Odoo Process X-Ray · order-to-cash

Beanline Trading (fictional)

What really happened to every sales order between 1 Sep 2025 – 31 Aug 2026, reconstructed from Odoo's own change history. The company and its data are fictional, generated to demonstrate the tool.

Sales orders analysed

560

1 Sep 2025 – 31 Aug 2026

Quotations confirmed

81%

453 of 560

Order to cash (median)

31.0 days

90% within 57.7 days

Orders with at least one problem

46%

207 orders, 9 kinds of problem

Key findings

Problems that are both frequent and concentrated somewhere specific, so there is something concrete to fix. Click one to jump to its details.

Changed after the customer confirmed: 75 orders (17%), 80% of them handled by Tom Peeters.
Warsaw DC ships late-week orders days later: orders confirmed on Thu and Fri take up to 2.3 days to ship instead of 1.0 days (55 orders).
Paid more than two weeks after the due date: 54 orders (13%), 98% of them from Restauracja Odra, Coworking Praga, Hotel Nad Wisłą and 2 more.
Invoiced before the goods shipped: 49 orders (11%), 100% of them shipped from Warsaw DC.
Shipped more than 3 working days after confirmation: 35 orders (8%), 54% of them containing Espresso Machine Pro.
Needed a credit note: 29 orders (7%), 86% of them shipped from Warsaw DC.
Delivery date pushed back twice or more: 14 orders (3%), 100% of them containing Espresso Machine Pro.

Changed after the customer confirmed

75 of 453 confirmed orders (17%).

80% of them are orders handled by Tom Peeters, which make up only 28% of confirmed orders: 48% of those orders are affected, against 17% on average.

Share of confirmed orders affected, by salesperson

Why it matters

Every change after confirmation means rework downstream, and a risk that the customer gets a different price or quantity than what they agreed to.

What to do in Odoo

Sales > Settings > Lock Confirmed Sales makes confirmed orders read-only, so a change needs a deliberate unlock. Then ask why these orders change: missing information at quotation time, or price corrections?

Show the 75 orders

Order	Customer	Salesperson	Warehouse
S00002	Bistro Flagey Corner	Tom Peeters	Brussels DC
S00026	Lunchbar Kouter	Sophie Lambert	Brussels DC
S00029	Business Park Diegem	Tom Peeters	Brussels DC
S00031	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00034	Office Hub Leuven	Tom Peeters	Brussels DC
S00046	Bakkerij Zuid	Tom Peeters	Brussels DC
S00048	Office Hub Leuven	Tom Peeters	Brussels DC
S00050	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00052	Brasserie du Canal	Tom Peeters	Brussels DC
S00054	Bistro Flagey Corner	Tom Peeters	Brussels DC
S00056	Kantine Noord	Tom Peeters	Brussels DC
S00064	Kawiarnia Rynek	Kasia Nowak	Warsaw DC
S00086	Café Sint-Pieters	Tom Peeters	Brussels DC
S00091	Koffiebar Meir	Tom Peeters	Brussels DC
S00095	Kantine Noord	Tom Peeters	Brussels DC
S00097	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00098	Lunchbar Kouter	Sophie Lambert	Brussels DC
S00113	Biurowiec Mokotowska	Kasia Nowak	Warsaw DC
S00134	Office Hub Leuven	Tom Peeters	Brussels DC
S00152	Stołówka Politechnika	Piotr Zieliński	Warsaw DC
S00156	Hotel Lindenhof	Tom Peeters	Brussels DC
S00157	Business Park Diegem	Tom Peeters	Brussels DC
S00160	Bistro Flagey Corner	Tom Peeters	Brussels DC
S00167	Campus Kitchen Louvain	Tom Peeters	Brussels DC
S00170	Lunchbar Kouter	Tom Peeters	Brussels DC
S00172	Tearoom Duinen	Tom Peeters	Brussels DC
S00173	Co-Work Ixelles	Tom Peeters	Brussels DC
S00179	Café Parvis	Tom Peeters	Brussels DC
S00188	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00189	Hotel Atelier Bruges	Tom Peeters	Brussels DC
S00194	Co-Work Ixelles	Tom Peeters	Brussels DC
S00201	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00210	Co-Work Ixelles	Tom Peeters	Brussels DC
S00216	Bakkerij Zuid	Tom Peeters	Brussels DC
S00219	Koffiebar Meir	Tom Peeters	Brussels DC
S00222	Office Hub Leuven	Tom Peeters	Brussels DC
S00233	Tearoom Duinen	Tom Peeters	Brussels DC
S00237	Brasserie du Canal	Tom Peeters	Brussels DC
S00259	Office Hub Leuven	Tom Peeters	Brussels DC
S00288	Hotel Lindenhof	Tom Peeters	Brussels DC
S00290	Kawiarnia Mokotów	Piotr Zieliński	Warsaw DC
S00295	Espresso Point Wavre	Tom Peeters	Brussels DC
S00298	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00299	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00300	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00318	Café Sint-Pieters	Tom Peeters	Brussels DC
S00322	Café Sint-Pieters	Tom Peeters	Brussels DC
S00326	Koffiebar Meir	Sophie Lambert	Brussels DC
S00327	Hotel Tatry View	Kasia Nowak	Warsaw DC
S00334	Tearoom Duinen	Tom Peeters	Brussels DC
S00359	Tearoom Duinen	Tom Peeters	Brussels DC
S00375	Café Sint-Pieters	Tom Peeters	Brussels DC
S00385	Office Hub Leuven	Tom Peeters	Brussels DC
S00404	Business Park Diegem	Tom Peeters	Brussels DC
S00408	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00410	Bistro Flagey Corner	Tom Peeters	Brussels DC
S00423	Hotel Lindenhof	Tom Peeters	Brussels DC
S00429	Café des Arts Mons	Tom Peeters	Brussels DC
S00432	Campus Kitchen Louvain	Tom Peeters	Brussels DC
S00445	Café Parvis	Tom Peeters	Brussels DC
S00464	Office Hub Leuven	Tom Peeters	Brussels DC
S00475	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00480	Bistro Flagey Corner	Tom Peeters	Brussels DC
S00483	Brasserie du Canal	Tom Peeters	Brussels DC
S00495	Hotel Atelier Bruges	Tom Peeters	Brussels DC
S00498	Co-Work Ixelles	Tom Peeters	Brussels DC
S00505	Station Coffee Mechelen	Tom Peeters	Brussels DC
S00512	Café Parvis	Tom Peeters	Brussels DC
S00535	Kawiarnia Ogród	Piotr Zieliński	Warsaw DC
S00537	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00539	Café des Arts Mons	Tom Peeters	Brussels DC
S00543	Hotel Lindenhof	Tom Peeters	Brussels DC
S00545	Office Hub Leuven	Tom Peeters	Brussels DC
S00549	Kawiarnia Rynek	Kasia Nowak	Warsaw DC
S00553	Koffiebar Meir	Tom Peeters	Brussels DC

Warsaw DC ships late-week orders days later

Orders confirmed on Thu and Fri wait up to 2.3 days (working days) before shipping from Warsaw DC, against 1.0 days on its fastest days.

55 orders were affected over the period.

Median working days from confirmation to shipment at Warsaw DC, by the day the order was confirmed

Why it matters

The delay is not spread evenly: it depends on the day the order comes in, which points to capacity or planning at the end of the week rather than to the products.

What to do in Odoo

Check staffing and picking capacity at the end of the week. Inventory > Settings > Batch, Wave & Cluster Transfers helps a team clear a backlog, and a clear same-week cut-off time sets honest expectations.

Paid more than two weeks after the due date

54 of 404 paid orders (13%).

98% of them are orders from Restauracja Odra, Coworking Praga, Hotel Nad Wisłą, Brasserie du Canal and Salon Mosan, which make up only 13% of paid orders: 98% of those orders are affected, against 13% on average.

Share of paid orders affected, by customer

Why it matters

Late payment costs working capital. It is usually concentrated on a few customers.

What to do in Odoo

Enable Accounting > Settings > Sales Credit Limit for these customers, send payment reminders before the due date (follow-up reports in Odoo Enterprise), and consider shorter payment terms.

Show the 54 orders

Order	Customer	Salesperson	Warehouse
S00003	Coworking Praga	Kasia Nowak	Warsaw DC
S00009	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00011	Kawiarnia Rynek	Piotr Zieliński	Warsaw DC
S00014	Coworking Praga	Piotr Zieliński	Warsaw DC
S00015	Restauracja Odra	Kasia Nowak	Warsaw DC
S00019	Restauracja Odra	Kasia Nowak	Warsaw DC
S00023	Restauracja Odra	Kasia Nowak	Warsaw DC
S00025	Salon Mosan	Tom Peeters	Brussels DC
S00043	Coworking Praga	Kasia Nowak	Warsaw DC
S00055	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00076	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00080	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00083	Restauracja Odra	Kasia Nowak	Warsaw DC
S00088	Restauracja Odra	Kasia Nowak	Warsaw DC
S00097	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00099	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00105	Coworking Praga	Piotr Zieliński	Warsaw DC
S00108	Coworking Praga	Piotr Zieliński	Warsaw DC
S00115	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00127	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00129	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00154	Brasserie du Canal	Sophie Lambert	Brussels DC
S00155	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00166	Coworking Praga	Kasia Nowak	Warsaw DC
S00187	Brasserie du Canal	Sophie Lambert	Brussels DC
S00190	Brasserie du Canal	Sophie Lambert	Brussels DC
S00202	Brasserie du Canal	Sophie Lambert	Brussels DC
S00232	Restauracja Odra	Kasia Nowak	Warsaw DC
S00237	Brasserie du Canal	Tom Peeters	Brussels DC
S00250	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00255	Brasserie du Canal	Sophie Lambert	Brussels DC
S00267	Coworking Praga	Piotr Zieliński	Warsaw DC
S00274	Coworking Praga	Piotr Zieliński	Warsaw DC
S00276	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00286	Coworking Praga	Kasia Nowak	Warsaw DC
S00297	Salon Mosan	Sophie Lambert	Brussels DC
S00303	Brasserie du Canal	Sophie Lambert	Brussels DC
S00316	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00337	Restauracja Odra	Kasia Nowak	Warsaw DC
S00349	Coworking Praga	Piotr Zieliński	Warsaw DC
S00366	Restauracja Odra	Kasia Nowak	Warsaw DC
S00377	Coworking Praga	Kasia Nowak	Warsaw DC
S00380	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00394	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00395	Brasserie du Canal	Sophie Lambert	Brussels DC
S00396	Coworking Praga	Piotr Zieliński	Warsaw DC
S00407	Salon Mosan	Tom Peeters	Brussels DC
S00414	Brasserie du Canal	Sophie Lambert	Brussels DC
S00416	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00441	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00451	Salon Mosan	Sophie Lambert	Brussels DC
S00462	Brasserie du Canal	Sophie Lambert	Brussels DC
S00485	Coworking Praga	Piotr Zieliński	Warsaw DC
S00511	Salon Mosan	Sophie Lambert	Brussels DC

Invoiced before the goods shipped

49 of 441 invoiced and shipped orders (11%).

100% of them are orders shipped from Warsaw DC, which make up only 43% of invoiced and shipped orders: 26% of those orders are affected, against 11% on average.

Share of invoiced and shipped orders affected, by warehouse

Why it matters

Invoicing what hasn't shipped yet leads to disputes and credit notes whenever the delivery changes.

What to do in Odoo

Set the Invoicing Policy to 'Delivered quantities' (Sales > Settings, or per product) so invoices only contain what has actually shipped.

Show the 49 orders

Order	Customer	Salesperson	Warehouse
S00037	Cukiernia Stare Miasto	Kasia Nowak	Warsaw DC
S00042	Kawiarnia Ogród	Kasia Nowak	Warsaw DC
S00063	Hotel Poznań Park	Kasia Nowak	Warsaw DC
S00072	Kawiarnia Rynek	Piotr Zieliński	Warsaw DC
S00097	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00108	Coworking Praga	Piotr Zieliński	Warsaw DC
S00116	Stołówka Politechnika	Kasia Nowak	Warsaw DC
S00122	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00131	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00142	Stołówka Politechnika	Kasia Nowak	Warsaw DC
S00174	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00177	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00183	Kawiarnia Ogród	Kasia Nowak	Warsaw DC
S00199	Kawiarnia Ogród	Piotr Zieliński	Warsaw DC
S00201	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00204	Bistro Kazimierz	Kasia Nowak	Warsaw DC
S00206	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00215	Café Nowa Huta	Piotr Zieliński	Warsaw DC
S00220	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00242	Hotel Poznań Park	Kasia Nowak	Warsaw DC
S00251	Piekarnia Żoliborz	Piotr Zieliński	Warsaw DC
S00266	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00267	Coworking Praga	Piotr Zieliński	Warsaw DC
S00286	Coworking Praga	Kasia Nowak	Warsaw DC
S00290	Kawiarnia Mokotów	Piotr Zieliński	Warsaw DC
S00296	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00301	Kawiarnia Mokotów	Kasia Nowak	Warsaw DC
S00312	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00330	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00337	Restauracja Odra	Kasia Nowak	Warsaw DC
S00365	Kawiarnia Ogród	Kasia Nowak	Warsaw DC
S00366	Restauracja Odra	Kasia Nowak	Warsaw DC
S00396	Coworking Praga	Piotr Zieliński	Warsaw DC
S00397	Stołówka Politechnika	Kasia Nowak	Warsaw DC
S00399	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00420	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00430	Cukiernia Stare Miasto	Kasia Nowak	Warsaw DC
S00435	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00441	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00442	Hotel Tatry View	Kasia Nowak	Warsaw DC
S00477	Piekarnia Żoliborz	Piotr Zieliński	Warsaw DC
S00485	Coworking Praga	Piotr Zieliński	Warsaw DC
S00499	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00519	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00542	Biuro Centrum Wola	Piotr Zieliński	Warsaw DC
S00546	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00548	Cukiernia Stare Miasto	Piotr Zieliński	Warsaw DC
S00556	Cukiernia Stare Miasto	Piotr Zieliński	Warsaw DC
S00559	Bistro Kazimierz	Kasia Nowak	Warsaw DC

Shipped more than 3 working days after confirmation

35 of 441 shipped orders (8%).

54% of them are orders containing Espresso Machine Pro, which make up only 5% of shipped orders: 79% of those orders are affected, against 8% on average. Also concentrated in orders confirmed on Thu and Fri (54% of the problem, 29% of the orders).

Share of shipped orders affected, by product

Why it matters

Slow shipping delays the invoice (and therefore the cash) and frustrates customers.

What to do in Odoo

Compare picking capacity by warehouse and weekday. Inventory > Settings > Batch, Wave & Cluster Transfers helps a team clear a backlog faster.

Show the 35 orders

Order	Customer	Salesperson	Warehouse
S00043	Coworking Praga	Kasia Nowak	Warsaw DC
S00046	Bakkerij Zuid	Tom Peeters	Brussels DC
S00055	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00064	Kawiarnia Rynek	Kasia Nowak	Warsaw DC
S00099	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00131	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00155	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00177	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00220	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00241	Business Park Diegem	Sophie Lambert	Brussels DC
S00247	Hotel Poznań Park	Piotr Zieliński	Warsaw DC
S00261	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00287	Hotel Atelier Bruges	Tom Peeters	Brussels DC
S00290	Kawiarnia Mokotów	Piotr Zieliński	Warsaw DC
S00296	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00297	Salon Mosan	Sophie Lambert	Brussels DC
S00302	Cukiernia Stare Miasto	Piotr Zieliński	Warsaw DC
S00316	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00328	Hotel Tatry View	Kasia Nowak	Warsaw DC
S00334	Tearoom Duinen	Tom Peeters	Brussels DC
S00359	Tearoom Duinen	Tom Peeters	Brussels DC
S00365	Kawiarnia Ogród	Kasia Nowak	Warsaw DC
S00375	Café Sint-Pieters	Tom Peeters	Brussels DC
S00393	Tearoom Duinen	Tom Peeters	Brussels DC
S00394	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00415	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00425	Espresso Point Wavre	Sophie Lambert	Brussels DC
S00440	Hotel Poznań Park	Kasia Nowak	Warsaw DC
S00442	Hotel Tatry View	Kasia Nowak	Warsaw DC
S00456	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00470	Biuro Centrum Wola	Kasia Nowak	Warsaw DC
S00519	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00547	Lunchbar Kouter	Sophie Lambert	Brussels DC
S00548	Cukiernia Stare Miasto	Piotr Zieliński	Warsaw DC
S00550	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC

Needed a credit note

29 of 441 invoiced orders (7%).

86% of them are orders shipped from Warsaw DC, which make up only 43% of invoiced orders: 13% of those orders are affected, against 7% on average.

Share of invoiced orders affected, by warehouse

Why it matters

A credit note is an invoice that had to be corrected: extra work for accounting and a worse experience for the customer.

What to do in Odoo

Fix the cause, not the symptom: check whether these orders were invoiced before shipping or changed after confirmation.

Show the 29 orders

Order	Customer	Salesperson	Warehouse
S00043	Coworking Praga	Kasia Nowak	Warsaw DC
S00063	Hotel Poznań Park	Kasia Nowak	Warsaw DC
S00072	Kawiarnia Rynek	Piotr Zieliński	Warsaw DC
S00097	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00102	Biurowiec Mokotowska	Kasia Nowak	Warsaw DC
S00107	Station Coffee Mechelen	Tom Peeters	Brussels DC
S00116	Stołówka Politechnika	Kasia Nowak	Warsaw DC
S00122	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00123	Lunchbar Kouter	Sophie Lambert	Brussels DC
S00142	Stołówka Politechnika	Kasia Nowak	Warsaw DC
S00201	Biurowiec Mokotowska	Piotr Zieliński	Warsaw DC
S00215	Café Nowa Huta	Piotr Zieliński	Warsaw DC
S00216	Bakkerij Zuid	Tom Peeters	Brussels DC
S00242	Hotel Poznań Park	Kasia Nowak	Warsaw DC
S00266	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00279	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00349	Coworking Praga	Piotr Zieliński	Warsaw DC
S00365	Kawiarnia Ogród	Kasia Nowak	Warsaw DC
S00366	Restauracja Odra	Kasia Nowak	Warsaw DC
S00378	Café des Arts Mons	Sophie Lambert	Brussels DC
S00380	Hotel Nad Wisłą	Kasia Nowak	Warsaw DC
S00396	Coworking Praga	Piotr Zieliński	Warsaw DC
S00415	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00420	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00435	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC
S00441	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00485	Coworking Praga	Piotr Zieliński	Warsaw DC
S00519	Bistro Kazimierz	Piotr Zieliński	Warsaw DC
S00559	Bistro Kazimierz	Kasia Nowak	Warsaw DC

Delivery date pushed back twice or more

14 of 453 confirmed orders (3%).

100% of them are orders containing Espresso Machine Pro, which make up only 6% of confirmed orders: 52% of those orders are affected, against 3% on average.

Share of confirmed orders affected, by product

Why it matters

Each postponement is a broken promise to the customer, and usually points to a stock or supplier problem on specific products.

What to do in Odoo

For the products involved, set reordering rules (Inventory > Operations > Replenishment) and realistic vendor lead times, so promised dates can be kept.

Show the 14 orders

Order	Customer	Salesperson	Warehouse
S00099	Hotel Nad Wisłą	Piotr Zieliński	Warsaw DC
S00177	Kawiarnia Sopot Molo	Kasia Nowak	Warsaw DC
S00241	Business Park Diegem	Sophie Lambert	Brussels DC
S00287	Hotel Atelier Bruges	Tom Peeters	Brussels DC
S00296	Café Nowa Huta	Kasia Nowak	Warsaw DC
S00316	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00334	Tearoom Duinen	Tom Peeters	Brussels DC
S00359	Tearoom Duinen	Tom Peeters	Brussels DC
S00393	Tearoom Duinen	Tom Peeters	Brussels DC
S00394	Restauracja Odra	Piotr Zieliński	Warsaw DC
S00425	Espresso Point Wavre	Sophie Lambert	Brussels DC
S00456	Hotel Horizon Namur	Tom Peeters	Brussels DC
S00470	Biuro Centrum Wola	Kasia Nowak	Warsaw DC
S00550	Piekarnia Żoliborz	Kasia Nowak	Warsaw DC

Other checks

These rules found problems too, but with no clear pattern behind them.

Check	Orders affected	Share
Overdue and still unpaid	26	6%
Cancelled after confirmation	12	3%

The process map

Every box is a step, every arrow means "this step came right after that one". Thicker arrows carry more orders, and the colour shows how long orders waited before the next step (scale below). Numbers read as orders · median wait. Rare paths (under 1.5% of orders) are hidden.

Arrow colour = median wait: short → longArrow width = number of orders

Show the map as a table

From	To	Orders	Median wait
Start	Quotation created	560	–
Quotation created	Quotation sent	427	4 hours
Payment received	End	404	–
Goods shipped	Invoice posted	392	1.1 days
Invoice posted	Payment received	351	27.8 days
Quotation sent	Order confirmed	345	1.9 days
Order confirmed	Goods shipped	291	1.0 days
Quotation created	Order confirmed	108	1.8 days
Order cancelled	End	90	–
Order changed after confirmation	Goods shipped	70	12 hours
Order confirmed	Order changed after confirmation	69	23 hours
Quotation sent	Order cancelled	59	27.7 days
Order confirmed	Invoice posted	49	5 hours
Invoice posted	Goods shipped	41	24 hours
Delivery rescheduled	Goods shipped	39	3.0 days
Order confirmed	Delivery rescheduled	32	1.0 days
Invoice posted	End	31	–
Goods shipped	Payment received	27	27.0 days
Credit note posted	Payment received	26	20.3 days
Quotation sent	End	23	–
Delivery rescheduled	Delivery rescheduled	22	2.9 days
Quotation created	Order cancelled	19	27.0 days
Goods shipped	Credit note posted	19	11.1 days
Order confirmed	Order cancelled	12	2.6 days
Invoice posted	Credit note posted	10	9.9 days
Quotation created	End	6	–
Order changed after confirmation	Delivery rescheduled	5	24 hours
Invoice posted	Delivery rescheduled	5	1.8 days
Goods shipped	End	3	–
Delivery rescheduled	Order changed after confirmation	3	1 hours
Invoice posted	Order changed after confirmation	3	16 hours
Credit note posted	End	3	–

Where the time goes

Median calendar days for each step, from the first time it happened to the first time the next one did. The whisker shows how long it takes for 90% of orders.

Show as a table

Step	Orders	Median	90th percentile
Quote to order	453	2.0 days	5.7 days
Order to shipment	441	1.1 days	4.2 days
Shipment to invoice	392	1.1 days	4.0 days
Invoice to payment	404	27.9 days	55.6 days
Order to cash	404	31.0 days	57.7 days

Shipping speed by warehouse and weekday

Median working days from confirmation to shipment, by the weekday the order was confirmed. Weekends are excluded, so a Friday order shipped on Monday counts as one day. Outlined cells were flagged as unusually slow.

	Mon	Tue	Wed	Thu	Fri
Brussels DC	1.064 orders	1.068 orders	1.048 orders	1.139 orders	1.032 orders
Warsaw DC	1.053 orders	1.135 orders	1.047 orders	2.027 orders	2.328 orders

Most common paths

The 36 different routes orders took, most frequent first (repeated steps are counted once).

206	37%	Quotation created → Quotation sent → Order confirmed → Goods shipped → Invoice posted → Payment received
62	11%	Quotation created → Order confirmed → Goods shipped → Invoice posted → Payment received
59	11%	Quotation created → Quotation sent → Order cancelled
36	6%	Quotation created → Quotation sent → Order confirmed → Order changed after confirmation → Goods shipped → Invoice posted → Payment received
23	4%	Quotation created → Quotation sent
19	3%	Quotation created → Order cancelled
18	3%	Quotation created → Quotation sent → Order confirmed → Invoice posted → Goods shipped → Payment received
17	3%	Quotation created → Order confirmed → Order changed after confirmation → Goods shipped → Invoice posted → Payment received

About this analysis

Source. 2,984 events read from Odoo through its JSON-2 API: sales orders, deliveries, invoices and credit notes, plus their chatter tracking (the status-change lines). All of them come from that change history.
Method. Plain counting and date arithmetic. Each problem is a short rule written in Python, and a pattern is only reported when it would be very unlikely by chance.
Limits. The data shows what happened, not why: every finding is a question to take to the people involved. Orders migrated from an older system have no change history. Weekdays and weekends are computed in Europe/Brussels. Overdue status as of 31 Aug 2026.