In the mid-20th century, the military started using scientific methods to manage their massive global logistics. Back then, field manuals like FM 38-1, Logistic Supply Management, were vital for providing guidance and definitive glossaries for military logisticians. Nowadays, thanks to computers, both military and commercial logistics organizations manage global supply chains. But in the business world the question is, “where are the common supply chain glossaries and guides that ensure organizations and their systems communicate seamlessly?” Could this lack of a shared, definitive supply chain lexicon explain why we struggle with data interoperability, collaboration, and adopting advanced technologies?

In this article, I’ll first provide examples of where this lack of common supply chain glossaries is hobbling organizations both operationally and digitally. These examples include logistics industry challenges such as supply chain visibility, intermodal operations, and data integration initiatives as well as many other types of digitization initiatives. Further, I’ll offer suggested solutions to help us refocus our efforts on improving our supply chain glossaries. Indeed, this is what supply chains need to increase data interoperability, strengthen collaboration, and better leverage new data-centric technologies. 

Examples Illustrating How Ambiguities in Supply Chain Glossaries Hinder Interoperability and Technological Innovation

Absolutely, the absence of robust supply chain glossaries and definitions are a principal roadblock to realizing seamless interoperability and technological innovation within the logistics industry. Without a shared understanding of key terms and processes, organizations struggle to align their strategies, workflows, and systems properly. Further, this ambiguity leads to miscommunication, errors, inefficiencies, and a lack of interoperability, both operationally and digitally. Indeed, ambiguous logistics terminology and business glossaries are impeding technological innovation within our supply chains. Below are examples where this lack of operational clarity is hobbling both interoperability and technology adoption.

1. Supply Chain Visibility: Too Much Data with Little Insights due to Lack of Business Specificity.

Despite more than fifty years of striving for supply chain visibility, many organizations in the logistics industry still are not there in terms of having timely information and insights on their operational activities. This continuing difficulty is often because their IT visibility systems are trying to do everything. Thus, these systems many times do not provide the information needed, nor is it timely. Indeed, what many of these systems lack are well-defined business requirements on the specific type of visibility needed. As a result, this lack of business specificity has led to costly project overruns and sporadic supply chain visibility. Click here for more on the need for businesses to identify exactly what type of supply chain visibility they need.

2. Intermodal Interoperability: Lack of Cooperation and Specificity Hobbles Digital Tech Adoption. 

Within the intermodal industry there are many issues with organizations cooperating, but also there is an absence of clear business terminology. What’s more, this ambiguity affects both physical and digital interoperability. As a result, the intermodal industry is challenged both operational as well as slow to adopt new digital technologies. Click here for more information on interoperability problems within the intermodal industry.

3. Data Interoperability: Data Gets “Lost in Translation” Due to Lack of Business Definition. 

Here, supply chains have a dire need for their systems to transmit meaningful data to multiple logistics partners, but many times the data gets “lost in translation”. This is a data interoperability problem that is affecting the entire supply chain industry. Indeed, there are too many times that data recipients do not have a clear understanding of the data that they received. So, the problem is not so much a technical challenge, but that businesses have not provided enough business definition to the data they transmit.  Click here for more on the issues that supply chains have with data interoperability.

4. More Challenges With Supply Chains Adopting Emerging Information Technology Due to Operational Clarity Issues.

Further, there are countless other supply chain examples where tech innovations are stalling due to operational clarity issues. As a result, promising  tech innovations are stalled. For instance, this includes tech initiatives such as AI, digital identity, knowledge graphs, digital transformation, data analytics, digital freight bill processing, and Decision Intelligence to name a few.  For more details, see my write-up on this, Examples of Tech Innovations Stalled in Supply Chains Due to Operational Clarity Issues.

Indeed, these examples above highlight that there is a need for us to refocus our efforts on improving our supply chain glossaries. This is the way to unlock data interoperability, strengthen collaboration and leverage the tech we need to go to the next level in supply chain excellence. Below I offer some suggested solutions for making supply chain glossaries more effective in meeting both the challenges and opportunities of digitalization.

Solutions to Refocus on Supply Chain Glossaries to Increase Interoperability 

To address these operational and technical challenges, supply chain leaders must prioritize defining and agreeing on common lexicons for both their organizations and their systems.. This involves collaborating with subject matter experts to develop clear, specific, and actionable definitions for key processes, metrics, and data elements for these supply chain glossaries. Ideally, these operational definitions should be widely accepted, updated regularly, and available to all stakeholders. By increasing operational clarity, organizations can facilitate better collaboration, faster technology adoption, and ultimately, superior supply chain performance. Below I have identified several actions to help move forward with improving the operational clarity of our supply chain glossaries.

1. Create a Sense of Urgency to Fix Ambiguous Business Glossaries: They Are Hobbling Both Data Quality and Operational Excellence. 

Absolutely, there is a direct correlation between ambiguous business glossaries and the deficiencies we have in both data quality and operational excellence within our supply chains. Moreover, I would expect this to worsen in the future as we continue to digitize our supply chains. This will be especially true if we do not address the ambiguity within our business glossaries. Hence, we need business leaders to step forward to prioritize fixing our ambiguous supply chain glossaries. For more on aligning our business glossaries with data quality initiatives to include the use of measurements, see TDAN’s article, Business Glossaries and Metadata: Using the Glossary to Drive Your Quality Strategy.

2. Adopt an Operational Definition Format for Business Glossaries.

As discussed previously, it is time for business glossaries to be more understandable. Further,  dictionary definitions are no longer enough. Namely, business glossary definitions need to include a measure, a metric, to assure a common understanding. Currently, it is commonplace for supply chain organizations and their systems to misunderstand each other due to ambiguous supply chain terminology. For more examples of this lack of operational clarity within the logistics industry, see my article, Supply Chain Business Communications Need Clarity: This Is What is Hobbling New Tech Innovations.

Supply Chain Business Communications Need Clarity: This Is What is Hobbling New Tech Innovations

3. Leverage Knowledge Graph Technology to Provide Definition and Context to Business Glossaries.

In recent years, knowledge graph tech has made great advancements and utility to clearly define objects and concepts. This may be just what we need for business glossaries. Specifically, both tech companies and organizations can use knowledge graphs to enable both systems and users direct access to digital knowledge. Further, these knowledge graphs are understandable to both tech and non-tech users as well as executives for knowledge access. For more information, see ontotext’s article, The Value of a Knowledge Graph: Four Business Perspectives.

Knowledge Graph Tech: Enabling A More Discerning Perspective For AI

4. Move Toward a More Encompassing, Shared Business Glossary for Supply Chains.

As mentioned earlier, the supply chain industry has countless, overlapping business glossaries. Also, most of these glossaries cover only one part of the supply chain. For instance, there are glossaries focused on U.S. intermodal shipping and there are proprietary glossaries maintained by parcel carriers for their service guides. Indeed, this is just a handful of examples. Overall, these countless, overlapping glossaries create major collaboration challenges.

Hence, it’s in our best interest to aim for a more unified approach to business glossaries instead of our current fragmented method. One possible first step would be a collaborative approach where businesses first agreed on common business metrics. As a result, this would lead to common measures within supply chain glossary definitions. For instance, in this article, Aligning Supply Chain Metrics to Improve Value, from Lora Cecere, she discusses a hierarchy of common supply chain metrics. Indeed, focusing on common supply chain metrics could be a great starting point for collaborating on business glossary definitions. Without a doubt, ambiguous dictionary definitions are no longer enough.

5. Identify the Most Appropriate Organizations to Champion a More Collaborative Business Glossary Development Process.

Securing Data Interoperability In The Supply Chain: Can The Government Make For Better Results?

As discussed previously, organizations that participate in supply chains need to work toward the development of better business glossaries. However, there also needs to be concrete steps to minimize the overlap of business glossaries across the supply chain. This would be very advantageous especially for logistics and transportation activities that span across many organizations, regulatory environments, and geographic locations. 

Organizations that can facilitate better collaboration include Governments, standards development organizations (SDO), trade associations, tech vendors, and other large stakeholders. Indeed, as a minimum, Governments and other large stakeholders could provide incentives to encourage more collaboration. This will help to quicken the development of a more comprehensive set of business glossaries. For more ideas on how to improve supply chain collaboration and data interoperability, see my article, Securing Data Interoperability In The Supply Chain: Can The Government Make For Better Results?

Summary.

So in this article, I provided examples of where a lack of definitive, shared supply chain glossaries is hobbling organizations both operationally and digitally. Further, I have offered five solutions that would help us refocus our efforts on improving our supply chain glossaries. Indeed, this is what supply chains need to increase data interoperability, strengthen collaboration, and better leverage new data-centric technologies. For a more detailed discussion on the need for operational definitions within supply chain 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

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