Course Overview

Supply Chain and Logistics Analytics is a comprehensive professional training program designed to equip supply chain managers, logistics professionals, procurement officers, operations managers, business analysts, warehouse managers, transportation planners, and decision-makers with advanced skills in analyzing supply chain data to improve efficiency, reduce costs, and enhance operational performance. As organizations increasingly adopt Supply Chain Analytics, Logistics Analytics, Procurement Analytics, Inventory Optimization, Transportation Analytics, Warehouse Analytics, Demand Forecasting, Supply Chain Management, Business Intelligence, and Data-Driven Operations, there is a growing demand for professionals who can transform supply chain data into actionable insights that support strategic and operational decision-making. This course provides participants with practical expertise in applying analytics across procurement, inventory management, transportation, warehousing, and end-to-end supply chain operations.

The training explores the complete supply chain analytics lifecycle, including data collection, integration, performance measurement, forecasting, optimization, risk management, dashboard development, and reporting. Participants will learn how to analyze procurement performance, supplier data, inventory levels, transportation networks, warehouse operations, customer demand patterns, and logistics costs using advanced analytical techniques. The course combines theoretical foundations with practical applications using real-world supply chain datasets and logistics management scenarios.

Participants will gain hands-on experience in supply chain performance analysis, demand forecasting, inventory optimization, route planning, predictive analytics, KPI monitoring, business intelligence reporting, and supply chain risk assessment. The course emphasizes operational excellence, cost reduction, customer service improvement, sustainability, resilience, and evidence-based decision-making. Through practical exercises and case studies, participants will develop confidence in designing and implementing analytics systems that improve supply chain visibility, agility, and efficiency.

The training further addresses emerging trends in supply chain management, including artificial intelligence, machine learning, Internet of Things (IoT), digital twins, blockchain-enabled logistics, real-time tracking systems, predictive maintenance, cloud-based supply chain platforms, and intelligent logistics ecosystems. Participants will develop competencies required to build data-driven supply chains that support organizational competitiveness, resilience, sustainability, and long-term growth.

Course Objectives

1. Understand the principles and applications of supply chain and logistics analytics.

2. Collect, manage, and analyze supply chain and logistics data effectively.

3. Measure and improve supply chain performance using analytical tools.

4. Apply forecasting techniques to demand and inventory planning.

5. Optimize procurement, warehousing, and transportation operations.

6. Conduct supply chain risk assessment and mitigation planning.

7. Develop dashboards and performance monitoring systems.

8. Utilize predictive analytics for operational decision-making.

9. Improve customer service and operational efficiency through analytics.

10. Apply emerging technologies to modern supply chain management challenges.

Organizational Benefits

1. Improved supply chain visibility and operational transparency.

2. Enhanced inventory management and reduced stock-related costs.

3. Better demand forecasting and production planning.

4. Improved transportation and logistics efficiency.

5. Reduced procurement and operational expenses.

6. Enhanced supplier performance management.

7. Increased customer satisfaction through timely deliveries.

8. Improved supply chain resilience and risk management.

9. Better decision-making through real-time analytics and reporting.

10. Increased competitiveness through optimized supply chain performance.

Target Participants

· Supply chain managers and coordinators

· Logistics and transportation professionals

· Procurement and sourcing officers

· Warehouse and inventory managers

· Operations and production managers

· Business intelligence and data analysts

· Demand planners and forecasting specialists

· Distribution and fleet management professionals

· Manufacturing and retail managers

· Government and public sector logistics officers

· Consultants and supply chain advisors

· Anyone involved in supply chain management, logistics, and operations

Course Outline

Module 1: Introduction to Supply Chain and Logistics Analytics

1. Fundamentals of supply chain analytics

2. Logistics management concepts and frameworks

3. Supply chain performance measurement

4. Data-driven decision-making in operations

5. Supply chain analytics lifecycle

6. Emerging trends in supply chain intelligence

Case Study:
Developing a supply chain analytics strategy to improve operational performance and customer satisfaction.

Module 2: Supply Chain Data Management and Integration

1. Supply chain data sources and systems

2. Enterprise Resource Planning (ERP) integration

3. Data collection and management techniques

4. Data quality assurance and governance

5. Supply chain information systems

6. Data visualization and reporting fundamentals

Case Study:
Integrating procurement, inventory, and logistics data into a centralized analytics platform.

Module 3: Procurement and Supplier Analytics

1. Procurement performance metrics

2. Supplier evaluation and scorecards

3. Spend analysis methodologies

4. Supplier risk assessment

5. Strategic sourcing analytics

6. Contract performance monitoring

Case Study:
Analyzing supplier performance data to improve procurement efficiency and reduce risks.

Module 4: Inventory Analytics and Optimization

1. Inventory performance measurement

2. Stock level analysis and control

3. ABC and XYZ inventory classification

4. Safety stock and reorder point optimization

5. Inventory turnover and carrying cost analysis

6. Inventory forecasting techniques

Case Study:
Optimizing inventory levels to reduce stockouts and excess inventory costs.

Module 5: Demand Forecasting and Planning

1. Demand forecasting methodologies

2. Time series forecasting techniques

3. Seasonal and trend analysis

4. Forecast accuracy measurement

5. Collaborative planning processes

6. Demand-driven supply chain strategies

Case Study:
Forecasting product demand to improve production and inventory planning.

Module 6: Warehouse Analytics and Operations Optimization

1. Warehouse performance metrics

2. Storage and space utilization analysis

3. Picking, packing, and fulfillment analytics

4. Workforce productivity measurement

5. Warehouse process optimization

6. Automation and smart warehouse technologies

Case Study:
Improving warehouse efficiency through performance analytics and process redesign.

Module 7: Transportation and Distribution Analytics

1. Transportation performance measurement

2. Route optimization methodologies

3. Fleet utilization analysis

4. Delivery performance monitoring

5. Freight cost analysis

6. Last-mile delivery optimization

Case Study:
Using logistics analytics to reduce transportation costs and improve delivery performance.

Module 8: Supply Chain Risk and Resilience Analytics

1. Supply chain risk identification

2. Risk assessment frameworks

3. Disruption impact analysis

4. Supplier and logistics risk monitoring

5. Resilience and contingency planning

6. Risk mitigation strategies

Case Study:
Assessing supply chain vulnerabilities and developing resilience strategies during disruptions.

Module 9: Predictive Analytics and Supply Chain Intelligence

1. Predictive analytics concepts

2. Machine learning applications in supply chains

3. Predictive maintenance for logistics assets

4. Demand and inventory prediction models

5. Intelligent decision-support systems

6. Performance forecasting techniques

Case Study:
Applying predictive analytics to improve supply chain planning and operational efficiency.

Module 10: Supply Chain Dashboards and Business Intelligence

1. KPI development and performance tracking

2. Dashboard design and visualization principles

3. Real-time monitoring systems

4. Executive reporting and scorecards

5. Interactive analytics tools

6. Data storytelling for supply chain management

Case Study:
Developing a real-time supply chain performance dashboard for executive decision-making.

Module 11: Digital Transformation and Emerging Technologies

1. Internet of Things (IoT) in logistics

2. Artificial intelligence and machine learning applications

3. Blockchain in supply chain management

4. Digital twins and simulation models

5. Cloud-based supply chain platforms

6. Smart logistics ecosystems

Case Study:
Implementing digital technologies to improve supply chain visibility and traceability.

Module 12: Strategic Supply Chain Analytics and Future Trends

1. Supply chain strategy development

2. Sustainable and green supply chain analytics

3. Global supply chain performance management

4. Future trends in logistics and operations analytics

5. Building a data-driven supply chain culture

6. Strategic roadmap for supply chain transformation

Case Study:
Designing an integrated supply chain and logistics analytics ecosystem that combines procurement intelligence, supplier performance management, inventory optimization, demand forecasting, warehouse analytics, transportation monitoring, predictive risk management, AI-powered decision support, business intelligence dashboards, and sustainability metrics to improve operational efficiency, resilience, customer satisfaction, cost optimization, and long-term organizational competitiveness.

Essential Information

Our courses are customizable to suit the specific needs of participants.
Participants are required to have proficiency in the English language.
Our training sessions feature comprehensive guidance through presentations, practical exercises, web-based tutorials, and collaborative group activities. Our facilitators boast extensive expertise, each with over a decade of experience.
Upon fulfilling the training requirements, participants will receive a prestigious Global King Project Management certificate.
Training sessions are conducted at various Global King Project Management Centers, including locations in Nairobi, Mombasa, Kigali, Dubai, Lagos, and others.
Organizations sending more than two participants from the same entity are eligible for a generous 20% discount.
The duration of our courses is adaptable, and the curriculum can be adjusted to accommodate any number of days.
To ensure seamless preparation, payment is expected before the commencement of training, facilitated through the Global King Project Management account.
For inquiries, reach out to us via email at training@globalkingprojectmanagement.org or by phone at +254 114 830 889.
Additional amenities such as tablets and laptops are available upon request for an extra fee. The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a certificate of successful completion. Participants are responsible for arranging and covering their travel expenses, including airport transfers, visa applications, dinners, health insurance, and any other personal expenses.

Supply Chain and Logistics Analytics Training Course