Measure receivables turnover by counterparty
The agent calculates receivables turnover and days sales outstanding per counterparty, tracks the trend month by month and names who slows the money down.
Medium · 20 min · once a month
Who it fits
- You need to show management or the bank whether customer settlements sped up or slowed down, not who specifically owes money.
- You changed the deferral terms and want to see whether it showed up in the actual payment days.
- Not a fit if you need a list of debtors to call: this is a metric and its dynamics, not a debt collection plan.
Calculate receivables turnover for [period] broken down by [months / quarters] using 1C data. Give company-wide figures: turnover in times, average days sales outstanding, average receivables for the period. Then the same metrics per customer and by groups [wholesale / retail / chains]. Calculate the average balance from monthly snapshots, not from the start and end of the period. If a counterparty has fewer than [three] shipments in the period, don't average their payment days — mark it "not enough data". Don't explain a change in the metric by seasonality or sales growth until you show the figures that confirm it. Output a Google Sheets table: company-wide dynamics, the counterparty breakdown, and a "not enough data" column.
Copy the prompt or open it straight in a chat with the agent.
Try for freeHow the agent does it
Agree on the formula
Say whether you calculate payment days on revenue with or without VAT and whether prepayments are included. Different formulas give different DSO, and periods can only be compared within one of them.
Run the calculation
The agent takes shipments, payments and outstanding balances from 1C, calculates the metrics on monthly snapshots and puts the trend into a spreadsheet.
Check the result
The metric is easy to improve by accident — with one large shipment at the end of the period; make sure the trend isn't about that
Review the turnover calculation. List: — counterparties whose metric was calculated on fewer than [three] shipments; — months where the average balance was taken from two points instead of snapshots; — the effect of large one-off shipments and prepayments on the final figure — show the numbers with and without them; — bad and disputed debts that push the average days up and turnover down; — which conclusions about the trend are backed by data and which are your interpretation. State the formula you used explicitly.
A second prompt — the agent uses it to review its own work and show what's left for you.
What you set
1C, Google Sheets. From you: the period, the granularity of the trend and the formula you use for DSO.