Queries · q237 · Chief Operating Officer · week 2, night 2
“Do apparel/footwear merchants, where picking discrepancies are concentrated, actually see more orders go unfulfilled or delivered slowly -- or is that purely an inventory/accounting issue with no customer-facing effect?”
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 2
Subject: Carrier picture confirms it — now I want to know what we can actually fix
Lena,
This is exactly the clarity I was hoping for — "it's the carriers, not the warehouses" is a much more actionable story than "fulfillment is inconsistent." A few things jumped out, including from what Daniel's and Tomasz's teams posted this week, and I want to chase them down before we draft anything for merchants or carrier partners.
What surprised me: Albion Parcel going from solid to broken in November and staying broken through December is different from Landfall and Lowlands, which sound like long-term weak performers we've just tolerated. One is a relationship we may need to end; the other looks like it could be an acute problem (capacity, a route, a depot) that might actually be fixable if we understood the trigger. I don't want to lump all three into one "bad carriers" conversation when they may need completely different responses.
I also noticed Daniel's team's finding that "where's my order" tickets spike in lockstep with late deliveries each November/December — that's a direct line from the carrier problem to support cost and customer satisfaction, and I'd like to be able to say that explicitly in my own numbers rather than borrowing his.
Questions for this week:
If it's a tight week, prioritize #1 and #2 — I want the carrier narrative airtight before I take it anywhere. Returns/restock cycle time can wait one more week if needed.
Thanks, Priya
The analyst · week 2, night 2, request 3 of 3
Night 1 resolved priority #1 cleanly, and the answer is more nuanced than "weak carrier = weak carrier": (a) Albion Parcel's collapse is NOT localized -- it hit both countries it serves (UK and Ireland) and literally every origin warehouse/merchant it ships for, uniformly, the moment November started (pct-within-3-days fell from ~70-93% to ~0-40% everywhere at once, transit days jumping from ~2-2.5 to 8-17 days across the board). That rules out "one bad depot" or "one bad merchant" and points to a systemic capacity failure at Albion itself -- useful to know before the carrier conversation, but it's a harder story (a carrier that broke under load everywhere), not an easy single-fix. (b) Landfall Freight is uniformly bad across all 18 countries it serves (14-38% within 3 days everywhere, no bright spots) -- genuinely a "this carrier can't be trusted" case. (c) Lowlands Express is the interesting exception: it's actually solid on its home turf (Netherlands 79.9%, Belgium 69.3%, France 63.0% within 3 days -- 64.5% of its volume) but poor everywhere else (15-36% within 3 days on the remaining 35.5%). That's a lane-reassignment fix, not a carrier breakup. Tonight I'm covering priority #2 (the reliability ceiling, using a clean full-year carrier table so I can compute the weighted improvement by hand) and starting on #3 (a non-censored PO view, restricting to purchase orders old enough to have fully played out) and #4 (whether the apparel/footwear picking discrepancies Fatima's team flagged show up in delivery shortfalls, not just inventory accounting).
The engineer · 1 dry run on the empty schema, then the submission
WITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id, t.industry, o.status, o.placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL ), order_qty AS ( SELECT oi.order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id ), order_shipment AS ( SELECT f.order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id ), order_flags AS ( SELECT t0.order_id, t0.tenant_id, t0.industry, t0.status, t0.placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id ) SELECT industry, COUNT(*) AS orders_placed_2025, ROUND(100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0), 1) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, ROUND(CAST(AVG(CASE WHEN is_fully_delivered=1 THEN EXTRACT(EPOCH FROM (max_delivered_at - placed_at))/86400.0 END) AS numeric), 2) AS avg_delivery_days, ROUND(100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0), 1) AS pct_within_5_days FROM order_flags GROUP BY industry ORDER BY pct_orders_with_fulfillment_shortfall DESC, industry ASC
“Query compiles and returns the expected columns. Submitting.”
“Submitted. Summary of the approach:
- Grain: one row per tenants.industry for 2025.
- orders_placed_2025: orders with placed_at in 2025 and terminal status (fulfilled, cancelled, refunded).
- pct_orders_with_fulfillment_shortfall: share of those orders where summed order_items.quantity_fulfilled fell short of summed quantity.
- orders_fully_delivered / avg_delivery_days / pct_within_5_days: restricted to status='fulfilled' orders that have at least one linked shipment (via fulfillments) and no shipment with a null delivered_at; delivery time is placed_at to the latest linked delivered_at.
Noted in the submit note: orders marked fulfilled but with zero linked shipment rows are excluded from the "fully delivered" subset (can't compute a delivery date for them), and tenants with a null industry are dropped since the report is organized by vertical.”
As Lena Hartmann saw it, from the small dataset the agents worked on
industry | orders_placed_2025 | pct_orders_with_fulfillment_shortfall | orders_fully_delivered | avg_delivery_days | pct_within_5_days --------------------------+--------------------+---------------------------------------+------------------------+-------------------+------------------ Beauty | 1561 | 4.7 | 1451 | 4.55 | 73.8 Apparel & Footwear | 7149 | 4.5 | 6264 | 3.84 | 82.4 Sports & Outdoor | 1014 | 4.2 | 916 | 4.05 | 77.8 Home & Living | 1658 | 4.0 | 1519 | 4.43 | 73.7 Jewelry & Accessories | 50 | 4.0 | 46 | 4.23 | 73.9 Consumer Electronics | 575 | 3.7 | 534 | 4.08 | 76.2 Books & Stationery | 159 | 3.1 | 151 | 4.16 | 80.1 Pet Supplies | 1448 | 3.0 | 1385 | 4.28 | 77.8 Office Supplies (B2B) | 526 | 1.9 | 512 | 3.95 | 77.3 Food & Coffee | 7210 | 1.7 | 6997 | 3.93 | 80.5 Industrial Supplies (B2B) | 773 | 1.6 | 758 | 4.26 | 72.2 (11 rows)
The memo and the queries that followed; links found by title, so inferred
It builds on:
Changed only where the benchmark needs the same result on every system
WITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id, t.industry, o.status, o.placed_at SELECT o.id AS order_id, o.tenant_id AS tenant_id, t.industry AS industry, o.status AS status, o.placed_at AS placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL),order_qty AS ( SELECT oi.order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled SELECT oi.order_id AS order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id),order_shipment AS ( SELECT f.order_id, SELECT f.order_id AS order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id),order_flags AS ( SELECT t0.order_id, t0.tenant_id, t0.industry, t0.status, t0.placed_at, t0.order_id AS order_id, t0.tenant_id AS tenant_id, t0.industry AS industry, t0.status AS status, t0.placed_at AS placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at s.max_delivered_at AS max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id)SELECT industry, COUNT(*) AS orders_placed_2025, ROUND(100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0), 1) AS pct_orders_with_fulfillment_shortfall, 100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, ROUND(CAST(AVG(CASE WHEN is_fully_delivered=1 THEN EXTRACT(EPOCH FROM (max_delivered_at - placed_at))/86400.0 END) AS numeric), 2) AS avg_delivery_days, ROUND(100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0), 1) AS pct_within_5_days AVG(CASE WHEN is_fully_delivered=1 THEN {{seconds_between(placed_at, max_delivered_at)}}/86400.0 END) AS avg_delivery_days, 100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0) AS pct_within_5_daysFROM order_flagsGROUP BY industryORDER BY pct_orders_with_fulfillment_shortfall DESC, industry ASCORDER BY pct_orders_with_fulfillment_shortfall DESC NULLS FIRST, industry ASC NULLS LAST
WITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id AS tenant_id, t.industry AS industry, o.status AS status, o.placed_at AS placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL ), order_qty AS ( SELECT oi.order_id AS order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id ), order_shipment AS ( SELECT f.order_id AS order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id ), order_flags AS ( SELECT t0.order_id AS order_id, t0.tenant_id AS tenant_id, t0.industry AS industry, t0.status AS status, t0.placed_at AS placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at AS max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id ) SELECT industry, COUNT(*) AS orders_placed_2025, 100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, AVG(CASE WHEN is_fully_delivered=1 THEN CAST(EXTRACT(EPOCH FROM (max_delivered_at - placed_at)) AS NUMERIC(18,6))/86400.0 END) AS avg_delivery_days, 100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0) AS pct_within_5_days FROM order_flags GROUP BY industry ORDER BY pct_orders_with_fulfillment_shortfall DESC NULLS FIRST, industry ASC NULLS LAST
WITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id AS tenant_id, t.industry AS industry, o.status AS status, o.placed_at AS placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL ), order_qty AS ( SELECT oi.order_id AS order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id ), order_shipment AS ( SELECT f.order_id AS order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id ), order_flags AS ( SELECT t0.order_id AS order_id, t0.tenant_id AS tenant_id, t0.industry AS industry, t0.status AS status, t0.placed_at AS placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at AS max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id ) SELECT industry, COUNT(*) AS orders_placed_2025, 100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, AVG(CASE WHEN is_fully_delivered=1 THEN CAST(divideDecimal(toDecimal128(dateDiff('microsecond', placed_at, max_delivered_at), 0), toDecimal128(1000000, 0), 6) AS Nullable(Decimal(18, 6)))/86400.0 END) AS avg_delivery_days, 100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0) AS pct_within_5_days FROM order_flags GROUP BY industry ORDER BY pct_orders_with_fulfillment_shortfall DESC NULLS FIRST, industry ASC 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 Lena Hartmann (analyst for the Chief Operating Officer):
Title: Fulfillment shortfall and delivery speed by merchant vertical, 2025
Question: Do apparel/footwear merchants, where picking discrepancies are concentrated, actually see more orders go unfulfilled or delivered slowly -- or is that purely an inventory/accounting issue with no customer-facing effect?
Grain: one row per merchant industry/vertical (tenants.industry), 2025
Columns:
- industry
- orders_placed_2025 (orders with placed_at in 2025 and a terminal status: fulfilled, cancelled, or refunded)
- pct_orders_with_fulfillment_shortfall (share of those orders where SUM(order_items.quantity_fulfilled) < SUM(order_items.quantity) for the order)
- orders_fully_delivered (subset of those orders where status='fulfilled' and every linked shipment, via fulfillments, has a non-null delivered_at)
- avg_delivery_days (placed_at to max linked shipment delivered_at, fully-delivered subset only)
- pct_within_5_days (fully-delivered subset only)
Details: Tables: orders, order_items, fulfillments, shipments, tenants (industry). Scope: orders.placed_at between 2025-01-01 and 2025-12-31, status in ('fulfilled','cancelled','refunded') for the shortfall calculation (terminal orders only, so the shortfall flag is a final-state fact, not an in-progress one). Group by tenants.industry. Round pct columns to 1 decimal, avg_delivery_days to 2 decimals. Order by pct_orders_with_fulfillment_shortfall descending, tie-break by industry ascending. Expect under 12 rows (one per distinct industry value).
Check your query with the warehouse's dry_run tool, then hand it in with submit.dry_runWITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id, t.industry, o.status, o.placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL ), order_qty AS ( SELECT oi.order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id ), order_shipment AS ( SELECT f.order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id ), order_flags AS ( SELECT t0.order_id, t0.tenant_id, t0.industry, t0.status, t0.placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id ) SELECT industry, COUNT(*) AS orders_placed_2025, ROUND(100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0), 1) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, ROUND(CAST(AVG(CASE WHEN is_fully_delivered=1 THEN EXTRACT(EPOCH FROM (max_delivered_at - placed_at))/86400.0 END) AS numeric), 2) AS avg_delivery_days, ROUND(100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0), 1) AS pct_within_5_days FROM order_flags GROUP BY industry ORDER BY pct_orders_with_fulfillment_shortfall DESC, industry ASC
STATUS: COMPILES (dry run on the empty schema, no data read) COLUMNS: industry, orders_placed_2025, pct_orders_with_fulfillment_shortfall, orders_fully_delivered, avg_delivery_days, pct_within_5_days
submitWITH terminal_orders AS ( SELECT o.id AS order_id, o.tenant_id, t.industry, o.status, o.placed_at FROM orders o JOIN tenants t ON t.id = o.tenant_id WHERE o.placed_at >= TIMESTAMP '2025-01-01' AND o.placed_at < TIMESTAMP '2026-01-01' AND o.status IN ('fulfilled','cancelled','refunded') AND t.industry IS NOT NULL ), order_qty AS ( SELECT oi.order_id, SUM(oi.quantity) AS qty_ordered, SUM(oi.quantity_fulfilled) AS qty_fulfilled FROM order_items oi GROUP BY oi.order_id ), order_shipment AS ( SELECT f.order_id, COUNT(s.id) AS shipment_count, SUM(CASE WHEN s.delivered_at IS NULL THEN 1 ELSE 0 END) AS undelivered_count, MAX(s.delivered_at) AS max_delivered_at FROM fulfillments f JOIN shipments s ON s.fulfillment_id = f.id GROUP BY f.order_id ), order_flags AS ( SELECT t0.order_id, t0.tenant_id, t0.industry, t0.status, t0.placed_at, COALESCE(q.qty_ordered, 0) AS qty_ordered, COALESCE(q.qty_fulfilled, 0) AS qty_fulfilled, CASE WHEN COALESCE(q.qty_fulfilled,0) < COALESCE(q.qty_ordered,0) THEN 1 ELSE 0 END AS has_shortfall, CASE WHEN t0.status = 'fulfilled' AND s.shipment_count IS NOT NULL AND s.shipment_count > 0 AND COALESCE(s.undelivered_count,0) = 0 THEN 1 ELSE 0 END AS is_fully_delivered, s.max_delivered_at FROM terminal_orders t0 LEFT JOIN order_qty q ON q.order_id = t0.order_id LEFT JOIN order_shipment s ON s.order_id = t0.order_id ) SELECT industry, COUNT(*) AS orders_placed_2025, ROUND(100.0 * SUM(has_shortfall) / NULLIF(COUNT(*),0), 1) AS pct_orders_with_fulfillment_shortfall, SUM(is_fully_delivered) AS orders_fully_delivered, ROUND(CAST(AVG(CASE WHEN is_fully_delivered=1 THEN EXTRACT(EPOCH FROM (max_delivered_at - placed_at))/86400.0 END) AS numeric), 2) AS avg_delivery_days, ROUND(100.0 * SUM(CASE WHEN is_fully_delivered=1 AND (max_delivered_at - placed_at) <= INTERVAL '5 days' THEN 1 ELSE 0 END) / NULLIF(SUM(is_fully_delivered),0), 1) AS pct_within_5_days FROM order_flags GROUP BY industry ORDER BY pct_orders_with_fulfillment_shortfall DESC, industry ASC
Submitted to tonight's batch. Your work on this request is done.