Car washes are highly automated systems. Vehicles are guided through precisely calibrated wash programs, chemicals are dispensed, processes run in short cycles, and customers expect consistently good results at all times. Yet, surprisingly, there is still a significant information gap in many places regarding the very core component of the operation: the supply of detergents.
Measurable savings potential: Digital fill-level data helps reduce emergency deliveries and safety stock, minimize manual checks, and prevent detergent losses. At the same time, deliveries can be planned more closely according to demand, and transport capacity can be utilized more efficiently.
Shampoo, active foam, wheel cleaners, waxes, drying aids, and other specialty chemicals must be reliably available. If even one of these products is missing, it can affect individual wash programs or, in the worst-case scenario, the entire operation. At the same time, operators should not maintain unnecessarily large detergent inventories, as storage space and the associated logistics also incur costs.
The key question is therefore:
This is exactly where digital inventory monitoring comes in. With IoT-based sensors, automated data transmission, and a central software platform, inventory levels can be continuously tracked and consumption trends made visible. Individual containers are transformed into a digitally controllable supply chain.
One example of this is the collaboration between Simoniz and Packwise. With ChemCheck, Simoniz relies on a solution for the digital monitoring of chemicals in car washes. Detergent levels, alerts, consumption data, and inventory levels are consolidated centrally in a cloud-based application. This use case demonstrates that optimizing car wash facilities begins not only with the washing technology itself, but also with inventory management, detergent consumption, restocking, and logistics.
Modern car washes are designed for efficiency. Numerous processes are automated and precisely coordinated. When it comes to monitoring detergent inventory, however, the situation is often quite different: Employees check containers on-site, estimate remaining quantities, or document inventory levels manually.
As a result, suppliers know when and how much was last delivered, but they do not automatically have up-to-date information on actual inventory levels and consumption. Without continuous measurement data, it is difficult to determine when the next restock is needed. This leads to a classic trade-off: too little inventory increases the risk of a shortage, while too much inventory results in unnecessary costs.
As the number of containers, products, and locations increases, manual monitoring becomes increasingly time-consuming. While the containers are physically located at the customer’s site, logistical planning often takes place at a completely different location.
Without reliable data, important information is missing: How much product is currently in the container? How quickly is it being used up? Which location needs to be restocked first? Are there any unusual spikes in consumption? If such questions are answered primarily based on experience, it makes efficient planning difficult.
When companies do not know exactly when a container will run out, they often keep extra detergent on hand as a safety stock. While this reduces the risk of a shortage, it ties up capital, requires storage space, and can lead to significant overall inventory levels across many locations.
The opposite problem arises when low inventory levels are detected too late. In such cases, additional deliveries must be organized on short notice, routes must be changed, or special trips must be scheduled. Digital fill-level data provides a better foundation here: Instead of compensating for uncertainty with high safety stock or last-minute reactions, planning can be based more heavily on actual consumption data.
Every manual inventory check takes time: Employees must inspect containers, document levels, and pass on information. With numerous containers and locations, this effort adds up.
Added to this is the risk of errors. Levels can be misjudged, entered late, or scattered across different systems. Automated level monitoring replaces these sporadic checks with continuous data, thereby reducing the manual administrative burden.
Sensor-based level measurement makes it possible to continuously monitor tanks and transmit measurement values digitally. This ensures that information is available regardless of the tank’s location.
It is not just the current fill level that matters. Only by analyzing multiple readings over an extended period can consumption trends become apparent. The question “When was the last time someone checked?” thus gives way to the far more relevant question: “How is consumption trending?” This data forms the basis for forecasts and more efficient replenishment planning.
Packwise starts right at the container. With the Packwise Smart Cap, relevant status and fill-level information can be captured and made available digitally. The data is then consolidated in Packwise Flow 2.0.
For car washes, this means that detergent inventory no longer needs to be managed exclusively through manual checks. Real-time container data can be used to better control inventory, consumption, and restocking. The hardware provides the data—the software turns it into actionable insights.
A key advantage of this approach is that it digitizes existing processes without requiring a complete overhaul of a car wash’s infrastructure.
Existing tanks become digitally trackable components of the operation. This allows digital level monitoring to be integrated into existing workflows without requiring extensive modifications to the facility’s infrastructure.
A single measurement value has only limited value if it is not placed in an operational context. That is why the software plays a central role. Packwise Flow 2.0 consolidates the information from the digitized containers and provides a centralized view of inventory and status.
This provides a decisive advantage, especially when dealing with multiple locations: information can be compared centrally and incorporated into planning. Detergent suppliers, for example, can take their customers’ inventory levels into account and coordinate deliveries more closely based on actual demand.
The strength of digital level monitoring lies not only in displaying a percentage value, but in deriving relevant decisions from it.
For example, two containers may both have a remaining stock of 30 percent. However, if the detergent is being used up much faster at Location A than at Location B, the actual restocking needs differ significantly. Trends in consumption and automated alerts help identify such differences early on and focus attention on containers that actually require action.
Without up-to-date data, action is often taken only after a low stock level has already been detected. The information is passed on, an order is placed, and the supplier arranges for the restock.
Continuous data changes this process. Consumption trends become visible earlier, and future needs can be better estimated. “The container is almost empty” becomes: “At the current rate of consumption, a restock will be needed in the foreseeable future.” This information advantage creates valuable planning flexibility.
In addition to the fill level, the container’s context can also be relevant. Especially with larger quantities of detergent or reusable containers, it’s important to know which containers are in circulation and to which location they are assigned.
Combined with fill level information, this provides a more comprehensive picture. Suppliers can better track which inventories are located at which customer sites and how these are changing. This allows for better coordination between production, warehousing, and distribution. Optimization thus extends beyond the individual car wash and can encompass the entire supply chain.
The benefits are particularly significant when an operator manages multiple car washes. Without a centralized solution, information silos quickly emerge: one location uses spreadsheets, another reports inventory levels by phone, and yet another places orders at fixed intervals.
A centralized software platform, on the other hand, creates a shared data foundation. Locations can be compared, anomalies identified more quickly, and inventory better coordinated. This transforms individual car washes into a digitally connected network of locations.
Continuous measurement data enables analyses that are virtually impossible with manual spot checks. Over extended periods, consumption histories are generated, which can be used to identify differences between locations, seasonal variations, or unusual consumption trends.
For example, increased detergent consumption is not necessarily caused solely by higher vehicle traffic. Dosage settings, processes, or technical anomalies can also play a role. Digital level measurement is thus evolving from a mere monitoring tool into a foundation for continuous process optimization.
The optimization of car wash facilities does not end at the conveyor belt. Detergent supply, warehousing, and logistics also influence overall efficiency. With up-to-date level and consumption data, deliveries can be better aligned with actual demand rather than following fixed intervals exclusively.
This allows deliveries to be prioritized, routes to be planned more effectively, and transport capacity to be utilized more efficiently. At the same time, it helps reduce excess safety stock and the associated product losses. Inventory management also benefits: The less information that needs to be entered manually, the lower the maintenance effort and the more up-to-date the data is. The goal is a demand-driven detergent supply system in which the right quantity is available at the right timeand at the right location.
The change brought about by digital level monitoring can best be described as a shift in the control principle.
Before: Inventory is checked on an ad hoc basis. Information is gathered through manual inspections. Deliveries are based more on fixed intervals, empirical values, or safety stock levels. In some cases, a low inventory level is not detected until immediate action is already required.
After: Containers continuously provide data. Fill levels and consumption trends become digitally visible. Alerts provide early warning of critical stock levels. Replenishment can be better aligned with actual demand, and inventory can be managed more transparently across multiple locations.
The technology thus changes not only the method of measurement but also the basis for decision-making.
Ultimately ,digitalization must make economic sense. The benefits of an IoT solution for car washes do not necessarily stem from a single major cost-saving measure. Rather, several smaller effects can work together along the entire process chain.
One key area is emergency deliveries.
The sooner a potential bottleneck is identified, the more time there is for regular delivery planning. This helps reduce the number of last-minute special deliveries.
A second lever is inventorymanagement .
Greater transparency can enable companies to critically review their safety stock levels. Instead of holding additional quantities to hedge against uncertainty, planning can be based more heavily on actual consumption data.
A third lever relates to working hours.
When inventory levels are available digitally, employees spend less time on repetitive manual checks and documentation.
The fourth lever relates to logistics.
Better demand forecasting can help plan routes more efficiently and allocate transportation capacity more effectively.
In addition, there are potential savings from reduced product losses and improved inventory turnover.
Companies can assess profitability, for example, by examining several cost categories. These include the number of emergency deliveries to date and their associated additional costs, the average value of the detergent inventory, the time spent on manual checks, losses due to excess inventory or underutilized detergent, as well as transportation and planning costs. This results in a simple initial calculation:
Current costs = Inventory costs + Inspection costs + Logistics costs + Special deliveries + Product losses
This is then compared with the processes following the implementation of the digital solution. It’s not just the direct savings that are interesting here; avoided costs also play a role. After all, a detergent shortage that is prevented in time does not appear as a visible savings—even though avoiding a disruption to operations can have significant economic value.
The greatest strength of a digital solution may therefore lie in the fact that it connects multiple areas simultaneously.
Digital inventory monitoring replaces manual checks and provides an up-to-date data foundation.
Early demand detection enables proactive replenishment and delivery planning.
Lower safety stock levels through planning based on actual consumption data.
With ChemCheck,Simoniz demonstrates how detergent inventory can be digitally monitored and managed.
Packwise Smart Cap & Packwise Flow 2.0 integrate container data with digital processes.
The result: more efficient processes, optimized logistics, and sustainable cost savings.
Would you like to learn more about how you can digitize and optimize your inventory monitoring and delivery processes with Packwise?
Schedule an appointment with our experts today - we’d be happy to advise you personally and show you the potential Packwise offers for your processes.