Arvind Devaraj, COO, NLDSL, explains why reliable, interoperable data through ULIP and LDB is vital for AI-ready logistics in India.
By Arvind Devaraj, COO, NLDSL
Over the past ten years, Artificial Intelligence (AI) has gained a reputation as one of the most widely discussed technology trends, with the potential to affect everything from production and medicine to finance and logistics. However, while most of the conversations about AI revolve around its (automated) processes, this technology relies on other factors that form the background of intelligent systems. This is because AI can only produce useful insights in the presence of correct, prompt, and organized data. Logistics deals with a great number of related activities carried out every day and the quality of information should determine the quality of the decisions. However, there should be reliable data ecosystems established in supply chains before the deployment of AI.
Data: The Foundation of Intelligent Logistics
Due to the movement of freight, transportation systems, ports, warehouses, and customs processes across contemporary logistics processes, a lot of data is generated. However, information sitting on different unrelated systems will not permit AI to find patterns and forecast changes. Therefore, intelligent logistics starts with data integration, standardization, and interoperability. By forming connected information networks, companies will be able to transform raw operational information into data useful for decision-making.
The Role of ULIP and LDB in AI-Ready Supply Chains
In India, the establishment of an efficient logistics ecosystem is being made possible with the help of digital solutions such as the Unified Logistics Interface Platform (ULIP) and the Logistics Data Bank (LDB). ULIP provides integration of data from all government systems and private sector players through a single online platform while LDB delivers real-time visibility of shipping containers in terms of their actual location at ports and on rail and road transportation. In this way, these two solutions remove impediments to the flow of information, enhance understanding of what is happening in real time, and create reliable digital systems making it easier for businesses. With the growing role of artificial intelligence, importance of such logistics ecosystems will keep increasing.
Artificial Intelligence is changing the way businesses operate all over the world, but the secret behind its success lies in one thing: reliable data. When it comes to logistics, the future of AI will strongly depend on the quality of data feeding the system.
Building AI-Ready Supply Chains
- High-quality data: trustworthy and timely data is key to gaining dependable insights with the help of AI.
- Interoperable systems: Digital platforms which are interconnected help in the accomplishment of AI by evaluating information coming from various participants.
- Predictive analytics: Visible in time- constant access to the logistics information allows to make changes in the process as the operation is going on.
- Real-time visibility: Continuous access to logistics information enables dynamic operational decisions.
- Collaborative ecosystems: data which is stored in a single place makes it possible for a company to improve the interaction with other companies, logistical companies, and state agencies.
- Responsible AI adoption: The implementation of AI in responsible way enables governance of the information, thus creating confidence in AI-based decision making.
Industry Perspective
In the logistics industry worldwide, AI is constantly being used to improve demand forecasting, inventory management, route planning, and predictive maintenance. However, firms that have achieved the greatest results from AI are not those with the most advanced algorithms but those with established digital foundations. Success in implementing AI technologies depends on investments in interlinked systems, regulated information flows, and reliable data sharing systems. Therefore, India must upgrade its data infrastructure in the course of digital transformation.
Looking Ahead
Logistics in the future will integrate AI technology with other technologies, such as IoT, Digital Twins, automation, and predictive analytics. But these disruptions will only create value if they are backed up with quality, real-time, and interoperable data. Companies with robust digital data ecosystems today will be in a better position to reap maximum benefits from AI technology tomorrow. In the next years, competitive advantage will not only come from implementation of AI but also from building intelligent data ecosystems that would enable AI to work efficiently.
Conclusion
Artificial Intelligence might be the future of logistics, but in order for intelligence to exist, it must be based on data. Data is, therefore, the basis of any successful AI application. Therefore, while organisations are gearing up for a digital future, they must pay just as much attention to data quality, interoperability, and visibility as they do to AI.
