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Introduction Key Learning Outcomes Training Methodology Who Should Attend? Outline

Introduction

As organizations progress toward Industry 4.0, supply chains are becoming increasingly dependent on data-driven technologies to support agility, responsiveness, and operational excellence. The growing volume of information generated across procurement, manufacturing, logistics, transportation, and customer channels presents significant opportunities to improve forecasting, optimize resources, and enhance supply chain visibility. Organizations that can effectively analyze and leverage this data gain a substantial competitive advantage in managing complex and rapidly changing supply chain environments.

The Big Data Analytics for Supply Chain Optimization training course provides participants with practical knowledge of how to utilize big data analytics, simulation models, and emerging digital technologies to improve supply chain performance. The course explores data sources, analytical methodologies, forecasting techniques, and optimization frameworks that enable organizations to make faster, more informed decisions while reducing costs and increasing operational efficiency.

Participants will learn how to integrate analytics into supply chain planning, develop data-driven optimization strategies, and utilize simulation technologies to evaluate alternative scenarios. The training course also examines the role of artificial intelligence, ERP integration, and real-time decision support systems in creating future-ready supply chain operations.

Key focus areas include:

Big data sources and analytics applications within supply chain operations
Supply Chain 4.0 and Industry 4.0 integration strategies
Predictive forecasting and data-driven decision-making techniques
Supply chain optimization through analytics and simulation models
Manufacturing, logistics, and inventory optimization using big data
ERP integration and real-time supply chain intelligence

Key Learning Outcomes

At the end of this Big Data Analytics for Supply Chain Optimization training course, participants will be able to:

Identify and utilize key sources of big data across supply chain and logistics operations
Apply advanced analytics techniques to improve forecasting and operational performance
Develop data-driven optimization models for supply chain decision-making
Build and evaluate simulation scenarios to support strategic planning initiatives
Improve inventory, distribution, and manufacturing performance through analytics
Integrate analytics outputs with ERP and supply chain management systems
Enhance organizational readiness for Supply Chain 4.0 transformation
Support real-time and predictive decision-making using data-driven insights

Training Methodology

This training course adopts a highly practical and application-focused approach that combines expert instruction, real-world case studies, software-based exercises, and guided analytics workshops. Participants gain hands-on exposure to supply chain simulation and analytics tools while developing practical capabilities in data interpretation, forecasting, optimization, and digital supply chain planning. Emphasis is placed on translating analytical insights into actionable business decisions that deliver measurable operational improvements.

Who Should Attend?

This Big Data Analytics for Supply Chain Optimization training course is ideal for:

Supply Chain Managers
Operations Managers
Business Improvement Specialists
Industry 4.0 Leaders and Practitioners
Project Managers
Finance Managers
IT Managers
Supply Chain Analysts
Logistics Professionals
Business Consultants

Course Outline

Day 1

Industry 4.0 and Its Impact on Supply Chain

Industry 4.0 introduction
Industry 4.0 drivers and impacts
Supply chain and logistics within the Industry 4.0
Vision of the Supply Chain 4.0 and the future of logistics

Day 2

Big Data in Supply Chain and Logistics

Big Data 5V’s in supply chain and logistics
- Volume
- Velocity
- Variety
- Value
- Veracity
Sources of Big Data within the supply chain and logistics
Data driven supply chain optimization (K-means, Apriori, Aykin and Babu algorithms)

Day 3

Supply Chain Optimization

Framework oriented on customer requirements
Optimizing the sell operations
Optimization of distribution
Optimization of inventory management

Day 4

Optimization of Manufacturing Process

Optimizing product design and innovation
Optimizing the production process
Big Data analysis of logistics activities
Using created models as agents for future models creation

Day 5

Integration of Modern Software with Existing ERP Software

The AnyLogic cloud
Interoperability of AnyLogic and AnyLogistics with ERP software platforms
RFID and vehicle tracking systems connectivity
Data extrapolation for faster analysis and computation

International Standards & Professional Alignment

Our training courses are aligned with internationally recognised professional standards and frameworks across leadership, strategy, finance, governance, risk, compliance, and audit. By integrating globally trusted models, we ensure learners develop practical, relevant, and industry-recognised capabilities.

Our trainings draw on leading international standards and professional frameworks, including ISO, ISACA, COSO, OECD, IIA, FATF, Basel, IFRS/ISSB, GRI, NIST, CPD, ILM and the OECD AI Principles. This alignment ensures consistency with global best practices across financial management, risk oversight, digital governance, sustainability, and strategic decision-making..

Designed in alignment with globally recognised professional bodies, our courses support continuous professional development, strengthen organisational capability, and provide clear pathways toward professional certifications valued worldwide.