Description

Introduction

In Advanced Analytics today’s fast-paced global economy, businesses must leverage it to optimize this operations, reduce costs, and enhance efficiency. This training explores how data-driven decision-making, predictive modeling, and AI-powered insights can improve supply chain performance. Participants will learn techniques for demand forecasting, inventory management, logistics optimization, and risk mitigation.

Prerequisites

• Basic understanding of supply chain management concepts
• Familiarity with data analytics and key performance indicators (KPIs)
• Experience with Excel, SQL, or BI tools (Power BI, Tableau) is beneficial
• Knowledge of statistical analysis and machine learning basics is a plus

TABLE OF CONTENT

1 . Introduction

1.1 Background
1.2 Purpose of the Document
1.3 Scope and Objectives
1.4 Key Definitions

2 . Overview of Advanced Analytics for Supply Chain

2.1 Definition and Concept
2.2 Importance in Modern Business
2.3 Key Components of Supply Chain Analytics

3 . Data Collection in Supply Chain Analytics

3.1 Types of Data Sources
3.2 Data Collection Methods
3.3 Challenges in Data Collection

4 . Data Processing and Cleaning

4.1 Data Pre-processing Steps
4.2 Cleaning and Validation Techniques
4.3 Tools and Technologies in Advanced Analytics for Supply Chain

5 . Key Metrics and Performance Indicators

5.1 Inventory Turnover
5.2 Order Fulfillment Cycle Time
5.3 Supplier Performance Metrics
5.4 Demand Forecast Accuracy

6 . Data Analysis Techniques

6.1 Descriptive Analytics
6.2 Predictive Analytics
6.3 Prescriptive Analytics
6.4 Case Studiesin Advanced Analytics for Supply Chain(Ref: Oracle Advanced Supply Chain Planning (ASCP) Fundamentals)

7 . Technological Tools for Supply Chain Analytics

7.1 Business Intelligence (BI) Tools
7.2 Advanced Analytics Platforms
7.3 Artificial Intelligence (AI) and Machine Learning (ML) Applications

8 . Integration with ERP Systems

8.1 Benefits of ERP Integration
8.2 Challenges and Solutions in Advanced Analytics for Supply Chain

9 . Real-world Applications and Case Studies

9.1 Case Study 1: Optimizing Inventory Management
9.2 Case Study 2: Enhancing Demand Forecasting

10 . Challenges and Solutions in Supply Chain Analytics

10.1 Data Security and Privacy
10.2 Integration Challenges
10.3 Overcoming Resistance to Change

Please Visit PowerBI Official Site: || Locus Academy ha s more than a decade experience in delivering the training/staffing on this Optimization for corporates across the globe. The participants for the training/staffing on Supply Chain Optimization are extremely satisfied and are able to implement the learnings in their on going projects.

Other useful references

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