Most supply chains generate enormous amounts of data and act on almost none of it, relying instead on instinct and habit while dashboards sit unopened in the background. Supply Chain Analytics exists to close that gap, turning raw operational data into decisions that actually improve cost, service, and reliability rather than simply documenting what already happened. The Supply Chain Analytics and Performance Management Training Course, is built for supply chain professionals responsible for making data a genuine part of daily decision-making, not a report generated after the fact.
This course treats analytics and performance management as connected disciplines built around action, not reporting for its own sake. Participants learn how to apply business intelligence tools to surface patterns hidden in operational data, how to define and track KPIs that reflect what actually matters to the business, and how to build dashboards that make performance visible to the people who can act on it. The course also covers predictive analytics techniques for anticipating disruption and demand shifts before they occur, disciplined performance measurement practices that hold teams accountable to meaningful standards, and how to build a culture of data-driven decisions that replaces instinct with evidence. Participants leave with a practical analytics framework they can apply directly to their own supply chain operations.
Course Objectives
By the end of the course, participants will be able to:
By the end of this course, participants will be able to:
Apply supply chain analytics principles to improve cost, service, and reliability
Use business intelligence tools to identify patterns in operational data
Define and track KPIs that reflect meaningful supply chain performance
Build dashboards that make performance visible to decision-makers
Apply predictive analytics techniques to anticipate disruption and demand shifts
Implement performance measurement practices that drive accountability
Build a data-driven decision-making culture across supply chain teams
Translate analytics findings into concrete operational improvements
Target Group
Supply chain analysts and performance management professionals
Supply chain and logistics managers responsible for KPI tracking
Business intelligence professionals supporting supply chain functions
Operations managers seeking to strengthen data-driven decision-making
Planning and forecasting professionals working with predictive analytics
Professionals preparing for leadership roles in supply chain analytics
Course Outline
Foundations of Supply Chain Analytics
Core principles connecting analytics to real operational decision-making
Distinguishing actionable analytics from data collected but never used
Business Intelligence for Supply Chain
Applying business intelligence tools to surface patterns in operational data
Structuring data sources to support reliable, timely analysis
Defining and Tracking KPIs
Selecting KPIs that reflect meaningful supply chain performance
Avoiding vanity metrics that look good but don't drive decisions
Building Effective Dashboards
Designing dashboards that make performance visible to decision-makers
Prioritizing clarity and actionability over data volume
Predictive Analytics for Supply Chain
Applying predictive analytics to anticipate disruption and demand shifts
Using predictive models to support proactive, not reactive, decisions
Performance Measurement Practices
Implementing performance measurement systems that drive accountability
Aligning individual and team performance with supply chain objectives
Building a Data-Driven Culture
Encouraging data-driven decisions across supply chain teams and leadership
Overcoming resistance to replacing instinct with evidence-based decisions
Turning Analytics Into Action
Translating analytics findings into concrete operational improvements
Closing the loop between insight generation and implemented change
Sustaining Analytics Maturity Long-Term
Building ongoing analytics capability rather than one-off reporting projects
Reviewing analytics practices regularly as data and tools evolve