Supply Chain Route Efficiency Data

This dataset provides granular, route-level supply chain logistics data including origin and destination details, shipment characteristics, timing, cost, carrier information, and efficiency metrics. It is designed for advanced analytics and machine learning applications to optimize route planning, reduce costs, and improve sustainability in logistics operations.

  • last updated 21 Aug 2025
  • by GoMask
The brief that made it

Machine learning-based route optimization and cost reduction

Sample rows

preview · 8 of 200 rows · all 34 columns
route_idstringtransport_modestringactual_travel_time_hoursfloatdelay_flagbooleandelay_reasonstringorigin_facility_idstringorigin_facility_namestringorigin_street_addressstringorigin_citystringorigin_statestringorigin_postal_codestringorigin_countrystringdestination_facility_idstringdestination_facility_namestringdestination_street_addressstringdestination_citystringdestination_statestringdestination_postal_codestringdestination_countrystringshipment_idstringshipment_typestringshipment_weight_kgfloatshipment_volume_m3floatdeparture_datetimedatetimearrival_datetimedatetimeactual_route_distance_kmfloatplanned_route_distance_kmfloatplanned_travel_time_hoursfloatcarrier_idstringcarrier_namestringtotal_route_cost_usdfloatfuel_consumption_litersfloatemissions_co2_kgfloatroute_efficiency_scorefloat
R0001truck18.67trueweatherF0035Midwest Distribution Center1200 Supply DrChicagoIL60609USAF0022East Coast Fulfillment Hub890 Atlantic AveNew YorkNY10003USAS0001apparel1540.259.22023-03-02T08:30:002023-03-03T03:10:001270.6125517.5CAR001TransLogix USA3120.5420.31050.70.85
R0002sea363.5trueport congestionF0042Pacific Freight Terminal981 Harbor WayLos AngelesCA90021USAF0087Shanghai Import Hub120 Pujiang RdShanghaiShanghai200030ChinaS0002electronics8200.549.82023-03-04T15:00:002023-03-19T17:30:009650.29500354CAR007Oceanic Freightways15200.7586504300.90.69
R0003rail14.33truemechanical issueF0018Toronto Storage Hub22 Queen St WTorontoONM5H 2N2CanadaF0053Montreal Distribution3010 Rue SherbrookeMontrealQCH3G 1G6CanadaS0003apparel320014.82023-03-05T06:50:002023-03-05T21:10:00541.754014CAR011NorthRail Logistics1350.6121.2410.30.74
R0004truck15.83truetrafficF0073Dallas Perishables Depot3000 Market StDallasTX75202USAF0094Mexico City Main Hub500 Av. ReformaMexico CityCDMX06600MexicoS0004perishables1200.86.92023-03-07T05:10:002023-03-07T21:00:001502.5150015.6CAR002FastFresh Logistics2750.9345.1900.60.81
R0005sea33.5truemechanical issueF0060Rotterdam Marine Terminal100 Maas LnRotterdamZH3011AANetherlandsF0102London Gateway Center230 Dock RdLondonENGE16 2LXUKS0005electronics5900.738.12023-03-08T11:00:002023-03-09T20:30:001061.5105533CAR008EuroMarine4350.65510.213300.77
R0006air9.67trueweatherF0057Berlin Express Warehouse44 Spree StBerlinBE10115GermanyF0039Dubai Air Cargo Hub12 Sheikh Zayed RdDubaiDU00000UAES0006electronics11807.52023-03-09T08:00:002023-03-09T17:40:004260.842509CAR014GlobalAero8450128.6230.90.68
R0007sea63.33trueport congestionF0030Senegal Export Terminal80 Route de DakarDakarDK11000SenegalF0028Morocco Import Center22 Casablanca RdCasablancaCS20100MoroccoS0007perishables10200.955.22023-03-10T19:40:002023-03-13T11:00:002273.4225060CAR009AfricaLines5150.8850.71840.20.61
R0008truck13.83trueaccidentF0069Central Distribution Hub700 Commerce BlvdMinneapolisMN55413USAF0047Denver Retail Outlet1800 Colfax AveDenverCO80202USAS0008apparel2300.613.32023-03-11T07:20:002023-03-11T21:10:001132.4113013CAR001TransLogix USA2560390.9990.80.79

What the 200 rows show

from the 200-row sample

Sea (transport mode) stands out: mean actual_travel_time_hours is 215.2, against 13.5 for the rest.

  • 85%delay_flag = true
  • 15.9median actual_travel_time_hours
  • 4shipment types
  • 11carrier names
  • 18origin countries
  • 22destination countries
Mean actual_travel_time_hours by transport_mode200 rows
020040010.9truck57 rows23.8rail30 rows9.3air40 rows215.2sea71 rows13.9multim…2 rows
actual_travel_time_hours200 rows, in bands of 50
0701401311199814990200400actual_travel_time_hours →

Median 15.9, from 4.0 to 364.5.

delay_reason169 rows with a value · 31 left blank
  1. weather34
  2. mechanical issue27
  3. port congestion25
  4. Weather15
  5. traffic12
  6. Port congestion9
  7. holiday closure8
  8. customs6
  9. customs delay6
  10. Mechanical issue5
34 columns by typefrom the column list below
  • string 21
  • float 10
  • datetime 2
  • boolean 1

Columns

34 columns in four groups
blueprint · 34 columns
columntypedescriptionexample
Text 21 columns
route_idstringUnique identifier for each supply chain route instanceuniqueR0001
origin_facility_idstringUnique identifier for the origin facility or warehouseF0035
origin_facility_namestringName of the origin facility or warehousePacific Freight Terminal
origin_street_addressstringStreet address of the origin facility1200 Supply Dr
origin_citystringCity of the origin facilityChicago
origin_statestringState or region of the origin facilityIL
origin_postal_codestringPostal code of the origin facility60609
origin_countrystringCountry of the origin facilityUSA
destination_facility_idstringUnique identifier for the destination facility or warehouseF0022
destination_facility_namestringName of the destination facility or warehouseShanghai Import Hub
destination_street_addressstringStreet address of the destination facility890 Atlantic Ave
destination_citystringCity of the destination facilityNew York
destination_statestringState or region of the destination facilityNY
destination_postal_codestringPostal code of the destination facility10003
destination_countrystringCountry of the destination facilityUSA
shipment_idstringUnique identifier for the shipment carried on this routeS0001
shipment_typestringType of goods or cargo being shipped (e.g., electronics, apparel, perishables)4 typesapparel
transport_modestringPrimary mode of transport used (e.g., truck, rail, air, sea)truck · rail · air · sea · multimodaltruck
carrier_idstringUnique identifier for the carrier or logistics providerCAR001
carrier_namestringName of the carrier or logistics provider11 namesTransLogix USA
delay_reasonstringReason for delay, if any (e.g., weather, traffic, mechanical issue)optionalweather
Numbers 10 columns
shipment_weight_kgfloatTotal weight of the shipment in kilograms0 or more1540.25
shipment_volume_m3floatTotal volume of the shipment in cubic meters0 or more · optional9.2
actual_route_distance_kmfloatActual distance traveled on the route in kilometers0 or more1270.6
planned_route_distance_kmfloatPlanned distance for the route in kilometers0 or more · optional1255
actual_travel_time_hoursfloatActual time taken for the route in hours0 or more18.67
planned_travel_time_hoursfloatPlanned time for the route in hours0 or more · optional17.5
total_route_cost_usdfloatTotal cost incurred for the route in US dollars0 or more3120.5
fuel_consumption_litersfloatTotal fuel consumed during the route in liters0 or more · optional420.3
emissions_co2_kgfloatTotal CO2 emissions generated by the route in kilograms0 or more · optional1050.7
route_efficiency_scorefloatCalculated efficiency score for the route (0-1, higher is better)0 to 1 · optional0.85
Dates and times 2 columns
departure_datetimedatetimeDate and time when the shipment departs from the origin facility2023-03-02T08:30:00
arrival_datetimedatetimeDate and time when the shipment arrives at the destination facility2023-03-03T03:10:00
True or false 1 column
delay_flagbooleanIndicates if the shipment was delayed compared to planned arrivaltrue

Use it for

  • delay flag85%169 of 200 rowsmean actual travel ti…10.9truck23.8rail9.3air215.2sea

    A logistics dashboard

    The delay_flag rate, actual_travel_time_hours by transport_mode and a breakdown of delay_reason. Excel, Power BI or Tableau.

  • Why do the 71 sea rows have a mean actual_travel_time_hours of 215.2?

    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 routes with origin_facility_id, origin_facility_name and origin_street_address to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 34 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows34 columns
Yours1,000 rows34 columnsorigin_street_address: UK only

blueprint · supply-chain-route-efficiency-data

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 34 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 captures route ID, transport type, and time
  • Include cost, distance, and delay metrics
  • Exclude routes with cancellations
  • Group by origin-destination pairs
  • Aggregate seasonal effects
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
supply-chain-route-efficiency-data

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