GS1 is a non-profit association that develops and promotes the implementation of data, barcode, electronic product code (RFID), and data synchronization standards to improve supply chain efficiency. In addition to cross-industry standards efforts, GS1 has a number of industry-specific groups, including the GS1 Foodservice Initiative that addresses the unique challenges of the foodservice supply chain. (For more information about the GS1 standards and the Foodservice Initiative visit https://www.gs1us.org/)
The purpose of GS1 standards is to provide a common language and method for sharing and tracking product information throughout the supply chain. For example, the GS1 Foodservice Initiative has defined standard data formats for identifying producers, distributors, products (Global Trade Item Number – GTINs), lot, date and other product attributes (in addition to means for sharing and synchronizing data). Common formats make it easier and less costly for distributors to manage data from multiple producers, as well as improving item-level tracking as products flow through the DC. In the long run, adoption of the standards will reduce DC costs—including the costs for managing recalls—but the savings may require changes both in the back-end systems that manage and share data, and in material handling processes within the DC.
To get maximum benefit from the standards efforts, DCs need to track product data as pallets received from manufacturers are broken down into cases and individual items that are shipped to end customers. To achieve this level of tracking often requires additional data entry steps that have the potential to increase operating costs. This is encouraging many DCs to rethink their material handling processes and technology choices. Rather than framing their choices as voice OR scanning, they are thinking anew about voice AND scanning.
Understanding the benefits of voice and scanning
The relative merits of voice or scanning for any task depend both on how products or locations are labeled (whether information is printed or barcoded) and the specific requirements for the business process. In instances where voice and scanning are both practical, the question becomes which technology will result in a more efficient, effective process?
In comparison to a scan- and screen-based RF process, the combination of voice direction with voice confirmation of a location check digit creates a highly fluid, efficient workflow for selectors. With voice processes, the selector will move as he or she listens and speaks, without the extraneous motion of stopping to scan or stopping to read a screen for the next instruction. Likewise, voice systems allow users to speak quantities and units of measure—“three cases”—as they work, rather than stopping to key enter or confirm quantities. Positively entering the quantity (by voice or key entry) is a check on accuracy; entering by voice is more efficient and accurate than key entry.
Capturing product level detail at the point of activity—which is at the heart of GS1 and related traceability initiatives—is a more complex matter. Most DCs today have products with mixed labeling. While some products may include GS1-128 barcodes that encode GTIN, lot, date, weight and other product level data, other products may have item data encoded in barcodes that do not conform to the GS1 standards. In addition, other products may only include printed lot or date information.
The prevalence of mixed labeling illustrates the importance of giving users the flexibility to enter product data by a variety of means. In an ideal world in which all products have product level data printed and barcoded in consistent formats, there would still be the question of which technology is best for the task from a process efficiency view. The important point is that neither speech recognition nor scanning is optimal for all tasks.
For example, when entering data by voice, there are some situations where you would want the voice system to repeat the spoken value back to the user for confirmation. This is common when entering the weights of variable weight products, to account for the fact that users will sometimes transpose digits or misread numbers. In those instances, scanning may save seconds per weight entered and improve data accuracy by eliminating human error.