In-stock countsPipeline is everything not on hand: FL and TX carry one all-inclusive
column; SE / Great Lakes and NE sum their buckets (in-transit + on-dock + on-order).
Turns stay on-hand-only either way.
Table scopeFilters the two tables below; the map always shows all five PODs.
Drill-down exists only where the extract carries District and Warehouse columns — Florida,
Texas and the Northeast arrive pre-aggregated to the POD, so they have no levels
beneath.
Check the source data
Southeast and Greatlakes Raw.xlsx also carries districts outside the five PODs — Franklin (28,158 rows), Long Island (47,643 rows). Those rows are excluded: they belong to PODs sourced from their own extract, and including them would double-count.
Data as of 2026-09-03 10:01 · built
2026-09-03 10:02
Extract
Last modified
Rows used
Feeds
FL_Raw.xlsx
2026-09-03 10:00
137,241
Florida
TX_Raw.xlsx
2026-09-03 10:01
138,706
Texas
NE_Raw.xlsx
2026-09-03 10:01
57,887
Northeast
Southeast and Greatlakes Raw.xlsx
2026-09-03 10:01
161,365
Great Lakes · Southeast
Run Refresh Dashboard.cmd to pull the current day from Power BI and rebuild.
The oldest extract here is 2026-09-03 10:00 — anything much older
than the rest did not refresh.
In-stock rate by velocity
Revenue-weighted, on velocity-coded items (A–E; code P excluded). Bars scale
0–100%. Every row is a POD-level rollup — a SKU counts once and is in stock if any location in
that scope has it. The ranking basis still differs by extract, so compare a POD against itself
down a column rather than across PODs along a row. Southeast takes Richmond's velocity and
supplements with Atlanta's for the
2,027 items Richmond doesn't rank; Great Lakes
takes the modal code across its four warehouses, ties going to the faster
velocity.
POD
All velocity-coded
A
B
C
D
E
Northeastvelocity (excl. P)
97.0%99.8%
99%100%7,640 SKU
96%100%7,113 SKU
94%100%9,866 SKU
89%98%12,521 SKU
84%99%14,326 SKU
FloridaPOD velocity (excl. P)
84.4%96.8%
85%98%7,806 SKU
86%98%7,199 SKU
80%93%11,114 SKU
73%80%8,935 SKU
73%88%3,311 SKU
Great Lakesstatewide velocity, modal across warehouses (excl. P)
94.4%100.0%
96%100%7,101 SKU
91%100%6,898 SKU
90%100%8,264 SKU
88%100%5,698 SKU
75%100%5,328 SKU
63MIwarehouse
78.7%100.0%
81%100%
75%100%
73%100%
68%100%
62%100%
71ILwarehouse
78.1%100.0%
81%100%
70%100%
84%100%
89%100%
44%100%
76INwarehouse
79.6%100.0%
83%100%
76%100%
65%100%
54%100%
57%100%
77OHwarehouse
36.0%100.0%
40%100%
29%100%
27%100%
30%100%
12%100%
TexasPOD velocity (excl. P)
78.5%96.2%
81%97%7,563 SKU
74%96%7,101 SKU
71%94%10,042 SKU
76%90%8,270 SKU
70%78%328 SKU
SoutheastRichmond velocity, supplemented by Atlanta (excl. P)
80.6%100.0%
81%100%7,332 SKU
82%100%7,340 SKU
82%100%8,698 SKU
85%100%8,214 SKU
48%100%3,236 SKU
Atlantadistrict
56.9%100.0%
54%100%
62%100%
64%100%
75%100%
49%100%
Richmonddistrict
71.8%100.0%
72%100%
73%100%
72%100%
77%100%
38%100%
53NCwarehouse
96.0%100.0%
96%100%
97%100%
97%100%
93%100%
100%100%
56VAwarehouse
64.1%100.0%
65%100%
64%100%
63%100%
70%100%
37%100%
58NCwarehouse
100.0%100.0%
100%100%
100%100%
100%100%
100%100%
100%100%
Inventory turns and days of supply
Unit turns = ADU × 261 selling days
÷ on-hand units. Days of supply = on-hand units ÷ ADU, in selling days. On-hand
only — pipeline units are listed but excluded from both.
POD
On-hand units
Pipeline units
YTD ADU
ADU L14
ADU L35
ADU
Turns
Days
ADU
Turns
Days
ADU
Turns
Days
Northeast
512,609
457,652
5,602
2.85×
91
5,371
2.73×
95
5,492
2.80×
93
Florida
276,251
133,189
1,721
1.63×
161
1,732
1.64×
160
1,729
1.63×
160
Great Lakes
251,813
183,486
1,606
1.66×
157
1,701
1.76×
148
1,733
1.80×
145
63MIwarehouse
75,506
44,868
405
1.40×
186
356
1.23×
212
377
1.30×
200
71ILwarehouse
73,072
54,500
953
3.40×
77
871
3.11×
84
874
3.12×
84
76INwarehouse
78,970
29,569
157
0.52×
502
215
0.71×
367
214
0.71×
369
77OHwarehouse
24,265
54,549
91
0.98×
267
258
2.77×
94
267
2.87×
91
Texas
134,402
146,313
1,446
2.81×
93
1,593
3.09×
84
1,631
3.17×
82
Southeast
168,484
212,022
3,047
4.72×
55
2,906
4.50×
58
3,030
4.69×
56
Atlantadistrict
48,921
72,039
1,044
5.57×
47
1,025
5.47×
48
1,080
5.76×
45
Richmonddistrict
119,563
139,983
2,003
4.37×
60
1,881
4.11×
64
1,950
4.26×
61
53NCwarehouse
17,160
346
64
0.97×
270
40
0.61×
430
49
0.75×
349
56VAwarehouse
87,950
139,636
1,924
5.71×
46
1,828
5.42×
48
1,886
5.60×
47
58NCwarehouse
14,453
1
16
0.28×
932
13
0.23×
1120
14
0.26×
1001
All PODs
1,343,559
1,132,662
13,423
2.61×
100
13,303
2.58×
101
13,615
2.64×
99
Method and caveats
In-stock = share of YTD revenue sitting on SKUs that are available. The toggle
switches what counts as available: on hand only (on-hand qty > 0, the strict
read) or on hand + pipeline (on-hand + pipeline qty > 0, crediting stock already
on the way). Pipeline means everything not on hand. Florida and Texas deliver that
as one all-inclusive column (Qty_InPipeLine / POD_Pipeline);
SE / Great Lakes and the Northeast break it into buckets, so every bucket present is
summed — InTransit + OnDock + OnOrder — to reach the same definition. Summing
only part of it would understate those PODs against FL and TX. A SKU-count version of each
is on the map cards; both cover velocity-coded items only.
The toggle does not affect turns or days of supply — those stay on on-hand units,
since pipeline stock is not yet available to sell.
Every POD is now velocity-filtered, but not on the same basis. Florida and Texas
carry a POD-level FinalVelocity (the two disagree on ~90% of shared items).
Northeast carries companywide velocity. SE / Great Lakes carries a district-level
Velocity. Codes are therefore never joined across extracts, and a letter is
only comparable within its own POD. Code P is not a velocity rank and is
excluded everywhere it appears.
Southeast velocity is Richmond-first. The two Southeast districts rank the same
item differently on 44% of the 19,513 items they both carry, so the POD cannot simply pool
them. Per the business rule, Richmond's code wins
(32,793 items) and Atlanta's supplements only
items Richmond does not rank (2,027 items).
The unified code is applied to every Southeast row, so the Atlanta and warehouse rows above
are bucketed on Southeast's ranking, not their own local one.
4,689 of
69,419 Southeast rows carry no A–E code in either
district and drop out of the universe.
Everything is rolled up to the POD. Great Lakes (4 warehouses, 91,946 rows to 34,728 items), Southeast (4 warehouses, 69,419 rows to 39,287 items) arrive at stocking-location grain and are rolled up to the POD — a SKU counts once and is in stock if any location in the POD has it, which is the grain the other extracts already arrive at. Per-location detail is in the scope slicer.
A SKU is credited if any location in the scope has it, so a POD figure always reads higher
than the same inventory measured per location — Southeast is 84.6% rolled up against 67.2%
per warehouse. The scope slicer holds the per-location view, which is the one that answers
whether a given DC can serve its own market without a transfer.
The SE / Great Lakes extract is pre-filtered to Total Inventory Value >
$0, unblocked and not-closed items, excluding warehouses 87FL / 88FL. The other
extracts carry their own filters, so universes are not identical POD to POD.
Turns are unit-based, not dollar-weighted: the extracts carry YTD revenue but no
unit cost, so a dollar turn cannot be computed from them without assuming a price.
ADU columns are per selling day, verified against the raw values: YTD ADU is units
÷ 155, ADU L14 is units ÷ 10, ADU L35 is units ÷ 25. Annualizing uses 261
selling days, which matches the L14 and L35 basis.
These rates are computed fresh from Instock/Dashboard/ and will not tie to
Pod_instock_07222026/RegionOverall.xlsx, which is a separate earlier pull with
its own universe.
Rebuild with python build.py after dropping new raw extracts in
Instock/Dashboard/.