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Introduction to Supply chain Analytics
Rating: 4.2 out of 5(15 ratings)
430 students

Introduction to Supply chain Analytics

Supply Chain Analytics, Supply Chain Management, Data Analytics Business Analytics,Logistics Operations,Management Data
Created byManagement Excellence Academy
Last updated 1/2025
English
English [Auto],

What you'll learn

  • Understand the Fundamentals of Supply Chain Analytics
  • Develop Core Analytical Skills
  • Analyze Key Supply Chain Processes
  • Apply Supply Chain Analytics in Real-World Scenarios

Course content

7 sections • 26 lectures • 1h 32m total length

  • What is Supply Chain Analytics?2:56

    Explore the fundamentals of supply chain analytics and how data-driven decisions optimize inventory, predict demand, and reduce costs using predictive modeling, optimization algorithms, and data visualization.

  • The Importance of Data in Supply Chain Management1:13

    Supply chain analytics enables smarter decisions amid market pressures and competitive advantage by leveraging data from IoT, social media, and ERP to reveal insights that reduce costs and boost responsiveness.

  • Key components of Supply chain analytics1:51

    Advance supply chain analytics by integrating data from suppliers, distributors, warehouses, and customers, applying descriptive, predictive, and prescriptive analytics, and using optimization models to guide decisions and optimize performance.

  • Types of Data in Supply Chain Analysis10:22

    Identify descriptive, predictive, and prescriptive analytics to understand past performance, forecast future demand, and guide data driven supply chain decisions.

  • Data Quality and its Impact on Analysis4:47

    Improve supply chain analytics by enforcing data quality dimensions—accuracy, completeness, consistency, timeliness, validity, and uniqueness—through cleansing, validation, governance, audits, and integration.

  • Ethical Considerations in Supply Chain Analytics19:21

    Embed ethics into supply chain analytics by balancing privacy, fairness, transparency, and accountability, while applying data governance and GDPR and CCPA guidelines to reduce bias and uphold social responsibility.

Requirements

  • No Prerequisites needed

Description


Course Description:

This course provides an introduction to the concepts and techniques of supply chain analytics. Students will learn how to leverage data and analytical methods to improve the efficiency, resilience, and profitability of supply chains. The course will cover a range of topics, including data collection and preparation, descriptive and predictive analytics, supply chain performance measurement, and the application of analytics to key supply chain processes such as demand forecasting, inventory management, and logistics.

Learning Outcomes:

Upon successful completion of this course, you will be able to:


  • Understand the key concepts and principles of supply chain analytics.

  • Apply data analysis techniques to solve real-world supply chain challenges.

  • Interpret and communicate analytical findings effectively to stakeholders.

  • Develop data-driven solutions to improve supply chain efficiency and performance.

  • Gain a competitive edge in the evolving field of supply chain management.

Who Should Take This Course:

This course is ideal for:

  • Students pursuing degrees in All engineering studies including but not limited to Supply Chain Management, Logistics, Operations Management, Business Analytics, and related fields.

  • Professionals seeking to advance their careers in supply chain management, Business analytics, Supply chain analytics, Data analyst, and logistics.

  • Individuals interested in developing a strong foundation in data-driven decision-making within the supply chain context.

Who this course is for:

  • This course is designed for undergraduate and graduate students, working professionals in supply chain roles, and individuals seeking to enter the field who possess a foundational understanding of quantitative concepts and a strong interest in data-driven decision-making.

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