Logistics
27 columns
120 rows
8 formats

E-commerce Last-Mile Delivery Risks

This dataset provides granular, real-world records of last-mile delivery events in e-commerce logistics, capturing delays, vehicle incidents, route types, and environmental conditions. It enables supply chain analysts and logistics managers to identify risk patterns, optimize delivery operations, and proactively mitigate disruptions in urban and suburban environments.

last updated 22 Jan 2026
by GoMask

The brief that made it

Risk analysis and mitigation for last-mile delivery operations

Sample rows

preview · 8 of 120 rows · all 27 columns

delivery_idstring	route_typestring	distance_kmfloat	start_address_statestring	order_idstring	vehicle_idstring	driver_idstring	scheduled_delivery_datetimedatetime	actual_delivery_datetimedatetime	delivery_statusstring	delay_minutesinteger	incident_typestring	start_address_streetstring	start_address_citystring	start_address_postal_codestring	start_address_countrystring	end_address_streetstring	end_address_citystring	end_address_statestring	end_address_postal_codestring	end_address_countrystring	vehicle_typestring	weather_conditionstring	temperature_celsiusfloat	risk_scorefloat	incident_descriptionstring	notesstring
DEL1001	urban	3.2	CA	ORD2001	VEH001A	DRV001	2024-06-03T09:15:00Z	2024-06-03T09:22:00Z	completed	7	none	221 Main St	San Francisco	94105	USA	17 Market St	San Francisco	CA	94103	USA	van	clear	19.1	0.11	blank	Routine delivery, no issues encountered.
DEL1002	urban	4.7	NY	ORD2002	VEH002B	DRV002	2024-06-03T10:00:00Z	blank	cancelled	blank	none	88 5th Ave	New York	10003	USA	45 Broadway	New York	NY	10004	USA	bike	rain	17.3	0.22	blank	Customer cancelled before dispatch.
DEL1003	urban	8.5	ENG	ORD2003	VEH001A	DRV003	2024-06-03T11:30:00Z	2024-06-03T11:52:00Z	delayed	22	none	12 King St	London	SW1A1AA	UK	77 Queen St	London	ENG	E1 6AN	UK	car	fog	12.9	0.36	blank	Minor traffic delays due to morning congestion.
DEL1004	urban	2.5	NY	ORD2004	VEH003C	DRV004	2024-06-03T08:40:00Z	2024-06-03T08:44:00Z	completed	4	none	205 Central Park W	New York	10024	USA	11 West 34th St	New York	NY	10001	USA	bike	clear	20.2	0.07	blank	Quick bike delivery, route clear.
DEL1005	suburban	7.1	ON	ORD2005	VEH004D	DRV005	2024-06-03T13:20:00Z	2024-06-03T13:27:00Z	completed	7	none	55 Maple Rd	Toronto	M5V3C6	CAN	89 Oak St	Toronto	ON	M4Y1R8	CAN	truck	clear	23.8	0.13	blank	Routine suburban delivery, sunny weather.
DEL1006	suburban	9.8	NSW	ORD2006	VEH005E	DRV006	2024-06-02T14:05:00Z	2024-06-02T14:45:00Z	delayed	40	none	14 Pine Ave	Sydney	2060	AUS	241 George St	Sydney	NSW	2000	AUS	van	rain	16.6	0.41	blank	Heavy rain caused minor flooding delays.
DEL1007	urban	3.6	IDF	ORD2007	VEH006F	DRV007	2024-06-02T16:30:00Z	2024-06-02T16:31:00Z	completed	1	none	301 Rue de Rivoli	Paris	75001	FRA	50 Avenue Foch	Paris	IDF	75116	FRA	car	clear	24.4	0.06	blank	Efficient delivery, light traffic.
DEL1008	urban	2.1	BE	ORD2008	VEH007G	DRV008	2024-06-02T18:00:00Z	2024-06-02T18:00:00Z	completed	0	none	11 Friedrichstr.	Berlin	10117	DEU	101 Unter den Linden	Berlin	BE	10117	DEU	bike	clear	22.7	0.04	blank	Prompt arrival, short route.
DEL1009	rural	86.2	MT	ORD2009	VEH008H	DRV009	2024-06-02T20:20:00Z	2024-06-02T21:00:00Z	delayed	40	none	310 Highway 1	Helena	59601	USA	800 Farm Rd	Bozeman	MT	59718	USA	truck	storm	9.5	0.76	blank	Thunderstorm slowed progress, minor delays.
DEL1010	rural	68.5	WLS	ORD2010	VEH009I	DRV010	2024-06-02T07:00:00Z	2024-06-02T07:55:00Z	incident	55	vehicle_breakdown	78 Route 73	Cardiff	CF10 3NQ	UK	16 Farm Lane	Swansea	WLS	SA1 1EE	UK	truck	fog	4.8	0.92	Truck broke down near end of route, required towing.	Vehicle breakdown caused major delay.
DEL1011	urban	5.9	IL	ORD2011	VEH010J	DRV011	2024-06-02T13:40:00Z	2024-06-02T13:45:00Z	completed	5	none	102 Main St	Chicago	60607	USA	300 Lake Shore Dr	Chicago	IL	60601	USA	car	clear	21.5	0.09	blank	Light traffic, delivery on schedule.
DEL1012	suburban	14.2	BC	ORD2012	VEH011K	DRV012	2024-06-02T15:00:00Z	2024-06-02T15:32:00Z	delayed	32	none	888 Elm St	Vancouver	V6B4A4	CAN	120 Cedar St	Vancouver	BC	V6E2H4	CAN	truck	fog	10.9	0.38	blank	Dense fog in suburbs, slowed traffic.
DEL1013	urban	1.7	ENG	ORD2013	VEH012L	DRV013	2024-06-02T17:05:00Z	2024-06-02T17:06:00Z	completed	1	none	401 Oxford St	London	W1D1LL	UK	2 Piccadilly	London	ENG	W1J9LL	UK	bike	clear	20.3	0.03	blank	Short route, prompt delivery.
DEL1014	rural	97.8	NZL	ORD2014	VEH013M	DRV014	2024-06-02T12:30:00Z	2024-06-02T13:50:00Z	incident	80	theft	1207 Route 12	Wellington	6011	NZL	300 River Rd	Palmerston North	NZL	4410	NZL	van	rain	8.1	1	Package stolen from vehicle at rest stop.	Major incident, police notified.
DEL1015	urban	2.6	MD	ORD2015	VEH014N	DRV015	2024-06-02T09:30:00Z	2024-06-02T09:35:00Z	completed	5	none	99 Calle Mayor	Madrid	28013	ESP	27 Gran Via	Madrid	MD	28013	ESP	van	clear	27.9	0.06	blank	Quick van delivery, no issues.
DEL1016	urban	2.8	ISL	ORD2016	VEH015O	DRV016	2024-06-02T11:30:00Z	blank	in_progress	blank	none	56 Laugavegur	Reykjavik	101	ISL	89 Skolavordustigur	Reykjavik	ISL	101	ISL	car	snow	-3	0.23	blank	Snowfall expected, delivery underway.
DEL1017	urban	8.9	SH	ORD2017	VEH016P	DRV017	2024-06-02T08:45:00Z	2024-06-02T09:00:00Z	completed	15	none	12 Main Rd	Shanghai	200001	CHN	100 Nanjing Rd	Shanghai	SH	200003	CHN	van	clear	26.2	0.12	blank	Busy morning, moderate delays.
DEL1018	suburban	10.4	VIC	ORD2018	VEH017Q	DRV018	2024-06-02T12:30:00Z	2024-06-02T12:53:00Z	delayed	23	none	320 Oak St	Melbourne	3002	AUS	21 Swanston St	Melbourne	VIC	3000	AUS	van	clear	18.7	0.28	blank	Minor traffic delays in suburbs.
DEL1019	rural	108.3	TX	ORD2019	VEH018R	DRV019	2024-06-02T19:40:00Z	2024-06-02T21:17:00Z	incident	97	traffic_accident	210 Route 11	Dallas	75201	USA	150 County Rd	Waco	TX	76706	USA	truck	fog	6.4	0.89	Truck involved in minor accident on highway.	Accident delayed delivery, no injuries.
DEL1020	urban	4.9	VIC	ORD2020	VEH019S	DRV020	2024-06-02T08:15:00Z	2024-06-02T08:24:00Z	completed	9	none	101 Collins St	Melbourne	3000	AUS	200 Queen St	Melbourne	VIC	3000	AUS	car	clear	22.1	0.1	blank	Smooth delivery, no traffic issues.

What the 120 rows show

from the 120-row sample

Rural (route type) stands out: mean distance_km is 69.7, against 6.4 for the rest.

7.2median distance_km
4vehicle types
5delivery statuses
5incident types
6weather conditions
13start address countries

Mean distance_km by route_type120 rows

distance_km120 rows, in bands of 20

Median 7.2, from 1.1 to 115.0.

start_address_state120 rows · top 10 of 38 values

ON14
ENG10
TX10
CA8
IDF8
NY7
NSW6
AB6
MA5
MT4

27 columns by typefrom the column list below

string 21
integer 1
float 3
datetime 2

Columns

27 columns in three groups

blueprint · 27 columns
column	type	description	example
Text 21 columns
`delivery_id`	string	Unique identifier for each delivery eventunique	DEL1001
`order_id`	string	Unique identifier for the e-commerce order associated with the delivery	ORD2001
`vehicle_id`	string	Unique identifier for the delivery vehicle	VEH001A
`driver_id`	string	Unique identifier for the driver responsible for the delivery	DRV001
`delivery_status`	string	Current status of the delivery (e.g., completed, delayed, incident, cancelled)completed · delayed · incident · cancelled · in_progress	completed
`incident_type`	string	Type of incident encountered during delivery (e.g., vehicle breakdown, traffic accident, theft, none)vehicle_breakdown · traffic_accident · theft · none · other · optional	none
`incident_description`	string	Detailed description of the incident, if any occurredoptional	Truck broke down near end…
`route_type`	string	Type of route taken (urban, suburban, rural)urban · suburban · rural	urban
`start_address_street`	string	Street address where the delivery route started	221 Main St
`start_address_city`	string	City where the delivery route started	San Francisco
`start_address_state`	string	State where the delivery route started	CA
`start_address_postal_code`	string	Postal code for the delivery route start location	94105
`start_address_country`	string	Country for the delivery route start location	USA
`end_address_street`	string	Street address where the delivery route ended (customer location)	17 Market St
`end_address_city`	string	City where the delivery route ended	San Francisco
`end_address_state`	string	State where the delivery route ended	CA
`end_address_postal_code`	string	Postal code for the delivery route end location	94103
`end_address_country`	string	Country for the delivery route end location	USA
`vehicle_type`	string	Type of vehicle used for delivery (e.g., van, bike, truck)van · bike · truck · car · other	van
`weather_condition`	string	Weather condition during delivery (e.g., clear, rain, snow, fog, storm)6 values · optional	clear
`notes`	string	Additional notes or comments about the delivery eventoptional	Routine delivery, no issu…
Numbers 4 columns
`delay_minutes`	integer	Number of minutes the delivery was delayed compared to the scheduled time0 or more · optional	7
`distance_km`	float	Total distance of the delivery route in kilometers0 or more	3.2
`temperature_celsius`	float	Ambient temperature during delivery in degrees Celsiusoptional	19.1
`risk_score`	float	Calculated risk score for the delivery event (0-1 scale, higher means greater risk)0 to 1 · optional	0.11
Dates and times 2 columns
`scheduled_delivery_datetime`	datetime	Planned date and time for delivery completion	2024-06-03T09:15:00Z
`actual_delivery_datetime`	datetime	Actual date and time when delivery was completedoptional	2024-06-03T09:22:00Z

Use it for

A logistics dashboard
Distance_km by route_type and a breakdown of start_address_state. Excel, Power BI or Tableau.
Why do the 24 rural rows have a mean distance_km of 69.7?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Deliveries120
DEL10013.2urban
DEL10024.7urban
DEL10038.5urban
A software demo
Believable deliveries with order_id, vehicle_id and driver_id to fill a screen in front of a buyer.

This dataset120 rows27 columns

Yours1,000 rows27 columnsstart_address_street: UK only

blueprint · e-commerce-last-mile-delivery-risks

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 27 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

Each row represents a unique delivery attempt for a specific order.
Include key risk signals: weather disruption, traffic congestion level, driver incident report, and vehicle sensor alert.
Capture delivery time deviation (minutes early/late) compared to scheduled window.
If a vehicle sensor alert is present, set risk score to high regardless of other signals.
Urban deliveries must have at least one potential risk flag in 60% of cases to reflect increased complexity.

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

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: e-commerce-last-mile-delivery-risks

What should your data show?

No signup. No card.

Sample rows

What the 120 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?