Logistics & TransportComplex automationSeveral jobs working together: multi-stage pipelines with state, branching on rules or AI decisions, approvals or escalations, 4+ systems, AI agents that act, or reconciliation across sources. Usually rolled out in stages.

A 7 AM fleet digest of yesterday's trips, costs and delays

For: Regional distribution fleet with 18 trucks

Typical impact

≈5 hrs/week of reporting removed

By 7 AM the automation combines yesterday's jobs from the TMS, GPS kilometers and idle time, and fuel card transactions into a one-page email digest with on-time rate, empty kilometers, fuel use and revenue per truck, plus the trucks that missed a target.

Typical results

7 AM

Digest in the owner's inbox every working day

4 KPIs

On-time, empty km, fuel use and revenue per truck

≈30%

Less idling once trucks are flagged daily

Figures reflect typical results for this kind of automation.

The challenge

An 18-truck fleet keeps its numbers in three places: jobs in the TMS, kilometers and idling in GPS tracking, and fuel on the fuel card portal. Pulling them together takes the operations manager most of a Monday, so problems such as a truck idling for hours or running empty show up a week late.

Before and after

Before With the automation

Hours per week compiling fleet reports

−91%
5.5 hrs
0.5 hrs

Days until a fuel or idling problem is noticed

−86%
7 days
1 days

Average idle minutes per truck per day

−30%
100 min
70 min

The automation

At 6 AM a Make scenario pulls yesterday's completed jobs from the TMS, kilometers and idle time from GPS, and fuel card transactions. It matches them per truck and calculates on-time delivery rate, empty kilometers, fuel per 100 km and revenue per truck. At 7 AM the owner and operations manager get a one-page email digest and a Google Sheets dashboard is refreshed. Trucks missing a target, such as more than 90 minutes of idling, are listed with their route.

How it works

  1. 01

    Data pulled at 6 AM

    The automation collects yesterday's completed jobs from the TMS, kilometers and idle time from GPS, and fuel card transactions.

  2. 02

    Matched per truck

    Jobs, trips and fuel purchases are matched to each truck by plate number and date.

  3. 03

    KPIs calculated

    On-time delivery rate, empty kilometers, fuel per 100 km and revenue per truck are worked out for the day and the month to date.

  4. 04

    Digest sent at 7 AM

    The owner and operations manager get a one-page email, and the Google Sheets dashboard is refreshed with the same numbers.

  5. 05

    Exceptions listed

    Trucks that miss a target, such as more than 90 minutes of idling, are listed with the route they ran that day.

Starts from

  • Completed jobs from the TMS
  • GPS km and idle time
  • Fuel card transactions

Delivers

  • One-page digest at 7 AM
  • Sheets dashboard refreshed
  • Trucks missing targets

The impact

Managers start the day knowing how yesterday went. About 5 hours a week of report building disappears, and problems surface the next morning instead of a week later. Once idling is visible daily, it typically falls by around 30%, from about 100 minutes per truck a day to 70.

Questions about this automation

What if a truck's fuel or GPS data is missing for the day?

The digest still goes out, with a short note on which truck or source had no data and the affected figures left blank. Fuel transactions that can't be matched to a plate, such as a card used in a different truck, are listed separately so the office can assign them.

Can we change the targets or add our own KPIs?

Targets live in a settings tab in Google Sheets, so the idle limit, the fuel per 100 km threshold or the on-time goal can be changed without touching the automation. Extra measures, such as cost per stop or tolls per route, can be added when the source data is available.

Which data sources does the fleet need to open up?

Read access or scheduled exports from the TMS, the GPS platform and the fuel card provider, plus a list linking plates, fuel cards and trucks. The daily digest comes first, followed by the dashboard and the exception rules, since this is a multi-step build, usually rolled out in stages.

Logistics & Transport

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