Module 1.1: Introduction to Supply Chain Analytics

  • The role of analytics in modern supply chains
  • Types of analytics: Descriptive, Diagnostic, Predictive, Prescriptive
  • The analytics maturity model
  • Building a data-driven culture
  • Common supply chain analytics use cases

Module 1.2: Understanding Supply Chain Data

  • Types of supply chain data (transactional, master, reference)
  • Key data sources: ERP, WMS, TMS, POS systems
  • Data quality fundamentals
  • Common data issues and how to address them
  • Data governance basics

Module 1.3: Key Performance Indicators (KPIs)

  • Financial metrics: Cost of Goods Sold, inventory carrying costs, freight costs
  • Operational metrics: order fulfillment rate, on-time delivery, cycle time
  • Customer service metrics: perfect order rate, fill rate, backorder rate
  • Inventory metrics: inventory turnover, days of supply, stock-out rate
  • Supplier performance metrics: lead time, defect rate, delivery performance

Hands-On Exercise:

  • Identify and calculate 10 key KPIs from sample supply chain data
  • Create a KPI dashboard framework for a fictional company
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