Digital supply chains are supposedly the new frontier. But let’s ask ourselves, “How is our digital transformation really going?” Maybe not as well as we’d hope? One major stumbling block for many digitization efforts is the inability of systems and technologies to communicate with one another. What we have is a data integration challenge, or more specifically, a data interoperability problem. Most importantly, we need to solve this critical problem as it is the number one barrier holding us back from achieving a seamless, data-ready supply chain and maximizing our tech investments.

In this article, I’ll share with you solutions that enables your organization to achieve data interoperability and get your systems talking to each other. First, I’ll highlight the current disjointed state of supply chain data. Next, I’ll detail for you the three key components needed to achieve data interoperability in today’s digital world. Namely, these are 1) a data transfer capability, 2) common terminology for intelligent data sharing, and 3) a method to achieve mutual trust between systems, users, and devices. So, let’s get started.

Current State of Supply Chain Data: Fragmented, Functional Silos, Poor Structure, Few Insights.

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

Supply chain data is a nightmare to work with. Indeed, it consists of disjointed, legacy software silos that actually inhibit visibility and collaboration. What’s worse is that most logistics data remains trapped within these departmental silos, each with its own data structure and format. Consequently, most of us are drowning in a sea of data that’s hard to fathom, and even harder to act upon. What’s worse is that within all this “big data” are precious insights buried under layers of incompatibility and ambiguity. 

For a more detailed discussion on supply chains’ data interoperability nightmare, see my article, Let’s Breakthrough The Data Interoperability Nightmare: It Is The Best Way To Unlock Supply Chain Innovation.

“Supply chain data is a nightmare to work with … consists of disjointed, legacy software silos that actually inhibit visibility and collaboration.”

The Three Ingredients Needed to Achieve Data Interoperability: Data Communications Channels, Shared Meaning, Mutual Trust.

Most of us will agree that to remain competitive in today’s world, our organizations must not only digitalize, but also be data ready. Indeed, how can organizations leverage emerging technologies and seamlessly exchange information, if their data is not ready and sharable? Hence, a critical component of this digitalization effort is data interoperability that enables seamless information exchange across systems. However, data interoperability is more than just having the capability to transfer data back and forth. In fact, there are three ingredients to achieving true data interoperability. These three components include: 

The Three Components to Achieve Data Interoperability

• Data Communications Channels. Capability to exchange data between systems and devices.
• Common Data Terminology to Share Meaningful Information. Must have standard terms and methods to effectively assure that the data transmitted is understood.
• Method to Achieve Mutual Trust.  Need to leverage digital identity technologies to enable trust between digital network partners, software agents, and devices. 

Next, I’ll detail each of these three critical ingredients needed to achieve data interoperability.

1. Data-Level Interoperability: A Communications Channel That Enables Data Transfer Between Systems.

The Best Ways To Access Data – Tech Solutions To Unlock Your Data Silos

First, the underlying substructure of data interoperability is the technical capability to both transfer and access data. This includes capabilities like using an API (Application Programming Interfaces) or a data transformation process such as Extract, Transform, Load (ETL) to integrate data.  Nowadays, most organizations have some level of capability for data-level interoperability.

Also, for a given data integration project, the IT integrator will need to decide on which type of data transfer method to use. This will depend on various factors. For instance, considerations include things like data set size, in-house IT expertise, data transfer types available from data sources, and budget limitations. While many businesses can handle the more simple projects internally, some integration projects may demand advanced cloud integration tools or skilled third-party vendors for success. For a more detailed discussion on types of data transfer solutions, see my article, The Best Ways To Access Data – Tech Solutions To Unlock Your Data Silos.

“… the underlying substructure of data interoperability is the technical capability to both transfer and access data.”

2. Semantic-Level Interoperability: Business-Led, Tech-Enabled To Assure the Data Sent Is Understood.

The second component of data interoperability is it has to be semantic, providing shared meaning of the data sent. Without a doubt, in data communications, both the sender and receiver need to have the same business interpretation of the data that is transferred from one system to another. That is the essence of semantic interoperability. Without this level of fluency, data is just a collection of digital bytes; with it, data becomes a reliable asset for electronic business transactions. As a result, businesses can move beyond simple data exchange and toward the real goal: the ability to take immediate, intelligent action on incoming information. For a concise definition of semantic interoperability, see below:

“Ensuring what is sent is what is understood”

European Commission – EIF

Today, semantic interoperability is the biggest stumbling block for digital supply chains. First, we have more systems increasingly generating more data, but the data is not have shared meaning across the supply chain. Second, most organizations fail to understand that data fluency problems are not necessarily a tech problem; it is primarily a business problem. See discussion below.

a. The Digital Transformation Challenge: More Complex Systems Generating More Data That Gets Lost in Translation.

The Way of Digital Transformation: A Business First, High Tech Reinvention 0f Processes and Culture

Without a doubt, a major challenge we have today is that we are generating and transferring increasingly more data for more complex business uses. Hence, as this massive growth in data continues, organizations struggle to share data at scale that is not only understandable, but actionable. As a result, massive amounts of data may be transferred between systems, but the meaning of the data gets lost in translation.

For more on tackling the problems with digital transformations, see my article, The Way of Digital Transformation: A Business First, High Tech Reinvention 0f Processes and Culture.

b. Semantic Interoperability is a Problem for Business to Solve.

So, it is critical that supply chain organizations start to realize that data interoperability is not just an IT problem to solve. Business organizations, not IT, must make sure that the data that their systems transfer is understandable and actionable to the receiving organization and their systems. For example, let’s look at a transportation carrier transmitting data to a shipper. In this case, one of the data elements is a date field. The question for the shipper is what does this date field represent. Is it a ship date, manifested created date, data transmission date, or just a random date? Indeed, this is a semantic interoperability problem, not a technical problem!

Ultimately, business must clearly define all these data elements and assign meaning to them. Based on my years of experience working with thousands of shippers and third-party logistics (3PL) providers, I recommend that businesses take the following four key actions.

Business-Led Improvement Areas to Achieve Semantic Interoperability

Achieving Logistics Interoperability: The Best Way to Breakthrough The Tangle Of Dumb Data Integrations

• Adopt a Data-Centric Mindset; Stop Being Application-Centric, treating data as a byproduct.
• Partner With Standards Development Organizations (SDO) to Advance Semantic Interoperability.
• Avoid Proprietary Data Interfaces.
• Leverage AI and Knowledge-Centric Tech to Enable Data Standards to Learn, Evolve, and Expand.

For a detailed discussion on semantic interoperability and how to move forward with achieving it in your business, see my article, Achieving Logistics Interoperability: The Best Way to Breakthrough The Tangle Of Dumb Data Integrations.

“… both the sender and receiver need to have the same business interpretation of the data that is transferred from one system to another. That is the essence of semantic interoperability.”

3. Trusted Interoperability: Leveraging Digital Identity Tech to Achieve Confidence in the Data Exchanged by Partners and Entities.

Data interoperability is only as strong as the trust you place in its source. Today we are at a crossroads where isolated data silos give way to a sprawling web of systems, AI agents and IoT devices. Without a doubt we are facing a security and regulatory minefield that demands a new level of security. Consequently, the central challenge for modern supply chains is balancing seamless data access with rigorous security. Hence, a comprehensive digital identity solution is now a crucial component of data interoperability to overcome today’s unprecedented data security challenges.

Indeed, it is time for all data owners to adopt robust digital identity solutions that can instantaneously authenticate and verify every “who” and “what” accessing their data. To gain a better understanding of the digital identity landscape, let’s first start with a definition of digital identity.

Definition of Digital Identity

“A digital identity is an online presence that represents and acts on behalf of an external actor in an ecosystem. An identity could belong to a legal entity, a financial intermediary, or a physical object … a digital identity is verified by a trust anchor, … so that those interacting with that actor’s digital identity have confidence the actor is who and what it claims to be.”

World Economic Forum

Digital Identity In Logistics And What To Know – The Best Security, Scary Risks

In the early days of data transfer, digital identity was simple. This was because connections were few, and a shared password or a quick call between IT teams was enough to secure an integration. Today, that simplicity has vanished. We now face an astronomical number of connections, persistent bad actors, rigid compliance mandates, and high levels of automation that demand constant, dynamic integration. Hence, in this complex landscape, digital identity has moved from a back-office task to a critical pillar of data interoperability.

For a detailed discussion of digital identity technology, especially for the supply chain industry, see my article, Digital Identity In Logistics And What To Know – The Best Security, Scary Risks. Key topics discussed include: 

“… a sprawling web of systems, AI agents and IoT devices … a security and regulatory minefield that demands a new level of security. Consequently, …a comprehensive digital identity solution is now a crucial component of data interoperability …”

Conclusion.

In summary, logistics leaders can only realize the benefits of a digital supply chain by conquering data interoperability. Indeed, data interoperability is a business-led, tech-enabled pursuit. Only through intelligent data exchange between systems and devices, will you achieve your digitalization objectives. As discussed, there are three key ingredients needed to achieve data interoperability in today’s digital world. Namely, these three data interoperability components are:

• A data transfer capability
• Common business terminology for intelligent data sharing
• A secure method to achieve mutual trust between systems, users, and devices.

Lastly, besides the references I have already cited above, please take a look at this article, Data Interoperability For Supply Chains: The Best Ways To Unlock Your Digital Assets And Empower Innovation. In this article, I’ll share with you nine practical ways to unlock your data assets and empower your digital supply chain.

Data Interoperability For Supply Chains: The Best Ways To Unlock Your Digital Assets And Empower Innovation

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.

Also, for more from SC Tech Insights, see the latest articles on Information Technology and Interoperability.