Duration 3 days – 21 hrs
Overview
This course equips participants with the essential data analysis skills required to support effective supply and operations management decisions. It focuses on using data to forecast demand, manage inventory, optimize procurement, and improve supply chain performance. Participants will learn how to interpret supply-related data, apply analytical techniques, and translate insights into actionable operational strategies that reduce costs, improve service levels, and increase efficiency.
Objectives
- Understand the role of data analytics in modern supply and operations management
- Analyze demand, inventory, procurement, and supplier performance data
- Apply basic forecasting and trend analysis techniques
- Identify supply chain inefficiencies using data-driven approaches
- Use data insights to support decision-making in supply planning and inventory control
- Communicate analytical findings clearly to management and stakeholders
Audience
- Supply Chain & Logistics Professionals
- Procurement & Purchasing Officers
- Inventory & Warehouse Managers
- Operations & Production Planners
- Business Analysts supporting supply functions
- Finance, Risk, or Planning professionals involved in supply decisions
- Supervisors and Managers responsible for supply and operations performance
Pre-requisites
- Basic understanding of supply chain or operations concepts
- Familiarity with spreadsheets (e.g., Microsoft Excel or Google Sheets)
- No advanced analytics or programming background required
Course Content
Module 1: Introduction to Data Analysis in Supply Management
- Overview of supply chain and operations management
- Why data analytics matters in supply decisions
- Types of supply chain data (demand, inventory, procurement, logistics)
- Descriptive, diagnostic, predictive, and prescriptive analytics
Module 2: Data Collection and Data Quality for Supply Chains
- Sources of supply and operations data
- Data accuracy, completeness, and timeliness
- Common data issues in supply and inventory management
- Data preparation and cleansing basics
Module 3: Demand Analysis and Forecasting Fundamentals
- Understanding demand patterns and variability
- Historical sales and consumption analysis
- Trend, seasonality, and moving averages
- Basic forecasting techniques for supply planning
- Forecast accuracy and error measurement
Module 4: Inventory Data Analysis and Optimization
- Key inventory concepts (EOQ, safety stock, reorder points)
- Inventory performance metrics (turnover, stockouts, carrying cost)
- Analyzing slow-moving and obsolete inventory
- Using data to balance service level vs. cost
Module 5: Procurement and Supplier Performance Analysis
- Spend analysis and procurement data insights
- Supplier performance metrics (cost, quality, delivery, reliability)
- Vendor comparison and evaluation using data
- Risk identification in suppliers and sourcing decisions
Module 6: Logistics and Distribution Data Analysis
- Transportation and delivery performance metrics
- Lead time and fulfillment analysis
- Cost-to-serve analysis
- Identifying bottlenecks in logistics operations
Module 7: Supply Chain Performance Measurement
- Key Supply Chain KPIs and dashboards
- Aligning metrics with business objectives
- Balanced scorecard approach for supply management
- Reporting and visualizing supply data for management
Module 8: Decision-Making Using Supply Analytics
- Translating data insights into operational decisions
- Scenario analysis and what-if planning
- Data-driven risk mitigation strategies
- Case study: Improving supply performance using analytics
Module 9: Practical Workshop and Case Study
- End-to-end supply data analysis exercise
- Group analysis and presentation of findings
- Management-level recommendations
- Lessons learned and best practices
