Spend Analytics

This course is designed to provide students with a comprehensive understanding of spend analytics and its applications in procurement and supply chain management. Students will learn how to collect, clean, analyze, and interpret spend data to gain insights into supplier performance, spend patterns, and cost savings opportunities. The course will cover key concepts and methods in spend analytics, including data warehousing, data mining, and data visualization. Additionally, students will explore the latest trends and emerging technologies in spend analytics.

Course Outline:

1. Introduction to Spend Analytics

• Definition of Spend Analytics
• Importance of Spend Analytics
• Key Concepts in Spend Analytics
• Applications of Spend Analytics

1. Data Collection and Preparation

• Types of Spend Data
• Data Collection Methods
• Data Cleaning and Preparation
• Data Warehousing

1. Data Analysis Techniques

• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics

1. Supplier Performance Analysis

• KPIs for Supplier Performance
• Benchmarking and Gap Analysis
• Contract Compliance Analysis
• Risk Management in Supplier Performance Analysis

1. Spend Pattern Analysis

• Types of Spend Patterns
• Cost Breakdown Analysis
• Spend Category Analysis
• Spend Variance Analysis

1. Cost Savings Analysis

• Types of Cost Savings
• Cost Reduction Techniques
• Value Analysis and Engineering
• Total Cost of Ownership Analysis

1. Advanced Topics in Spend Analytics

• Real-time Spend Analytics
• Spend Analytics for Services Procurement
• Artificial Intelligence and Machine Learning in Spend Analytics
• Emerging Technologies in Spend Analytics

Prerequisites:

• Basic understanding of procurement and supply chain management concepts
• Familiarity with Microsoft Excel or similar spreadsheet software
• Familiarity with statistical analysis concepts

Recommended Textbook:

• “Spend Analysis: The Window into Strategic Sourcing” by Kirit Pandit and Tim Cummins.

Assessment:

• Midterm Exam (30%)
• Final Exam (40%)
• Group Project (30%)

Note: The course syllabus and assessment methods are subject to change based on instructor’s discretion.