Supply Chain Analytics, KPIs, Dashboards & Data-Driven Decision Making Course
Introduction
Data-driven decision-making is revolutionizing supply chain management by enabling organizations to monitor performance, identify bottlenecks, and optimize operations. This course equips participants with practical skills to analyze supply chain data, define KPIs, and implement dashboards for actionable insights.
Understanding supply chain performance requires measuring the right indicators. Participants will learn how to develop, monitor, and interpret KPIs across procurement, production, logistics, and distribution to improve efficiency, reduce costs, and enhance service levels.
The course emphasizes advanced analytics techniques including descriptive, predictive, and prescriptive analytics. Participants will gain hands-on experience with data modeling, trend analysis, and scenario planning to drive informed operational and strategic decisions.
Dashboards and visualization tools are critical for effective communication of insights. Participants will explore best practices in dashboard design, reporting, and storytelling to ensure supply chain metrics are transparent, actionable, and aligned with organizational objectives.
Emerging trends such as AI-driven analytics, machine learning, real-time monitoring, and digital twins are reshaping supply chain intelligence. This course introduces participants to these technologies to create proactive, resilient, and highly responsive supply chains.
By the end of the course, participants will be able to design and implement analytics frameworks, select appropriate KPIs, develop interactive dashboards, and apply data-driven insights to optimize decision-making across supply chain functions.
Who Should Attend
- Supply Chain Managers and Directors
- Procurement and Sourcing Professionals
- Logistics and Distribution Managers
- Operations Managers
- Business Analysts and Data Analysts
- ERP and IT System Managers
- Production and Manufacturing Managers
- Finance and Performance Managers
- Quality Assurance and Compliance Officers
- Strategic Planning Officers
- Project and Program Managers
Duration
10 Days
Course Objectives
- Equip participants with practical skills to design and implement supply chain analytics frameworks for better decision-making.
- Develop the ability to define, monitor, and analyze KPIs across supply chain operations to enhance performance and efficiency.
- Provide techniques to collect, clean, and interpret supply chain data from multiple sources for actionable insights.
- Strengthen understanding of descriptive, predictive, and prescriptive analytics for informed operational and strategic decisions.
- Enhance competencies in dashboard development, data visualization, and storytelling to communicate supply chain performance clearly.
- Enable participants to apply scenario planning, trend analysis, and forecasting techniques for proactive supply chain management.
- Equip participants to leverage AI, machine learning, and advanced analytics tools for predictive insights and operational optimization.
- Strengthen skills in linking analytics outputs to business strategy, cost reduction, and service level improvement initiatives.
- Provide knowledge on integrating analytics platforms with ERP, SCM, and other digital supply chain systems for seamless reporting.
- Develop capabilities to continuously evaluate and improve supply chain KPIs, metrics, and dashboards for maximum impact.
- Enable participants to identify inefficiencies, bottlenecks, and risk areas using data-driven analysis and actionable insights.
- Equip participants to implement best practices and emerging trends in supply chain analytics for competitive advantage.
Comprehensive Course Outline
Module 1: Introduction to Supply Chain Analytics
- Role of analytics in modern supply chains
- Overview of data-driven decision-making
- Challenges and opportunities
- Case studies of successful analytics adoption
Module 2: Data Sources and Collection
- Internal vs external supply chain data
- Data extraction methods
- Data quality and cleaning
- ERP and SCM system integration
Module 3: Data Management and Governance
- Data storage and management frameworks
- Ensuring data accuracy and consistency
- Regulatory and compliance considerations
- Master data management
Module 4: Descriptive Analytics in Supply Chains
- Trend analysis and historical insights
- Operational performance review
- Reporting techniques
- Visualizing supply chain data
Module 5: Predictive Analytics Techniques
- Forecasting demand and supply
- Predictive modeling for inventory and production
- Machine learning applications
- Risk prediction and scenario analysis
Module 6: Prescriptive Analytics & Optimization
- Decision optimization models
- Resource allocation strategies
- Cost-benefit analysis
- Inventory and network optimization
Module 7: KPI Development and Monitoring
- Identifying critical supply chain metrics
- Performance measurement frameworks
- Benchmarking best practices
- Aligning KPIs with strategic goals
Module 8: Dashboard Design & Data Visualization
- Principles of effective dashboards
- Interactive reporting techniques
- Storytelling with data
- Tools: Power BI, Tableau, Excel
Module 9: Real-Time Monitoring & IoT Integration
- IoT sensors and real-time data capture
- Event-driven analytics
- Supply chain visibility dashboards
- Alerting and automated reporting
Module 10: Predictive Maintenance & Operational Analytics
- Analytics for production and equipment reliability
- Cost reduction through predictive maintenance
- Integrating predictive insights into operations
- KPI tracking for maintenance performance
Module 11: Strategic Analytics for Supply Chain Planning
- Linking analytics to supply chain strategy
- Integrated business planning (IBP)
- Scenario and sensitivity analysis
- Risk mitigation strategies
Module 12: Financial & Procurement Analytics
- Spend analysis and cost tracking
- Supplier performance evaluation
- Budget monitoring and forecasting
- Analytics-driven procurement decisions
Module 13: Customer Service & Logistics Analytics
- On-time delivery and service level KPIs
- Route optimization and distribution efficiency
- Predictive shipment tracking
- Customer satisfaction monitoring
Module 14: Emerging Technologies in Analytics
- AI and machine learning applications
- Digital twins for supply chain modeling
- Cloud-based analytics platforms
- Automation of reporting and dashboards
Module 15: Case Studies & Practical Application
- Industry-specific analytics examples
- Hands-on exercises and projects
- Problem-solving using real data
- Lessons learned from implementations
Module 16: Implementation & Continuous Improvement
- Developing analytics roadmaps
- Change management in analytics adoption
- Continuous KPI refinement
- Establishing a culture of data-driven decision-making
Training Approach
The instructor led trainings are delivered using a blended learning approach and comprises of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields.
All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.
Certification
Upon successful completion of the training, participants will be awarded a certificate of completion by Steady Development Center.
Training Venue
The training will be held online. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, tutorials and all required training manuals. Any other personal expenses are catered by the participant.
For registration and further enquiries, contact us on:
- Tel: +254 701 180 097
- Email: training@steadytrainingcenter.com
Tailor-Made Option
This course can be customized to suit the specific needs of your organization and be delivered on-line to any convenient location.
Terms Of Payment
Upon agreement by both parties’ payment should be made to Steady Development Center’s official account at least 3 working days before training begins to facilitate adequate preparation.
