lean-analytics

Lean Analytics is a framework skill for choosing and auditing startup metrics, distilled from Alistair Croll and Benjamin Yoskovitz's Lean Analytics. It solves the problem of teams drowning in dashboards full of numbers that flatter but never change a decision. Its core principle is to focus on the One Metric That Matters (OMTM) right now, matched to your business model and stage, and to treat everything else as noise that feels like progress. A metric earns attention only if it changes what you do next.

The skill distinguishes good metrics (comparative, understandable, expressed as a ratio or rate, and behavior-changing) from vanity metrics (totals, cumulative charts, blended averages that only go up). It teaches lens pairs (qualitative vs quantitative, exploratory vs reporting, leading vs lagging, correlated vs causal), the discipline of cohorts and segments to keep time and comparisons honest, and the OMTM paired with a counter-metric and a pre-committed 'line in the sand.' A reproducible 0-10 scoring rubric rates metric choices, dashboards, and instrumentation plans and reports the changes needed to reach 10/10. Reference files cover metrics by business model, the five startup stages, benchmarks, and detailed case studies (a SaaS dashboard cut from 34 widgets to one number, a marketplace measuring the wrong thing) showing the method applied end to end.

It targets founders, product managers, and growth teams choosing metrics for a startup or feature, auditing a dashboard for vanity metrics, setting targets and baselines, or instrumenting a product by model and stage. It is a benign analytical and conceptual guide with no executable code, external calls, or risky behavior.