This course provides participants with a foundational understanding of how analytics supports supply chain decision-making. It focuses on transforming raw supply chain data into meaningful insights that improve operational performance. Participants will learn core analytical concepts, key performance metrics, and basic techniques used to analyze, interpret, and communicate supply chain data effectively.
By the end of the course, participants will be able to:
- Understand the role of analytics in supply chain management
- Identify key supply chain KPIs and metrics
- Clean and organize supply chain data
- Apply basic descriptive and predictive analytics techniques
- Translate analytical results into actionable decisions
The role of analytics in supply chains
- Fundamental analytical terminology and approaches
- Understanding the challenges and opportunities of big data
- Identifying the most important characteristics of supply chain KPIs
Capturing data strategies
- Mining data from suppliers, inventories, transportation, and customers
- Assessing data quality through quantified metrics
- Cleansing and normalizing data, as demonstrated in a detailed exercise
Processing data strategies
- Overview of analytics maturity models, techniques, and software
- Interpreting data accurately to avoid common pitfalls
- Analysing key criteria to prioritize products and customers
Data-driven decision-making
- Generating value from data through descriptive to prescriptive techniques
- Combining predictive and optimizing supply chain analytics
- Introduction to advanced automated analytics
- Supply chain and logistics professionals
- Operations and procurement staff
- Business analysts
- Supervisors and managers seeking data-driven decision skills