Every order through pick, pack and ship this quarter: where the queue builds, and what the delay costs.
Live flow · Receive → Ship · bottleneck highlighted
Filters persist across every tab. Click any bar, dot or table row to drill down. Chips show active filters — click to remove.
Too few rows to rank on. This dashboard gates every rate
ranking at 30 rows because below that the ordering is sampling noise. The totals below are
real; the rates and the “worst” tiles are not reliable at this size.
No rows match these filters.Nothing is being calculated, because there is nothing to calculate from — a rate over
zero rows is not zero, it is undefined, and showing you a number here would be a wrong one.
Orders
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On-time %
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Work in progress
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Lead time · P50
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Bottleneck stage
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Cumulative flow — arrivals vs shipments
Cumulative orders received vs shipped, by day. Vertical gap = orders in the building (WIP); horizontal gap = lead time. The widening gap late in the quarter is the backlog building.
When orders arrive — weekday × hour
Order intake by weekday and hour of day · darker = busier. Illustrative of the arrival shape this data models (synthetic).
fewermore
On-time %
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Fragile on-times
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cleared with <10% SLA headroom
Late orders
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Lateness concentration
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Gini · higher = fewer clients own the misses
On-time rate by week — with control limits
Weekly on-time % against a p-chart centre-line and ±3σ limits (limits widen when a week ships fewer orders). Points outside the band are special-cause, not noise. 13 weeks is a short baseline — limits are indicative.
Client reliability — who we're actually failing
Each dot is a client · x = order volume (log) · y = on-time % · size = late orders · dashed = 90% target. Bottom-right = big clients missing SLA.
Carrier on-time vs target
On-time % per carrier (teal) inside a 100% track · navy tick = 90% target
Lead time · P50
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median receive → ship
P90
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slowest 1-in-10
P99
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worst 1-in-100 · the tail
Over 8 hours
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Stage dwell spread — P10 → P90
Per stage: light bar = P10–P90 range, teal = middle-half (P25–P75), navy tick = median. A wide bar is an unpredictable stage — the tail is where SLAs break.
Cycle-time distribution
Shipped orders by total time receive → ship · dashed lines mark P50 / P90 / P95
SLA headroom by priority — median slack vs cut-off
Median hours of slack (SLA − actual) per service level. Teal = comfortable; coral = median order already breaching. Zero line = on the SLA.
Bottleneck stage
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Its share of cycle
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of median receive → ship time
Breach minutes
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of all SLA-breach time
Late orders analysed
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broken down by culprit stage
Where the time goes — cycle-time waterfall
Median dwell stacked stage by stage up to the total lead time. The bottleneck stage is highlighted.
What broke the late orders
For each late order, the stage whose dwell most exceeded its cohort's normal — share of breach-minutes by culprit stage. A decomposition of where misses diverge, not a causal claim.
Which stage separates late from on-time?
Lateness rate as each stage's dwell rises (deciles, fastest → slowest). The steepest-climbing line is the stage that most discriminates a late order. Association, not cause — the biggest, most variable stage naturally lifts hardest.
Pick productivity
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lines picked / labour-hour
Labour cost / order
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Understaffed weeks
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actual heads > roster
Backlog to clear
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at current pick rate
Heads on the floor — planned roster vs actual demand
Full-time-equivalents needed each week to clear the work (bars) vs the fixed roster (line), per stage total. Bars above the line = weeks the work needed more FTE than the roster carried. DC-level; not affected by filters.
Productivity by stage — units per labour-hour
Throughput per labour-hour at each stage (Pick measured in lines). Navy tick = target. Below target = the stage soaking up hours.
Labour cost per order — by week
Weekly labour cost ÷ orders shipped · the unit-economics view of the floor · dashed = quarter average
Open orders
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Already breaching
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past SLA, still open
At risk · < 4 h left
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breach imminent
Most backed-up client
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SLA-at-risk — open orders by time to breach
Open orders bucketed by SLA time remaining (SLA − time already waited). Red = already past SLA; amber = breaching within 4 h. This is the firefighting queue.
Backlog age profile
Open orders by how long they've waited in the DC · darker = older
Backlog by client
Open orders still in the DC, worst 12 clients · click to drill
Carrier + handling / order
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excludes labour — see Labour tab
Revenue / order
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fee charged
Contribution before labour / order
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Loss-making clients
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Client profit cliff — who pays, who costs
Clients ranked by total contribution (revenue − cost to serve). Bars = each client's contribution (teal = profit, coral = loss); line = running cumulative. The dip at the right is the loss-makers dragging total profit down.
Carrier scorecard — cost vs reliability
Each bubble is a carrier · x = cost to serve · y = on-time % · size = volume · top-left = best value
Margin by order profile
Contribution margin % for each priority × order-type cohort · teal = profitable, coral = loss · n shown; thin cells (n<50) greyed.
Detail breakdown
Aggregated on current filters · click headers to sort · click a row to filter