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Recently, I wrote about the role of integrated supply chain platforms in enabling integration and helping companies navigate complex global markets. In fact, making supply chains more efficient requires not only unifying technology and standardizing processes, but also standardizing data. Data plays a starring role, providing real-time insights, optimizing operations, and ensuring timely delivery. But without a common language and data definitions, even the most sophisticated datasets can become a chaotic jumble. This is where data standardization comes in and acts as a conductor to ensure everyone is acting in unison.
Data standardization has been successful in some industries, but not in the complex world of logistics.
The International Standard Book Number (ISBN) is a prime example of successful data standardization. Assign a unique identifier to every book edition, enabling efficient cataloging, ordering, and inventory management across publishers, distributors, and bookstores. The healthcare industry has Health Level Seven (HL7), a set of international standards for exchanging information electronically. This allows hospitals, clinics, pharmacies, and insurance companies to exchange patient medical records, test results, and other important data. The financial services industry has the International Bank Account Number (IBAN) and the Society for Worldwide Interbank Financial Telecommunication (SWIFT), a messaging system for secure financial transactions.
There are clear reasons why the logistics industry faces unique hurdles when it comes to data standardization. Logistics involves a vast network of stakeholders, from manufacturers, distributors, logistics providers, retailers, and even customers. Each participant may have its own internal systems and data formats, making standardization a complex task. Logistics operations often involve cross-border operations and are subject to various regulations and data privacy laws. Achieving globally accepted standards can be difficult. Many logistics companies still rely on legacy IT systems that are not designed to handle standardized data exchange. Upgrading these systems can be expensive and time consuming. Standardization ultimately requires cooperation and investment from all stakeholders. The benefits may not be immediately apparent to all participants, making widespread adoption difficult.
Data discrepancies can have serious consequences. Imagine a scenario where a box labeled “10 widgets” arrives at the warehouse, but upon inspection it turns out it contains 12. This simple discrepancy caused by differences in units of measurement (box vs. individual units) can have ripple effects. Inaccurate inventory records, delayed deliveries, and disrupted production schedules. This is just one example of the problems that arise from data inconsistencies in the supply chain.
Inconsistent data formats and definitions make it difficult to clearly understand inventory levels, shipping locations, and potential disruptions. Misinterpretation of data can lead to delays in order fulfillment, shipping of incorrect products, and increased processing times. When different players use different data formats, communication becomes fragmented and prevents collaboration and proactive problem solving. Data inconsistencies require manual intervention and rework, leading to increased labor costs and missed opportunities for efficiency.
Data standardization acts as a force that brings order to chaos. In warehousing, standards exist for optimizing pallet sizes, container dimensions, and warehouse layouts to facilitate efficient use of space and product handling. When it comes to transportation management, standardization in areas such as electronic cargo bidding, route guidance, and shipment status updates is streamlining communication between logistics providers and shippers.
Establishing a common set of definitions, formats, and protocols for exchanging information across the supply chain can further benefit the logistics industry and strengthen the supply chain. Standardized data allows you to track shipments, inventory levels, and potential disruptions across your supply chain network in real time. Streamlined data exchange facilitates faster processing, reduces manual intervention, and optimizes logistics operations. A common data language facilitates communication and collaboration between stakeholders, enabling proactive problem solving and improved decision-making. Standardization eliminates data errors and streamlines processes, reducing costs associated with manual intervention and rework. Finally, accurate and timely deliveries facilitated by efficient logistics lead to increased customer satisfaction and improved brand reputation.
However, standardizing data in logistics is not an easy task. Developing and adopting common data standards requires collaboration between industry players, government agencies, and technology providers. More emphasis needs to be placed on implementing data management platforms that facilitate standardized data exchange, and analytics are essential. But that’s not all. Employees need training to understand and use standardized data formats and processes. And finally, data standards must be continually reviewed and updated as technology evolves and new needs arise.
In today’s interconnected world, a data-driven approach is essential for supply chain success. By adopting data standardization, logistics providers and all parties in the supply chain can pave the way for a future of seamless communication, optimized operations, and a more resilient and efficient ecosystem. Masu. Despite current challenges with data standardization, progress is being made. We are seeing several industry efforts to drive this standardization. (Examples include GS1, NFDH, ASTN F49, and IATA.) Cloud-based platforms and data management solutions facilitate data exchange and integration between disparate systems. Additionally, governments in some regions have introduced regulations that require companies to adopt certain data standards for compliance purposes. The recently approved EU Supply Chains Act (CSDDD) could indirectly promote data standardization by requiring companies to map their supply chains and report on their environmental and human rights practices . This will require more structured data collection and may lead to a push for standardized formats.
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About the author
bad de munk is an industry thought leader with over 30 years of supply chain and logistics experience. He has worked for major international companies such as EY, GE Capital, Penske Logistics, and PepsiCo, as well as several technology companies. He also served as vice president of research at Gartner for eight years and most recently as chief industry officer at project44. He is a member of his inner circle of executives at the Forbes Technology Council and his CSCMP.
