Think your supply chain woes stem from poor data quality? Think again. The real culprit lurking behind failed system integrations and botched trading partner collaborations is far more basic – weak business glossaries. It’s like trying to build a house where every contractor has their own definition of what a “door” is. When organizations can’t agree on what basic supply chain terms mean, even the most sophisticated software solutions become expensive money pits. This gap not only hampers effective communication but also leads to data silos, inefficiencies, and missed opportunities for innovation. 

This article looks at the shortcomings of current supply chain business glossaries. Specifically, there is a need to replace traditional lexicon’s dictionary definitions with measurable, operational definitions. Moreover, I’ll spell out that business glossaries are the missing link for both supply chain collaboration and data interoperability. Also, I’ll provide examples of how existing supply chain glossaries fail, highlighting how their ambiguous dictionary definitions hobble technology adoption. Lastly, I’ll point to a better way to achieve seamless, understandable data interfaces by remaking our business glossaries to use operational definitions.

1. Business Glossaries and Data Dictionaries Defined.

First, when it comes to seamless data integrations, technical data dictionaries and business glossaries play completely different roles. A data dictionary is a technical rule book for your system and its interfaces, defining data fields, formats, and relationships. In contrast, a business glossary provides a common language for your supply chain to operate and collaborate. To elaborate, let’s look at the definitions for these reference sources.

So to compare, a business glossary is a shared language guide for a business, or even a whole industry – ensuring everyone has a common understanding of key business terms and definitions. For instance, a glossary would clarify business terms like “order complete” to ensure all stakeholders are on the same page. A data dictionary, on the other hand, is simply the technical manual defining data formats and rules. For example, it would specify that an “order_date” should be in YYYY-MM-DD format or that “quantity” must be a positive integer.

For a more detailed discussion on these terms, see castrodoc’s article, What is a Data Glossary? and atlan’s article, Data Dictionary: Examples, Templates, Best Practices, and How To Make a Data Dictionary. 

“A data dictionary is a technical rule book for your system and its interfaces … In contrast, a business glossary provides a common language for your supply chain to operate and collaborate.”

2. Achieving Data Interoperability: A Data Dictionary Minimizes Errors, A Business Glossary Maximizes Understandability.

So, data dictionaries keep your systems from crashing, but business glossaries keep your operations from crashing. Take a simple term like “on-time delivery.” Your data dictionary ensures the date field is formatted correctly, but your business glossary defines whether “on-time” means “arrived at the warehouse” or “unloaded and available for picking.” This distinction isn’t just a case of arguing over definitions – it’s the difference between smooth operations and chaos when both collaborating and integrating with trading partners and their systems. Let’s now dig into what roles these two authoritative reference sources play in terms of supply chain interoperability.

a. Data Dictionaries Needed for Both Data Integration and Interoperability.

While a well-specified data dictionary – typically found in API, EDI, or proprietary specifications – enables seamless integration and error-free transfer between systems. However, integration alone does not guarantee that data is actionable or understandable. Without a doubt, data interoperability solves this knowledge gap by pairing seamless data transfer with shared understandability. Only by achieving both can the Supply Chain Industry move beyond mere data exchange to a “Data Ready” ecosystem where information is immediately useful across all organizations and machines.

b. We Need Business Glossaries to Achieve Data Interoperability.

So, the biggest challenge with data exchange isn’t technical – it’s semantic. Indeed, most organizations can move data fairly easily between systems. However, if senders and receivers interpret the data differently, it’s useless. That’s why a business glossary matters. It ensures everyone understands business terms the same way, making true data interoperability and business collaboration possible. For a more detailed discussion on the data interoperability within supply chains, see my article, Let’s Breakthrough The Data Interoperability Nightmare: It Is The Best Way To Unlock Supply Chain Innovation.

Let’s Breakthrough The Data Interoperability Nightmare: It Is The Best Way To Unlock Supply Chain Innovation

“… data dictionaries keep your systems from crashing, but business glossaries keep your operations from crashing.”

3. Supply Chain Examples of Business Glossaries Lacking Operational Clarity.

Traditional business glossaries are failing our digital supply chains. This is because their definitions for business terms are not measurable to assure mutual understanding between organizations and their systems. In logistics, where collaboration spans many functions and borders, ambiguous terms create significant misunderstandings and friction. For instance, the business term “lead time,” is vaguely defined and inconsistently calculated, ranging from measuring from order placement, order acceptance, or payment clearance. This lack of clarity disproportionately impacts the Supply Chain Industry, leading to costly mistakes and fracturing seamless interoperability. The following three examples illustrate how current industry glossaries and their “plain old” dictionary definitions lack measurable accuracy.

a. GS1 Attribute Business Definitions Standard.

This 2019 GS1 business definitions standard by the Consumer Goods Forum identifies and defines 180 attributes (business terms). In this case, the definition specification includes the following data elements: business name, business definition, examples, and usage statement. Though useful, this particular business glossary does not have an explicit requirement for a measure or metric for each business term. For instance, it defines “First Ship Date/Time”, but fails to specify whether the time is local to the vendor or other time standard such as Greenwich Mean Time. Hence, this standard enables the transfer of data without error, but leaves too much room for misinterpretation of what the date actually means.

b. Form and Style for ASTM Standards: Part E – Terminology.

Within ASTM International’s 2023 standards style document, the terminology section describes definitions as follows:  

“Write definitions of terms and definitions specific to a standard in the dictionary-definition form. Include term, part of speech, definition, and, when applicable, a delimiting phrase.”  

ASTM standards style document

In this case, even though this glossary definition standard includes “a delimiting phase”, it still does not explicitly require a measure or metric. Thus, this business glossary with this dictionary-type definition standard is open to misinterpretation from both a business and automation perspective. 

c. FMC Maritime Transportation Data Initiative (MTDI) Lexicon.

This 2023 Recommendations on the Maritime Transportation Data System Requirements, Appendix 1.7, from the Federal Maritime Commission (FMC) provides approximately 200 terms as part of a MTDI Lexicon. Again, this is useful, but it only provides dictionary-type definitions. For instance, it defines “received” as a “The event associated with receiving a document or a set of information …”. However, without specifying measurable thresholds (like type of document or document ID requirement), it is impossible to consistently identify or act on this event information. For instance, an international shipment could have multiple documents associated with it such as a BOL or a commercial invoice, or a customs form.

So, these are just a few examples of business glossaries that lack operational clarity. The primary reason for these ambiguities is that they do not require a measure or metric in defining business terms and concepts. Indeed, these examples of operational ambiguity are representative of most, if not all, supply chain business glossaries. 

“Traditional business glossaries are failing our digital supply chains. This is because their definitions for business terms are not measurable to assure mutual understanding between organizations and their systems.”

4. The Problem with Overlapping Business Glossaries.

Another self-inflicted challenge with supply chain business glossaries is that there are too many of them. For example, many standard development organizations (SDOs) such as UN/CEFACT, WCO, GS1, IMO, IATA, ICC, and ASTM International offer business glossaries for supply chain organizations. There are also countless proprietary business glossaries developed by businesses, tech vendors, agencies, and associations in the supply chain industry. To illustrate, see DFM Data Corp “Onion” diagram below that depicts a representative proportion of different organizations directly or indirectly involved with supply chain standards development. Moreover, many of these organizations also develop their own business glossaries.

So, the supply chain industry has an extremely difficult task ahead to bring clarity to their conflicting, ambiguous business glossary definitions. Nevertheless, how else can our supply chain industry achieve true collaboration and data interoperability? For more on the challenges with aligning business glossaries within the supply chain, see Michael Darden’s posting, Enabling Fluid Global Trade by Aligning Terms, Data, and Attributes.

“Another self-inflicted challenge with supply chain business glossaries is that there are too many of them.”

5. Business Glossaries – The Fatal Flaw of Supply Chain Collaboration and Data Interoperability.

Now, here’s the uncomfortable truth: we can spend millions on the latest supply chain software, but if our business glossaries are weak, we’re building on quicksand. For instance, when Company A’s“urgent order” means “ship within 24 hours” but Company B’s means “ship next available,” no amount of technical integration will prevent service failures. This misalignment isn’t just causing confusion – it’s destroying value across our supply chains, one misinterpreted term at a time. To sum it up, there are basically two major deficiencies with our current supply chain business glossaries. These include:

• Lack of Measurable Business Definitions Impede Understandability. The current state of our supply chain business glossaries are subject to misinterpretation, both operationally and for advancing digital innovations. There is a need for operational clarity, namely, measurable operational definitions. 
• Overlapping Business Glossaries Hobble Collaboration and Interoperability. Without a doubt, today there is no “master” business glossary that applies to all logistics functions or is universally accepted globally. As a result, all these different business glossaries impeded cross-functional and end-to-end data interoperability and collaboration across the supply chain.

“we can spend millions on the latest supply chain software, but if our business glossaries are weak, we’re building on quicksand.”

Next Steps.

Despite significant investment in information technology, fragmented and ambiguous business glossaries remain the primary impediment to supply chain ROI. To overcome this, the industry must rationalize overlapping glossaries and establish standardized, measurable definitions. Eliminating this semantic ambiguity ensures that data exchanged between trading partners is universally understood. By doing this we transform disjointed communication into a seamless, “Data Ready” ecosystem that drives true collaboration and operational success. For more details on how we can improve our feeble business glossaries, see my article, Poor Operational Definitions Impede Supply Chain Tech Adoption: Now Is the Time For A Big Change.

Poor Operational Definitions Impede Supply Chain Tech Adoption: Now Is the Time For A Big Change

“If you cannot measure it, you cannot improve it.”

Lord Kelvin

Need help with an innovative solution to make your supply chain data ready? I’m Randy McClure, and I’ve spent many years solving data readiness challenges to help decision-makers gain better, faster insights and for organizations to leverage data-intensive technologies. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in pilot projects and program management for emerging technologies. If you’re ready to modernize your data infrastructure or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.

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