Think your supply chain data problems stem from poor technology? 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 for measurable, operational definitions over traditional dictionary definitions. Moreover, I’ll spell out that business glossaries are the missing link to supply chain collaboration and data interoperability. Indeed, they are more than data dictionaries that IT departments use to set up systems’ data interfaces. Also, I’ll provide examples of how existing supply chain glossaries fail, highlighting how their ambiguous dictionary definitions hinder 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.

A data dictionary is your system’s technical rulebook – it defines data fields, formats, and relationships. For instance, an “order_date” must be YYYY-MM-DD or “quantity” must be a positive integer. But a business glossary? That’s your supply chain’s common language. It explains what “order complete” actually means to your business. For example, is it when the item ships, when it’s delivered, or when payment clears? So, without this clarity, your trading partners might think they’re speaking the same language, but they’re not even close. Next, let’s look at some definitions.

a. Data Dictionary Definition.

First, a data dictionary is:

“A place where business and/or technical terms and definitions are stored. Typically, data dictionaries are designed to store a limited set of metadata concentrating on the names and definitions relating to the physical data and related objects.“

DAMA

b. Business Glossary Definition.

Next, a business glossary is:

“a collection of business terms and their definitions. Its main goal is to establish a shared understanding of concepts within an organization, creating a unified language.”

castordoc

So to compare, a business glossary is your company’s shared language guide – ensuring everyone has a common understanding of key business terms and definitions. A data dictionary, on the other hand, is simply the technical manual defining data formats and rules. Ideally for business glossaries, a supply chain should have one business glossary because its entire purpose is to share understanding. However, when it comes to data dictionaries,  there are multiple documents as each systems’ data interfaces has different technical requirements. 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. 

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

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 integrating with trading partners.

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

Now, from an IT data integrator perspective, all that is needed to transfer data from one system to another is a good data dictionary as described above. Usually a data dictionary is found within a data provider’s specification documentation such as for an application programming interface (API), proprietary file transfer, or electronic data interchange (EDI) to name a few. 

Indeed, with a well-specified data interface document, it is fairly easy for supply chain partners to achieve data integration, seamless data transfer from one system to another without errors. However, that does not necessarily mean that the data will be actionable or understandable to the receiving system or organization. In fact, this is where data interoperability comes in. Data interoperability is when the data sent is actually understood. So, data interoperability encompasses both data integration and shared understandability.

b. Business Glossaries Needed for Data Interoperability.

So, the 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 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

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

Despite their importance, current business glossaries often fail to support the rapid global and digital expansion of supply chains. Indeed, traditional business glossaries do not offer sufficient, measurable definitions for digital supply chains to transfer meaningful, actionable data. For instance,  look at how different companies define “lead time” – some count from order placement, others from order acceptance, and still others from payment clearance. Indeed, these clarity issues adversely affect supply chains more than other industries. This is because many logistics operations have the need to collaborate across business functions as well as across geographic borders dramatically increasing the chances for misunderstandings.

a. Examples of Supply Chain Business Glossaries That Lack Operational Clarity.

Below are three examples of business glossaries in the supply chain industry that lack measurable accuracy that operational definitions can provide.

1) 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 data actually means.

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

Within this 2023 ASTM standards style document, the terminology section describes terminology 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.”  

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. 

3) 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, especially when multiple documents are involved.

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. 

b. Overlapping Supply Chain Business Glossaries.

Another 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 scope of the work to collaborate and improve the clarity of business glossaries within the supply chain industry is immense. How can the supply chain industry achieve true collaboration and data interoperability when it has conflicting, ambiguous business glossaries. 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.

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

Now, here’s the painful truth: you can spend millions on the latest supply chain software, but if your business glossary is weak, you’re building on quicksand. 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 your supply chain, 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:

a. 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. 

b. 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. Indeed, disparate business glossaries, some proprietary, are a major cause contributing to functional data silos that are hobbling supply chain operations today.

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

Lord Kelvin

Next Steps.

This article makes it clear that our supply chains have less than adequate business glossaries. As a result, both business collaboration and data interoperability suffer. In fact, despite the amount of money we spend on new information technology, this business glossary issue is the biggest impediment for supply chains to achieve any real ROI on their tech investments.

So, what will get us back on track? It is for us as an industry to overhaul our supply chain business glossaries where we use measurable operational definitions to assure understandability between trading partners. Undoubtedly, this will assure that the data that our supply chain systems transmit is understood by our trading partners. For more details on this solution to get us out of this interoperability mess, 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

For more from SC Tech Insights, see the latest articles on Interoperability, Information Technology, and Supply Chains.