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KPI & Indicator Library
A curated library of leading and lagging indicators with guidance on interpretation, limits, and using metrics to inform decisions and experiments.
KPI & Indicator Library
Find ready indicators and design patterns that help teams measure progress, learn faster, and turn numbers into decisions instead of busywork.
Why this library matters
Teams often know they should "measure what matters" but struggle to choose indicators that clarify action. This library collects common leading and lagging measures, explains how to calculate and interpret them, and highlights typical limits or risks so you can pick a small, meaningful set that supports learning and improvement rather than scorekeeping.
What you will understand and be able to do
After exploring this library you will be able to: (1) identify candidate indicators for quality, delivery, safety, customer experience, finance, and learning; (2) distinguish leading from lagging signals and choose the right mix; (3) write concise learning questions and map each indicator to decisions, owners, cadence, and experiments; and (4) avoid common traps like over-measurement, vanity metrics, and misaligned incentives.
Who benefits
This library is designed for frontline managers, improvement leads, team leads, small business owners, operations and service managers, quality and safety coordinators, nonprofit directors, educators, and consultants—anyone who must measure progress and convert measurement into better, repeatable decisions.
Practical examples
Use the library to translate general patterns into concrete measures for your context. Examples include: a roofing contractor choosing 'jobs completed on time', 'call-to-schedule conversion rate', and 'rework rate'; a restaurant tracking 'table turnover time', 'average check', and 'repeat customer rate'; a hospital unit monitoring 'time-to-triage', 'medication-error rate', and 'discharge delays'; a factory tracking 'first-pass yield', 'mean time between failures', and 'on-time shipments'. Each example explains calculation, cadence, owner, probable confounders, and a simple experiment you can run in a huddle.
How to use this with your teams
Recommended steps: browse categories to discover candidate metrics; pick 3–6 primary indicators tied to your most important learning questions; define owners, measurement cadence, and thresholds; surface these measures in a short "Measure What Matters" KPI huddle; design one quick experiment and record results; iterate based on evidence. The best measurements are small, owned, and connected to explicit decisions.
What this library is not
It is not a turnkey analytics platform, a one-size-fits-all KPI program, or a guarantee of performance. The value comes from tailoring indicators to your context, ensuring data quality, assigning ownership, and using measures to drive experiments and organizational learning.
Next steps and platform fit
If you copy this collection into your Hunger Engine, you can tailor indicator definitions to local context, assign owners, and seed simple trackers or worksheets to capture baseline values. Pair the library with the "Measure What Matters" KPI huddle to practice turning indicators into short experiments and recorded decisions that become organizational memory.
Make useful resources part of something bigger.
The Hunger Engine is moving toward living domains, toolkits, and collections that people and organizations can explore, acquire, tailor, extend, and improve. A useful resource can become part of a personal collection, team toolbox, site-specific domain, or shared enterprise capability.
Start with what you're hungry to improve. As your needs grow, collections can bring together knowledge, audits, forms, dashboards, data, AI, integrations, and other capabilities without requiring you to start from scratch.