R2 — Build only on data you already own — transaction history, CRM, scheduling, no-show patterns; that is the only category with native defensibility

Rule: When recommending a build of analytics or a data-driven tool, build it on data the business already owns — transaction history, customer repeat-purchase patterns, scheduling and no-show data, service-call history. Do not build on rented / public data you could instead consume.

Why: First-party operational data is the only data category with native defensibility (Synthesis: data is a defensible asset only when proprietary + hard to replicate + tightly coupled to a feedback loop + continuously refreshed — otherwise it is an operational byproduct any competitor can buy or collect, Andreessen Horowitz, "The Empty Promise of Data Moats" (Casado & Lauten, 2019) — most "data network effects" are really scale effects that diminish). A boutique law firm that learns which matters turn into long-term clients, or an HVAC contractor who knows which service calls predict a future system replacement, has genuine differential advantage. The data is a byproduct of running the business; the build effort turns it into a decision.

How to apply:

• The first question on any "data project" scope: what data does the business already generate that nobody else has?
• If the answer is "none yet," start with collecting and storing it; don't skip to analysis.
• Pair with R1 — Rent (or use free) for data ABOUT THE OUTSIDE WORLD; you will never out-collect the Census Bureau for the external-data side.