Supply Chain and Logistics Business Intelligence Applications Training Course: Optimizing Operations and Enhancing Decision-Making

Introduction

In today’s fast-paced global economy, supply chain and logistics operations generate vast volumes of data from procurement, inventory, transportation, and distribution activities. Business Intelligence (BI) empowers organizations to transform this data into actionable insights, improving operational efficiency, reducing costs, and enhancing decision-making. Through advanced analytics, predictive modeling, and interactive dashboards, BI solutions provide a comprehensive view of supply chain performance, enabling companies to anticipate disruptions, optimize resources, and streamline logistics operations.

This training course equips participants with the knowledge and practical skills required to apply Business Intelligence in supply chain and logistics contexts. Through real-world case studies, hands-on exercises, and BI platform integration, learners will explore supply chain data modeling, operational analytics, risk management, and predictive forecasting. By the end of the course, participants will be able to design and implement BI solutions that improve supply chain visibility, enhance logistics performance, and support data-driven decision-making.

Duration: 10 Days

Target Audience

  • Supply chain analysts and logistics managers
  • Business Intelligence professionals in operations
  • Data analysts working with supply chain or logistics datasets
  • Operations managers seeking efficiency improvements
  • Decision-makers responsible for strategic and operational supply chain planning

10 Objectives

  1. Understand the fundamentals of supply chain and logistics analytics
  2. Explore BI tools and techniques for operational and strategic insights
  3. Design data models and reporting frameworks for supply chain operations
  4. Implement ETL/ELT pipelines for logistics and operational datasets
  5. Apply predictive analytics for demand forecasting and risk mitigation
  6. Integrate BI dashboards for real-time supply chain monitoring
  7. Ensure data quality, governance, and compliance in analytics
  8. Optimize BI performance for complex supply chain datasets
  9. Examine industry best practices and case studies
  10. Develop and deploy a comprehensive supply chain and logistics BI project

15 Course Modules

Module 1: Introduction to Supply Chain and Logistics BI

  • Overview of BI in supply chain and logistics
  • Key benefits for operational efficiency and decision-making
  • Core components of supply chain BI systems
  • Emerging trends in logistics analytics
  • Data-driven decision-making in supply chain management

Module 2: Supply Chain Data Sources

  • Procurement, inventory, and transportation data
  • Warehouse management system (WMS) data
  • Enterprise resource planning (ERP) integration
  • External data sources (suppliers, carriers, market trends)
  • Data quality and integration challenges

Module 3: Data Modeling for Supply Chain Analytics

  • Star and snowflake schemas for supply chain datasets
  • Fact and dimension tables for operational metrics
  • Normalization vs denormalization for reporting
  • Designing models for KPIs and performance metrics
  • Optimizing models for large-scale datasets

Module 4: ETL/ELT Processes in Supply Chain BI

  • Extracting data from multiple operational systems
  • Transforming data for analytics readiness
  • Loading into warehouses or BI platforms
  • Automating workflows for efficiency
  • Monitoring and troubleshooting pipelines

Module 5: Inventory and Warehouse Analytics

  • Monitoring stock levels and turnover rates
  • Warehouse performance metrics
  • Inventory optimization strategies
  • Forecasting stock requirements
  • KPI tracking for storage efficiency

Module 6: Transportation and Logistics Analytics

  • Monitoring delivery performance and transportation costs
  • Route optimization and fleet management
  • Carrier performance evaluation
  • Transportation KPIs and benchmarking
  • Reducing lead times and operational bottlenecks

Module 7: Supplier and Procurement Analytics

  • Supplier performance and reliability assessment
  • Cost analysis and negotiation insights
  • Risk assessment in procurement
  • Vendor scorecards and reporting
  • Forecasting procurement needs

Module 8: Demand Forecasting and Planning

  • Predictive analytics for demand trends
  • Sales and operations planning integration
  • Scenario modeling and simulation
  • Balancing supply and demand
  • Reducing stockouts and overstock situations

Module 9: Real-Time Supply Chain Monitoring

  • Event-driven analytics for logistics
  • Low-latency dashboards and alerts
  • Tracking shipments and inventory in real-time
  • Operational reporting for managers
  • Automated notifications for critical events

Module 10: Risk Management in Supply Chain BI

  • Identifying operational, financial, and market risks
  • Risk scoring and prioritization
  • Predictive risk modeling
  • Mitigation strategies
  • Reporting risk exposure to stakeholders

Module 11: BI Tool Integration for Supply Chain

  • Connecting BI platforms to operational systems
  • Interactive dashboards for supply chain and logistics metrics
  • Automated reporting and visualization
  • KPI tracking for operations and finance
  • Real-world integration examples

Module 12: Cloud and Hybrid Supply Chain BI Architectures

  • Cloud-based storage and analytics solutions
  • Hybrid deployments for sensitive supply chain data
  • Security and compliance considerations
  • Scalability and cost optimization
  • Deployment best practices

Module 13: Data Governance and Compliance

  • Ensuring data accuracy and consistency
  • Access control and user management
  • Regulatory compliance considerations
  • Audit trails and reporting standards
  • Governance frameworks for BI in supply chain

Module 14: Advanced Analytics and Optimization

  • Predictive modeling for demand and supply planning
  • Optimization of logistics and warehouse operations
  • Machine learning for forecasting and anomaly detection
  • Prescriptive analytics for decision-making
  • Industry case studies and success stories

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport Pick Up is provided by the institute. Accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

For More Details call: +254-114-087-180

 

Supply Chain And Logistics Business Intelligence Applications Training Course: Optimizing Operations And Enhancing Decision-making in Kenya
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