Last-Mile Delivery Route Efficiency
This dataset provides granular, route-level metrics for last-mile delivery operations, including planned and actual timings, stop-level performance, delay analysis, and contextual factors such as region and weather. It enables logistics companies to benchmark route efficiency, identify bottlenecks, and optimize delivery processes for improved customer satisfaction and operational cost savings.
Sample rows
preview · 8 of 200 rows · all 21 columns| route_idstring | weather_conditionsstring | route_efficiency_scorefloat | regionstring | delivery_datedate | vehicle_idstring | driver_idstring | planned_start_timedatetime | actual_start_timedatetime | planned_end_timedatetime | actual_end_timedatetime | total_stopsinteger | completed_stopsinteger | delayed_stopsinteger | total_distance_kmfloat | planned_duration_minutesinteger | actual_duration_minutesinteger | average_stop_time_minutesfloat | total_delay_minutesinteger | on_time_delivery_ratefloat | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| R1001 | clear | 0.89 | Central City | 2024-06-01 | V-101 | D-201 | 2024-06-01T07:30:00 | 2024-06-01T07:32:00 | 2024-06-01T11:30:00 | 2024-06-01T11:45:00 | 12 | 12 | 1 | 39.5 | 240 | 253 | 21.1 | 15 | 91.67 | Minor paperwork delay at stop 8. |
| R1002 | windy | 0.96 | Downtown | 2024-06-02 | V-102 | D-202 | 2024-06-02T06:45:00 | 2024-06-02T07:00:00 | 2024-06-02T10:25:00 | 2024-06-02T10:35:00 | 8 | 8 | 0 | 27.4 | 220 | 230 | 28.8 | 10 | 100 | Efficient loading, all stops completed early. |
| R1003 | rainy | 0.41 | East Industrial | 2024-06-03 | V-103 | D-203 | 2024-06-03T08:00:00 | 2024-06-03T08:20:00 | 2024-06-03T11:40:00 | 2024-06-03T12:10:00 | 9 | 8 | 5 | 31.6 | 220 | 250 | 27.7 | 30 | 37.5 | Heavy rain caused delays at stops 3-7. |
| R1004 | clear | 0.81 | West Suburbs | 2024-05-31 | V-104 | D-204 | 2024-05-31T07:00:00 | 2024-05-31T07:05:00 | 2024-05-31T12:00:00 | 2024-05-31T12:03:00 | 15 | 15 | 2 | 56.2 | 300 | 303 | 20.2 | 3 | 86.67 | Efficient route, minor delays at stops 4 and 12. |
| R1005 | foggy | 0.19 | Periphery | 2024-06-04 | V-105 | D-205 | 2024-06-04T05:50:00 | 2024-06-04T06:00:00 | 2024-06-04T09:10:00 | 2024-06-04T09:50:00 | 7 | 6 | 6 | 18.1 | 200 | 240 | 40 | 40 | 0 | Dense fog resulted in delayed stops and one missed. |
| R1006 | rainy | 0.32 | Airport Zone | 2024-06-05 | V-106 | D-206 | 2024-06-05T08:20:00 | 2024-06-05T08:30:00 | 2024-06-05T10:30:00 | 2024-06-05T10:40:00 | 6 | 5 | 3 | 16.9 | 130 | 140 | 28 | 10 | 40 | Customs checks caused delays. |
| R1007 | clear | 0.98 | South Rural | 2024-05-28 | V-107 | D-207 | 2024-05-28T09:00:00 | 2024-05-28T09:00:00 | 2024-05-28T13:45:00 | 2024-05-28T13:49:00 | 20 | 20 | 1 | 122.8 | 285 | 289 | 14.5 | 4 | 95 | Record efficiency, marathon route. |
| R1008 | rainy | 0.18 | East Industrial | 2024-06-06 | V-108 | D-208 | 2024-06-06T07:10:00 | 2024-06-06T07:30:00 | 2024-06-06T11:50:00 | 2024-06-06T12:20:00 | 10 | 9 | 7 | 21.5 | 280 | 310 | 34.4 | 30 | 22.22 | Traffic jams due to heavy rain. |
| R1009 | clear | 0.91 | Central City | 2024-06-07 | V-109 | D-209 | 2024-06-07T06:50:00 | 2024-06-07T07:00:00 | 2024-06-07T10:10:00 | 2024-06-07T10:15:00 | 13 | 13 | 2 | 45.7 | 200 | 205 | 15.8 | 5 | 84.62 | Minor delay due to paperwork. |
| R1010 | windy | 0.29 | Airport Zone | 2024-06-08 | V-110 | D-210 | 2024-06-08T08:00:00 | 2024-06-08T08:10:00 | 2024-06-08T10:20:00 | 2024-06-08T10:25:00 | 5 | 4 | 2 | 19.3 | 140 | 145 | 36.3 | 5 | 50 | Windy conditions caused minor delays. |
| R1011 | clear | 0.95 | Downtown | 2024-06-09 | V-111 | D-211 | 2024-06-09T09:40:00 | 2024-06-09T09:45:00 | 2024-06-09T10:40:00 | 2024-06-09T10:50:00 | 1 | 1 | 0 | 2 | 60 | 70 | 70 | 10 | 100 | VIP client ceremonial delivery. |
| R1012 | foggy | 0.11 | East Industrial | 2024-06-10 | V-112 | D-212 | 2024-06-10T10:00:00 | 2024-06-10T10:20:00 | 2024-06-10T12:00:00 | 2024-06-10T12:35:00 | 9 | 7 | 7 | 28.5 | 120 | 155 | 22.1 | 35 | 0 | Low visibility, multiple stops missed. |
| R1013 | clear | 1 | North City | 2024-06-11 | V-113 | D-213 | 2024-06-11T06:00:00 | 2024-06-11T06:00:00 | 2024-06-11T10:00:00 | 2024-06-11T09:50:00 | 14 | 14 | 0 | 49.8 | 240 | 230 | 16.4 | 0 | 100 | Early finish, all stops on time. |
| R1014 | windy | 0.78 | Central City | 2024-06-12 | V-114 | D-214 | 2024-06-12T07:15:00 | 2024-06-12T07:18:00 | 2024-06-12T10:45:00 | 2024-06-12T10:55:00 | 8 | 8 | 2 | 25.7 | 210 | 220 | 27.5 | 10 | 75 | Wind caused minor delays at stops 1 and 6. |
| R1015 | clear | 1 | Downtown | 2024-06-13 | V-115 | D-215 | 2024-06-13T09:30:00 | 2024-06-13T09:30:00 | 2024-06-13T10:45:00 | 2024-06-13T10:44:00 | 1 | 1 | 0 | 1.1 | 75 | 74 | 74 | 0 | 100 | Special event delivery. |
| R1016 | clear | 0.85 | Central City | 2024-06-14 | V-116 | D-216 | 2024-06-14T08:40:00 | 2024-06-14T08:42:00 | 2024-06-14T12:00:00 | 2024-06-14T12:20:00 | 10 | 10 | 2 | 32.4 | 200 | 220 | 22 | 20 | 80 | Efficient route, minor delays at stops 3 and 7. |
| R1017 | rainy | 0.22 | Periphery | 2024-06-15 | V-117 | D-217 | 2024-06-15T07:00:00 | 2024-06-15T07:15:00 | 2024-06-15T09:45:00 | 2024-06-15T10:10:00 | 5 | 4 | 3 | 15.5 | 165 | 190 | 47.5 | 25 | 25 | Flooding caused delays and one missed stop. |
| R1018 | clear | 0.96 | South Rural | 2024-06-01 | V-118 | D-218 | 2024-06-01T06:30:00 | 2024-06-01T06:35:00 | 2024-06-01T11:00:00 | 2024-06-01T11:09:00 | 18 | 18 | 0 | 67.2 | 270 | 279 | 15.5 | 9 | 100 | All stops completed on time. |
| R1019 | rainy | 0.28 | Airport Zone | 2024-06-02 | V-119 | D-219 | 2024-06-02T09:20:00 | 2024-06-02T09:29:00 | 2024-06-02T10:40:00 | 2024-06-02T10:53:00 | 7 | 6 | 4 | 14.6 | 80 | 93 | 15.5 | 13 | 33.33 | Late start, customs delay. |
| R1020 | windy | 0.77 | Central City | 2024-06-03 | V-120 | D-220 | 2024-06-03T08:00:00 | 2024-06-03T08:10:00 | 2024-06-03T11:00:00 | 2024-06-03T11:20:00 | 11 | 11 | 3 | 36.9 | 180 | 200 | 18.2 | 20 | 72.73 | Windy conditions caused delays at stops 2, 6, and 8. |
What the 200 rows show
from the 200-row sampleClear (weather conditions) stands out: mean route_
- 0.78median route_
efficiency_ score - 9median total_
stops - 8median completed_
stops - 2median delayed_
stops - 22.8median total_
distance_ km - 180median planned_
duration_ minutes
Median 0.78, from 0.0 to 1.0.
- string 6
- integer 6
- float 4
- date 1
- datetime 4
Columns
21 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 6 columns | |||
route_id | string | Unique identifier for each delivery routeunique | R1001 |
vehicle_id | string | Unique identifier for the delivery vehicle assigned to the route | V-101 |
driver_id | string | Unique identifier for the driver assigned to the route | D-201 |
region | string | Geographical region or zone covered by the route9 regions | Central City |
weather_conditions | string | Weather conditions during the route (e.g., clear, rainy, snowy)6 values · optional | clear |
notes | string | Additional notes or comments about the routeoptional | Special event delivery. |
| Numbers 10 columns | |||
total_stops | integer | Total number of delivery stops on the route1 or more | 12 |
completed_stops | integer | Number of stops successfully completed0 or more | 12 |
delayed_stops | integer | Number of stops that experienced delays beyond scheduled time0 or more | 1 |
total_distance_km | float | Total distance covered by the route in kilometers0 or more | 39.5 |
planned_duration_minutes | integer | Planned duration for the route in minutes1 or more | 240 |
actual_duration_minutes | integer | Actual duration taken for the route in minutes1 or more | 253 |
average_stop_time_minutes | float | Average time spent at each stop in minutes0 or more | 21.1 |
total_delay_minutes | integer | Total delay experienced on the route in minutes0 or more | 15 |
on_time_delivery_rate | float | Percentage of stops delivered on or before scheduled time (0-100)0 to 100 | 91.67 |
route_efficiency_score | float | Calculated efficiency score for the route (0-1 scale)0 to 1 | 0.89 |
| Dates and times 5 columns | |||
delivery_date | date | Date on which the delivery route was executed | 2024-06-01 |
planned_start_time | datetime | Scheduled start time for the delivery route | 2024-06-01T07:30:00 |
actual_start_time | datetime | Actual start time when the delivery route began | 2024-06-01T07:32:00 |
planned_end_time | datetime | Scheduled completion time for the delivery route | 2024-06-01T11:30:00 |
actual_end_time | datetime | Actual completion time for the delivery route | 2024-06-01T11:45:00 |
Use it for
A logistics dashboard
Route_
efficiency_ score by weather_ conditions and a breakdown of region. Excel, Power BI or Tableau. Why do the 79 clear rows have a mean route_
efficiency_ score of 0.92? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Routes200R10010.89clearR10020.96windyR10030.41rainy
A software demo
Believable routes with delivery_
date, vehicle_ id and driver_ id to fill a screen in front of a buyer.
This dataset200 rows21 columns
Yours1,000 rows21 columnsregion: UK only
blueprint · last-mile-delivery-route-efficiency
Behind this dataset
Same schema. As many rows as you need.
These 200 rows came out of a blueprint — 21 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
- Record route start and end points
- Include delivery timing and traffic data
- Flag delayed deliveries
- Track driver route deviations
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
- last-mile-delivery-route-efficiency