2026 Katzscan Newsletters

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Acquiring a company? Check that data. 

While helping a consumer product company conform with some supply chain compliance requirements, I noticed something that looked amiss with their item data, specifically the item data attributes associated with GTINs (Global Trade Identification Numbers). 

GTINs are assigned by the manufacturer and provided to retailers and grocers, acting as a translation item identifier between the manufacturer’s item number and the retailer or grocer’s SKU (stock keeping unit). The most common GTIN is the UPC (Universal Product Code), the 12-digit barcode on consumer products. GTINs are also used to represent case (carton) packs.  Master data management of item GTINs between the manufacturer, their 3PL or distributor, and the customer (retailer or grocer) is a key function in supply chains like retail and grocery. 

Investigating further, and verifying my findings using the check digit calculator on the GS1US website, I discovered that the check digits on many of the GTINs in a subset of the item data were indeed invalid. When I presented this to my client, I was informed that the item data was acquired during an acquisition and simply merged into my client’s existing ERP system “as is”. No one had checked the validity of the item data including the GTIN attributes. 

Invalid GTINs aren’t just an internal issue; they are an external problem as well. GTINs are typically included by customers in the line-item data on the X12-EDI purchase orders (EDI850) and sent back in the EDI856 ASN (Advance Ship Notice) and EDI810 invoice. Surprisingly, my client’s customers – retailers and grocers – never checked to validate whether the GTINs they were receiving were valid. 

Barcode check digits are used by scanners to validate the contents of the barcode. If a check digit is invalid, the barcode may not be readable by a scanner. 

The important lesson here is that data must be validated before being merged from another company such as during an acquisition. You don’t know how well – or how poorly – the acquiring company did in managing their data and ensuring that it met industry or regulatory standards. Don’t just accept acquired data on face value: run audit programs to ensure that the data your company is accepting meets your company’s data standards before you merge the acquired data into your company’s ERP or other business system. And if your company doesn’t have data standards, develop them.  

Analytics before AI

During the vendor selection phase of an ERP (Enterprise Resource Planning) software project last year, one of the software vendors was touting the AI (Artificial Intelligence) capabilities of the ERP system they were representing. My client commented that they were interested in exploring these features. I jumped in and immediately shut down this conversation, after which my client agreed that it was too far a reach. 

My client was replacing a 35-year old accounting system that had essentially been so heavily modified over the decades that it could no longer perform accurate mathematics. Purchase orders and invoices were created in Excel templates. The monthly financials were double-entered into Excel spreadsheets because the reports from the accounting system had failed to be accurate for years. The only printer the Unix-based system could support – a dot matrix printer – was visible behind the Operations Director on video meetings. 

As I explained to my client and reinforced in software vendor meetings, the initial objective of migrating to a modern ERP system for this company was – among other basics – to simply get accurate analysis reports direct from the software. Forget about AI, we just needed analytics that my client could rely on and that didn’t require rekeying numbers into Excel worksheets. 

I’ve written a lot about AI in my editorial articles for Supply Chain Management Review. They are cautionary tales about what AI cannot do, or about how not to implement AI. Here is a company that has never had good system-generated analysis reports … let’s start there before we jump to AI. 

And without the need for much consideration, my client completely agreed with me. AI wasn’t mentioned again throughout the project. 

A Stibo Systems whitepaper released in 2025 reveals startling statistics about the sad state of customer data. Surveying 500 business leaders in the US across various industries, the results reveal that 69% do not fully trust their customer data with 48% finding it incomplete. Over 80% of business leaders are not comfortable making sales forecast, pricing, or inventory decisions based on currently available customer data. The whitepaper is worthwhile reading for its statistics on how bad customer data is and the negative impact it has on execution.  

If your company is considering implementing AI, think about whether you first have good analytics. If not, you probably don’t have good data. Without good data and good analytics reporting, how will you be able to judge if the AI output is in line with expectations or parameters? What will your check-and-balance be as you implement the AI? 

Recklessly leaping into AI is the wrong approach. Cautiously stepping into AI is the better way. Data is the foundation.  

30 Years.

This month is not only the beginning of a new year; it is also the 30th anniversary of Katzscan Inc. Tempus fugit. I honestly don’t know where the time went. As I reflect on what I’ve accomplished, it’s a lot. 

Three published books, the first two available in hundreds of university libraries worldwide. Last year I had the pleasure of being interviewed by a master’s degree student in Hamburg, Germany who read and incorporated one of the themes of my first book – Detecting and Reducing Supply Chain Fraud – as a core part of his thesis. His master’s thesis scored an 88 out of 100 after which he graduated with his master’s degree in Global Logistics & Supply Chain Management from Kuehne Logistics University. 

Two peer-reviewed papers for Henry Stewart Publications’ Journal of Supply Chain Management, Logistics, & Procurement. Both papers passed the peer-review committee on the first submission. 

I’ve been a monthly editorial writer for Supply Chain Management Review – one of the leading supply chain publications – since 2023. My article series on The Perfect Order was published last year by SCMR. And a nice highlight last year was when Costco’s Connection magazine published my article “Don’t get foiled, what business leaders can learn from the sport of fencing” based on my third book Attack, Parry, Riposte: A Fencer’s Guide To Better Business Execution in their July 2025 issue for the For Your Business article. 

(You can find links to all of my articles – including some PDF downloads – on the Katzscan website on the Articles & Audio page which is under the Media menu link.) 

Over 60 US and international presentations. Over 60 US and international articles. 

All of the above while helping leading companies with their software (selection, implementation, utilization), supply chain (compliance, financial penalty chargeback reduction, relationship improvements), data (analysis, mapping), and business operations (increased efficiencies, documentation).  

It’s been quite the 30 years, much more than I could have imagined when I started out. 

I hope you’ll take the opportunity to look around the Katzscan website and see for yourself what I’ve been up to these past three decades. 

And if the past is prolog, I’m not done yet, as there is much more to look forward to achieving and many more companies for me to help. 

In appreciation to all of those who helped me get to where I am today.