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The PRISM Composite Score Model is a practical framework for turning data into decisions. It unifies rigorous data management with Results-Based Management (RBM) to identify, weigh, and prioritize indicators for planning, monitoring, and adaptive policy. Using clear quality criteria-sensitivity, specificity, reliability, validity, simplicity, utility, and affordability-it converts expert judgment into transparent composite scores, benchmarks them against standards, and uses group consensus to validate results. PRISM strengthens causal links from inputs and activities to outputs, outcomes, and objectives, cutting duplication and focusing resources where they matter most. Sound data practices-accurate entry, consistent definitions, documented baselines and targets, audit trails, and open reporting-keep scoring consistent and adjustments timely across sectors. The manual is organized for action: Chapter 1 introduces indicators; Chapters 2-5 show how to build and apply the model; Chapter 6 supports training; Chapter 7 examines ethics; Chapter 8 looks ahead to data-driven governance; Chapters 9-10 integrate data and RBM. Case studies and exercises turn concepts into skills.
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The PRISM Composite Score Model is a practical framework for turning data into decisions. It unifies rigorous data management with Results-Based Management (RBM) to identify, weigh, and prioritize indicators for planning, monitoring, and adaptive policy. Using clear quality criteria-sensitivity, specificity, reliability, validity, simplicity, utility, and affordability-it converts expert judgment into transparent composite scores, benchmarks them against standards, and uses group consensus to validate results. PRISM strengthens causal links from inputs and activities to outputs, outcomes, and objectives, cutting duplication and focusing resources where they matter most. Sound data practices-accurate entry, consistent definitions, documented baselines and targets, audit trails, and open reporting-keep scoring consistent and adjustments timely across sectors. The manual is organized for action: Chapter 1 introduces indicators; Chapters 2-5 show how to build and apply the model; Chapter 6 supports training; Chapter 7 examines ethics; Chapter 8 looks ahead to data-driven governance; Chapters 9-10 integrate data and RBM. Case studies and exercises turn concepts into skills.