to understand metrics (or other model of reality), it seems to help to understand and respect the metric's limitations > The map of reality is not reality. Even the best maps are imperfect. That’s because they are reductions of what they represent. If a map were to represent the territory with perfect fidelity, it would no longer be a reduction and thus would no longer be useful to us. A map can also be a snapshot of a point in time, representing something that no longer exists. This is important to keep in mind as we think through problems and make better decisions. > > Even the best and most useful maps suffer from limitations, and Korzybski gives us a few to explore: > 1. The map could be _incorrect_ without us realizing it > 2. The map is, by necessity, a _reduction_ of the actual thing, a process in which you lose certain important information; and > 3. A map needs _interpretation_, a process that can cause major errors. > ... > You do not understand a model, map, or reduction unless you understand and respect its limitations. We must always be vigilant by stepping back to understand the context in which a map is useful, and where the cliffs might lie. > > — [The Map Is Not the Territory - Farnam Street](https://fs.blog/map-and-territory/) ## Some thoughts: - Numbers and metrics are abstractions of reality. - The metric could be incorrect due to data quality issues - The metric could be abstracted inaccurately, such as not using [[non-vanity metrics seem to often be percentages (or percentiles)]] when cohorts are fitting - The metric could be simply interpreted differently than the creator of the metric intended to - could be partially mitigated with: [[alignment on key concepts seems to tackle value risk and usability risk and might increase speed of change]] ## Further reading: - [The Map Is Not the Territory - Farnam Street](https://fs.blog/map-and-territory/) - [The Black Swan by Nassim Taleb](https://www.goodreads.com/book/show/242472.The_Black_Swan) seems tangentially related