Most diesel distributors plan their deliveries based on estimates and calls. The customer notifies them when they are almost out of product, and from there, everything is a race against time: an urgent delivery, a route that is rearranged on the fly, and a margin that narrows. It's a model that has worked for years but today leaves quite a bit of money on the table.
The monitoring of diesel tanks changes that starting point. Instead of waiting for the customer to call, the distributor sees the level of each tank in real-time and knows, days in advance, who will need a refill. With this information, the operation stops reacting and starts planning.
This article reviews the costs of distributing blindly, what changes with real-time data, and what is needed for that data to be reliable and truly integrate into your management system.
The cost of blind deliveries
Working without visibility of your customers' tanks
comes at a price that rarely appears on any invoice, but is paid every
week:
- Urgencies that disrupt the day's route. A last-minute call forces a truck to be diverted, alters the order of deliveries, and incurs unplanned miles.
- Trips that could have been grouped. Without knowing who will need product and when, it is difficult to fill the truck and chain nearby deliveries on a single route.
- Customers who run out of diesel at the worst moment. When that happens, the customer suffers the incident, but also starts to look for whether another distributor can provide a more reliable service.
None of these costs are avoidable if planning depends on the customer notifying. The underlying problem in this type of scenario is the lack of information, and that is where remote monitoring of diesel tanks comes in.
What changes when you see the level of each tank in real time
With a sensor in the tank and a platform that collects the
readings, the distributor gains three capabilities that they did not have before:
- Anticipation of orders. The platform learns the consumption pattern of each tank and alerts before the level reaches a critical point. You can prepare automatic diesel orders based on actual consumption, not on the calendar or on intuition.
- Optimisation delivery routes. By knowing in advance who will need product, you can make deliveries by area and plan the truck loading with criteria. The route is designed based on data, and urgent trips cease to set the pace of the operation.
- Relación más sólida con el cliente. Un cliente al que se le repone antes de quedarse sin producto recibe un servicio que percibe como anticipación, no como reacción. Esa fiabilidad es lo que sostiene la fidelización en la distribución de gasóleo.
There's an idea that sums up the change: the best salesperson is the one who calls the customer before the customer needs to call, or before they start comparing prices with the competition. With real-time monitoring, this no longer relies on memory or luck: the platform predicts when restocking is needed, and the distributor gets ahead.
The result is a diesel distribution management that plans with days to spare instead of improvising. It applies equally whether you serve industry, agricultural operations, communities, or heating oil: the pain is the same whenever you depend on not knowing how much is left in the customer's tank.
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Not all tanks are the same
An underground diesel tank is nothing like a large-capacity above-ground one, nor like the irregularly shaped ones found in many older installations. An IoT monitoring solution is only useful if it adapts to this reality, not the other way around.
NivelWatcher is built around our own sensor, designed and manufactured by Celestia TST, which installs on the tank in under a minute and without any construction work. Depending on the type of installation, you choose ultrasonic or radar measurement, each suited to different conditions. If you want to get into the detail of when each technology makes sense, we cover it in our article on radar versus ultrasound for fuel management..
Connectivity is also tailored to the location, with options like Sigfox, LoRa, or NB-IoT cellular network, ensuring data transmission even from tanks in areas with low coverage. Managing the sensor from start to finish allows it to be adjusted to each tank in terms of size and connectivity, something that an integrator reselling third-party hardware can hardly offer.
The platform: all your tank park on one screen
The sensor measures. The NivelWatcher platform turns those
readings into decisions, from a single panel accessible from mobile, tablet or
desktop computer.
From there you control the stock of all your
clients' tanks at once, with automatic alerts when any approach the
replenishment point. The analytics learn the actual consumption of
each point, anticipates when product will be needed and feeds both
the generation of orders and the planning of routes, without relying on
memory or the client's call.
The platform also manages who sees what. You can assign roles and permissions to your sales team, to other distributors or to the clients themselves, thus opening new ways to provide service that were not viable before: fixed rate, automatic order confirmation, consumption discounts or direct notifications to the client. Monitoring the fuel level becomes part of your business relationship.
With our platform or with yours
To take advantage of the data, you do not have to change your way of
working. You can use the NivelWatcher platform as is, or integrate the
readings from the sensors into your own ERP, CRM or management software via
API. The logic is simple: the technology adapts to your operations.
The recommended starting point is a pilot on your
own tanks, to validate the system in real operation before scaling.
It is the path you will see in the case below: starting with a few sensors
and expanding the deployment once the results have been verified.
A real deployment: Propenor
Propenor, distributor of liquid fuel for the Cobo
Group, started with a pilot of five NivelWatcher sensors in its
clients' tanks to validate the system in real operation. After verifying the
results, it expanded the deployment to fifty devices in its network.
With real-time visibility of the levels, Propenor
moved from planning based on calls and estimates to anticipating demand, and
reduced its distribution costs by 10%. You can read the full journey,
with the testimony of its team, in the case of Propenor.
Frequently asked questions
It is a system that measures the level of each tank in real time using a sensor and sends the readings to a platform. With that data, the distributor knows days in advance who will need to replenish and plans the deliveries without relying on the customer to call. The measurement is done by ultrasound or radar depending on the tank, and in the case of radar, the error drops to 0.1-0.2%.
Yes. The LevelWatcher sensor is installed in the tank in less than a minute, without construction and without cutting off the supply. Depending on the type of installation, either ultrasound or radar is chosen, and the connectivity is adjusted to the location with Sigfox, LoRa or NB-IoT, so that the data reaches even from tanks in areas with poor coverage.
Yes. The solution applies equally whether you serve industry, agricultural operations, communities or heating oil. The problem is the same whenever you depend on not knowing how much is left in the customer's tank, and demand anticipation works in all those cases.
Yes. You can use the LevelWatcher platform as is or integrate the readings into your ERP, CRM or management software via API. You do not have to change your way of working: the technology adapts to your operations.
The recommended starting point is a pilot on your own tanks, to validate the system in real operation before scaling. This is what Propenor did, starting with five sensors and expanding to fifty after verifying the results, with a 10% reduction in distribution costs.
Do you distribute fuel oil and want to see how it would work in your operations?
Request a pilot on your own tanks.
Written by Ana Escalante Galán, Head of Marketing and Communications at Celestia TST
Technical review: Alberto Puras Trueba, Business Development and Innovation Management.