Insights

Notes from the field.

On finance analytics, PE value creation, and what we see inside portfolio companies.

Your data is not ready for AI, and that is a solvable problem

The four-level readiness stack, the two dimensions that define it, and the failure mode we see most: a Level 4 capability bought before the data reaches Level 2.

What a quality of earnings report is not built to tell you

A QoE answers the diligence question well. The value-creation question — what is driving the variation, and what would it take to move it — is a different scope.

Revenue leakage is a data architecture problem

Pricing drift, discount creep, and unbilled time are rarely hidden. They are usually just unjoined — sitting in a system that never connected to the customer dimension.

A source of truth is a commitment, not a deliverable

The model can be built in weeks. Keeping one definition per metric, owned by a named person, is a standing decision the finance team makes every month after that.

Start with a diagnostic, not a commitment.

Phase 1 is scoped to answer one question: is the opportunity real, and how big is it? If the numbers do not support a Phase 2, we will say so.