- Creating Effective Measurement Systems for Better InsightsDesign useful measurement systems by measuring outcomes not activities, using leading and lagging indicators together, and building in resistance...
- How Goodhart's Law Breaks MetricsWhen a measure becomes a target, it ceases to be a good measure. People optimize for metrics, not goals, creating distortion and gaming.
- Interpreting Data Without Fooling YourselfInterpret data correctly by avoiding confirmation bias, p-hacking, confusing correlation with causation, and survivorship bias in your analysis.
- KPIs Explained Without BuzzwordsKPIs (Key Performance Indicators) are the few metrics that actually matter for your goals. Not all metrics are KPIs, only those that drive real...
- Leading vs Lagging Indicators ExplainedLagging indicators report outcomes after the fact while leading indicators point to what comes next. Learn to choose both and avoid the common traps.
- Quantitative vs Qualitative MetricsQuantitative metrics measure numbers like revenue and time. Qualitative metrics assess quality like feedback and satisfaction.
- Understanding Measurement Bias: How It Skews ResultsMeasurement bias: Systematic error in data collection distorting results consistently (not random noise, predictable direction).
- Vanity Metrics vs Meaningful MetricsVanity metrics look impressive but don't drive decisions: total users, page views. Meaningful metrics change behavior: active users, retention,...
- What Should Be Measured and WhyMeasure what drives outcomes, not what's easy to measure. Focus on outcomes over activities, and use leading indicators to predict future results.
- Why Measurement Changes BehaviorWhat gets measured gets optimized. Measurement creates visibility, accountability, and focuschanging behavior whether intended or not.
- Why Metrics Often MisleadMetrics mislead through gaming the numbers, proxy failure not representing what matters, context loss, and aggregation hiding important details.