for:
✅ Supply Chain Managers & Analysts – Using data for strategic planning.
✅ Operations & Logistics Professionals – Optimizing transportation and distribution.
✅ Procurement Officers – Leveraging analytics for supplier performance evaluation.
✅ IT & Data Science Teams – Developing AI-driven supply chain solutions.
✅ Business Executives & Decision-Makers – Enhancing data-driven leadership.
✅ Manufacturing & Inventory Managers – Improving stock management with predictive analytics.
Training Methodology
✔ Instructor-Led Training (ILT) – Sessions led by supply chain analytics experts.
✔ Hands-on Practical Exercises – Using analytics tools like Tableau, Power BI, and Python.
✔ Case Studies & Group Discussions – Learning from real-world success stories.
✔ Simulations & Role-Playing – Engaging activities for data-driven decision-making.
✔ E-Learning Modules – Self-paced online content and interactive lessons.
✔ Assessments & Certification – Knowledge evaluation and certification upon completion.