In the lightning-fast world of digital commerce, the seamless flow of data is essential for making informed decisions and driving business success. However, one of the biggest hurdles in data interoperability is ensuring that the data shared is correctly understood when it is exchanged between systems and organizations. Often, the root cause of misunderstandings are a lack of clear business definitions and semantic context, leading to ambiguity and misinterpretation. So, why do businesses and their systems exchange data that is not understood? In this article, I’ll identify the core reasons behind these “dumb” data integrations. Further, I’ll detail with examples the obstacles that negatively affect both data integrity and interoperability in our digitally integrated world.

“…  why do businesses and their systems exchange data that is not understood?”

1. What Does Data Integrity, Integration, and Interoperability Have to Do With Each Other?

In today’s interconnected digital landscape, data integrity, integration, and interoperability are the cornerstones of efficient and effective business operations. Though these three terms are interrelated, they mean different things to different people. As a result of these differences in understanding and frequent misunderstandings, most organizations struggle to fully leverage business insights from data available. In particular, they are both frustrated and underwhelmed when establishing data transfer interfaces between business systems. So to better explain this digital disconnect, let’s start with some definitions. 

Definitions for Data Integrity, Integration and Interoperability

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

“Data integrity is the assurance that an organization’s data is accurate, complete and consistent at any point in its lifecycle. Maintaining data integrity involves safeguarding an organization’s data against loss, leaks and corrupting influences.”

IBM

“Data integration is the process of achieving consistent access and delivery for all types of data in the enterprise.”

AWS

“[Data (Semantic) interoperability is] ensuring what is sent is what is understood”

EIF

Indeed, these definitions highlight the sources of frustration businesses often have with IT departments when setting up data transfer interfaces between systems. Without a doubt, all businesses desire their data to be accurate, complete, and consistent (data integrity) and to be understood (interoperable) when it is transferred to another system. However, what businesses often get is data that is integrated but not properly understood by the receiving system. As a result, the value of data transferred between systems is routinely diminished. For more on this topic, see my article, This Is What Semantic Interoperability Is: It’s The Best Last Chance For Seamless Supply Chains.

2. The Reasons Why Data Integrity Suffers Due to Poor IT Integrations.

Undoubtedly, poor IT integrations will severely undermine data integrity, leading to a cascade of problems that can ripple through an organization. When we do not properly integrate systems, data becomes fragmented, inconsistent, and unreliable. This results in incorrect reports, flawed analytics, and misguided business decisions. The root cause often lies in the assumption that simply connecting systems will ensure seamless data exchange, which is far from the truth. Let’s look in more detail on the reasons why data integrity is adversely affected by poor IT integrations.

a. The Enterprise Integration Myth that Data Exchanged is Data Understood.

First, one of the most pervasive myths in enterprise integration is that data exchanged is data understood. More specifically, this myth assumes that once data is transferred from one system to another, it will be interpreted correctly. So in many cases, the crux of the issue lies not in the transmission of data, but in its interpretation. For example, a date field may represent a purchase date in the source system. However, when this transmitting system transfers the data to the target system, this receiving system misinterprets the date field as a ship date. As a result, this causes errors in calculations and reports in the receiving system.

b. Examples of Data Integration Where Data Loses Its Meaning.

As discussed previously, a data integrator can successfully establish a data interface between two systems, but that does not necessarily mean data interoperability will occur. Here are some examples:

Revealing Examples Of How Murky Operational Definitions Really Foul Up And Make Feeble Supply Chain Interoperability

First, let’s take an example from supply chains. In many cases, different organizations will have varying definitions of basic business terms such as “shipped” and “delivered”.  As a result, the sender will transmit ambiguous data and the receiver will misinterpret it upon receipt. For instance, a warehouse system may transmit a “shipped” status message for a package when in reality the shipper’s operation has only printed a barcode label for the package. As a result, the customer reasonably expects that the package is on its way upon receiving the “shipped” status message versus it still sitting on the shipping dock.

Here’s another example of failed data integrations – a financial system interfacing with a marketing system. In this case, the financial system uses a different definition for “revenue” than the marketing system. As a result, the data will be misinterpreted. This can lead to inaccurate financial reports and misguided marketing strategies. For more examples of data disconnects due poor business definitions, see my article,  Revealing Examples Of How Murky Operational Definitions Really Foul Up And Make Feeble Supply Chain Interoperability

c. Data Integrity Lost When Context and Clear Definitions Are Not Shared Between Systems.

So, there’s a gap between organizations actually integrating their systems and truly achieving true data interoperability. In particular, a knowledge gap often exists regarding the data transferred between the two organizations and their systems. While the receiving system will usually import the data successfully, it will lack the knowledgeable context and clear business definitions needed to make it understandable. Indeed, semantic interoperability is essential. This is what empowers organizations and their systems to exchange meaningful data with their partners’ systems. Hence, semantic interoperability closes the knowledge gap and enables the achievement of true data integrity between systems.

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

More References.

• Semantic Interoperability Solutions – Achieving Logistics Interoperability: The Best Way to Breakthrough The Tangle Of Dumb Data Integrations.
• Ambiguous Business Glossaries – Feeble Business Glossaries: Know It’s The Greatest Killer Of Supply Chain Collaboration And Data Interoperability.
• Steps to Achieve Data Interoperability – Semantic Digital Interoperability: This Is The Ultimate Way To Make Supply Chains Seamless. 
• Semantic Interoperability Success Stories – Semantic Interoperability Examples That Turn The Tables From Having Dumb Data Communications To Being Really Informative.
• Data Interoperability Needs – The Data Interoperability Challenge: It’s The Need For Tech Standards, Compliance, Security, Massive Resources, And Be Understandable.

Feeble Business Glossaries: Know It’s The Greatest Killer Of Supply Chain Collaboration And Data Interoperability

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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