Why IT Should Stop Neglecting Product Data

Loraine Lawson

The Automotive Aftermarket Industry Association estimates its industry could save as much as $1.7 billion annually-assuming $100 billion in transactions between suppliers and direct customers-if it could just eliminate the product data errors in the supply chain. That's a lot of cash for any industry-and all from bad product data.

 

Everybody loves to talk about the customer-who they are, where they live, what they like, what they don't like, where they shop and whether John B. Smith is the same as Jon Bernheim Smith. Meanwhile, product data is seen as a supply chain or manufacturing problem, according to Paige Roberts, market manager for the Integration Division at Pervasive Software and one of my favorite Twitter dataheads.

 

That would be fine if the business never had to deal with product data, but obviously it does-and that means business end users need access to that product data through enterprise systems.

 

Okay, what's the big deal, you say? Integrate it and move on.

 

Oh, if only it were that easy, but as Roberts explains in a recent Information Management article, it's easy to make costly mistakes with product data-like accidentally doubling the number of 7 -inch, 28-tooth steel circular saw blades when you actually meant to order 5,000 saws, plus 5,000, 7 -centimeter, 28-thread stainless-steel screws. Alas, who knew that the system would misinterpret a data field that read "7 28 stain"?


 

The problem is that business and IT have been so focused on customer data that most of the solutions, best practices, references and models only speak to customer data-and neglect to take into account the idiosyncrasies of product data.

 

In the article, Roberts explores the five issues that make product data so darn tricky:

 

  1. Description fields (the free text field allows people to put in whatever descriptions pop into their heads at that moment). Hullo unstructured data! These really need to be replaced by structured fields, she points out.
  2. Ignored standards. As with all things tech-and, to be fair, most things period-there are plenty of standards but no one's using them.
  3. Inconsistency in the data. Customer data is pretty straight-forward. You have an address? Great, the post office has standards and everybody knows them and pretty much follows them. You have a first name and a last name-a pretty widely followed naming convention that's easy to program to. But that's just not the case for product data, she notes.
  4. Language barriers. It's a global economy, and a global supply chain. Unfortunately, the words are not global, and neither is the data describing it. Are you sure you just ordered the right engine?
  5. Missing information. 'Nuff said.

 

Unfortunately, she doesn't supply any answers except to find the right people, consultants and vendors (hey, kudos for the subtle marketing message there, Paige!). But then again, it's not an easy problem, so I can't blame her for that.

 

Fortunately, awareness is a big part of the solution. Given the Automotive Aftermarket Industry Association's estimates on the savings for one industry, I have to think it's worth your time to investigate the problem further.



Add Comment      Leave a comment on this blog post

Post a comment

 

 

 

 


(Maximum characters: 1200). You have 1200 characters left.

 

null
null

 

Subscribe to our Newsletters

Sign up now and get the best business technology insights direct to your inbox.