September 2026
February 2026
- Feb 27, 2026ConceptsMeasuring Success: Metrics vs KPIs in OrganizationsGoodhart never said metrics are bad. He said a measure used as a target ceases to be a good measure, and that distinction between a metric that informs and a target that carries consequences is the conceptual hinge. Google Flu Trends shows the cost of missing it: search volume was a defensible proxy for flu prevalence until media-driven searching broke the link, and the system kept reporting confidently. Covers vanity metrics, proxies, validity and reliability.
- Feb 9, 2026ConceptsInterpreting Data Without Fooling YourselfCorrelation confusion, p-hacking, base rate neglect, Simpson's paradox, survivorship bias, regression to the mean, cherry-picking and ignored effect sizes, each with a worked example and a countermeasure. Simmons, Nelson and Simonsohn's 2011 False-Positive Psychology paper showed that undisclosed analytical flexibility can push false positive rates as high as 61 percent while the nominal threshold stays at 5 percent.
- Feb 9, 2026ConceptsCreating Effective Measurement Systems for Better InsightsIf a measure becomes a target, people set the target where they can comfortably reach it. Google's answer when it adopted OKRs was to build anti-sandbagging pressure into the system itself, expecting key results to land at 60 to 70 percent. The NHS case shows the other half of the design: once waiting times alone were gamed, adding safety, outcome and access metrics meant improving one dimension by manipulation became visible in another.
- Feb 6, 2026ConceptsVanity Metrics vs Meaningful MetricsEric Ries defined vanity metrics as numbers that feel good without helping you understand your situation. A startup reporting 100,000 downloads avoids saying 90% never opened the app and 200 people pay. The actionability test is one question: if this metric moves, what do you do differently? Page views up 30% gives no answer; conversion rate down 15% sends you into the funnel. Why they survive, and why context decides.
- Feb 6, 2026ConceptsQuantitative vs Qualitative MetricsThe sharpest illustration is Kalev, Dobbin, and Kelly's study of 708 companies over 31 years: the quantitative data showed diversity training and grievance procedures moved managerial diversity almost not at all while mentoring and task forces did, and the organizational case studies explained why, because programs that generated paperwork without changing decision-making were gamed. Both methods were needed to see it.
- Feb 5, 2026ConceptsWhy Metrics Often MisleadGoodhart noticed every monetary aggregate the Bank of England targeted lost its predictive validity once it became a target, and the pattern repeats. Wells Fargo staff opened an estimated 3.5 million unauthorized accounts chasing cross-selling numbers, and in 2014 the UK Statistics Authority stripped police-recorded crime of its National Statistics designation after an inspectorate report found around 19 percent of crimes under-recorded.
- Feb 5, 2026ConceptsWhat Should Be Measured and WhyA metric deserves tracking only if it aligns with a real goal, is actionable, can be collected reliably, either predicts or measures an outcome, and is not redundant. The article separates outcomes from outputs and drivers, caps each goal at three to seven metrics, and reframes selection through Hubbard's point that a measurement is worth making when the uncertainty it removes is worth more than its cost.
December 2025
November 2025
September 2025
- Sep 13, 2025IdeasMeasurement Tools for Performance TrackingWhat gets measured gets managed, as Ridgway noted in 1956, even when measuring it is pointless or harms the organization. Most tracking tools count things without saying whether the counts predict anything, so teams optimize vanity metrics and game dashboards while the business deteriorates. A team can be 80 percent through its task list without having validated the core algorithm. Separating validation, execution and impact milestones fixes what a percentage bar hides.
- Sep 8, 2025IdeasData-Driven Business IdeasClimate Corporation started in 2009 by combining free government weather, soil and crop yield data into hyper-local risk models that traditional insurers mispriced. Monsanto bought it in 2013 for $930 million. The data was free; the value was in the combination and the decision it informed. Data businesses compound, because each point makes the set more valuable, and defend themselves, because a competitor can copy an interface in weeks but not five years of cleaned data.
August 2025
- Aug 17, 2025IdeasKey Issues in Measurement and MetricsA hospital published ER wait times and they fell dramatically, but patients were triaged faster then waited longer in treatment rooms: the system optimized time to first clinical contact while total treatment time got worse. Charles Goodhart observed in 1975 that any statistical regularity collapses once pressure is placed on it for control. The streetlight effect explains why: lines of code are easy to count, so they stand in for productivity.
- Aug 14, 2025IdeasEngaging Data Analysis Project IdeasA student tracked sleep, caffeine, exercise, screen time and energy for 90 days to explain why Wednesdays exhausted her. The correlation was not Tuesday night sleep but late-night screen time two nights earlier, a lag introspection cannot detect. Personal data beats a public dataset on motivation and on context, since you know the March spike was a security deposit. Sources include transactions, time logs, fitness apps and calendars.
- Aug 7, 2025IdeasData Monetization IdeasRaw data is almost never the product. Dunnhumby turned Tesco Clubcard transaction records into market intelligence for brands, reaching over $400 million in annual revenue by 2010 before Tesco bought the firm outright in 2011. This guide maps the full spectrum from operational savings to raw data licensing, with the five external product archetypes, GDPR penalties reaching 4 percent of global annual revenue, and why pricing optimization often beats selling anything.
July 2025
October 2023
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