Nowadays, logistics organizations know that their data holds the key to incredible insights and a competitive edge. However, many struggle to harness this power due their data being scattered across many systems, linked by a labyrinth of data integrations. Worse, even if this data gets transmitted to another system, the meaning of the data often gets lost in translation, resulting in “dumb” data that is practically useless. As supply chains move forward with digitalization, there is indeed a better data integration approach than just continuing to expand this tangled mess of data connections. This better data integration approach is called semantic interoperability.

In this article, I’ll explain what semantic interoperability is and why it is the best approach for businesses to exchange meaningful data across their supply chains. Further, I’ll detail the benefits of semantic interoperability and how other industries and disciplines are advancing it. Also, I have four recommendations on how best for logistics and standards organizations to move forward with achieving semantic interoperability. First of all, businesses need to adopt a data-centric mindset. Also, we need knowledgeable business leaders leading these interoperability efforts. Further, I’ll highlight how we can leverage emerging tech such as AI and knowledge graphs to accelerate the implementation of semantic interoperability in supply chains.

1. Semantic Interoperability May Be the Answer, But What Is It?

Most supply chain leaders may not be familiar with the term “semantic interoperability,” but they are likely acquainted with “data integration.” Indeed, both terms relate to the transfer of data between different systems, yet semantic interoperability emphasizes the understandability of data once received. It is crucial that both sender and receiver share a common understanding of the transmitted data. Below is a simple definition of semantic interoperability

Semantic Interoperability Definition 

“Ensuring what is sent is what is understood”

European Commission – EIF

What I like about this definition is that it clearly identifies the intent of semantic interoperability. Namely, that the most crucial component of digital communications is that both the sender and receiver have a mutual understanding of what was sent. Moreover, semantic interoperability ensures that the data is useful and actionable for supply chain partners. For a more detailed explanation of semantic interoperability, see my article, This Is What Semantic Interoperability Is: It’s The Best Last Chance For Seamless Supply Chains.

This Is What Semantic Interoperability Is: It’s The Best Last Chance For Seamless Supply Chains

2. What Would Happen If We Achieved 100% Semantic Interoperability in Our Supply Chains?

Imagine a world where all supply chain systems acted in concert, seamlessly exchanging meaningful data. Indeed, each link in the supply chain would have near-perfect information (total visibility) to act with optimal efficiency. Better yet all logistics planners and operators could fully leverage data-centric applications such as AI and data analytics. In fact, there would be no more miscommunications, less guessing, and minimum exceptions that today ripple across supply chains. Without a doubt, this lack of semantic interoperability causes disruption, mayhem, and ultimately dissatisfied customers. To list, below is just a sampling of the many benefits of achieving semantic interoperability within supply chains.

The Many Ways Supply Chains Benefit From Semantic Interoperability

The bottom line is supply chain data interoperability enables supply chain staff and systems to take action with quality data that is highly accurate, complete, not duplicated, timely, and meaningful. Moreover, it is data that supply chain partners can trust, a Single Source of Truth (SSOT). Indeed, semantic interoperability results in supply chain excellence and unleashes innovation. For a more detailed discussion on the challenges and benefits of data interoperability, 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. Examples of Where Other Disciplines Like Healthcare, IoT, and Language Translation Are Advancing Toward Semantic Interoperability.

It is not just supply chains that are grappling with semantic interoperability. In fact, interoperability is critical for most industries and disciplines to include healthcare, defense, language translation, and Internet of Things (IoT) to name a few. What’s more, many of these disciplines are well on their way in this transformative process toward semantic interoperability. The question is, do these disciplines hold a blueprint that the logistics industry can emulate to drive innovation within supply chains? To help answer this question, below are some examples of semantic interoperability initiatives on-going in other industries and disciplines.

Examples of Five Semantic Interoperability Advancing in Different Industries

Semantic Interoperability Examples That Turn The Tables From Having Dumb Data Communications To Being Really Informative

• Healthcare: For instance, semantic interoperability through health information exchanges allows healthcare systems to share patient data that is both secure and meaningful.
• Department of Defense: Within DoD, semantic framework ensures that data from different stakeholders is not only collected but also understood and utilized effectively.
• Language Translation Software: In this case, translation software are using neural networks to discern language patterns to efficiently translate more complex sentences.
• Internet of Things (IoT): Here, IoT vendors and standards groups have successfully collaborated to enable their devices to communicate and work together intelligently.
• Logistics Industry: Indeed, semantic interoperability is crucial for attaining seamless supply chains. However, the quest for total interoperability has proven elusive for most in logistics. Without a doubt, the biggest challenge in supply chains is the industry’s traditional IT data integration approach, with their custom data interfaces between application-centric data silos.

For a detailed explanation of how semantic interoperability is advancing in these industries, see my article, Semantic Interoperability Examples That Turn The Tables From Having Dumb Data Communications To Being Really Informative.

So, there are many industries and disciplines that are both committed and having success with achieving semantic interoperability. However, many supply chain organizations struggle with semantic interoperability because of their tangled web of system integrations that tie up their data in application-centric silos.

4. Four Things Need to Happen For Supply Chains to Achieve Semantic Interoperability.

In the fast-paced world of logistics, seamless supply chains are the holy grail. Imagine a world where data flows effortlessly between systems, where every stakeholder speaks the same language, and where decisions are made with crystal-clear insights. This isn’t just a pipe dream; it’s the promise of semantic data interoperability. Indeed, semantic interoperability is more than traditional IT data integration, with their custom data interfaces between application-centric data silos. In fact, semantic interoperability is totally focused on the meaningful exchange of data that is both understandable and actionable across the supply chain. This is the way to achieve seamless supply chains.

In fact, below I’ll highlight my recommendations for a four-step process that logistics organizations can use to transition from their current tangled web of custom data integrations to a seamless supply chain.

Four Steps to Attain Supply Chain Data Interoperability

1. Adopt a Data-Centric Mindset. This is the first step. Here, supply chain organizations must shift their mindset from application-centric to data-centric. The key is to stop treating data as a by-product, and start using it as a strategic asset.
2. Leverage Standards Development Organizations (SDOs). Indeed, supply chains need to do better at leverage emerging and established data standards. This will assure advancement toward meaningful data exchanges.
3. Move Away From Proprietary “Dumb” Data Interfaces. Without a doubt, we need to move away from costly proprietary data interfaces that are both fragile and lock our precious supply chain data in rigid application silos.
4. Leverage Emerging Digital Technologies and Methodologies. Unquestionably, supply chains need to leverage emerging tech such as AI, knowledge graphs, and digital identity tech to further enable semantic interoperability within their organizations.

For a much more detailed explanations of these four steps to achieve supply chain interoperability, see my article, Semantic Digital Interoperability: This Is The Ultimate Way To Make Supply Chains Seamless.

Semantic Digital Interoperability: This Is The Ultimate Way To Make Supply Chains Seamless

Conclusion.

In the past, our supply chains were transformed by standardizing bar codes and ocean containers to achieve better interoperability. Now to fully leverage data-centric tech like AI, we need to achieve interoperability with our supply chain data. In this article I offer a blueprint with four recommendations on how best for logistics and standards organizations to move forward with achieving semantic interoperability. First, businesses need to adopt a data-centric mindset. Further, we need knowledgeable business leaders working with SDOs to lead these interoperability efforts. Additionally, it is time to move away from proprietary “dumb” data interfaces. Lastly, we need to leverage emerging tech such as AI and knowledge graphs to accelerate the implementation of semantic interoperability in supply chains.

OK, semantic interoperability will not happen overnight, but it will happen over time to transform your logistics operations. Just think what the standardization of bar codes and ocean containers did for the industry in the past.

Logistics Data Interoperability: Advice To Make It Understandable, Usable, Secure

Need help with an innovative solution to make your supply chain systems work together? I’m Randy McClure, and I’ve spent many years solving data interoperability and visibility problems. 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 proof-of-concept and operational pilot projects 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.

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