Logistics Delivery Delay Causes

This dataset provides detailed records of logistics shipments, including origin and destination addresses, scheduled and actual delivery dates, and comprehensive information on the causes and duration of delivery delays. It enables in-depth analysis of delay patterns, supports predictive analytics for on-time delivery, and helps optimize logistics operations and route planning.

  • opened 8 times
  • last updated 12 Jul 2025
  • by GoMask
The brief that made it

Predictive modeling of delivery delays

Sample rows

preview · 8 of 200 rows · all 25 columns
shipment_idstringshipment_typestringshipment_volume_m3floatis_delayedbooleanorigin_countrystringorigin_street_addressstringorigin_citystringorigin_statestringorigin_postal_codestringdestination_street_addressstringdestination_citystringdestination_statestringdestination_postal_codestringdestination_countrystringscheduled_pickup_datedateactual_pickup_datedateexpected_delivery_datedateactual_delivery_datedatedelay_duration_daysintegerdelay_causesstringprimary_delay_causestringcarrier_namestringshipment_weight_kgfloatroute_idstringvehicle_typestring
SHP00001parcel0.13falseUSA1423 Maple AveChicagoIL60616218 Oak StreetDallasTX75201USA2023-01-152023-01-152023-01-182023-01-180blankblankFastTrack Logistics18.2RT101truck
SHP00002container14.2trueFrance60 Rue de RivoliParisÎle-de-France7500190 WilhelmstrasseBerlinBerlin10117Germany2023-02-102023-02-112023-02-182023-02-224customs,weathercustomsEuroWay Freight4230EU209rail
SHP00003parcel0.21falseUSA80 Market StreetSan FranciscoCA941054400 W 45th AveDenverCO80212USA2023-03-182023-03-192023-03-222023-03-220blankblankSummit Express26.4RT112van
SHP00004pallet1.17falseCanada190 Bay StreetTorontoONM5J2T62400 Rue SherbrookeMontrealQCH3H1G9Canada2023-04-012023-04-022023-04-042023-04-040blankblankMapleLeaf Transport168.2CA042truck
SHP00005pallet0.98trueAustralia101 Elizabeth StSydneyNSW200033 Collins StMelbourneVIC3000Australia2023-02-252023-02-252023-02-282023-03-011traffic,staffingtrafficDownUnder Logistics117.8AU302van
SHP00006pallet0.41trueUSA2400 Main StreetLos AngelesCA900077890 BroadwaySeattleWA98101USA2023-03-052023-03-052023-03-092023-03-112weather,trafficweatherPacific Haulage52.7RT234truck
SHP00007container12.8trueSingapore21 Changi AveSingaporeCentral4860419 Jalan RajaKuala LumpurWP Kuala Lumpur50450Malaysia2023-04-072023-04-082023-04-162023-04-204customs,staffingcustomsStraits Freight3870.5SEA15rail
SHP00008document0.0009falseUK10 Baker StreetLondonGreater LondonNW1 6XE5 O'Connell StDublinLeinsterD01T2A4Ireland2023-03-292023-03-302023-04-032023-04-030blankblankTransAtlantic Express0.02UKIE9air

What the 200 rows show

from the 200-row sample

Container (shipment type) stands out: mean shipment_volume_m3 is 22.6, against 0.39 for the rest.

  • 46%is_delayed = true
  • 0.28median shipment_volume_m3
  • 5primary delay causes
  • 6vehicle types
  • 21delay causeses
  • 33destination countries
Mean shipment_volume_m3 by shipment_type199 rows
020400.15parcel66 rows0.93pallet50 rows22.6contai…31 rows0.00docume…35 rows0.54other17 rows
shipment_volume_m3199 rows, in bands of 10
09018017883612104070shipment_volume_m3 →

Median 0.28, from 0.00 to 65.0.

origin_country199 rows with a value · 1 left blank
  1. USA68
  2. Canada18
  3. France12
  4. UK12
  5. Singapore11
  6. Switzerland11
  7. South Africa9
  8. Australia7
  9. Brazil6
  10. UAE6
25 columns by typefrom the column list below
  • string 17
  • integer 1
  • float 2
  • date 4
  • boolean 1

Columns

25 columns in four groups
blueprint · 25 columns
columntypedescriptionexample
Text 17 columns
shipment_idstringUnique identifier for each shipment.uniqueSHP00001
origin_street_addressstringStreet address where the shipment originated.1423 Maple Ave
origin_citystringCity where the shipment originated.Chicago
origin_statestringState or region where the shipment originated.IL
origin_postal_codestringPostal code of the origin location.60616
origin_countrystringCountry where the shipment originated.USA
destination_street_addressstringStreet address where the shipment is to be delivered.218 Oak Street
destination_citystringCity where the shipment is to be delivered.Dallas
destination_statestringState or region where the shipment is to be delivered.TX
destination_postal_codestringPostal code of the destination location.75201
destination_countrystringCountry where the shipment is to be delivered.USA
delay_causesstringComma-separated list of primary causes for the delivery delay (e.g., weather, traffic, customs, vehicle breakdown, staffing).optionalcustoms,weather
primary_delay_causestringThe main cause of delay for the shipment.5 causes · optionalcustoms
carrier_namestringName of the carrier or logistics provider handling the shipment.FastTrack Logistics
shipment_typestringType of shipment (e.g., parcel, pallet, container, document).parcel · pallet · container · document · other · optionalparcel
route_idstringIdentifier for the route taken by the shipment.optionalRT101
vehicle_typestringType of vehicle used for the shipment (e.g., truck, van, air, rail, ship).6 values · optionaltruck
Numbers 3 columns
delay_duration_daysintegerNumber of days the delivery was delayed (0 if on time or early).0 or more0
shipment_weight_kgfloatTotal weight of the shipment in kilograms.0 or more · optional18.2
shipment_volume_m3floatTotal volume of the shipment in cubic meters.0 or more · optional0.13
Dates and times 4 columns
scheduled_pickup_datedateDate when the shipment was scheduled for pickup.2023-01-15
actual_pickup_datedateDate when the shipment was actually picked up.optional2023-01-15
expected_delivery_datedateDate when the shipment was expected to be delivered.2023-01-18
actual_delivery_datedateDate when the shipment was actually delivered.optional2023-01-18
True or false 1 column
is_delayedbooleanIndicates if the delivery was delayed (true) or on time (false).false

Use it for

  • is delayed46%92 of 199 rowsmean shipment volume …0.15parc…0.93pall…22.6cont…0.00docu…

    A logistics dashboard

    The is_delayed rate, shipment_volume_m3 by shipment_type and a breakdown of origin_country. Excel, Power BI or Tableau.

  • Why do the 31 container rows have a mean shipment_volume_m3 of 22.6?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable shipments with origin_street_address, origin_city and origin_state to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 25 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows25 columns
Yours1,000 rows25 columnsorigin_street_address: UK only

blueprint · logistics-delivery-delay-causes

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
  • List shipment IDs with origin/destination pairs
  • Include weather, route, and carrier info
  • Categorize causes: traffic, weather, logistics, etc.
  • Label delayed vs. on-time
Rows
Open the blueprint in Data Factory

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

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