Queries · q004 · Chief Executive Officer · week 1, night 2
“Why do our two trailing-12-month fee-revenue totals disagree, and what is the correct definition of a 'settled' payout?”
Fictional people at a fictional company, each played by a language-model agent. Who they are and what they are told
The manager, at the start of week 1
Subject: A few questions to get me oriented before the board meeting
Hi Hannah,
Thanks for taking these on this week — I know slots are tight, so please prioritize in the order below and don't force everything into this week if it doesn't fit cleanly. I'd rather get three solid answers than five rushed ones.
What I need this for: I'm building my mental model of the business ahead of the board meeting at the end of January, and I want my first real conversation with the board to show I understand where we're strong, where we're exposed, and what I'm watching closely. Your Friday memo will be the backbone of that.
Let me know if any of these need narrowing once you've had a look at what's feasible — happy to discuss before you lock in the report requests.
Thanks, Maren
The analyst · week 1, night 2, request 1 of 3
Before building anything else on top of payouts data, I need to resolve a real problem: Report 1 (merchant-level) implies total trailing-12-month fee revenue of ~€53.2k, but Report 3 (vertical-level) sums to ~€93.6k for the same window — a 1.76x gap. The two engineers used different status filters (Omar: status NOT IN bad list + paid_at not null; Bea: status = 'paid' only), and a narrower filter producing a LARGER total than a broader one is backwards, so something else is off too (possibly which date field anchors the window, or paid_at integrity by status). I'm spending one slot tonight on a reconciliation report to pin down the correct definition before I trust any revenue numbers further. The other two slots move to Maren's priority #2 (growth), using orders (which has a documented status enum, so no ambiguity) rather than payouts, so this work isn't blocked by the reconciliation.
The engineer · 1 dry run on the empty schema, then the submission
WITH converted AS ( SELECT p.status, p.paid_at, p.arrival_date, p.currency_code, p.gross_amount, p.fee_amount, er.rate FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) ) SELECT status, COUNT(*) AS total_payout_count, COUNT(*) FILTER (WHERE paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01') AS count_paid_in_window, COUNT(*) FILTER (WHERE paid_at IS NULL) AS count_paid_at_null, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN fee_amount / rate END), 2) AS fee_revenue_eur, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN gross_amount / rate END), 2) AS gross_volume_eur, MIN(paid_at) AS earliest_paid_at, MAX(paid_at) AS latest_paid_at, MIN(arrival_date) AS earliest_arrival_date, MAX(arrival_date) AS latest_arrival_date FROM converted GROUP BY status ORDER BY total_payout_count DESC, status
“Query compiles and matches the requested grain and columns. Submitting.”
“Submitted. The report will show, per payout status, total counts, the 2025 paid_at-window counts and null-paid_at counts, EUR-converted fee/gross sums for that window, and the min/max of both paid_at and arrival_date — which should directly expose whether paid_at is sparsely populated outside "settled" statuses and how far arrival_date's span diverges from paid_at's, explaining the 1.76x discrepancy between the two prior reports.”
As Hannah Brooks saw it, from the small dataset the agents worked on
status | total_payout_count | count_paid_in_window | count_paid_at_null | fee_revenue_eur | gross_volume_eur | earliest_paid_at | latest_paid_at | earliest_arrival_date | latest_arrival_date -----------+--------------------+----------------------+--------------------+-----------------+------------------+---------------------+---------------------+-----------------------+-------------------- paid | 26949 | 11286 | 0 | 53185.85 | 1991449.08 | 2023-01-03 09:00:00 | 2025-12-31 09:00:00 | 2023-01-03 | 2025-12-31 in_transit | 63 | 0 | 63 | NULL | NULL | NULL | NULL | 2026-01-01 | 2026-01-03 (2 rows)
The memo and the queries that followed; links found by title, so inferred
Later queries that build on this report:
It builds on:
Changed only where the benchmark needs the same result on every system
WITH converted AS ( SELECT p.status, p.paid_at, p.arrival_date, p.currency_code, p.gross_amount, p.fee_amount, er.rate p.status AS status, p.paid_at AS paid_at, p.arrival_date AS arrival_date, p.currency_code AS currency_code, p.gross_amount AS gross_amount, p.fee_amount AS fee_amount, er.rate AS rate FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date))SELECT status, COUNT(*) AS total_payout_count, COUNT(*) FILTER (WHERE paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01') AS count_paid_in_window, COUNT(*) FILTER (WHERE paid_at IS NULL) AS count_paid_at_null, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN fee_amount / rate END), 2) AS fee_revenue_eur, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN gross_amount / rate END), 2) AS gross_volume_eur, SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN CAST(fee_amount / rate AS NUMERIC(18,6)) END) AS fee_revenue_eur, SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN CAST(gross_amount / rate AS NUMERIC(18,6)) END) AS gross_volume_eur, MIN(paid_at) AS earliest_paid_at, MAX(paid_at) AS latest_paid_at, MIN(arrival_date) AS earliest_arrival_date, MAX(arrival_date) AS latest_arrival_dateFROM convertedGROUP BY statusORDER BY total_payout_count DESC, statusORDER BY total_payout_count DESC NULLS FIRST, status NULLS LAST
WITH converted AS ( SELECT p.status AS status, p.paid_at AS paid_at, p.arrival_date AS arrival_date, p.currency_code AS currency_code, p.gross_amount AS gross_amount, p.fee_amount AS fee_amount, er.rate AS rate FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) ) SELECT status, COUNT(*) AS total_payout_count, COUNT(*) FILTER (WHERE paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01') AS count_paid_in_window, COUNT(*) FILTER (WHERE paid_at IS NULL) AS count_paid_at_null, SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN CAST(fee_amount / rate AS NUMERIC(18,6)) END) AS fee_revenue_eur, SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN CAST(gross_amount / rate AS NUMERIC(18,6)) END) AS gross_volume_eur, MIN(paid_at) AS earliest_paid_at, MAX(paid_at) AS latest_paid_at, MIN(arrival_date) AS earliest_arrival_date, MAX(arrival_date) AS latest_arrival_date FROM converted GROUP BY status ORDER BY total_payout_count DESC NULLS FIRST, status NULLS LAST
The agents' own records, as the role play wrote them; only the personal data of the person who ran it is redacted
Report request from Hannah Brooks (analyst for the Chief Executive Officer): Title: Payout status & date-field reconciliation Question: Why do our two trailing-12-month fee-revenue totals disagree, and what is the correct definition of a 'settled' payout? Grain: one row per payouts.status value Columns: - status - total payout count (all time) - count with paid_at between 2025-01-01 and 2025-12-31 - count with paid_at null - fee revenue EUR (sum fee_amount, converted, for rows with paid_at in that window) - gross volume EUR (sum gross_amount, converted, same rows) - earliest paid_at - latest paid_at - earliest arrival_date - latest arrival_date Details: Source: payouts table only (no join needed). For every distinct value of status, report the counts and date ranges above. Convert gross_amount and fee_amount to EUR using exchange_rates: amount_eur = amount / rate where rate has base_code='EUR', quote_code=payouts.currency_code, as_of = payouts.paid_at date (if paid_at is null, skip that row from the EUR sums but still count it). This should let me see: (a) the full list of status codes and their relative sizes, (b) whether paid_at is reliably populated only for truly settled payouts, and (c) whether arrival_date spans a meaningfully different window than paid_at (which could explain why a prior vertical-level report's total came out ~1.76x higher than a prior merchant-level report's total for the 'same' window). Order by total payout count descending. Check your query with the warehouse's dry_run tool, then hand it in with submit.
dry_runWITH converted AS ( SELECT p.status, p.paid_at, p.arrival_date, p.currency_code, p.gross_amount, p.fee_amount, er.rate FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) ) SELECT status, COUNT(*) AS total_payout_count, COUNT(*) FILTER (WHERE paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01') AS count_paid_in_window, COUNT(*) FILTER (WHERE paid_at IS NULL) AS count_paid_at_null, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN fee_amount / rate END), 2) AS fee_revenue_eur, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN gross_amount / rate END), 2) AS gross_volume_eur, MIN(paid_at) AS earliest_paid_at, MAX(paid_at) AS latest_paid_at, MIN(arrival_date) AS earliest_arrival_date, MAX(arrival_date) AS latest_arrival_date FROM converted GROUP BY status ORDER BY total_payout_count DESC, status
STATUS: COMPILES (dry run on the empty schema, no data read) COLUMNS: status, total_payout_count, count_paid_in_window, count_paid_at_null, fee_revenue_eur, gross_volume_eur, earliest_paid_at, latest_paid_at, earliest_arrival_date, latest_arrival_date
submitWITH converted AS ( SELECT p.status, p.paid_at, p.arrival_date, p.currency_code, p.gross_amount, p.fee_amount, er.rate FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) ) SELECT status, COUNT(*) AS total_payout_count, COUNT(*) FILTER (WHERE paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01') AS count_paid_in_window, COUNT(*) FILTER (WHERE paid_at IS NULL) AS count_paid_at_null, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN fee_amount / rate END), 2) AS fee_revenue_eur, ROUND(SUM(CASE WHEN paid_at >= DATE '2025-01-01' AND paid_at < DATE '2026-01-01' THEN gross_amount / rate END), 2) AS gross_volume_eur, MIN(paid_at) AS earliest_paid_at, MAX(paid_at) AS latest_paid_at, MIN(arrival_date) AS earliest_arrival_date, MAX(arrival_date) AS latest_arrival_date FROM converted GROUP BY status ORDER BY total_payout_count DESC, status
Submitted to tonight's batch. Your work on this request is done.