Introduction

Modern organizations rely on performance analytics to translate data into actionable insights, improve decision-making, and accelerate results.
This advanced program equips performance analysis managers with the tools, methods, and leadership skills to design KPI systems, build insight-driven narratives, and influence performance outcomes across functions.

Course Objectives

By the end of this course, participants will be able to:

• Design and optimize performance measurement systems aligned to strategy
• Build meaningful KPIs, targets, and scorecards that drive outcomes
• Apply advanced analytical methods to diagnose performance issues
• Develop executive-ready insights, storytelling, and recommendations
• Improve forecasting, scenario planning, and performance reviews
• Strengthen governance, data quality, and performance management routines

Target Audience

This course is designed for:

• Performance Analysis Managers and Performance Analysts
• Strategy, PMO, and Business Planning professionals
• KPI owners and department performance coordinators
• Operational excellence, transformation, and reporting leaders
• Managers responsible for dashboards, scorecards, and performance reviews

Course Outline

Day 1: Strategic Performance Measurement Foundations

• Linking strategy to measurable outcomes (OKRs, Balanced Scorecard overview)
• KPI architecture: input, output, outcome, and impact measures
• Defining SMART KPIs, thresholds, and target-setting logic
• KPI ownership, accountability, and measurement cadence
• Activity: KPI redesign clinic (audit and improve existing KPIs)

Day 2: Data, Dashboards & Insight Generation

• Performance data foundations: sources, definitions, and data governance basics
• Data quality management: common issues and practical controls
• Dashboard design principles: clarity, relevance, and decision usability
• Segmentation and root-cause exploration (Pareto, drill-down logic)
• Workshop: Build an insight-focused dashboard storyboard

Day 3: Advanced Performance Analytics & Diagnosis

• Driver-based performance models and value-tree analysis
• Variance analysis (plan vs. actual, trend, mix, volume, efficiency)
• Correlation vs. causation: interpreting relationships responsibly
• Identifying leading indicators and early warning signals
• Practical activity: Performance diagnosis simulation using a case dataset

Day 4: Forecasting, Scenario Planning & Performance Reviews

• Forecasting methods for managers (trend, rolling forecasts, simple regression concepts)
• Scenario planning: best/base/worst cases and trigger-based actions
• Designing effective performance review routines (WBR/MBR/QBR)
• Turning insights into action: initiatives, owners, timelines, and benefits tracking
• Case study: Performance recovery plan for an underperforming unit

Day 5: Executive Reporting, Storytelling & Influence

• Executive reporting: insight narrative structure and decision framing
• Data storytelling: visuals, context, and recommendation clarity
• Communicating risk, trade-offs, and confidence levels
• Stakeholder influence and challenging conversations with leaders
• Final group project: End-to-end performance insight pack + action p lan presentation