By Anshul Jain
The supply chain is a complex organism. It is the junction where manufacturers, suppliers, shippers, and government bodies converge. The increased application of AI has helped streamline processes. In addition to the above, it provides an unprecedented opportunity to bridge gaps and forge stronger connections among different stakeholders.
As India's manufacturing and logistics landscape evolves, the role of AI goes beyond mere automation. It is the catalyst that is driving modern commerce with efficient communication, data-driven decision-making, and collaborative innovation across the entire supply chain. Here’s how AI can create a unified ecosystem that enhances transparency, agility, and effectiveness, ushering in a new era of supply chain cohesion in India.
Integrated data and collaboration
AI-based tools are the perfect way to integrate data from multiple stakeholders in one place. With transparency, secured access, and visibility, AI has helped different stakeholders along the supply chain access information in real time. Manufacturers, shippers, suppliers, etc. can access this shared repository of information and keep adding relevant data to it, reducing information asymmetry.
Demand and supply forecast
AI algorithms analyse big data, which includes both historical data and real-time insights. Access to these market insights, consumer behaviour, and other variables along the supply chain can help keep the supply chain robust. Be it manufacturers or distributors, AI can keep them apprised of demand fluctuations. Manufacturers can adjust production schedules accordingly or tie up with multiple vendors to ensure regular supply. This updated information and predictions can ensure enhanced alignment, minimising excess or less
Sustainability goals
With the growing logistics sector, both the private and public sectors are cognizant of the national sustainability goals as well. With the help of AI-based tools, stakeholders can access data related to energy consumption, carbon emissions, waste generation, etc. across the supply chain. These parameters provide insights to stakeholders on how to implement sustainable practises that align with the government's environmental goals.
Regulatory compliance
AI is the framework that turns data into information. AI-based tools can monitor regulatory changes and compliance requirements set by government bodies. It can automatically alert manufacturers, suppliers, and shippers to tweak and adjust operations to ensure compliance. With a safe, accessible, visible, and agile system for documentation, AI has made it easy for all the stakeholders to maintain compliance.
Risk management
The government is actively working towards enhancing the logistics sector. The same is true for the private sector as well. With this enhanced growth, there is also a need for effective risk management. AI analyses supply chain data to identify potential risks and disruptions. This helps stakeholders, including government bodies, develop robust contingency plans to mitigate the impact of unforeseen events.
Centralised collaboration portals
Private and public partnerships are the future of the logistics sector. AI-powered collaboration platforms provide a centralised space where all stakeholders can communicate, share data, and collaborate on various aspects of the supply chain. This optimises coordination and ensures everyone is on the same page. Insights from this can also help accelerate and increase any future PPP partnerships.
By leveraging AI's capabilities, manufacturers, suppliers, shippers, and government bodies can transcend silos, make more informed decisions, optimise processes, and enhance overall supply chain efficiency. AI acts as a unifying force that transforms the supply chain into a cohesive ecosystem where stakeholders work together towards shared goals.
The writer is the CTO and co-founder at Roadcast.
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