Glossary · Method
Plan test
A plan test reads a business plan, growth strategy, value creation plan or investment thesis, pulls out the AI plays in it and the growth targets that lean on them, and shows play by play whether the data they need is there and can be trusted.
Over the plan period we will grow net revenue retention to 115%, supported by AI-led renewal risk scoring.
AI playCustomer churn prediction
NeedsOne customer ID across CRM and billing
LeverabilityNeeds work
Why117 customers with no shared ID
In plain terms
Plans make promises that quietly depend on data. “Grow net revenue retention through AI-led renewal risk scoring.” “Cut days sales outstanding with an automated collections agent.” A plan test asks of each one: is the data this play needs actually there, and can it be trusted?
We read the document, whether it is a business plan, growth strategy, value creation plan, board paper or investment thesis, and pull out every AI play in it, along with the growth targets that lean on each play.
Each play is mapped to the data it needs: which systems, which fields, how much history and which records must agree. Then we check that data in the company’s own exports, and mark the play with a Leverability read: deploy now, needs work or blocked.
What a plan test doesn’t do matters as much. It doesn’t say whether a target will be hit; that depends on far more than data. It says whether the data the AI play needs is there and can be trusted, which is the part a plan usually assumes without checking.
Plan tests are part of the AI Investment Review. A Truth Score Read can test a single proposal in the same way.
- See it in a real memoThe sample Truth Score ReadReal engine output on generated test data, not a client
- How we measure itThe method, including the capPillars, weights, bands and what is never guessed
- What happens to your exportsSecurity and data handlingExports only, NDA and data processing agreement first
Questions
Plan test, answered.
The questions people ask about Plan test, answered in plain English.
Book the callWhich documents can be tested?
Business plans, growth strategies, value creation plans, 100-day plans, board papers, investment memos and theses, under NDA like everything else.
Does the plan test say whether we will hit our targets?
No. It says whether the data each AI play needs is there and can be trusted. Hitting a target depends on much more than data.
What if the plan has no AI in it?
Then we agree on the first call which AI plays are being considered, and test those.
Related terms
Keep reading.
- The Truth Score Leverability read The Leverability read says which AI ideas your data can use now, which need fixes first, and which it can’t support at all, with the reason in your own records. Read the definition
- Method Remediation roadmap A remediation roadmap is a prioritised list of data fixes, each with an owner, an effort estimate and a “done when” test, written to hand to your own team or any outside firm. Read the definition
- AI readiness AI readiness AI readiness is whether a company’s data can support the specific AI it is about to pay for: whether the data can be trusted, and whether it can run that use case. Read the definition
- The Truth Score Truth Score™ The Truth Score™ is DataTruth’s score out of 100 for how far a company’s data can be trusted, built from six weighted pillars and placed in one of four bands, A to D. Read the definition
Find out which of your AI plays can run. Before you pay for them.
Exports from two or more systems, matched between them, every red flag checked by hand. A signed memo with your Truth Score and a Leverability read, within 5 working days of complete exports.
Starts with a 30-minute call. Commits you to nothing.