LISA & KISSME: A Signal-Based Architecture for Interpreting KPI Clusters

In complex organizations, KPIs rarely operate in isolation. Performance signals often form dynamic clusters, where lead indicators precede or amplify movement across related metrics. This paper introduces the LISA model (Lead Indicator Signal Architecture, a structured methodology for organizing KPIs into harmonized signal groups, each anchored by a lead term and its trailing companions. We further introduce the KISSME approach (KPIs and Inter-Signal System Metrics for Evaluation) to simplify the taxonomy and support speculative analysis across functional domains. The LISA Table offers a starting framework with fifteen common KPI clusters used in strategic forecasting, operational diagnostics, and signal alignment. The goal is to provide a compact, repeatable toolkit for data-aware teams seeking better early signals, fewer surprises, and cleaner cross-functional interpretation.