Industrial-scale food producers manage potentially hundreds of individual labels per each product code, item code, SKU, or material items, which creates a headache for version control and maintenance. The complexity of managing so many labels leads to data errors and human errors that negatively affect quality. According to the USDA’s Food Safety and Inspection Service (FSIS) the ten most common labeling mistakes food producers make are:

  1. The label is illegible or portions of the label are illegible.
  2. The label is incomplete in that not all required labeling features are provided.
  3. The label application form is incomplete.
  4. The formulation, processing procedure, or supporting documentation do not agree with the information on the label.
  5. Product standards are not met.
  6. Product name is incorrect.
  7. Ingredients statement problems.
  8. Nutrition facts problems.
  9. Nutrient content claims are incomplete or do not comply with regulatory requirements.
  10. Undefined nutrient content claim is used, e.g., leaner, low carbohydrate, very low in fat.

How CAT Squared Makes Managing Labels Easier:

CAT Squared's food labeling software simplifies label management by consolidating many of our customers' labels into a few standard templates. Once configured, the system can use one label template as a dynamic label, automatically pulling product data associated with that product code in the company's database. CAT Squared also supports custom labels since many producers supply and package for customers who require a specific design.

"Our customers use our labeling systems on all types of processes," said Tyler Carroll, CAT Squared's technical project manager. "Some labels are used on completely automated scale lines and others are used with auto print-and-apply stations. Aside from box-end labels, we print labels for pallets, materials, consumer unit price (UPC), etc. When combined with our Receiving Module, Production Control Module, and Warehouse Management Module, our system ensures complete traceability by tracking the movement of all ingredients, supplies, and product inventory through the plant."

For more great information and resources on labeling, click here to download FSIS’s datasheet on how to avoid ten common labeling mistakes.

Request a demo of our food labeling software and a CAT Squared expert will run you through the process, from design to printer to tracking and analysis.

Kathy Barbeire

Written by Kathy Barbeire

Throughout my career, I’ve helped organizations think of creative ways to (1) harness new technology to maximize effectiveness, (2) collect relevant data to measure and improve performance, and (3) use data to tell compelling stories to customers and stakeholders. In 2015, I became CAT Squared’s marketing manager. In this role, I monitor industry trends to (1) ensure our products are flexible enough to adapt to new industry standards and (2) prepare our customers for new technologies with the potential to disrupt the industry. I’ve represented CAT Squared as a participant in a blockchain learning group that has grown out of Blockchain for Arkansas (BC4AR), an initiative launched by Governor Asa Hutchinson to promote capacity building around blockchain technology. As my own knowledge and capacity grow, I develop new content to educate our supply chain partners and help them prepare for the transition ahead. Prior to launching my career, I graduated magna cum laude from the University of Arkansas at Little Rock (UALR) with a Bachelor of Arts degree in professional and technical writing and a double minor in sociology and information technology. I later returned to UALR and completed the MBA program. Before joining CAT Squared, I applied my passion for data-driven storytelling to help nonprofits define their goals, track program metrics, and engage donors and community stakeholders in their missions to fight hunger, poverty, and homelessness, first as a program manager for the Our House Homeless Shelter in Little Rock, and then at The Salvation Army Central Arkansas Area Command.