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A pale grey map of Istanbul with a pink route line running through numbered stops.

PRODUCT · ROUTE OPTIMIZATION

Which point, in which order, in which vehicle?

The decision layer that builds a route against distance, time and capacity. For FMCG field teams and logistics distribution: it produces the plan, pushes it to the field and brings back what actually happened.

USE CASES
4
MEASURES
6
TRAVEL MODES
3

01 · THE PROBLEM

Routes get built, but nobody measures them.

The same loss in FMCG field work and in distribution: excess kilometres, missed visits, late deliveries.

01

The route is built from habit

The order follows whatever the representative is used to; nobody computes the alternative.

02

Capacity is not in the plan

Vehicle volume, delivery window and working hours sit outside it.

03

Territories are unbalanced

One representative carries forty points, another eighteen; the workload is never measured.

04

Drift is invisible

The gap between the planned route and the visit that happened is not reported.

Kilometres are the most invisible line in the budget: nobody asks at the planning stage, and everyone sees it at the end of the month on the fuel bill.

02 · THE APPROACH

A route is an output; its input is data.

The optimisation engine reads four layers together and produces a route you can actually run.

A pale grey map of Kartal and Maltepe with a cloud of pale blue sales points; a pink route line follows the road network through them and stops at ring-shaped markers.
The sales points in frame, and the visit order chosen through them.

1

Point data

Sales point, dealer or delivery address, tied to a coordinate and verified.

2

Constraint set

Vehicle capacity, delivery window, working hours, visit frequency.

3

Network and time

Distance and duration over the real road network, traffic profile included.

4

Optimisation engine

Order and assignment produced against a total distance, time and cost target.

Output: a day-by-day visit order for every vehicle and every representative, estimated arrival times, total distance and time — on the map and in a table.

03 · USE CASES

One engine, two different jobs.

A representative's week and a vehicle's day out of the depot come from the same model.

A pale grey map of Küçükçekmece and Bahçelievler with two routes: a pink round spread across a wide area on the left, and a compact navy round leaving a square navy depot marker on the right.
Two rounds on one ground: visits spread across a territory, and a delivery round out of a depot.

FMCG

The representative's day, put in order.

  1. Planned by visit frequency

    Each sales point's frequency — weekly, fortnightly — becomes an input to the plan.

  2. A route per day

    The representative's week becomes a visit list split across days.

  3. Visit duration counts

    Average time spent at a point is included in the route.

  4. Runnable in the field

    The route lands in the mobile app; the representative checks in and runs the survey on site.

LOGISTICS

Every vehicle leaves the depot with its own route.

  1. Vehicle assignment

    Orders are distributed to vehicles by capacity; each vehicle takes its own route.

  2. Delivery window

    The customer's accepted hours enter the model as a constraint.

  3. Multi-depot network

    With more than one depot, an order is tied to the most suitable one.

  4. Return and second run

    The return to depot and a second run within the day are both calculated.

04 · TERRITORY AND DEPOT

Territory before route: balance the workload.

The field is divided into balanced, contiguous territories against the number of representatives and vehicles.

A pale grey map of Kadıköy with three nested drive-time areas around a square depot marker; addresses inside them are deep blue, those outside are pale.
Drive-time contours out of one depot; the addresses beyond them stay pale.

1

Balanced workload

Territories are equalised on point count and visit load.

2

Contiguous territory

Single-piece territories, not fragments — the transit kilometres between fragments disappear.

3

Headcount from capacity

How many representatives or vehicles each territory needs is calculated.

Territories change once a year; routes change every week. Both come out of the same model.

Is the depot in the right place?

Drive-time analysis measures the reach of your existing depots and transfer points.

  1. Coverage by time

    The area reachable in fifteen, thirty, forty-five and sixty minutes, computed on the real road network.

  2. Points left outside

    Addresses that fall outside the target delivery time are listed.

  3. New depot scenarios

    Candidate depot locations are compared on the coverage they add.

  4. The same method fits a branch

    A dark store, a transfer hub or a dealer uses the same model.

05 · THE PRODUCT SCREEN

Route, distance matrix and reach analysis on one screen.

A pale grey map of Şişli with a web of thin blue lines joining the stops to one another; a pink route runs over it through numbered stops.
Every link between the stops, and the order chosen, on one map.

01

Stop list

Reorder by hand, or optimise.

02

Travel mode

Car, on foot and by bicycle; the traffic profile can be switched on.

03

Distance matrix

A kilometre and minute table between points, exportable.

04

Reach rings

Ten, twenty and thirty minute reach areas, on the map.

The values in the screen images are illustrative.

06 · IN THE FIELD

Do not leave the plan on a screen; put it on the team's phone.

The Sahanın Gücü mobile app carries the route into the field and brings back what happened.

A pale grey map of Avcılar and Beylikdüzü with a wide pale pink ribbon following the road network; the addresses inside it are pink, those outside pale blue.
The addresses that fall inside the buffer along the route are marked.

  1. Filter along a route

    Draw a route between two points, give it a buffer, and every point along it is listed.

  2. Visit plan

    The optimised order reaches the team with its date and the person assigned.

  3. Check-in and survey

    The visit is verified by the location it happened at; field data is written onto the point.

  4. Planned against actual

    Completed visits flow back to the centre live; drift is reported.

07 · WHAT WE MEASURE

A saving is not a claim; it is a measurement.

These are measured before and after during the pilot; the saving figure comes out of your own data.

01

Total kilometres

Distance covered per plan and per vehicle.

02

Route duration

Time on the road separated from time spent at the point.

03

Visit completion

How many of the planned visits actually happened.

04

Cost per point

The share of fuel, time and staff cost that falls on each point.

05

On-time delivery

The rate of compliance with the delivery window.

06

Workload balance

The spread of load between representatives and vehicles.

The pilot runs four to six weeks: the first two measure the current state, the rest compare it against the optimised plan.

08 · SETUP AND INTEGRATION

It installs beside your systems, not in place of them.

01

Order / visit data

A daily transfer from ERP, CRM or Excel.

02

Address verification

A free-text address is tied to a coordinate at building level.

03

Optimisation

Route and assignment produced together with the constraints.

04

Write-back

The result returns to your system and to the mobile app over the API.

Cloud

Next Geo hosts it; no separate server is needed.

On-premise

It runs on the organisation's own infrastructure.

REST API

Scoring, geocoding, routing and distance endpoints are ready.

Setup averages two weeks including data preparation, and starts with a pilot territory.

NEXT STEP

Let's measure your routes together.

We start with one pilot territory and your existing visit or order data. The first two weeks measure the current state; the saving figure comes out of your data.