Route optimisation is working out which vehicle or field team visits which stops, and in what order, so that total distance, time or cost is as low as possible while respecting constraints such as vehicle capacity, delivery time windows and driver shifts. Unlike manual planning, it can compare far more options than a person could try one by one as stops and constraints grow.
The 7 a.m. planning scramble
In a business that runs deliveries, the first hour of the day often looks the same. The dispatcher pulls orders from the ERP, splits them into areas based on experience and hands drivers a list by phone or on paper. During the day an urgent order arrives, a customer asks for an afternoon slot, a van breaks down, and the plan is rebuilt through a flurry of phone calls. By evening some vehicles have come back half empty and some customers did not get their delivery in the promised window.
Field service teams see the same picture. Technicians head out to breakdowns, maintenance visits and installations, and which job goes to whom, in what order, often lives in one person's head. When that person is on leave, planning falters and productivity can drop. We cover work orders and technician management end to end in our field service management guide; this article focuses on the routing side of that system. In water utilities, repair crews are routed from the map where pipes and valves are held in a water network GIS inventory.
The real problem with manual planning is not that it is wrong but that it does not scale. With ten stops an experienced planner will find a good sequence. As stops, vehicles and constraints multiply, the number of possible combinations explodes, and even the best planner ends up choosing something reasonable rather than something optimal.
What unplanned routes cost
Almost all domestic freight in Türkiye moves by road:
According to the Ministry of Environment, Urbanisation and Climate Change Environmental Indicators, road accounted for 90.6% of domestic freight transport in Türkiye in 2023.
That means every inefficiency in fuel, driver hours and vehicle wear goes straight to cost. The most visible form of inefficiency is running empty. According to Eurostat's "Road freight transport by journey characteristics" report, more than one fifth (21.8%) of the distance travelled by road freight vehicles in the EU in 2025 was driven empty. That figure is for the EU, but it would be no surprise to find a similar gap in fleets that do not plan return loads and stop sequences.
Tracking cost per vehicle, fuel and maintenance in one record is covered in our fleet management system guide.
Part of the cost lands on the customer side. Missed delivery windows, repeat visits, cancelled orders and "where is my van?" calls to customer service rarely appear as a separate line in the accounts, yet they happen every day. In the cold chain, a delay means lost product; we look at how temperature monitoring ties into routing in reefer truck temperature monitoring.
Another way to cut cost is to see the load coming. For farm produce, haulage from field to factory can be planned weeks ahead using pre-harvest data such as drone crop yield estimation, so vehicle and trip numbers are not left to the last day.
There is a hidden cost in the warehouse too. When the route is settled late, loading slips to the last minute, and parcels loaded in the wrong order mean unloading and reloading at every stop. Letting the route plan set the loading sequence, and passing that to your warehouse management system (WMS), shortens both morning loading and time spent at each stop.
Which constraints does route optimisation handle?
Academics call this the "vehicle routing problem". In real life, what makes it hard is not distance but constraints. Good route optimisation weighs all of these at once:
- Vehicle capacity: weight, volume, pallet count; sometimes chilled and ambient compartments separately.
- Time windows: "deliver between 09:00 and 12:00", "closed over lunch", "weekdays only".
- Driver and crew constraints: shift start, breaks, overtime limits; for field teams, skills such as electrical, mechanical or a particular equipment brand.
- Vehicle and road constraints: city-centre zones closed to lorries, weight limits, bridge heights.
- Priority and service time: urgent breakdowns, contract customers, the expected time spent at each stop.
- Start and end points: a single depot, several depots, or crews who start from home.
In Türkiye, as in the EU, commercial drivers' driving and rest times are limited by regulation and recorded by tachograph. If those limits are not entered as constraints, the "best" route on paper may be one that cannot legally be driven.
Static versus dynamic routing
| Approach | How it works | Where it fits | Weak spot |
|---|---|---|---|
| Manual planning | A planner sequences stops from experience | Few stops, regular customers | Does not scale, depends on one person |
| Static optimisation | Calculated once each morning | Deliveries known in advance | Blind to changes during the day |
| Dynamic optimisation | Recalculated for new orders, traffic and delays | Field service, urgent jobs, couriers | Needs live data and a mobile app |
For most businesses the right starting point is static optimisation. Dynamic routing makes sense once live location and job status start flowing in from vehicles and crews; we explain how that data should flow in real-time reporting.
Moving to route optimisation in six steps
- Clean your addresses and geocode them. Routing software can be no better than your address data. Incomplete, duplicated or misspelt customer addresses cannot be turned into coordinates. Do this alongside a clean-up of data quality and duplicate records.
- Write the constraints down. List the rules that live in the planner's head: which customers want mornings, which vehicles cannot enter which areas, which technicians can do which jobs.
- Choose what you are optimising. Total kilometres, total time, number of vehicles or on-time delivery rate? The goals can conflict, so management must set the priority. Pick metrics using the approach in how to set KPIs.
- Pilot in one area. For a depot or a region, compare the optimised plan with the current one over a few weeks. Measure kilometres, time per stop and on-time delivery.
- Give drivers and technicians a mobile app. The route should land on their phone, and proof of delivery, photos, signatures and job outcomes should be recorded from the field at once. Otherwise nobody can see the gap between plan and reality.
- Feed the results back. Actual stop times, delays and cancellations should become inputs to the next plan. Businesses that want to see order volumes ahead can also size vehicles and crews with AI demand forecasting.
How to measure success
The value of route optimisation shows when you compare the same metrics before and after the pilot. The most useful are:
- Kilometres per delivery or job: total kilometres move with order volume, so look per stop.
- On-time delivery rate: the share of deliveries made inside the promised window, the metric customers feel most directly.
- Vehicle fill and empty running: how much of each vehicle's capacity is used and how much of the return leg is driven empty.
- Plan adherence: how closely drivers follow the suggested sequence. Low adherence usually means the plan does not reflect reality on the ground.
- Planning time: how long the dispatcher spends on the plan each morning. As it falls, the planner has time to deal with exceptions.
Tracking these daily on a management dashboard lets everyone judge the pilot's result from the same figures.
Location data and KVKK
Vehicle and employee location becomes personal data once it is linked to a person. Under KVKK, Türkiye's personal data protection law (Law No. 6698, broadly comparable to the GDPR), processing must rest on one of the legal grounds set out in the law, employees must be told through a privacy notice why the data is processed, the data must be limited to that purpose, and it must be erased, destroyed or anonymised when the retention period ends. Not collecting location outside working hours and restricting access by role is a good start, and it is sensible to have your legal adviser review the details.
How we do this at Digital Bridge
We build route optimisation as a workflow that runs from order to proof of delivery, not as a map screen on its own:
- Discovery and requirements analysis. We review your current planning process, order sources, vehicle and crew set-up and the planner's rules on site, then write the constraint list and success metrics with you. Needs specific to logistics firms are summarised on our logistics and transport solutions page.
- Map and address foundations. We clean customer addresses, geocode them, and define zones and road constraints in a geographic information systems (GIS) layer. For an example of managing spatial data, see our GIS for municipalities guide.
- Integration. We take orders from the ERP and stock and loading data from your warehouse management system, and turn the plan into work orders. For field crews we connect this flow to field service management.
- Mobile app and pilot. We build a mobile app for drivers and technicians and start with a pilot in one area. Reporting pilot results side by side with the current plan ties the roll-out decision to evidence.
Delivery paperwork matters as much as the route. When delivery notes, proof-of-delivery photos and customer correspondence are scattered, nothing can be found when a dispute arises. With SmartFiles, part of our own Smart360 product family, these documents can be kept in department or project areas with version history. For fake emails targeting payment instructions in logistics, see our article on logistics email fraud.
Your next step
Start by pulling last week's actual trips: kilometres per vehicle, number of stops, on-time delivery rate and empty returns. That table shows where optimisation will make a difference. Send it to us through our contact page; we will review your current plan with you and propose the pilot area and scope in writing. More data and analytics guides are on our Data & Analytics hub.