Six key questions to improve the quality of your item master data


Eniko Tucker

Following customer data, the second-most popular data domain in a master data management (MDM) program is usually item/product data. Typically companies concentrate on their customer domains first, as their sales and marketing operations usually win the argument that better servicing customers should be their number-one objective.

But if you’re a supply chain or engineering VP, having access to the most up-to-date and accurate information is critical to your business operations because it enables you to make the right decisions based on validated insights.

Understanding how improved data quality can reduce operational costs and boost efficiencies might not be immediately recognizable, especially without a sound root-cause analysis that can shed light on process breakdowns or data-quality issues. Knowing the right questions to ask to uncover the issues crippling your organization is the first step to improving your item MDM and increasing your ROI.

The value of root-cause analysis

In our experience, we’ve seen that organizations often do not take the time to perform thorough root-cause analysis of their customer complaints or operational process breakdowns. Thus, they fail to recognize how less than desirable data quality contributes to operational impediments. Companies that put blinders on toward data quality may miss out on the opportunities of a strategic MDM implementation, which—if executed right—results in improved data quality and operational gains for trade compliance, purchasing, engineering, shipping—basically the entire supply chain.

Six key questions

We believe that maintaining an accurate item master with a single view of truth can help supply chain, engineering, and operations realize significant benefits. Quantifying the business benefits of item MDM (whether financial or operational) requires a deep understanding of your organization’s business processes and corporate drivers—and realizing that the correlation between better quality of item/product data and improved business outcome is not always obvious. Here are six questions to ask to help your company become more data-centric.

How much money did you pay in penalties to customs agencies this year?

Every day companies ship goods to and from the United States. If companies do not pay close attention and comply with applicable trade compliance laws, rules, and regulations, the US Customs and Border Protection (CBP) agency or any of the international customs agencies may impose fines, penalties, forfeitures, or liquidated damages. Section 484 of the Tariff Act states: “the importer of record is responsible for using reasonable care to enter, classify, and determine the value of imported merchandise… an importer of record’s failure to exercise reasonable care could delay release of the merchandise and, in some cases, could result in the imposition of penalties.”

Data inaccuracies in trade compliance attributes (e.g., unit price; country of origin [COO]) can thus result in serious customs fines and penalties. How confident are you that your COO is accurately labeled on your commercial invoice and your packaging? Are you at risk of customs’ fines due to missing or inaccurate values in your item master?

How many orders do you have that are past the promised ship date?

There could be several reasons why a shipment does not arrive as expected—it may not have been shipped on time, delivered to the wrong address, damaged during the shipping process, etc. Have you taken a closer look at the data attribute “lead time” and the measurement “on-time shipment”? If parts required for the assembly of the item you need to ship are not available in your warehouse, production cannot produce the finished goods. Improving the quality of your lead-time data can improve your warehouse operations efficiency and help you avoid customer dissatisfaction.

Are your customers confused and complaining about your products?

Do you ever talk to your fellow colleagues from customer care about the conversations they have each day with complaining customers? If your product descriptions are misleading and customer-service reps are routing calls to product management all the time, perhaps it would be worth concentrating your efforts on improving the accuracy of your product descriptions. It would not only eliminate confusion, it would also eliminate unnecessary work for switchboard operators, product management, and everyone in between.

Did you fail a compliance audit this year?

Products are categorized into one of the nine “hazard-class” categories depending on the type of hazard they can cause (e.g., explosives, gases, flammable solids, radioactive materials, corrosives, etc.). Failure to classify your products properly may not only result in serious fines but can have tragic consequences. If your products’ hazard classifications are not accurate you run the risk of not passing trade compliance or compliance engineering audits.

Do you know which business unit deserves recognition for generating the most revenue last quarter?

The product hierarchy (reference data) is used to group products according to different criteria. Upon review of your product categories, you may discover that your products are not categorized into the proper item group, and therefore causing issues with financial reporting. If the data lacks quality it may be impossible to do consolidations.

Are your service representatives having difficulty servicing your customers?

The product data attribute “replaced by” or “superseded by” explains whether there is a replacement for a particular item. Make sure your system tells service representatives clearly whether your products are still available or have been superseded as part of a new product offering. You can improve productivity by eliminating unnecessary work to chase down the correct information from your product management team.


While it can be a daunting task to explain the value of item data, the importance of closing the gaps that might be causing pain points throughout your organization cannot be understated. As you start deepening your understanding of the processes that consume data and making the correlation of how data quality of certain data elements can lead to cost savings, revenue generation, reduced risks, or better compliance, you will be able to influence the adoption of item MDM across your organization—because you will be able to impact the bottom-line profit.


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