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The Future of India's Logistics and Shipping Revolution

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Hemanta Banerjee, Vice President of Public Cloud Data Services, Rackspace Technology

With diverse data analytics experience, Hemanta Banerjee, Vice President of Public Cloud Data Services, Rackspace Technology is an engineer, engineering manager, product manager, sales, and professional services helps customers to get value from their investments in data platforms and analytic solutions.

To keep the enterprise sector moving smoothly, the $ 317.26 billion logistics, transport, and shipping industry must stay on course with precise and timely operations. Companies must modernize their operations using AI, automation, and data-driven insights to meet the increasing demands of e-commerce, manufacturing, and other industries. By doing so, they can improve efficiency, reduce costs, and ensure timely deliveries.

Making the Most Out of Data
The positive news is that the logistics, transport, and shipping industries have access to vast amounts of data from their operations. However, not all organizations are using this data for their competitive advantage especially because most of it is unstructured and siloed. That's why data modernization ensures smoother operations and continuous productivity.

As EY projects India's economy to grow to a $26 trillion economy by FY48, this growth will create substantial opportunities in the transportation and logistics sector, which is expected to expand at a ~4.5 percent CAGR from 2022 to 2050, reaching 15.6 trillion-ton km by 2050. Logistics, transport, and shipping companies need to use AI to optimize processes like network repair to import On-Time Delivery Percentage to be able to tap into this growth.

Having a unified platform that is capable of exploiting this data generated is imperative. Organizations must modernize their data infrastructure to leverage existing unstructured data to support their future workloads and processes.

This rests on understanding the company’s domain, comprehending how to ingest unstructured data onto a common platform, and exploring new data concepts, such as synthetic data, which can be deployed to train artificial intelligence (AI) and machine learning models.

Data Modernisation and AI
According to NASSCOM, AI is set to boost the productivity of logistics companies by more than 40 percent by 2035. Presently Artificial Intelligence is revolutionizing logistics operations by offering numerous advantages such as enhanced accuracy, cognitive automation, cost reduction, and time efficiency. AI's primary function is to automate routine tasks and anticipate future needs.
Additionally, it provides significant benefits in route optimization and reducing shipping costs, making it a valuable asset in the logistics industry.

The key challenge, however, is that unlocking AI's full potential depends on having access to the right kind of data. These capabilities are achievable only through a thorough analysis of the extensive data that companies possess.

Furthermore, because data modernization helps businesses make the most out of their unstructured data, it is immensely important to clarify what data is available, what it can be used for, and how that benefits the business. That ultimately gives decision-makers a fuller picture and gets AI projects off

Driving Resilience
While data modernization is essential, prioritizing data security is equally vital. As logistics operations increasingly transition to digital platforms, the significance of cybersecurity intensifies. By implementing a robust cybersecurity strategy, logistics firms can safeguard their operations and gain a competitive advantage in an industry where trust and reliability are critical.

Data modernization stands as a pivotal strategy for enhancing operational resilience and efficiency within the logistics, transport, and shipping sectors


However, spending must be approached strategically and businesses do not need to navigate this alone. They can tap the expertise of vendors to assist them in their data modernization journeys in ways that prime them for resiliency. Key services to consider include advisory functions, which help organizations assess their current state and determine the best solutions to harness their data; day-one services that assist with data migration, transformation, or modernization, often supported by platforms like Amazon Web Services; and day-two services, which focus on optimizing the efficiency of systems and workloads running in the cloud.

Data modernization stands as a pivotal strategy for enhancing operational resilience and efficiency within the logistics, transport, and shipping sectors. By embracing data modernization, organizations can unlock the potential of data, enabling informed decision-making, predictive analytics, and the adoption of advanced technologies like AI and machine learning.



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