Operate · the run state
Every queue, one day, one canvas
This is the operation as it stood at the close of Thu, Sep 11. 36 queues across 12 towers, ranked not by how large they are but by how fast they are changing … more
Health
What the day did to the operation
Arrival against service is the only pair that tells you whether tomorrow is worse than today. more
Of the 36 queues on this canvas, this one is ranked first because releasing it frees the most work: it holds 18.2% of everything standing, and it is taking on 1,825 more items a day than it clears, so the share is rising. At the day service rate of 6,755 items, and only if nothing else arrived, what is already standing in it is 4.6 days of work. Its oldest item has been waiting 31.7 h, and 414 of the 6,755 items it did serve cleared outside commitment.
The name recorded against most of the work in this queue in the sampled ledger week is Chidi Obi. That is who this constraint belongs to.
Detail on the record
The blockage map
Every queue in the operation, grouped by tower. more
All queues at the close of the day
36 queues · 169,293 items standing · deepest is 30,764
Three numbers follow each bar: items standing at the close, the day net change, and the age of the oldest item in the queue. The bars are an exhaustive map of the operation — all 36 queues appear, and their standing depths sum to the 169,293 on the tile above. A queue opens the series with work already in it, so standing depth is not arrivals minus service.
What to pick up
Flow rather than stock
Ranked by how much work releasing the queue would free — standing depth plus five days of the rate at which it is falling behind. more
Every queue, ranked by what releasing it frees
16 queues are taking on more than they clear
| # | Queue | Tower | Arrived | Served | Net | Standing | Normal | vs normal | Days of work | Inside | Oldest |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Order desk | O2C | 8,580 | 6,755 | +1,825 | 30,764 | 17,768 | +73% | 4.6 | 94% | 31.7 h |
| 2 | Invoice processing | S2P | 11,727 | 9,362 | +2,365 | 18,299 | 6,104 | +200% | 2.0 | 70% | 41.2 h |
| 3 | Buying desk | S2P | 9,284 | 7,710 | +1,574 | 19,669 | 11,279 | +74% | 2.6 | 79% | 2.8 d |
| 4 | Agent run desk | AIO | 5,151 | 4,045 | +1,106 | 20,242 | 10,086 | +101% | 5.0 | 68% | 3.8 d |
| 5 | Postings desk | R2R | 7,549 | 6,000 | +1,549 | 15,277 | 4,705 | +225% | 2.5 | 78% | 46.9 h |
| 6 | Model routing | AIO | 3,621 | 3,053 | +568 | 12,342 | 5,762 | +114% | 4.0 | 77% | 3.3 d |
| 7 | Make and release | M2D | 5,518 | 4,811 | +707 | 7,207 | 1,606 | +349% | 1.5 | 74% | 35.5 h |
| 8 | Artwork studio | C2L | 2,772 | 2,903 | -131 | 9,222 | 5,996 | +54% | 3.2 | 87% | 3.1 d |
| 9 | Report certification | D&A | 1,847 | 1,737 | +110 | 4,492 | 3,087 | +46% | 2.6 | 95% | 43.0 h |
| 10 | Incident desk | ITS | 4,671 | 4,731 | -60 | 4,220 | 1,245 | +239% | 0.9 | 96% | 26.1 h |
| 11 | Time and claims | H2R | 9,171 | 8,733 | +438 | 1,777 | 815 | +118% | 0.2 | 69% | 11.1 h |
| 12 | Prompt and policy | AIO | 3,453 | 3,508 | -55 | 3,777 | 4,005 | -6% | 1.1 | 93% | 22.8 h |
| 13 | Media operations | A2L | 1,700 | 1,574 | +126 | 2,820 | 715 | +294% | 1.8 | 78% | 38.5 h |
| 14 | Change and access | ITS | 5,220 | 5,396 | -176 | 3,065 | 3,773 | -19% | 0.6 | 71% | 17.4 h |
| 15 | Formulation | C2L | 3,251 | 4,189 | -938 | 2,675 | 3,678 | -27% | 0.6 | 68% | 17.4 h |
| 16 | Metric governance | D&A | 1,446 | 1,224 | +222 | 1,511 | 395 | +283% | 1.2 | 90% | 22.3 h |
| 17 | Quality control | M2D | 1,016 | 1,107 | -91 | 2,278 | 1,335 | +71% | 2.1 | 91% | 2.4 d |
| 18 | Payroll operations | H2R | 7,646 | 8,425 | -779 | 2,255 | 4,245 | -47% | 0.3 | 92% | 12.4 h |
| 19 | Move and deliver | M2D | 6,491 | 6,137 | +354 | 482 | 214 | +126% | 0.1 | 69% | 18.7 h |
| 20 | Cash and collections | O2C | 2,548 | 2,607 | -59 | 1,751 | 926 | +89% | 0.7 | 70% | 13.7 h |
| 21 | Replenishment | P2P | 1,605 | 1,642 | -37 | 1,532 | 1,128 | +36% | 0.9 | 94% | 38.5 h |
| 22 | Service requests | ITS | 4,429 | 4,838 | -409 | 1,464 | 3,426 | -57% | 0.3 | 81% | 8.3 h |
| 23 | Trade promotion | A2L | 2,366 | 2,215 | +151 | 513 | 155 | +232% | 0.2 | 71% | 19.7 h |
| 24 | Reconciliation | R2R | 4,503 | 4,934 | -431 | 991 | 665 | +49% | 0.2 | 67% | 19.8 h |
| 25 | Sales and operations planning | P2P | 1,419 | 1,325 | +94 | 94 | 362 | -74% | 0.1 | 90% | 13.3 h |
| 26 | Billing and credit | O2C | 7,888 | 7,801 | +87 | 87 | 470 | -81% | 0.0 | 93% | 15.9 h |
| 27 | Launch gates | C2L | 1,883 | 2,183 | -300 | 455 | 1,701 | -73% | 0.2 | 74% | 8.6 h |
| 28 | Data quality | D&A | 2,711 | 2,687 | +24 | 24 | 213 | -89% | 0.0 | 82% | 14.7 h |
| 29 | Employee lifecycle | H2R | 3,660 | 3,844 | -184 | 8 | 187 | -96% | 0.0 | 82% | 15.0 h |
| 30 | Obligation management | LGL | 1,969 | 1,969 | 0 | 0 | 268 | -100% | 0.0 | 74% | 0 min |
| 31 | Supplier operations | S2P | 4,628 | 4,628 | 0 | 0 | 1,893 | -100% | 0.0 | 63% | 0 min |
| 32 | Close management | R2R | 2,528 | 2,830 | -302 | 0 | 251 | -100% | 0.0 | 85% | 0 min |
| 33 | Contract desk | LGL | 4,384 | 4,384 | 0 | 0 | 1,021 | -100% | 0.0 | 82% | 0 min |
| 34 | Forecast desk | P2P | 1,411 | 1,411 | 0 | 0 | 63 | -100% | 0.0 | 66% | 0 min |
| 35 | Campaign briefing | A2L | 4,879 | 4,879 | 0 | 0 | 883 | -100% | 0.0 | 70% | 0 min |
| 36 | Matter management | LGL | 932 | 932 | 0 | 0 | 123 | -100% | 0.0 | 92% | 0 min |
"Normal" is the mean standing depth for that same queue over the 25 modeled days before the one on screen, so it is a comparison of a queue with itself rather than with any other queue. "Days of work" divides what is standing by what was served on the day. Both are unavailable at the start of the series, where there are no prior days to average.
Now versus normal
19 queues are more than ten percent above their own 27 day mean
The first 12 of 19 are shown, deepest departure from normal first.
31,003 items cleared outside their commitment. They are spread across 36 queues, and the deepest single contributor is Invoice processing with 2,842. Commitment here is measured against what was served on the day; items still standing have not yet been judged against it.
Actions
What is waiting on a person
A queue is worth acting on when it is growing, not when it is large. more
Recover a queue missing its commitment
Some of what was served on the day cleared outside the service level for that queue.
Add service to a growing queue
More arrived than was served on the day on screen, so the queue is deeper tonight than this morning.
Break up a queue holding over three days of work
At the day service rate, clearing what is already in it takes more than three days.
Escalate an item older than 72 hours
The oldest item in the queue has been waiting three days or more.
Explain a queue running above its own normal
Depth is more than ten percent above the mean of the prior 27 days for that same queue.
Operations
What this desk is allowed to start
A surface that only reports is not operable. more
Trigger and bound
This page can rank every queue by depth, by growth and against its own prior distribution, and name the one whose release frees the most work. more
Live observability
What the record shows right now
Direction of travel on the day on screen, an exhaustive partition of all 36 queues: each queue either grew, drained or held level.
Current distribution
36 queues
Is policy and strategy coming to fruition
Whether the written intent is holding here
79.6% of what was served on the day cleared inside commitment, with 1,636,528 items left standing.
Nothing on the record settles this
The written position is that work is managed by flow rather than by backlog size, and that a commitment is a promise about each item rather than an average. more
This page animates a modeled series. The 365 days between Sun, Aug 17 and Sun, Aug 16 were generated from a fixed seed for Brightvale, an invented company, and nothing on this canvas is attached to a running queue in any real system. Moving the day changes which generated row is being read. It does not replay anything that happened.
Brightvale Consumer Group is an invented company. more
Two conventions matter for reading it. Queues open the series carrying work, so standing depth is not the running total of arrivals minus service, and the two should not be reconciled against each other. And unlike the ledger, none of this is sampled: arrival, service and depth are full population counts, so multiplying them by fifty to match the ledger sample would be wrong in both directions.
The binding constraint is computed, not chosen. It is the queue with the highest standing depth plus five times the rate at which it is falling behind — a deliberate weighting that puts growth ahead of size. A different weighting names a different queue, and the ranking below it changes with the day on screen.