How it works
We connect to your systems alongside the fleet that works for you, your own or carriers’. The system plans how many drivers and vehicles are needed, assigns orders and re-plans them during the day, and our team keeps working on results and improvements.
After rollout
We do not stand between you and your fleet. You keep the relationship with drivers and carriers; we provide the decisions and keep working on their quality.
We receive live information on resources and orders. Information on resources comes at two levels: for planning, all the fleet’s vehicles and all drivers with their availability; during execution, the resources actually available at that moment, that is the drivers who have come to work and the vehicles ready to drive.
For orders, we receive not just addresses but also their requirements: pickup and delivery time windows, maximum transport time, weight, volume and the type of vehicle needed, for example refrigerated. Plus every update: a new order, a cancellation, a driver’s absence, a vehicle breakdown.
We send plans and decisions: how many drivers and vehicles to prepare for each day and hour, which vehicle handles which order and in what sequence, and during the day the re-planning of whatever has changed.
The relationship stays the same. The tools change. We make the most of the apps and systems you already have in place. If there are none, we provide ours, and where needed we introduce changes together with you. We collect knowledge about delivery points (gate codes, photos of locations, tips on access and parking) in the driver app, so a new driver works well from day one.
Our analysts and engineers continuously analyse results and deviations, fine-tune the system, and propose and implement further improvements. This is not technical support but continuous work on your fleet’s results. Because of how we are paid, fleet productivity and the unit cost of delivery are our KPIs too.
The starting point
Because high quality has to be maintained amid constant change. Large companies cannot afford late or missed deliveries, yet they do not know in advance how many orders will come in, from where and to where, who will not turn up for work, which vehicle will break down or where traffic will stop. To deliver quality anyway, they keep spare resources, and that costs money.
The most common approach: the delivery area is split into fixed areas, and each customer always goes on the same route. Each area is sized so that, even at peak, everything that may come from it fits in the vehicle and in the time available.
So every route carries its own buffer: with 20 routes, that is 20 buffers. It is easy to manage, but the vehicles’ capacity, volume and working time are not used optimally.
When a dispatcher tries to plan dynamically, the work becomes very time-consuming. People have limited time and perception: they do not notice everything or manage to take everything into account. Add fatigue, distraction and bad days.
Decisions are therefore far from optimal and inconsistent: in a similar situation one decision is made one day and the opposite the next, although only one is optimal.
Most systems work by simple rules. For example, they set the delivery sequence within a route and guide the driver with navigation, leaving the split into routes and resource planning to people or handling them with simple automation.
They miss the hundreds of nuances that determine the result.
The effect is the same: the fleet needs more vehicles, hours and kilometres than the orders require. A well-tuned system maintains the same quality standards with much smaller buffers.
The mechanism
Above all from dispatch decisions, and to a lesser extent from better navigation. Cutting the fleet and buffers is easy; doing it without losing quality is hard. Two foundations make it possible: dynamic order assignment and an accurate forecast.
One buffer instead of many
Fixed routes
Each route has its own buffer. One runs out of space while another leaves half empty.
One dynamic fleet
The system splits orders between vehicles every day. One shared buffer covers the whole volume, much smaller than the sum of the fixed routes’ buffers.
A forecast narrows the buffer
Without a forecast
You expect 1,000 to 2,000 orders, so the fleet must be ready for 2,000, although there are often only about 1,000.
With an accurate forecast
A range of 1,000–1,200 orders: the fleet only needs to be ready for 1,200.
Illustrations with example numbers.
The foundation: dynamic order assignment. The system distributes orders live between the vehicles and drivers available at that moment. It takes into account time windows, maximum transport time, capacity, other requirements and the specifics of the logistics in question, and when something goes wrong (a breakdown, an absence, a traffic jam) it immediately re-plans the work of the others.
The second foundation: an accurate forecast. Demand has a random component, but it can largely be predicted. It depends, however, on many factors that differ from industry to industry, so building a reliable forecasting model is hard and few companies use one. We have been developing such models for years: the more accurate the forecast, the fewer resources need to be planned for the day.
Only then: fewer vehicles and one shared buffer. On these foundations you can reduce the number of drivers and vehicles and replace the separate buffers of fixed routes with one shared buffer, much smaller than their sum. Without them, a smaller fleet quickly takes its toll on quality.
Dynamic assignment does not mean the plan changes every few minutes. Orders are pre-assigned to vehicles straight away, roughly by direction, and most of them stay on their original vehicle until departure. Reassignments affect only part of the orders, usually between neighbouring routes, so order in the warehouse is maintained (how this works in the warehouse).
A shared fleet also makes forecasting itself easier. With a fixed split into routes, each area is in practice served by its own single-vehicle fleet, and the number of orders from one area is much harder to predict than from the whole territory. The total across all routes is largely repeatable from day to day, while individual routes fluctuate far more. It is a simple statistical effect: the fluctuations of individual areas partly cancel each other out.
Many fleets, for example in on-demand delivery and courier companies, already work as one shared fleet and still do not reach similar productivity. Simpler order dispatching mechanisms, which miss the dozens of nuances our system takes into account, need larger buffers, and therefore higher resource costs, to avoid losing quality.
An optimal split rarely looks obvious. A map shows only where the points are and how far apart they are, and simply ordering stops to minimise kilometres is a relatively easy task. What it does not show is what decides the order in practice: that a point is not yet open and cannot come first, that another has priority and a short delivery window, that a stretch of road has tolls, roadworks or traffic jams at that time of day. That is why a route that looks illogical on a drawing often turns out cheaper than the one a person would plan by eye.
Navigation matters too, but most fleets use navigation with consumer origins. It accounts for vehicle size and weight, but it does not find the optimal route taking road tolls into account, and in the last mile it will not take a courier through a car park or a gate. Ours does, which can cut a trip by two junctions and 10 minutes (how the system knows how long a trip will take).
Orders assigned live to available vehicles; new orders, cancellations, breakdowns and absences handled without waiting for a person.
Fewer kilometres and slip-ups.
The right number of vehicles and working hours for every day and every hour, based on the order forecast.
Fewer vehicles and working hours.
Orders split dynamically between vehicles instead of fixed routes with separate buffers.
Fewer vehicles and kilometres.
More orders in a single trip means shared pickup time and shared kilometres.
Fewer kilometres and working hours.
The system forecasts the driver’s arrival and signals when to prepare the order for exactly that moment. Nobody waits for the goods, and the goods do not wait for the driver.
Fewer working hours, better delivery quality.
Vehicles and drivers spend less time waiting without an order.
Fewer working hours and vehicles.
Data flows into the system automatically, decisions go back to drivers and pickup points, and people handle only the exceptions.
Data on vehicles and drivers, their availability and actual presence, and on orders with their requirements reaches us from your systems, usually through a ready-made integration, with every update.
The system plans how many drivers and vehicles will be needed in the coming days and hours, based on the order forecast, and builds schedules from the drivers and vehicles at your disposal. Schedules follow demand rather than habit.
Each order goes to an actually available vehicle that will fulfil it at the lowest cost, respecting pickup and delivery windows, maximum transport time and requirements for capacity and vehicle type. Drivers receive orders in an app, and the pickup point is told what to prepare and when.
A new order, a cancellation, a traffic jam, a breakdown or a driver’s absence: the system notices immediately and re-plans routes or hands the order to another driver on its own.
Your dispatchers deal only with the few situations that need a person. You set the decision criteria and can take manual control at any time.
Our team continuously analyses results and deviations, fine-tunes the system, and proposes and implements further improvements.
They stop building plans by hand and start looking after the criteria and the exceptions. You keep full control of your fleet.
Dispatch decisions are made automatically. Supervision comes down to the few alerts that need a person and to checking that teams on the ground follow the agreed rules.
You see every decision the system makes live, and afterwards you can trace every order to the minute. You set the criteria and can take control in any situation.
The system records when each job started and ended, how many kilometres were driven and where there were delays. Settling accounts with carriers and clients no longer requires collecting data by hand.
The result is lower fixed costs of the management team and less pressure on managers.
Who our solutions are for
In changing logistics at scale: where orders, demand and conditions change from day to day and even within a day, and there are often only minutes or seconds for an optimal decision. That is where people and off-the-shelf systems deviate most from the optimum, so a well-tuned system delivers the biggest savings.
Wholesalers with many warehouses and hundreds of customers a day, including food service and grocery wholesale. Deliveries are often made by carriers paid for vehicles and hours.
Delivery fleets, in-house or subcontracted, serving many locations of a chain. Orders come in live, and delivery takes minutes.
Fleets working in delivery areas, with pickups coming in during the day, including those paid per parcel, where the courier company decides how many vehicles and couriers to deploy.
Pharmaceutical, bakery and other local deliveries with many drop points a day.
Shops and retail chains that deliver shopping to customers, with many deliveries a day.
Carriers and companies that plan truck transport between plants, warehouses and customers.
What matters is the nature of the logistics rather than the industry itself. If most of the points in the list apply to your company, let us check the potential on your data. The audit and data analysis are free.
Who our client is
No. Our client is whoever cares about the fleet’s productivity: whoever pays for vehicles, driver working hours and kilometres and decides how the fleet works. Depending on how transport is paid for, we connect at a different point in the chain.
Own fleet
Fleet costs and planning decisions are in the same hands.
Carriers paid for vehicles and hours
Every unnecessary vehicle, hour and kilometre is the shipper’s cost. The carrier is paid directly for these resources and does not decide on the plan.
Carrier paid per order
The rate per order is agreed and the carrier bears the fleet costs. It decides on the plan, so it gains from optimisation.
We do not just sell tools. We become part of your team: our fee depends on the scale of the savings, so we work on your fleet’s results not only during rollout but throughout the cooperation.
| Typical software vendor | Dispatch Rangers |
|---|---|
| Sells access to an application to hundreds of companies. | We work with a small number of clients and know their operations. |
| Configuration, training and rollout at further locations are the client’s job. | We roll out together with you: on site for the first rollouts, and at further locations we support your teams remotely. |
| After rollout, the client is looked after by an account manager who may handle support tickets. | After rollout, our team actively and continuously oversees and analyses results and deviations, and looks for and proposes further improvements. |
| The vendor’s revenue does not depend on the client’s results. | Our fee is a fraction of the savings, so it depends on your result. |
| The result depends on how the client uses the tool. | We share responsibility for the quality of decisions with you; tools are only a means to an end. |
Without a team’s continuous work, even a good tool delivers only part of its potential.
Start with a conversation and historical data on your fleet and orders. The analysis is free. If we do not see potential, we will tell you straight away.