Decision tree
Build ARR you can prove, from the ground up.
A decision tree, not a template. Start with your business model, follow the branches through source data, a data-quality assessment, methodology trade-offs, and movement buckets, then monitor and diagnose. Pick your model and the tree adapts to the questions that actually apply to you.
- Stage 01
What is your business model?
Everything downstream branches from here, how ARR even exists is different for each.
- Stage 02
What is your source data?
Name the system of record for every field that touches revenue, before you trust any of it.
- Stage 03
Run a full Data Quality Assessment
You can't build ARR on data you haven't tested. The DQA is the high-level lens for everything that follows.
- Stage 04
Choose your ARR construction methodology
Every decision here is a trade-off. Make each one once, document it, and enforce it. Your model dims the ones that don't apply.
- Stage 05
Define your movement buckets
Define the unit, period, currency and reporting perimeter, then reconcile opening ARR plus movements to closing ARR. Classify each movement event once; a customer can have several events.
- Stage 06
Build the bridge, then monitor it
ARR is a rate, not a quarterly artifact. Reconcile continuously and watch it like uptime.
- Stage 07
Reconcile the movements, then investigate causes
Start with the reader’s decision, the evidence and the next useful question. Apply MECE to the scoped movement breakdown, then use these lenses to investigate possible causes.
- Stage 08
Turn diagnosis into strategy, and execute
Use the supported diagnosis to choose one or more actions. Name the expected effect, costs and risks, then measure the result.
You don't calculate ARR once. You build the system that produces it.
This is the build order. The Recurring & Reoccurring Quality of Revenue Metrics are what you produce, and the Readiness Ladder helps you review controls and identify gaps.