Despite the impressive array of high-tech tools and advanced supply chain analytics at our disposal, logistics organizations still struggle to gain total visibility of their shipments. The root of the problem? Bad shipment data. Just consider the fragmented state of shipment data – it’s often dispersed across many systems, inaccurate, incomplete, outdated, and duplicated. And, even if a company had 100% perfect shipment data with up-to-date shipment status, sharing this treasure trove effectively with other systems remains a challenge. What we really need is a common data framework for supply chain systems to generate intelligent tracking statuses. This is what will “ensure what is sent is what is understood” to achieve total supply chain visibility.

^{“ensure what is sent is what is understood”}

In this article, I’ll discuss how data interoperability issues impact supply chain analytics and shipment visibility. Mainly, it’s a problem with the shipment data. We depend too much on various custom-built, proprietary tracking systems, which often provide unclear and incomplete updates on shipments. I’ll also explore a solution to this problem – an intelligent tracking data framework. This data framework will help solve these shipment data interoperability problems by enabling different systems to speak the same language. As a result, we can get better shipment updates. Hence, overall supply chain analytics will improve because the data will be consistent and interoperable.

1. Supply Chain Analytics Falls Short Due to Lack of Shipment Data Interoperability.

Despite the potential of supply chain analytics, its effectiveness is often undermined by the fragmented, ambiguous nature of shipment data and tracking statuses. This disjointed situation leads to shipment data interoperability issues. Hence, supply chains are hampered in gaining a comprehensive view of their operations, leading to misinformed decisions and inefficiencies. Indeed, this lack of data interoperability between organizations makes it difficult to establish a common digital framework for communication. Surprisingly, most supply chain managers do not fully realize how big of a problem shipment data interoperability is. To detail, below are 11 reasons why shipment data interoperability is such a problem for supply chain analytics and decision-making.

11 Reasons Why We Have Poor Shipment Data Interoperability

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

1. Inconsistent Data Formats. Here, one uses csv format, another uses XML; data elements are not consistent.
2. Lack Of Standardized Codes. In this case, one uses UPC codes, another uses EAN codes, another proprietary codes.
3. Limited Data Sharing Capabilities. Indeed, this is because there is a lot of front-end work to integrate systems.
4. Manual Data Entry And Reconciliation. Here, humans make data entry errors or systems use freeform text that are not intelligible to other systems.
5. Lack Of Real-Time Visibility. This is because data is in silos, duplicated, and not up-to-date.
6. Incomplete Or Inaccurate Data. A case of Garbage In, Garbage Out (GIGO) – ambiguous data, missing data, and so on.
7. Non-Standardized Naming Conventions. Here, one company refers to a product as “Widget A”, another refers to it as “Product 123”.
8. Lack of Data Validation Checks. As a result, data is imported with errors, then corrupted data is shared and duplicated within other systems.
9. Incompatible Data Integration Tools. In this case, one company uses APIs, another uses file-based data transfer.
10. Proprietary System Lock-In. Here, it is difficult to migrate or upgrade legacy systems; proprietary system-to-system data integrations are difficult to untangle.
11. Ineffective Digital Identity Solution. Lastly, systems either lacks usability, data security, or both  due to inadequate user verification, authorization, and authentication.

For more detailed discussion on these data interoperability issues, see Why Is Data Interoperability Such A Nightmare For Supply Chains?

2. Ambiguous, Customized Tracking Statuses Are Holding Back Supply Chain Analytics and Better Decision-Making.

Custom-Built Shipment Statuses: Digital Supply Chains Can Do Better And Need A Reckoning To Eliminate This Insidious Habit

Over the years, supply chains have created countless customized tracking status interfaces. These customized data integrations have created a labyrinth of data flows, making digital supply chains neither seamless nor very insightful. As a result, data interoperability issues are now the norm, resulting in poor operational visibility for most supply chains. Surprisingly, new tech like AI won’t resolve these interoperability issues. This is because this is primarily a business problem where the data lacks the operational clarity to communicate meaningful information to the intended recipients. Moreover, this challenge is worsening as we increase functionality, automation, and global expansion of our supply chains.

For a detailed discussion on this subject to include examples, see my article, Custom-Built Shipment Statuses: Digital Supply Chains Can Do Better And Need A Reckoning To Eliminate This Insidious Habit.

3. Intelligent Tracking Statuses Enables Both Total Visibility and Better Shipment Analytics.

Imagine a world where supply chains had available every shipment status, from “Shipped” to “Delivered,” and this information was actionable to all intended receivers. Indeed, this data interoperability would revolutionize shipment analytics. Furthermore, if all supply chain partners could seamlessly exchange intelligent tracking status, shipping operations would become faster, response times quicker, and proactive supply chain actions the norm. Indeed, these scenarios demonstrate how intelligent tracking statuses can strengthen analytics and enhance decision-making. Thus, this ensures timely delivery of goods to their intended destinations as well as improving shipment analytics from forecasting through post-shipment analytics. So, what steps can we take to enable our systems to generate intelligent tracking statuses?

a. First, Need to Unify Shipment Data Using a Universal Load ID.

If we really want to solve the current disjointed state of shipment statuses, we need to first start with unifying shipment data. Currently, data for even one shipment is often scattered across the supply chain within various departments and organizations. Further, the shipment data is tied to a multitude of reference numbers such as purchase order, customer reference number, tracking numbers, invoice numbers and so on. Worse, the fragmented nature of shipment data makes it difficult to establish a Single Source of Truth (SSOT). 

Better Shipping Data Analytics Results: Use Of Load IDs To Achieve The Best Efficiency, Visibility, And Financials

So because this data is not unified, supply chain systems and organizations do not have a real picture of the current status of shipments. Imagine the immense benefits supply chains could reap by tapping into unified shipment data and total visibility. Plus, with access to unified shipment data, they could truly leverage advanced, data-driven technologies such as data analytics, AI, and decision intelligence to achieve remarkable results!

This is where the concept of using a Universal Load ID, if implemented, can unify all our shipping data. This load ID is more than just a carrier’s tracking number, it is a load ID that a shipper or their representative can create to unify shipment data to include planning data, shipment status, and financials. For more details about this Universal Load ID concept as well as use cases, see my article, Better Shipping Data Analytics Results: Use Of Load IDs To Achieve The Best Efficiency, Visibility, And Financials.

b. A Need for Intelligent Tracking: Shipment Statuses That Provide Meaningful Insights Are What Enables Total Shipment Visibility.

Now, unifying shipment data around a single reference number such as a Universal Load ID is the first step in gaining total shipment visibility. The next step is the ability to easily and effectively transmit intelligent tracking updates across the supply chain to the receivers and subscribers of a shipment’s status. Specifically, these shipment status recipients can include end-customers, internal supply chain systems, 3rd party partners, government agencies, and other systems. Indeed, it is critical that these recipients of shipment statuses have an understanding of the data sent. Thus, they can make the best decisions and act upon good information. So what we need is a common data framework for systems to generate intelligent, meaningful tracking statuses.

Poor Shipping Data Analytics – Here Are The 4 Reasons Impeding High Tech Visibility And Optimization

As discussed previously, shipment status updates today are increasingly unintelligible, Hence, we are challenged both to leverage cutting-edge technology and meet the needs of our modern supply chains. What we have is a serious data interoperability problem. The European Interoperability Framework (EIF) calls this a semantic interoperability problem. Their definition of semantic interoperability is as follows:

“Ensuring what is sent is what is understood”

European Commission – EIF

So to sum up this shipping data interoperability problem, we need both total visibility of the data as well as assure that the data is timely and understandable. Hence, this calls for a way to unify shipping data such as the use of a Universal Load ID. Further, there is a need to make sure that all supply chain stakeholders can receive shipment status that is understandable, and thus, actionable. This calls for an intelligent tracking data framework that I will discuss next.

4. An Intelligent Tracking Data Framework.

So, supply chains have disconnected, incomplete, and duplicated shipping data, However, this is more than just a “Where’s My Stuff? type problem. The root problem is that there is no single source of truth (SSOT) that unifies shipment visibility from initial planning to final profit analysis. What we need is an Intelligent Tracking Data Framework that links all shipping data across the supply chain. This will enable all supply chain stakeholders to have a common view of shipment-related activities from planning through execution and settlement to post-shipping analysis. First, let’s look at the types of shipment visibility problems we have, and then we can look at how an Intelligent Tracking Data Framework can help us unify shipping data.

a. Our Shipment Visibility Problem: Why We Can’t Track Every Move from Planning to Profit.

Effective shipment visibility is crucial for optimizing supply chain operations. From the initial planning stages to the final profit analysis, tracking every move ensures that all stakeholders have the necessary information to make informed decisions. However, most supply chain stakeholders have a myopic, disjointed view of shipment visibility, much like “blind men trying to describe an elephant”. Indeed, the major reason for this is that we rely on many disparate enterprise systems that separate our shipping data into distinct silos. For instance, these systems disconnect our shipping data between products, shipments, cost types, service performance, and unplanned events. Also, there are many types and reasons we seek shipment visibility to include the following:

Types of Shipment Visibility

• Transportation Visibility: Find My Stuff.
• Capacity Visibility: Identify Choke Points in the Supply Chain.
• Shipment Data Analytics Visibility: Measure Performance.
• Rates Visibility: Manage Transportation Spend.
• Supply Chain Planning Visibility: Prepare for Future Operations.
• Strategic Supply Chain Visibility: Innovate And Optimize Processes.

So, supply chains continue to have significant shipment visibility problems despite the best AI and analytics tools. Indeed, we need a way to link all shipping data together, including data from forecasting, shipment booking, the transport of goods, and final settlement. What we need is an Intelligent Tracking Data Framework

b. A Connected Shipment Visibility Framework: Unified Shipping Data, One Source of Truth.

So, there is definitely a need for unified shipping data. Without one, unifying source of truth, supply chains are practically helpless to leverage the latest AI and advanced analytics. Only with a one data framework to enable Connected Shipment Visibility, can we empower supply chains to see with clarity. Hence with actionable Insights, they can seize opportunities, improve operations, and avoid unintended consequences. Moreover, decision-makers can act both confidently and rapidly with connected shipping information. Indeed, a unified data framework using Transport Load Ids provides unparalleled visibility across the supply chain from planning to profit. Below, are the key components for an Intelligent Shipping Data Framework. Also, see diagram below.

Intelligent Tracking Data Framework

• Forecast Visibility: Long-Range Planning and Optimization Using Aggregated Shipping Requirements.
• Planning Shipment Loads: Gain Visibility of Rates and Capacity to Book the Best Transport.
• Execute Movement: Achieving Shipment Visibility and Managing Exceptions.
• Settlement: Reconcile Contract Rates Against Load Movement Performance.
• Post-Analysis: Use Shipment Visibility Feedback to Diagnose, Gain Insights, and Improve Operations.

Indeed, what we need is an Intelligent Shipping Data Framework to unify our supply chain data.Today, there is no single source of truth (SSOT) that unifies shipment visibility from initial planning to final profit analysis. For a detail discussion on an Intelligent Shipping Data Framework, see my article, The Best Shipment Visibility: One Source Of Truth Framework For Better Planning, Execution, Post-Analysis.

The Best Shipment Visibility: One Source Of Truth Framework For Better Planning, Execution, Post-Analysis

5. The Advantages of Intelligent Tracking Interoperability For Supply Chain Event Management.

Now, the benefits of implementing an intelligent tracking data framework are far-reaching. For one, it enables intelligent tracking that instills both confidence and understandability in the shipment status data that supply chain organizations transmits. Thus, this enables comprehensive shipment visibility allowing companies to respond proactively to any disruptions.

Also, this intelligent tracking data framework fosters a collaborative ecosystem where all supply chain partners can align their strategies and operations. Further, data accuracy is enhanced, reducing the risk of errors, discrepancies, and uncertainty. Ultimately, data interoperability paves the way for advanced analytics and automation. Hence, setting the stage for a more resilient, agile, and situational aware supply chain that can adapt to rapidly changing situations and the ever-evolving demands of the market.

Below are 12 advantages for adopting an intelligent tracking data framework for your supply chain systems.

Advantages of Intelligent Tracking

1. Enhances Visibility for Customers and Across the Entire Supply Chain. Tracking interoperability enables a clear view of movement throughout the entire supply chain.
2. Improves Accuracy and Reduced Errors. Interoperable tracking systems minimize ambiguity and maximize trust that statuses are correct.
3. Increases Carrier and 3rd Party Accountability. Clear tracking of goods creates an accountable environment, where each participant’s actions are transparent.
4. Facilitation of Compliance and Reporting. Intelligent tracking statuses simplify compliance with regulations by providing accurate information and confidence in reporting.
5. Better Customer Experience by Delivering Accurate Status to Reduce Delays. Intelligent tracking status provides all stakeholders confidence and foresight to avoid mishaps.
6. Streamlines the Recall Process for Faster Response. Tracking interoperability speeds up the identification and retrieval of defective products during recalls.
7. Increases Efficiency with Automated Data Capture. Intelligent, standardized tracking enables fully automated information sharing that is actionable..
8. Streamlines Coordination Across Multiple Stakeholders. Intelligent tracking statuses ensure that all stakeholders have access to the same information, facilitating coordinated actions.
9. Bolsters Security and Reduces Fraud Risks. Reliable tracking strengthens security measures and reduces the risk of fraud within the supply chain.
10. Better Data for Logistics Planning. Comprehensive and consistent tracking data improves the quality of analytics, leading to more accurate demand forecasting, asset allocation, and network planning.
11. Leveraging Data Analytics for Optimizing Operations. Rich tracking data, when analyzed, can uncover trends and insights for both strategic supply chain decisions and improving operations..
12. Better Analytics to Reduce Costs and Improve Financials. With accurate, detailed shipment data, analyst can uncover hidden cost, non-value charges, and strengthen negotiation positions with vendors.

Surprisingly Supply Chain Visibility Has Many Forms: See Which One Is Best To Be Your Business’ First Focus

More References:

For more information on intelligent tracking and supply chain event management, See

• My article on supply chain visibility: Surprisingly Supply Chain Visibility Has Many Forms: See Which One Is Best To Be Your Business’ First Focus
• My article on the need for a Transport Load ID to unify shipping data: Unifying Shipping Data Using Transport Load IDs: Here Are 10 Ways It Can Unlock Analytics And Empower Logistics Tech.
• CTSI-Global’s Boost Shipment Efficiency with Enhanced Supply Chain Event Management

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.

Unifying Shipping Data Using Transport Load IDs: Here Are 10 Ways It Can Unlock Analytics And Empower Logistics Tech