Making The Switch to Automated Labeling

Data annotation is defined as the process of putting a label on the available data found in different formats and medium. In a growing enterprise and business, labeling and barcode problems and challenges are very much present. Barcodes are the widely preferred method of placing a label on products, with RFID labeling growing as a competitor. However, as one’s business continues to grow relying on manual labeling then data encoding, with the rapid increase of individual data, will be more costly. With how much time and cost you might have to pay for any mislabeled items, labor costs and errors, an automated labeling system may be more beneficial and efficient.A quality system is designed to run for several years, ensuring to meet your demands as a company and help your company grow. Here are benefits to consider when making the switch.
  1. Reduction of Manual and IT Labor Costs
As previously mentioned, it is the key benefit of starting an automated labeling system. As the one responsible for placing labels is now a machine, you can allocate your employees to other jobs that machine wouldn’t be able to do, making them more productive. Furthermore, while the initial investment might be steep, machines require no salary, benefits and breaks which a regular employee is entitled to.IT costs also fall under here as there wouldn’t be a need for data encoding as a properly implemented system can easily integrate and add the product data to the database in conjunction to any pre-existing system. This allows the IT department to focus on resources in other parts of the system such as security and network maintenance.
  1. Reduction of Labeling Errors and Issues
Labeling errors will always pop up in every other batch and it would be the end user who would suffer more compared to the person who was responsible on placing the label. Common issues are as follows:
  • Incorrect or Improper Data
  • Dead Zone or Damaged Labels
  • Quality of Placement
  • Print/Color Quality
These are the 4 common problems encountered during and after manual labeling. An automated system would alleviate or even eliminate these problems. As we are only people, it is inevitable that mistakes like this are bound to happen and it’ll increase as the number of things that need to be labelled increases, mistakes like these are costly as they can lose time to finding the right data and entry alongside correcting the mistake in the database.
  1. Standardized Labeling
Standardization is making something conform to a standard, the lack of it causes inconsistency between products. May it be the present, past or future, there is a specific standard that most things follow. While we are unable to change how things were labelled in the past, the integration of an automatic labeling system would make it easy to implement a standardized labelling format that would be carried on in the future. This ensures that products and items can still be identified and familiarized in the future without a difference in how they were labeled. It would make future employees easier to train as you already have a consistent way of labeling products.
  1. Fragmented or Repeated Labeling
Similar to the previous notion, an automated system can prevent things from getting relabeled in an effort to update its data. Furthermore, it can also prevent data from getting fragmented from the usage of multiple labels. This ensures that all the data required to know about the product is available in one label without the need to look around the product for any additional information. This can be driven further using an RFID system as its implementation can further enhance these as RFID are more reusable, allows for larger data capabilities and can be updated accordingly.
Categories: General

Nicolas Desjardins

Hello everyone, I am the main writer for SIND Canada. I've been writing articles for more than 12 years and I like sharing my knowledge. I'm currently writing for many websites and newspapers. I always keep myself very informed to give you the best information. All my years as a computer scientist made me become an incredible researcher. You can contact me on our forum or by email at [email protected].