Day 1: Designing Performance Governance and Authority

Performance Governance Principles

• Distinguish operational measurement from enterprise governance
• Identify decisions requiring standardized rules
• Expose risks from conflicting roles
• Diagnose governance failure within performance system

Ownership and Accountability Roles

• Separate result ownership from data production
• Assign approval, validation, and interpretation responsibilities
• Match authority with intervention capability
• Build role matrix for shared indicators

Decision Rights and Escalation

• Define authority over targets and indicators
• Specify cases requiring higher escalation
• Prevent bypassing governance under performance pressure
• Simulate a disputed KPI amendment decision

Day 2: Engineering the KPI Dictionary

Indicator Definition Standards

• Write indicator purpose, boundaries, and context
• Fix formulas and measurement units
• Define exclusions and special cases
• Review definitions that expose inconsistent interpretation

Sources Frequency and Responsibilities

• Link elements to data fields/sources
• Choose frequency matching decision speed
• Assign collection validation and close responsibilities
• Prepare complete data card for indicator

Managing KPI Changes

• Document reason for any formula amendment
• Protect historical comparability when definitions change
• Set effective date per new version
• Create version register for KPI dictionary

Day 3: Data Quality and Reporting Confidence

Performance Data Quality Controls

• Test completeness accuracy consistency and timeliness
• Set acceptance limits before publishing results
• Handle missing data without concealing problem
• Apply quality checklist to KPI sample

Validation and Reconciliation

• Compare primary sources with final reports
• Use sampling to detect transformation errors
• Reconcile differences across multiple systems
• Run reconciliation review for sensitive indicator

Transparency of Constraints and Estimates

• Disclose estimated values and confidence levels
• Distinguish legitimate corrections from result manipulation
• Explain data-limit effects on management decisions
• Draft quality note for incomplete indicator

Day 4: Review Cycle and Corrective Pathway

Performance Reviews by Management Level

• Define issues to each management level
• Avoid replicating same meeting across layers
• Escalate deviations by impact, not color
• Design an interconnected review calendar

Management by Exception

• Set thresholds requiring analysis and intervention
• Separate natural variation from sustained deviation
• Prioritize issues by consequence for results
• Build exception list for executive review

Accountability and Closure

• Assign owners and deadlines per decision
• Track commitments until closure is evidenced
• Record non-delivery causes without excuse framing
• Role-play accountability around recurring deviation

Day 5: Performance System Governance Laboratory

Designing the Governance Model

• Connect committee roles within governance architecture
• Define data and report approval points
• Establish indicator and target change pathways
• Build governance model for enterprise unit

Stress-Testing the System

• Resolve conflicting numbers for same result
• Respond to highly sensitive late indicator
• Make decisions with weak source reliability
• Simulate performance close and review week

Implementation and Transition Plan

• Prioritize governance requirements before automation
• Train KPI owners and analysts
• Use pilot period before mandatory implementation
• Prepare transition plan across measurement cycles

• Governance cases exposing conflicts in ownership and definitions
• KPI dictionary and data-quality control laboratory
• Review and escalation simulations under realistic pressure
• Governance-model project tested before implementation