C-KPIP Exam Dumps
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| Certification Provider: | The KPI Institute |
|---|---|
| Exam Code / Number: | C-KPIP |
| Exam Name: | Certified KPI Professional Exam |
| Exam Questions: | 77 |
| Last Updated: | Jun 21, 2026 |
| Corresponding Certification: | KPI Measurement |
(287 Up Votes)The KPI Institute C-KPIP Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| KPI Typology | - Efficiency vs effectiveness KPIs - Leading vs lagging KPIs - Qualitative vs quantitative KPIs |
| Understanding KPIs | - SMART objectives decomposed - KPI related terminology - KPI lifecycle |
| KPI Selection at Operational Level | - Operational dashboard - Department scorecard |
| Working with Targets | - KPI documentation processes - Targets in practice - Negative behaviors when setting - Challenges in working with targets |
| KPI Selection | - KPI selection techniques - KPI selection for organizational scorecard - KPI selection sources |
| KPI Project Coordination | - KPI workshop briefing pack - The business case for KPI implementation - Primary and secondary data sources - KPI project plan |
| Data Visualization | - Usability in terms of visual design - Best practices in scorecard design - Guidelines to design efficient templates - Scorecard and dashboard examples - Best practices in dashboard design |
| KPI Documentation | - KPI documentation process - Weights and Indexes - KPI documentation form design - KPI documentation form functions - Organizational KPI libraries development |
| The World of KPIs | - Governance - KPIs concept map - Challenges in performance measurement - Organizational levels - The value added by KPIs |
| KPIs in Context | - KPIs cascaded to functional area - KPI selection for industry |
| KPI Taxonomy | - Interdisciplinary systemic worldview - KPI use case scenarios - KPI DNA map |
| KPI Measurement | - KPI report - Data gathering communication - Change log |
| Data Gathering | - Community of Practice - KPI activation techniques - KPI reporting data sources - KPI activation tools - Communication with data custodians - Guidelines to improving - Data quality dimensions |