Supply chain data is broken, and businesses know it. Every day, companies face a stark reality: their critical data is scattered across dozens of systems that refuse to communicate. The problem gets more complex daily: new solutions flood the market while legacy systems stubbornly cling to valuable data. Indeed, most businesses are stuck managing multiple versions of their data, spread across different platforms and departments. The consequences to this lack of data interoperability? Data is inaccurate, incomplete, out-of-date, and delayed, resulting in endless reconciliation efforts and lost opportunities. Worse, this mass of disjointed data offers little insights and stifles innovation. 

The good news is that many of your competitors are in this same data interoperability nightmare. So, the answer is not to do nothing!  Undeniably, it’s time for you to get more data savvy and focus on taking steps, some big and some small, to improve your supply chain’s data interoperability. Moreover, there is no “silver bullet” for achieving seamless supply chain interoperability. However, there are solutions today that can help you move toward that goal. In this article, I’ll show you some of the best ways to unlock your digital assets and empower innovation within your supply chain.

1. Leverage Standardized Data Formats for Increased Data Interoperability.

Let’s first start with global interoperability standards. They are crucial for unifying transparent supply chains across both public and private sectors. One major advantage of standardized data formats is that your data sources are not locked into proprietary software apps that will eventually become obsolete. Also, there are many supply chain-centric data formats that are governed by both U.S. and International data standards organizations.

For an example of a Standards Development Organization (SDO), the  ASTM International technical committee F49 is focused on standardizing digital information in the supply chain. Also, an associated initiative, the Transport Unit IDentifier (TUID) Working Group, has a standardized solution for global logistics’ goods movement process. More data standardization examples include Electronic Data Interchange (EDI) and EDIFACT for exchanging electronic documents.

Another example of a SDO is GS1 that offers many interoperability standards such as GS1 General Specifications Standard for bar codes and Global Shipment Identification Number (GS1 GSIN) for shipment visibility. Indeed, these types of interoperability standards allow different supply chain systems to exchange product information seamlessly, regardless of the software they use.

2. Take Advantage Of Data Sharing Platforms That Are Independent Of Software

Utilizing collaborative data sharing platforms enables supply chain stakeholders to securely share and verify data in real-time, regardless of the software applications they use. To detail, there are three ways businesses can share data using these platforms.  these include:

• Content Collaboration Tools. For example, you can use Google Drive where individuals can share content. Also, businesses can use a content collaboration tool to semi-automate the sharing of files. See, Gartner’s Content Collaboration Tools – Reviews And Rating for more information on these types of collaborative data sharing platforms.
• Enterprise-Level Data Collaboration Platforms. These platforms are designed to simplify, automate, and centralize the collaboration and sharing of data assets. See Narrative’s What is a Data Collaboration Platform? for more information on what these platforms can do for an organization. Also, see Slashdot for a listing of different data collaboration platforms.
• Build Your Own Collaborative Data Sharing Platform. For example, a business could use existing databases or data lakes to build a collaborative data sharing platform. Further, businesses could use APIs and other 3rd-party tools to extract needed source data. For example with parcel invoice data, Shiplab provides carrier billing data pipelines for shippers..

3. Implement Data Integration Interfaces Like Application Programming Interfaces (APIs).

By implementing APIs or other system integration interfaces, companies can integrate their supply chain management systems with external partners’ systems. Thus, this enables seamless data exchange and synchronization. For example, an ecommerce company can integrate its order management system with a logistics provider’s system using APIs to automatically update shipment status. For a more detailed discussion on data integration, see my article, The Best Ways To Access Data – Tech Solutions To Unlock Your Data Silos.

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

4. Make Use of Automation Such As Robotic Process Automation (RPA) And AI to Digitize Processes

Also, businesses can use traditional automation as well as emerging technologies to streamline data sourcing, data processing, and data optimization. Indeed, automation can eliminate repetitive manual tasks in the supply chain, such as data entry or order processing. By eliminating manual tasks, automation can also reduce data errors, multiple copies of data, and the timeliness of data availability. 

For instance, robotic process automation (RPA) bots can extract relevant information from supplier invoices and automatically update inventory systems, reducing errors and improving data interoperability. For a more detailed discussion on how to leverage different types of business automation available today, see my article, Business Automation AI Remake: First Just Tech To Empower Processes And Now Operate Autonomously.

5. Take Advantage Of Partner Relationship Management Platforms to Increase Data Interoperability.

Supplier Management Data Analytics: Beyond Just Better Compliance, But To Strengthen Relationships, Assure The Best Outcomes, And Mitigate the Unexpected

Implementing Partner Relationship Management (PRM) Platforms can definitely increase data interoperability. For example, there are Supplier Relationship Management (SRM) systems that enable companies to collaborate closely with suppliers. For SRM platforms this can include sharing critical data such as demand forecasts and production plans in real-time. As a result this leads to better supply chain coordination and data interoperability. For more on supplier management, see my article, Supplier Management: Optimize, Make Compliant, Assure Quality, Mitigate Where Risky.

Indeed, PRM platforms in general create a collaborative environment where all supply chain participants can share data and insights effectively. These platforms provide a centralized hub for managing partner communications, document sharing, and performance tracking. Thus, using software platforms like this can greatly enhance data sharing with partners for a particular supply chain function. However, the downside is that the data in these software vendor’s systems may not be available to other parts of your organization or for other use cases in the future. 

6. Employ Cloud-Based Solutions for Improved Data Interoperability

You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric

Adopting cloud-based solutions allows supply chain stakeholders to access and share data from anywhere at any time. Also, these solutions offer real-time access to information, enabling better decision-making and improved collaboration. Further, cloud solutions often come with built-in integration capabilities that make it easier to connect with various supply chain partners and systems. For example, a cloud-based inventory management system enables suppliers, manufacturers, and retailers to view real-time inventory levels. Thus, improving coordination and data interoperability across the supply chain network. 

On the other hand, beware of any software-centric cloud solution such as a Software-as-a-Service (SaaS) provider. This is because these vendors are likely to have a lock on your business data, making it very difficult for you to extract the data for other purposes. Thus as with any software-centric solution, you run the risk of creating just another data silo. For more on the dangers of being application-centric, see my article, You Need To Think Data Centric To Be A Successful Business: Stop Being Data Driven, Application Centric.

7. Leverage A High-Tech 3rd Party Logistics (3PL) Provider To Digitize Your Supply Chain.

Another solution to address supply chain interoperability challenges is to utilize a high-tech 3PL. In fact, modern 3PL providers are increasingly acting as technology enablers for their clients. 3PL providers are able to invest in advanced digital platforms and integration capabilities that would be costly for individual companies to develop independently. By partnering with a tech-savvy 3PL, organizations can quickly access sophisticated digital capabilities and established partner networks. As a result, businesses can accelerate their supply chain digitization journey while reducing implementation risks and costs.

Also, another compelling reason for a business to leverage a high-tech 3PL is that their own internal IT staff struggles with supply chain integration and new, emerging technologies. Indeed, integration is no simple feat, as most supply chains need to collaborate with numerous partners and their diverse number of systems. For more discussion on the merits of a 3PL acting as your IT integrator, see my article, The Digital Supply Chain Challenge: Is A High Tech 3PL The Best Way?

The Digital Supply Chain Challenge: Is A High Tech 3PL The Best Way?

8. Use Computer Vision AI to Exchange Image-based Supply Chain Transactions to Streamline Data Interoperability

Picture-Perfect Tech for Supply Chain Visibility: The Use Of Emerging Computer Vision AI To Find Out What Happened

Computer vision in logistics is transforming how we capture and process visual data in the supply chain. This technology enables automated reading of shipping labels, real-time inventory monitoring, and quality control through AI-equipped cameras and sensors. For instance, computer vision systems can automatically capture and process shipping documents, track warehouse activities, and verify product conditions, converting visual information into structured data that can be shared across the supply chain network.

For more information, see vision.ai’s article, 25+ Applications of Computer Vision in Logistics. Also, see my article on what computer vision tech can do for shipment visibility, Picture-Perfect Tech for Supply Chain Visibility: The Use Of Emerging Computer Vision AI To Find Out What Happened.

For more articles from Supply Chain Tech Insights, see latest posts on supply chains, information technology, and data.

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