SI Data Ops

Buyer collection · updated 2026-10-12

For a finance manager: draft the month-end variance commentary with every figure traced, and know where AI tools send your data

Trace each variance against budget or last month to the ledger lines, ask for the reason from a named person, and write down what each AI tool does with the data you put in.

Trace every number

A month-end variance draft against budget or last month is only useful if each number and percentage can be recomputed from the export. Reconcile the actual figure to its ledger lines, then subtract the budget or prior-period figure to reproduce the variance; block delivery on any mismatch. A reason for a variance should come from a note someone wrote, or be asked as a question.

  • Every figure recomputed from the export.
  • Every "because" quotes a note or becomes a question.
  • No forecast or advice wording.

Ask where the data goes

For each AI tool your team uses, write down what goes in, whether inputs train models by default, how long they are kept and how to switch training off. Terms differ between consumer, business and API plans and change over time, so date every cell and mark unknowns as unknown.

Which paid job fits

The variance job drafts one page against budget or last month, tied to ledger lines and rehearsed on three past months, and a monthly version repeats it. For commentary on a report pack you already produce, for any team, see the report-pack commentary job. The data-handling job builds a sourced table for up to five tools, and a monthly refresh lists what changed. Neither is legal advice, and a named person owns what is published.

Sources and limits

  • Ledge: month-end close benchmarks for 2025 Checked 2026-10-12.
    • A vendor survey of 100 respondents found 94% use Excel in the close and 50% take six or more business days; cash reconciliation takes 20 to 50 hours a month.
  • Fathom: best AI accounting tools Checked 2026-10-12.
    • Fathom sells a Commentary Writer inside its plans; its blog says every AI paragraph is "source-linked to the underlying metrics, calculations, and report components" and that accountants can edit and approve the explanations.
  • ICAEW: generative AI guide, do and don't Checked 2026-10-12.
    • ICAEW's generative AI do's and don'ts say to keep client and confidential data off public AI tools, to have policies and guidelines on how AI is used, and to be transparent when AI has been used.