In this article, I am going to lay out the case that the biggest challenge to supply chains is data interoperability. In fact, I’ll be so bold as to call this massive and continuing failure of data interoperability, a supply chain nightmare!  Just think about it. The key function of any supply chain is to get the right product to the right place at the right time. To do this paramount supply chain function, you need to have data that is not only integrated, but, also, accurate, complete, and timely. So, it is impossible for supply chains to work well when there is a lack of data interoperability between different systems and partners.

However, it is not time to give up hope. In this article, I’ll provide you a description of what supply chain data interoperability is and identify for you its many benefits. What’s more, I’ll describe relatable examples of what happens when a supply chain lacks data interoperability. Lastly, I’ll give you eight examples of solutions that can go a long way in improving data interoperability in your supply chain. So, let’s unlock innovation in our supply chains! 

“data interoperability is key for getting the right information to the right person at the right time”

1. What Is Data Interoperability And How Is It Important To Supply Chains?

Basically, data interoperability for logistics refers to the seamless exchange of information between different systems and platforms within a supply chain. Here is a definition for data interoperability:

“… the ability to access and process data from multiple sources without losing meaning and then integrate that data for mapping, visualization, and other forms of representation and analysis.”

Global Partnership For Sustainable Development Data

Two Levels Of Data Interoperability

Further, there are two parts or stages to data interoperability. These are:

“Data-level Interoperability: Data-level or syntactic interoperability enables data to be shared across applications and platforms.

Semantic-Level Interoperability: This type of interoperability allows the data to be interpreted correctly…”

AIMultiple

Undeniably, supply chain professionals must understand the distinction between these two levels of data interoperability. First, data-level interoperability will only result in data transfer but doesn’t provide meaningful insights. In too many cases, supply chain organizations only focus only on this data-level integration. In contrast, semantic-level interoperability is what is crucial for exchanging insightful information. This is because this level of interoperability turns data into actionable information. Unquestionably, this is what is essential for supply chain success and competitiveness. So together, these two data interoperability capabilities allow data to flow smoothly between systems and enable the distribution of usable information. This is what is key to get the right information to the right place at the right time.

2. The Interoperability Benefits For Supply Chain Excellence And Innovation.

Successfully resolving data interoperability issues within supply chains has far-reaching implications. Indeed, it opens the door for data-intensive technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) to gain traction more effectively. Positively, these emerging technologies play an integral role in refining operational efficiency, cost optimization, risk mitigation, and overall business agility. Unlocking supply chain innovation truly begins with overcoming the data interoperability nightmare that plagues many industries today to include supply chains. Here are just a sampling of the many benefits of achieving data interoperability between your various supply chain systems.

Benefits Of Supply Chain Data Interoperability

For more information on the benefits of data interoperability, see Tokenex’s What Is Interoperability and Why Is It Important?

3. Why Is Data Interoperability Such A Nightmare For Supply Chains?

Data interoperability poses significant challenges for supply chains due to the diverse range of technologies, numerous stakeholders, and massive amounts of data involved. Moreover, the complexity is compounded by differing data standards, data protection requirements, and the continuous need to keep supply chain data updated. As a result, data interoperability becomes a nightmare for supply chain managers seeking to streamline operations and improve services. To list, below are 12 data-related reasons why data interoperability is such a nightmare for supply chains.

12 Data-Related Reasons for Poor Supply Chain Data Interoperability

For a detailed explanation with examples of these 12 data-related reasons for poor supply chain data Interoperability, see my article, The Data Interoperability Challenge For Supply Chains: 12 Reasons For It And Why Tech Alone Will Never Overcome.

The Data Interoperability Challenge For Supply Chains: 12 Reasons For It And Why Tech Will Never Overcome It Alone

4. Eight Solutions To Achieve Better Supply Chain Data Interoperability And Unlock Innovation.

Without a doubt, data interoperability is a complex challenge for supply chains. In particular, this is due to the dynamic nature of the industry, numerous technology solutions, and legacy systems that create data silos with inaccurate, incomplete, and outdated information. However, the good news is that most of your competitors have the same data interoperability nightmare. Moreover, all supply chain organizations can take steps, big or small, to improve their data interoperability. To detail, below are eight solutions to improve your data interoperability.

8 Data Interoperability Solutions for Supply Chains

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

1. Leverage Standardized Data Formats for Increased Data Interoperability
2. Take Advantage Of Data Sharing Platforms That Are Independent Of Software
3. Implement Data Integration Interfaces Like Application Programming Interfaces (APIs)
4. Make Use of Automation Such As Robotic Process Automation (RPA) And AI to Digitize Processes
5. Take Advantage Of Partner Relationship Management Platforms to Increase Data Interoperability
6. Employ Cloud-Based Solutions for Improved Data Interoperability
7. Leverage A High-Tech 3rd Party Logistics (3PL) Provider To Digitize Your Supply Chain
8. Use Computer Vision AI to Exchange Image-based Supply Chain Transactions to Streamline Data Interoperability

For more details and examples of data interoperability solutions, see my article, 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.

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