What to do first

These are the changes that move the grade. Each check is named later in the report.

1. Assign an owner to $2.3M of ARR. 48 active accounts have no rep, and the top rep holds 28.7% of ARR. The missing owners and the concentration in one rep come from the same accounts, so one round of assignments addresses both. The parent field is the least-covered tag, so fill it during the same pass. This moves Multi-Dimensional Insights toward B and clears the items holding the decision-ready view at “not yet.”
2. Add a definitions tab. Write one line each for the terms the file does not define yet: MRR, GRR, new and reactivation. Keep the existing lines for ARR, NRR, churn, expansion and cohort. The written definitions include 5 of the 9 standard terms. Completing the set lets a reader reproduce the KPI table from written terms, and a diligence review will expect it.
3. Normalize 2 tag fields. Segment and status each contain case or whitespace variants of the same value. One normalization pass removes them and moves Multi-Dimensional Insights up one band.
4. Send the inputs a diligence review expects. Add unit or price data, or payments data, to the next upload. If you can, export tags as of each month so a buyer can see whether a customer’s segment changed over the year. You do not need to send anything extra for the test of whether a new product line copies a price the account already had. That test did not run because no month moved the whole book.
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), 17,447 rows. Hazards handled: none. Checks run: 39 of 41. The remaining 2 could not be checked; they 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+)

Audit-Grade Accuracy, Cohort-Centric Design and Anomalies have nothing open. All of the lost points sit in ownership, tag coverage and tag spelling, and in written definitions.

Each check

Each item below is one part of the rubric. The heading says what was tested. 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 measures how much of the latest book has no product and how much has no owner.

In this file, every account has a product, so 0% of ARR is unassigned by product. The owner side does not hold: 48 accounts, or 20% of ARR, have no owner. Check score 30.

A buyer would ask: who is accountable for renewing and expanding these accounts?

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

In this file, the definitions include 5 of the 9 standard terms. MRR, GRR, new and reactivation are not defined. Check score 56.

A buyer would ask: under what definition is each headline figure calculated?

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); Bookings with no product or no owner, product side (CP-05); 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 measures the top owner’s share of the latest book and the share with no owner.

In this file, 3 reps carry the book. The top rep holds $3.2M, a 28.7% share. The unassigned accounts noted above sit outside any rep. Check score 30.

A buyer would ask: how much of the book depends on one relationship, and how much has none?

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 measures how much of the latest book sits on accounts with a real value.

In this file, the 6 tags cover 80% of the book on average. Parent is the least-covered field, and the rep field has the owner gap described above. Check score 55.

A buyer would ask: can the book be cut by parent customer and by owner, not only by product and region?

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

In this file, 2 fields, segment and status, contain more than one spelling of the same value. Check score 80.

A buyer would ask: does a segment cut count every account in that segment, or only the ones spelled one way?

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 month moved the whole book. This test only runs inside such a month, and this file has none.
• Tags stay stable over the year (SG-07): tags are not tracked month by month. The file stores one tag per account rather than one per month, so changes in segment over time cannot be seen yet.

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. Rules version caeb8e512330. Readiness views:

• Decision-ready: not yet. The owner gaps are current.
• Diligence-ready: no. The same owner gaps apply, and unit or price data, or payments data, is missing.
• AI-ready: yes.

Next step

The Strategic Revenue Intelligence Assessment walks through these findings with a FinQore analyst. It also 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.