Cambridge
Academy
In London

Introduction

Well-designed KPIs turn strategy into measurable outcomes, guide daily decisions, and drive continuous improvement. Senior KPI leaders must ensure KPIs are defined consistently, linked to value drivers, set with credible targets, and used in effective performance routines. This advanced program equips participants with practical methods to design, validate, and deploy KPI systems that leaders trust and teams act on.

 

Course Objectives

• Design KPI frameworks aligned to strategy, value drivers, and operating realities

• Create clear KPI definitions, calculation logic, and metadata standards

• Set credible targets, thresholds, and baselines using practical methods

• Identify leading indicators and build driver-based performance models

• Prevent KPI failure through governance, data integrity checks, and quality controls

• Build KPI dashboards and performance cadences that drive action and accountability

 

Target Audience

• Senior Managers responsible for KPI design, governance, and performance measurement

• Performance management, strategy, and reporting leaders

• PMO, operational excellence, and transformation professionals

• Finance, operations, HR, and service leaders accountable for KPI ownership

• BI, analytics, and data governance professionals supporting KPI delivery

 

Course Outlines

Day 1: KPI Strategy Alignment & KPI Architecture

• Connecting strategy to measurement: outcomes, drivers, and success criteria

• KPI hierarchy: enterprise, functional, operational; input/output/outcome/impact measures

• Selecting KPIs that matter: relevance, controllability, and decision usefulness

• KPI portfolio design: balancing leading/lagging, efficiency/effectiveness, risk/quality

• Activity: KPI portfolio diagnostic (identify gaps, overlaps, and “vanity metrics”)

 

Day 2: KPI Definitions, Standards & Metadata (KPI Dictionary)

• KPI definition anatomy: name, intent, formula, units, grain, filters, and exclusions

• Data sources and lineage: system of record, transformation rules, and traceability

• Handling edge cases: exceptions, timing rules, and partial-period logic

• Change control: versioning, approvals, and retirement rules

• Workshop: Build a KPI dictionary page + calculation specification for 5 priority KPIs

 

Day 3: Target Setting, Thresholds & Baselines

• Target types: absolute, relative, benchmarked, and trajectory-based targets

• Setting baselines: historical analysis, seasonality considerations, and normalization

• Thresholds and guardrails: RAG logic, tolerance bands, and escalation triggers

• Avoiding dysfunctional targets: gaming, unintended consequences, and equity impacts

• Practical activity: Target-setting simulation (define baselines, targets, and RAG thresholds)

 

Day 4: Leading Indicators & Value Driver Modeling

• Leading vs. lagging indicators: selection criteria and validation logic

• Value driver trees: linking activities to outcomes and financial/non-financial value

• Root-cause and driver analysis: Pareto, variance analysis, and segmentation

• Building KPI bundles: “health sets” for functions, products, or services

• Case study: Design a driver-based KPI model and recommended interventions

 

Day 5: KPI Deployment, Dashboards & Performance Cadence

• KPI governance: ownership, accountability, review forums, and decision rights

• Dashboard design: clarity, hierarchy, exceptions-first reporting, and commentary standards

• Performance cadence: WBR/MBR/QBR routines, action tracking, and follow-through

• KPI quality controls: validation checks, reconciliations, and audit-ready evidence