What to do first

These changes move the grade, in order of effect. The check each one answers is cited in “Each check” below.

1. Assign an owner to $62.8M of ARR. 936 active accounts have no rep. The top rep holds 25.7% of ARR, and the parent field is the least-covered tag. Filling owners addresses both high-severity findings. It is the single change that most affects the decision-ready and diligence-ready lenses. Moves Multi-Dimensional Insights toward B.
2. Add a definitions tab. Write one line each for ARR, MRR, NRR, GRR, churn, new, expansion, reactivation and cohort. Written definitions let a buyer reproduce the KPI table without asking how each figure was built. This raises the definitions score inside Unified, Finance-Approved Foundation.
3. Normalize 2 tag fields. The segment and status fields carry case or whitespace variants of the same value. One normalization pass removes them. Moves Multi-Dimensional Insights up one band.
4. Send the inputs a buyer will ask for. Add units or prices, or payments, so the diligence lens can be assessed. Export tags as of each month so segment stability can be graded. This raises the share of the file that is graded rather than assumed.
5. Re-grade after each month-end close. A monthly re-grade catches broken ties, duplicates and status drift before they reach the board pack. It keeps Audit-Grade Accuracy where it is.

Where the grade comes from

Inputs: 2 file(s), 8 sheet(s), 320,662 rows. Hazards handled: none. Checks run: 39 of 41. The remaining 2 could not be checked and are listed below.

• Unified, Finance-Approved Foundation: 87.3 (B+)
• Audit-Grade Accuracy: 100 (A+)
• Cohort-Centric Design: 100 (A+)
• Multi-Dimensional Insights: 77.5 (B-)
• Anomalies: 100 (A+)

Three pillars score in full. The two below A both trace back to ownership and tag coverage.

Each check

Each heading below is one check in the rubric, written as a plain statement. The short code is the citation.

Unified, Finance-Approved Foundation

Bookings with no product or no owner

Unified, Finance-Approved Foundation. Cited as CP-05, owner.

This check measures how much of the latest book has no product, and how much has no owner.

In this file, product is assigned across the whole book (product unassigned 0%). Ownership is the gap: 936 accounts have no owner, which is 25% of the book. A buyer would ask who manages those relationships today. Check score 30.

Next step. Assign a product and an owner to the unassigned book before the next export.

The words in the definitions were written down

Unified, Finance-Approved Foundation. Cited as CP-07.

This check looks for the standard terms in the definitions text. It does not test whether those words match the numbers.

In this file, 5 of the 9 terms are written down: ARR, NRR, churn, expansion and cohort. MRR, GRR, new and reactivation are missing. A buyer would ask how those four figures are defined before relying on them. Check score 56.

Next step. Write a short definition for each headline term the summary uses, in the same words the rubric expects.

Came through clean: Enough history to follow a customer (CP-01); Months where the whole book went quiet (CP-02); A customer goes quiet without a churn mark (CP-03); Revenue with no customer behind it (CP-04); the product side of Bookings with no product or no owner (CP-05, product); The product file covers the same months as billing (CP-06); Billed customers appear on the customer list (CP-08).

Audit-Grade Accuracy

Came through clean: The bridge foots on its own (CR-01); Customer detail matches the bridge ending (CR-02); Movements rebuild from the customer rows (CR-03); Product lines tie to billing (CR-04); The amount matches the status word (CR-05); Statuses tell a legal story over time (CR-06); Headline KPIs can be reproduced (CR-07); The bridge and the KPI table agree (CR-08); Product and segment totals add up (CR-09); Duplicate dollars that break the tie (CR-10).

Cohort-Centric Design

Came through clean: Customers have a start date (CO-01); The start date matches the first revenue month (CO-02); Too many customers share one start month (CO-03); A returning customer kept the same key (CO-04); Contract end dates exist and fall after the start (CO-05); Retention looks earned, not just unexpired (CO-06); A trailing year has a year of history behind it (CO-07).

Multi-Dimensional Insights

One owner does not hold the book

Multi-Dimensional Insights. Cited as SG-06.

This check measures the top owner’s share of the latest book and the share with no owner.

In this file, the book is split across 3 reps. The top rep holds $64.4M, a top share of 25.7%. Another 25% has no owner at all. A buyer would ask how the unowned book is covered, and what happens to the top rep’s accounts if that rep leaves. Check score 30.

Next step. Reassign concentrated accounts and fill the unassigned ones so the book is not one rep’s.

Those tags actually cover the book

Multi-Dimensional Insights. Cited as SG-02.

For each tag, this check measures how much of the latest book sits on accounts with a real value.

In this file, the 6 tags cover a mean of 79.2% of the book. Product, package, region and segment are fully covered. Rep coverage is partial, and the parent field is blank. A buyer would ask how concentration looks once child accounts roll up to their parent. Check score 55.

Next step. Fill the blank tags on the accounts that carry the book, starting with product and owner.

The same idea is spelled one way

Multi-Dimensional Insights. Cited as SG-04.

This check groups tag values that match once case and spacing are removed, and scores how many spellings each idea has.

In this file, 2 tags need normalizing: segment and status. A buyer cutting the book by segment would see the same category split across spellings. Check score 80.

Next step. Pick one spelling for each category and apply it across the file.

Came through clean: The cuts a buyer expects are present (SG-01); A tag is a category, not free text (SG-03); Parent accounts are used (SG-05).

Anomalies

Came through clean: One customer spikes for a month and reverts (AN-01); A customer drops to zero and comes back unmarked (AN-02); One month moves the whole book (AN-03); Amounts do not match the file’s own format (AN-05); Duplicate rows (AN-06); The book sits in a few customers (AN-07); Prices did not move where an escalator was promised (AN-08); A sentence in the talking points does not match the file (AN-09).

What we could not check

• A new product line copies a price the account already had (AN-04): no single month moved the whole book, so there was no month in which to look for copied prices.
• Tags stay stable over the year (SG-07): the file stores one tag per account rather than one per month, so changes over time cannot be seen.

How this was graded

Weights: Unified, Finance-Approved Foundation 25%, Audit-Grade Accuracy 30%, Cohort-Centric Design 15%, Multi-Dimensional Insights 15%, Anomalies 15%. Bands: A ≥ 90, B ≥ 75, C ≥ 60, D ≥ 45. Bridge convention detected: monthly_sum, meaning the bridge was read as the sum of monthly customer rows. Rules version caeb8e512330. Lenses: decision-ready not yet, diligence-ready no, AI-ready yes.

Next step

The Strategic Revenue Intelligence Assessment walks through these findings with a FinQore analyst and shows what a decision-ready and diligence-ready cube looks like for your business. Your files are retained in FinQore infrastructure for the stated retention period and deleted on request.