# Your Tech Stack Isn't Broken. It's Never Been Asked to Agree With Itself.

Every tool got added to solve a real problem. Nobody ever went back to check whether they still agree on the same facts.

## Most teams audit the wrong thing

- The wrong audit: counting how many tools you have, chasing the newest point solution, benchmarking spend against competitors.
- The right audit: tracing one deal's data start to close, counting handoffs not tool logos, naming who owns the source of truth.

## The five tests: run this against your stack as it actually works

- If a board member asked for the pipeline number right now, could two people in this company give the same answer without opening Slack first?
- How many times does one lead's data get manually re-typed, copy-pasted, or CSV-uploaded between the first touch and the first sales call?
- Name a tool in your stack that, if it vanished tomorrow, nobody would rebuild the workaround it's currently costing someone to maintain.
- What percentage of reps update the CRM the same day the call happens, not the same week?
- When marketing and sales disagree about what drove a closed deal, which system's data wins, and has anyone written that down? That's not a data problem. That's a governance problem wearing a data costume.

## Frequently asked questions

### How is this different from a full RevOps maturity assessment?

It's the 20-minute internal version you run before you call anyone. A real assessment audits every workflow and integration; this audit tells you whether you have a problem worth paying someone to fix.

### Who should actually fill this out?

Whoever owns the CRM day to day, plus one working rep. The leader's mental model of the stack and the rep's daily experience of it rarely match.

### What if we fail most of these tests?

Don't start ripping out tools. Map the handoffs between them first — most drag comes from the process gaps between systems, not from any one tool being wrong.

### Does adding more AI tools fix this?

No. A stack with a data-integrity problem just produces AI outputs built on bad inputs, faster.