Getting Good with Case Labeling for Supply Chain

We’re always surprised by what we see in practice. Sometimes those surprises are good. Sometimes? Well…not so good.

We routinely observe unusual case label barcoding across the fresh foods supply chain.

Why does this matter?

Diverging from industry best practices for case labeling adds friction, confuses customers and confounds data capture activities.

Let’s recount just two from recent examples and close with some recommendations on “getting too good” on your product case labeling.

The following examples present problems for trading partners across the supply chain. While the manner of coding may work within the supplier’s four walls – these won’t result in useful case labels for downstream trading partners. If you suspect you’re doing any of these or something similar, stop and seek out our help. That’s what we’re here for.

Has anyone ever explained to you how barcode scanners work? Probably not. Once you understand however it will assist you in making better decisions.

What follows is intended to help you understand how scanners and software systems actually “read” barcodes. And, to point out coding practices that should be avoided at all times.

It doesn't matter if your scanner has been programmed to only recognize certain features of the data in the barcode. If your practices are shoddy it may still confuse the scanner, no matter how creatively it's been programmed.

Fresh Produce

Encoded Data (data string in the barcode):

241NE109OLIV132603041026063031

Printed Human Readable (alpha characters below the barcode):

(241)NE109OLIV(13)260304(10)26063031

What the barcode scanner sees and does:

The scanner first sees “241”. When checking its library of Application Identifiers (AI), it finds that 241 designates a Customer Part Number with a field description of up to 30 alphanumeric digits. This is an incorrect use of the AI for which you can read more here (p. 216).

Furthermore, whomever encoded the string failed to include the FNC1 character after the Customer Part Number. Thus, the scanner does not recognize that there are also a date code (13) and a Lot Code (10) as part of the string.

Data Outcome:

The scanner sees only the entire string of data as the customer part number. If the date and lot codes were important to the receiver, they would need to be manually identified and keyed in for capture and retention.

Business Outcome:

·         Incorrect data capture – what is expected by the receiver’s system will not agree with what is provided from the barcode.

·         Additional time spent correctly identifying and capturing product data.

·         Friction with the scanner and system due to incorrect use of GS1 standards.

Incorrectly encoding data in this manner assumes staff receiving this item can decipher the AIs and data of the human readable information. This is a dangerous assumption. In our experience the majority of warehouse, stock keeping, logistics, food service and retail staff are not trained to decipher barcode data strings.

We’re fortunate that the company elected to add parenthesis to the human readable information. Otherwise, we could only conclude they chose one very long customer part number as a means of identifying the case of Organic Olive Spring Mix.

SEAFOOD

We have many examples of incorrect use of GS1 for seafood case labels. This example is typical of observed misuse and illustrates how incorrect use can cascade into multiple levels of incorrect information.

When you don’t follow the encoding rules the scanner and receiving system do their best to make sense of what is scanned. The scanner and system will “insert” unintended intelligence into your data string with disastrous results.

Encoded Data (data string in the barcode):

0240026070111214205240004943

Printed Human Readable (alpha characters below the barcode):

0240026070111214205240004943

What the barcode scanner sees and does:

The scanner first sees “02”. When checking its library of Application Identifiers, it finds that 02 designates a “GTIN of Contained Trade Items” with an 8, 12, 13 or 14 digit field. This is an incorrect use of the AI for which you can read more here (p. 209).

Because it sees at least 14 digits after the 02 it assumes this is a 14-digit GTIN. [An intelligent system will also note that the Check Digit of the GTIN is incorrect and should be “5” instead of “4”.]

AI (02) is a fixed length field, and the scanner does not expect to see a FNC1 after the end of the 14 digits. So, it continues to decipher the remaining data.

In this case the scanner expects to see another AI to define the remaining data in the string. It sees “20”, which designates an Internal Product Variant number with a field length of 2 digits. More can be learned here (p. 214).

This is another fixed field and after interpreting what it believes is AI (20) with a value of “52” it keeps reeding expecting the next AI.

The next few digits indicate AI (400) which is a Customer Purchase Order Number, with a value of 04943.

Data Outcome:

The data which was meant to convey a Box No., Variable Measure Weight and Lot Number are not encoded correctly. The data scanned would be useless to the receiver.

Business Outcome:

·         Incorrect data capture – the creator strung together data relevant to their product for their internal use which is indecipherable to downstream customers.

·         Scanning product identified in this manner would prove futile to the receiver - It would have been better if this supplier didn’t place ANY barcode on the case.

Conclusion and Recommendations

These examples illustrate how the best of intentions with case label identification can result in inaccurate or useless data capture with trading partners.

So what can you do?

Assess your current state. Are you receiving complaints from customers regarding the usefulness or inaccuracies of your case labeling? If you are that’s a sign you should take action.

Are staff responsible for programming and operating barcode labeling equipment trained in the use of GS1 standards? If not, there’s a chance they may be incorrectly applying the standards and rendering your barcoded labels useless to trading partners.

Get smart about coding for your industry. Research your industries best practices for case labeling. For example, the Produce Traceability Initiative (PTI) have put together some fairly solid guidance on barcode labeling.

You can also look at retailer requirements for barcoding from Walmart and others for approaches that 1, align you to GS1 standards and 2, keep you in compliance with retailer mandates.

If you don’t have the time and technical capacity to learn the details of barcoding for case and logistics labels, then consult with industry experts. Here at MDB we have the experience and can work with you to quickly identify your needs, propose workable solutions, train your personnel on the use of GS1 standards, and connect you with the necessary hardware and software providers.

Your goal should be to get good at barcoding.

What is good?

Providing case labels with data and barcodes that provide value for your internal operations and value for your customers through the ability to rely upon your case labeling day after day.

PS: Need a really handy tool to decode and evaluate supply chain case labeling? Try the MDB GS1 Barcode Parser for FREE. http://mdb.limited/scv

‍