Logistics
25 columns
200 rows
8 formats

Logistics Shipment Delay Prediction

This logistics shipment delay prediction dataset provides granular details on shipments, including route information, carrier performance, weather conditions, and both predicted and actual delays. Designed for supply chain managers and analysts, it enables proactive scheduling, risk assessment, and service optimization by offering actionable insights into delay patterns and their causes.

opened 15 times
last updated 20 Aug 2025
by GoMask

The brief that made it

Predicting shipment delays for proactive scheduling

Sample rows

preview · 8 of 200 rows · all 25 columns

shipment_idstring	weather_condition_departurestring	carrier_on_time_ratefloat	origin_statestring	scheduled_departure_datetimedatetime	actual_departure_datetimedatetime	scheduled_arrival_datetimedatetime	actual_arrival_datetimedatetime	origin_citystring	origin_countrystring	destination_citystring	destination_statestring	destination_countrystring	carrier_idstring	carrier_namestring	route_distance_kmfloat	route_typestring	vehicle_typestring	weather_condition_arrivalstring	delay_predicted_minutesinteger	delay_actual_minutesinteger	shipment_statusstring	priority_levelstring	shipment_typestring	notesstring
SHIP0001	clear	0.92	IL	2024-06-01T07:15:00Z	2024-06-01T07:21:00Z	2024-06-01T11:30:00Z	2024-06-01T11:47:00Z	Chicago	USA	St. Louis	MO	USA	CR001	SwiftLine Logistics	467.4	highway	truck	clear	14	17	delivered	standard	general	Minor delay due to urban congestion on approach to St. Louis.
SHIP0002	rain	0.84	blank	2024-06-02T08:00:00Z	2024-06-02T08:02:00Z	2024-06-02T10:45:00Z	2024-06-02T11:09:00Z	Paris	France	Berlin	blank	Germany	CR002	EuroFreight GmbH	1054.6	rail	train	rain	23	24	delivered	express	general	Weather-related delay near border crossing, otherwise on schedule.
SHIP0003	clear	0.93	NSW	2024-06-03T13:10:00Z	blank	2024-06-03T19:00:00Z	blank	Sydney	Australia	Melbourne	VIC	Australia	CR003	Pacific Transport	878.3	highway	truck	blank	8	blank	scheduled	standard	general	Shipment scheduled for early afternoon departure, all paperwork ready.
SHIP0004	storm	0.62	MH	2024-06-04T02:30:00Z	2024-06-04T03:02:00Z	2024-06-04T18:00:00Z	2024-06-04T19:17:00Z	Mumbai	India	Dubai	blank	UAE	CR004	Oceanic Global	1938.2	sea	ship	storm	180	197	delayed	critical	perishable	Severe storm at departure and arrival ports caused significant delay.
SHIP0005	fog	0.89	TX	2024-06-05T05:45:00Z	2024-06-05T06:00:00Z	2024-06-05T09:15:00Z	2024-06-05T09:42:00Z	Dallas	USA	Houston	TX	USA	CR005	TransAmeriX	385.9	highway	truck	clear	11	27	delivered	express	general	Early morning fog increased travel time between Dallas and Houston.
SHIP0006	clear	0.97	blank	2024-06-06T14:20:00Z	2024-06-06T14:32:00Z	2024-06-06T17:00:00Z	2024-06-06T17:09:00Z	Tokyo	Japan	Osaka	blank	Japan	CR006	Nippon Railways	515.2	rail	train	rain	6	9	delivered	standard	general	Short weather delay in Osaka, otherwise smooth delivery.
SHIP0007	fog	0.74	NY	2024-06-07T23:10:00Z	2024-06-07T23:36:00Z	2024-06-08T04:00:00Z	2024-06-08T05:30:00Z	New York	USA	London	blank	UK	CR007	Atlantic Air Cargo	5567.1	air	airplane	rain	29	90	delayed	express	perishable	Fog at JFK led to delayed departure; rain in London further delayed unloading.
SHIP0008	rain	0.95	blank	2024-06-08T06:45:00Z	2024-06-08T06:46:00Z	2024-06-08T09:20:00Z	2024-06-08T09:20:00Z	Manchester	UK	Edinburgh	blank	UK	CR008	BritTrans	357.8	highway	truck	clear	4	0	delivered	standard	general	No delays, shipment arrived exactly on schedule.
SHIP0009	clear	0.88	blank	2024-06-09T12:00:00Z	blank	2024-06-09T16:45:00Z	blank	Johannesburg	South Africa	Cape Town	blank	South Africa	CR009	Continental Freight	1397.2	rail	train	blank	18	blank	scheduled	standard	general	Scheduled rail shipment, no expected weather disruptions.
SHIP0010	snow	0.81	ON	2024-06-10T09:50:00Z	2024-06-10T10:12:00Z	2024-06-10T16:30:00Z	2024-06-10T18:01:00Z	Toronto	Canada	Montreal	QC	Canada	CR010	Maple Express	542.7	rail	train	snow	45	91	delayed	critical	hazardous	Winter storm affected both departure and arrival cities, hazardous material protocols delayed clearance.
SHIP0011	clear	0.91	CMX	2024-06-11T04:00:00Z	2024-06-11T04:04:00Z	2024-06-11T09:45:00Z	2024-06-11T09:53:00Z	Mexico City	Mexico	Guadalajara	JAL	Mexico	CR011	Azteca Cargo	551.4	highway	truck	clear	9	8	delivered	express	general	Slight delay due to morning traffic, shipment delivered ahead of predicted delay.
SHIP0012	storm	0.59	blank	2024-06-12T20:30:00Z	2024-06-12T20:47:00Z	2024-06-13T03:00:00Z	2024-06-13T04:20:00Z	Shanghai	China	Sydney	NSW	Australia	CR012	blank	7834.5	sea	ship	storm	920	1060	delayed	critical	perishable	Adverse sea conditions and port strikes caused major delay for perishable shipment.
SHIP0013	clear	0.88	DL	2024-06-13T17:05:00Z	2024-06-13T17:32:00Z	2024-06-14T01:00:00Z	2024-06-14T01:10:00Z	Delhi	India	Mumbai	MH	India	CR013	IndiRoad	1416	highway	truck	clear	12	10	delivered	standard	general	Timely delivery with minor congestion near Mumbai toll.
SHIP0014	rain	0.92	RJ	2024-06-14T07:30:00Z	blank	2024-06-14T12:45:00Z	blank	Rio de Janeiro	Brazil	Sao Paulo	SP	Brazil	CR014	BrasilCargo	429.7	highway	truck	blank	7	blank	scheduled	standard	general	Rain forecast but all systems go for highway delivery.
SHIP0015	clear	0.71	blank	2024-06-15T15:10:00Z	2024-06-15T15:45:00Z	2024-06-16T00:15:00Z	2024-06-16T02:01:00Z	Dubai	UAE	Singapore	blank	Singapore	CR015	AsiaFreight	5849.3	air	airplane	fog	88	106	delivered	critical	hazardous	Arrival delayed by fog at Changi Airport, hazardous goods required extra inspection.
SHIP0016	clear	0.89	blank	2024-06-16T11:00:00Z	2024-06-16T11:05:00Z	2024-06-16T15:00:00Z	2024-06-16T15:07:00Z	Frankfurt	Germany	Prague	blank	Czech Republic	CR016	CentralRail	507.9	rail	train	clear	4	7	delivered	express	general	Border crossing checks caused minimal delay, otherwise smooth trip.
SHIP0017	rain	0.86	blank	2024-06-17T06:30:00Z	2024-06-17T06:41:00Z	2024-06-17T09:45:00Z	2024-06-17T10:05:00Z	Lagos	Nigeria	Accra	blank	Ghana	CR017	WestAfrica Transport	426.5	highway	truck	rain	13	20	delivered	standard	other	Rain on both ends resulted in longer unloading and customs check.
SHIP0018	clear	0.87	blank	2024-06-18T23:30:00Z	blank	2024-06-19T05:45:00Z	blank	Beijing	China	Hong Kong	blank	China	CR006	Nippon Railways	1978	rail	train	blank	41	blank	scheduled	express	general	Rail shipment scheduled for overnight, expected minor delay at customs.
SHIP0019	storm	0.73	blank	2024-06-19T14:55:00Z	2024-06-19T15:10:00Z	2024-06-19T21:00:00Z	2024-06-19T22:19:00Z	Cape Town	South Africa	Walvis Bay	blank	Namibia	CR018	AfricaSea Lines	1249.2	sea	ship	clear	60	79	delivered	critical	hazardous	Early storm prompted route change, hazardous cargo required extra checks.
SHIP0020	clear	0.86	WA	2024-06-20T13:30:00Z	2024-06-20T13:39:00Z	2024-06-20T19:45:00Z	2024-06-20T20:15:00Z	Perth	Australia	Adelaide	SA	Australia	CR019	Outback Transport	2131	highway	truck	clear	19	30	delivered	standard	general	Minor delays due to road construction near Adelaide.

What the 200 rows show

from the 200-row sample

Storm (weather condition departure) stands out: mean carrier_on_time_rate is 0.67, against 0.87 for the rest.

0.88median carrier_on_time_rate
3priority levels
4route types
4vehicle types
4shipment statuses
4shipment types

Mean carrier_on_time_rate by weather_condition_departure200 rows

carrier_on_time_rate200 rows, in bands of 0.05

Median 0.88, from 0.58 to 0.98.

origin_state80 rows with a value · 120 left blank

NSW9
CA9
ON8
TX7
QLD7
DL5
VIC5
NY4
RJ4
WA4

25 columns by typefrom the column list below

string 17
integer 2
float 2
datetime 4

Columns

25 columns in three groups

blueprint · 25 columns
column	type	description	example
Text 17 columns
`shipment_id`	string	Unique identifier for each shipmentunique	SHIP0001
`origin_city`	string	City where the shipment originated	Chicago
`origin_state`	string	State or province of the shipment originoptional	IL
`origin_country`	string	Country of the shipment origin	USA
`destination_city`	string	City where the shipment is to be delivered	St. Louis
`destination_state`	string	State or province of the shipment destinationoptional	MO
`destination_country`	string	Country of the shipment destination	USA
`carrier_id`	string	Unique identifier for the carrier company responsible for the shipment	CR001
`carrier_name`	string	Name of the carrier companyoptional	SwiftLine Logistics
`route_type`	string	Type of route used (e.g., highway, rail, air, sea)highway · rail · air · sea · mixed	highway
`vehicle_type`	string	Type of vehicle used for shipment (e.g., truck, train, airplane, ship)truck · train · airplane · ship · other · optional	truck
`weather_condition_departure`	string	Weather condition at the time and location of departure6 values · optional	clear
`weather_condition_arrival`	string	Weather condition at the time and location of arrival6 values · optional	clear
`shipment_status`	string	Current status of the shipmentscheduled · in_transit · delivered · delayed · cancelled	delivered
`priority_level`	string	Priority level of the shipmentstandard · express · critical · optional	standard
`shipment_type`	string	Type of goods being shipped (e.g., perishable, hazardous, general)perishable · hazardous · general · other · optional	general
`notes`	string	Additional notes or comments about the shipmentoptional	Minor delay due to urban …
Numbers 4 columns
`route_distance_km`	float	Total distance of the shipment route in kilometers0 or more	467.4
`delay_predicted_minutes`	integer	Predicted delay for the shipment in minutes0 or more · optional	14
`delay_actual_minutes`	integer	Actual delay for the shipment in minutes (if known)0 or more · optional	17
`carrier_on_time_rate`	float	Carrier's historical on-time delivery rate (0-1)0 to 1 · optional	0.92
Dates and times 4 columns
`scheduled_departure_datetime`	datetime	Scheduled date and time of shipment departure	2024-06-01T07:15:00Z
`actual_departure_datetime`	datetime	Actual date and time when shipment departedoptional	2024-06-01T07:21:00Z
`scheduled_arrival_datetime`	datetime	Scheduled date and time of shipment arrival	2024-06-01T11:30:00Z
`actual_arrival_datetime`	datetime	Actual date and time when shipment arrivedoptional	2024-06-01T11:47:00Z

Use it for

A logistics dashboard
Carrier_on_time_rate by weather_condition_departure and a breakdown of origin_state. Excel, Power BI or Tableau.
Why do the 21 storm rows have a mean carrier_on_time_rate of 0.67?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Shipments200
SHIP00010.92clear
SHIP00020.84rain
SHIP00030.93clear
A software demo
Believable shipments with scheduled_departure_datetime, actual_departure_datetime and scheduled_arrival_datetime to fill a screen in front of a buyer.

This dataset200 rows25 columns

Yours1,000 rows25 columnsorigin_city: UK only

blueprint · logistics-shipment-delay-prediction

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 25 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Track shipments by route and carrier
Incorporate weather condition impact
Flag delayed shipments
Analyze seasonal delay trends

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: logistics-shipment-delay-prediction

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A logistics dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?