As a Senior Sales Consultant at EIKONA Logistics, he knows the requirements of the logistics sector inside out and finds customised solutions.
Manual pallet management is time-consuming and error-prone – especially if it is still handled using a tool such as Excel. With the high number of pallet notes, it's easy to get lost. Good pallet account software makes the work much easier – and even more so if it is AI-supported and manual typing of data is a thing of the past.
After all, pallets, pallet cages and containers are indispensable for transport and are also a valuable resource from a financial point of view. When a lorry is dispatched, it is therefore necessary to record exactly how many pallets are unloaded and whether new pallets are loaded in return. You can find out how easy it is to do this here.
Like many digital logistics applications, a good pallet account is web-based (and not old-school via Excel) so that all users can log in directly via their normal browser using their access data. The software should offer as many functions as necessary, but also as few as possible. In short: a pallet management tool does not need many features, but the right ones. The most important features are master data administration and, of course, the star of the show, pallet pooling.
Basically, every pallet note contains the same information:
AI takes advantage of that. It reads the information on the ticket and converts it into structured data so that it is available for subsequent processes such as calculating the current pallet count. This means that nobody has to manually enter the license plate of the delivering truck, the shipping company, the number of unloaded pallets, etc. into a pallet account app or (web-based) software; the AI does the work automatically.
It only takes a few seconds from the fluttering note on the pallet to the structured data record that is booked directly in the pallet account. Here's how it works:
How many load carriers are currently in circulation? What is the pallet stock level? These questions can be answered quickly with the information from pallet pooling.
A good AI-supported pallet tool can be implemented in the company within a few days, when the AI has been specially trained for logistics processes. It is therefore worth choosing a provider with extensive logistics experience that has been incorporated into the development of the artificial intelligence.
Then there is only the company-specific training, based on the individual processes of the respective company. For example, if more than 100 completely different pallet notes from a large number of suppliers and forwarders have to be reliably interpreted, the training will take a little longer than if the AI only has to interpret 20 different documents.
Data protection must, of course, be a top priority: Sensitive business data should never be used to train other software. The AI only learns within the protected scenario in the respective company and knows the master data and document types used after a short time.
In order to customise the tool even more to suit the company’s processes, certain logics can be set. For example, a full goods consignment can never consist of more than 36 pallets. If an 86 is incorrectly written on the pallet note instead, an error message immediately indicates that something is wrong with the booking in question.
Does your company have a closed loading equipment pool for a specific area? This is not a problem for a good pallet tool; you can simply create different (closed) company accounts. Exchange partners and other master data are also entered during setup. This speeds up the process later on and reduces the susceptibility to errors, as the AI only has to select the right name from X different names when reading the pallet notes instead of having to decipher every letter correctly.
The big advantage: the tool arrives at the user's premises ready to use, i.e. perfectly customised by the IT service provider, and can be used straight away. So there's no need to worry about the magic in the background.
Whether it’s neat or messy: The AI also recognises handwritten additions without any problems. After all, corrections are often necessary during unloading: If a pallet is broken during transport, the planned number is no longer correct. A quick cross-out and the correct number written over it, and voilà, everything fits again. Regular OCR software could no longer read the pallet note this way, but AI can. Anyone thinking: “But what if the AI has read a number incorrectly and we have noted 28 instead of 29 unloaded pallets?” Don’t worry: although the AI reads more reliably than a human eye (and never makes typos), the transactions in the pallet account still go through a screening process. Filter functions such as “for checking” indicate with one click which notes should be cross-checked before they are finally posted.
Transferring data from the note to the pallet account by hand all day long is really not an interesting task. The manual process is not only monotonous for employees, but also error-prone, as it’s easy to make a typo. So how do I manage a pallet account that works quickly and reliably?
AI is already being used effectively in many areas of logistics and is also a great help in loading equipment management. Once trained, it reads all photographed notes automatically and in a matter of seconds. This not only saves time, but also money, as all loading equipment is recorded correctly. The online pallet account is always up to date and loading equipment management is no longer a chore.
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