Transit times / Caterpillar Inc Tabitha Lox

Caterpillar Inc Tabitha Lox

53 ocean import shipments. Delayed 4.2 points less often than the dataset average of 43.8%.

53
Shipments
39.6%
Arrived late
21 shipments
1 days
Average delay, when late
median 1 days
1 days
Worst single delay

How late, when late

Every shipment placed in a band. Early and on-time are shown too, so the delayed share is read against the whole, not on its own.

1
1.9%
Early
31
58.5%
On time
21
39.6%
1–3 days
0
0%
4–7 days
0
0%
8–14 days
0
0%
15+ days

By carrier

All 1 carriers used.

% delayed avg days late, when laten = shipments
  1. Maersk
    39.6%
    1d
    5321 late

By route

All 3 lanes.

% delayed avg days late, when laten = shipments
  1. Jawaharlal Nehru > Newark, Nj
    52.9%
    1d
    3418 late
  2. Colombo Harbor > Newark, Nj
    0%
    160 late
  3. Mina Raysut > Newark, Nj
    100%
    1d
    33 late

By supplier

Top 12 of 18 suppliers; 6 shipments across the remaining 6 not shown.

% delayed avg days late, when laten = shipments
  1. Rishi Laser Pvt Ltd
    50%
    1d
    2010 late
  2. Castco
    87.5%
    1d
    87 late
  3. Ceva Logistics India Pvt Ltd
    0%
    50 late
  4. Ve Commercial Vehicles Ltd
    50%
    1d
    42 late
  5. Wheels India Limited
    0%
    20 late
  6. Caterpillar India Private Ltd
    0%
    20 late
  7. Steelcast Limited
    0%
    10 late
  8. Iconic Castings Private Limited
    0%
    10 late
  9. Subajeyam Turners
    0%
    10 late
  10. Magna Electro Castings Limited
    0%
    10 late
  11. Craftsman Automation Ltd
    0%
    10 late
  12. Gnutti Carlo India Private Limited
    0%
    10 late

By vessel

Vessel names are in the most recent data only — 53 of 53 shipments (100%) name one, across 6 ships. This chart covers that subset, not the whole.

% delayed avg days late, when laten = shipments
  1. Seroja Lima
    0%
    150 late
  2. Good Prospect
    100%
    1d
    1111 late
  3. Maersk Denver
    100%
    1d
    1010 late
  4. Madrid Express
    0%
    80 late
  5. Ain Snan Express
    0%
    80 late
  6. Maersk Seletar
    0%
    10 late

Delay rate by arrival date

Share of each day’s arrivals that came in late. A single late vessel puts the same delay on every container it carried, so a tall isolated bar is usually one sailing rather than a bad week — the count under each bar is the check on that.

100%
n=11
2026-07-29
0%
n=15
2026-08-04
100%
n=10
2026-08-05
0%
n=8
2026-08-07
0%
n=8
2026-08-09
0%
n=1
2026-08-11

By destination port

Where the delay actually lands — a congested discharge port shows up here rather than under the carrier.

% delayed avg days late, when laten = shipments
  1. Newark, Nj
    39.6%
    1d
    5321 late

By supplier country

Origin-side effects: a country whose shipments are consistently late points at booking or documentation, not at the ocean leg.

% delayed avg days late, when laten = shipments
  1. India
    42.9%
    1d
    2812 late
  2. Sri Lanka
    0%
    130 late
  3. Norway
    90%
    1d
    109 late
  4. Vietnam
    0%
    20 late

Reading this

Delay is measured against each shipment’s own estimated arrival on the same manifest record, so it reflects what was promised for that shipment. Average days late is taken over delayed shipments only.

A delay is usually a property of one sailing: every container off a late ship arrives the same day. It is not only that — an estimated arrival is set per bill of lading at booking, so two containers on the same ship can carry different delays. Across the shipments that name a vessel, two thirds of same-ship, same-day groups share a single delay value and a third do not.

Watch the counts. A carrier or lane with a handful of shipments can show a dramatic rate off one or two late arrivals — the n beside every bar is there so a small sample is never mistaken for a pattern.

Track a shipment live →