Towards Unified Indian Logistics with Data Science and Artificial Intelligence

Unifying Indian Logistics with Data Science and Artificial Intelligence

In a panel discussion on ‘Data in Coronavirus Times’ hosted by the National Council of Applied Economic Research (NCAER), CEO of NITI Aayog, Amitabh Kant stated that the government should actively share important information to help researchers, medical representatives, and the country’s public to successfully fight the pandemic. 

“The government needs to actively share standardized data with the transparency of definitions. That is the only way we will be able to take the right policy decisions,” Kant said.

Real-time data has been a valuable resource in battling COVID-19 and preventing it from spreading in several countries, and in some Indian states so far. But, overall, the availability of data in real-time is a challenge. Kant, in fact, commended the state governments of Kerala and Karnataka for putting out accurate real-time data quickly. 

“Even during COVID-19, I have seen Karnataka share contact tracing information. Kerala shared demographic information. This has made it easier to target vulnerable populations and plan containment strategies,” he said.

Data is indeed a superpower in today’s tough times. Accurate data can help not only welfare authorities with the containment of the disease but can also navigate businesses across varied sectors towards better days in a post-pandemic world. 

The pandemic has pushed businesses all over to adapt to the changing consumer demands, market dynamics, and stand strong amidst the crisis with innovative offerings. Resilience and agility are much needed for enterprises in the supply chain to remain competitive and face the new world. Faster, smarter, and more efficient logistics is the true differentiator for modern supply chains

In the discussion, Kant also indicated that the NITI Aayog Think Tank will be undertaking data initiatives through public-private partnership models for a unified logistics interface platform in India. 

“We are working on a unified logistics interface platform where data analytics and AI will be used for smart routing and forecasting of shipments and to bring down the cost of logistics in India.”, Kant said. NITI Aayog’s initiative to optimize Indian logistics with the help of data capabilities could be the beginning of a revolution in the country’s logistics sector. 

What can AI & Data-Driven Logistics Do?

Advancements in data science and Artificial Intelligence can act as catalysts for strengthening Indian supply chain systems in many ways. 

Demand and Supply Forecasting

With data science capabilities, companies can make effective use of readily available big data sets and predict demand and supply levels. Today, data analysis techniques like baseline statistical analysis and advanced simulation modeling are being used for improving demand forecast accuracy. 

Organizations can process data to predict future demands based on products, geographical regions, consumer profiles, seasons, festivals, etc. and plan sales, dispatches, and inventory management more efficiently.

Accurate Mapping of Addresses

In a country like India, mapping addresses accurately is a big challenge for logistics enterprises. People do not usually write precise postal addresses, and locating remote and complex addresses on a map for delivery is often cumbersome. With data science and machine learning, geocoding of even the fuzziest addresses is possible with minimal effort. 

In simple terms, geocoding is the process of converting a description of a location such as an address, or a name of a place to a location on the earth’s surface or a virtual map. With accurate geocoding, processing dispatches, shipments, and carrying out last-mile delivery operations is faster and easier for businesses.

Smart Route Planning and Optimization

Planning delivery routes and dispatches in India is complex. When handling tons of shipments and delivery orders, finding the most appropriate mix of the fleet, and the most optimal delivery routes is essential for successful secondary and last-mile operations. 

With the help of AI-driven route optimization solutions, supply chain enterprises can now plan daily dispatches accurately within minutes and assign the shortest and most efficient routes to delivery executives. Advanced Route Optimization software also considers real-time scenarios such as traffic congestion, vehicle availability, and rider know-how to optimize the entire delivery planning process in a cost-effective manner.

End-to-End Supply Chain Visibility

Clear visibility across logistics operations is gaining importance for both supply chain managers as well as end customers. Real-time data analytics is a powerful tool in bringing greater visibility throughout supply chain operations. By analyzing on-ground data in real-time, logistics managers can keep a close eye on shipment and delivery activities being carried out by their staff. They can monitor on-ground activities effectively and take necessary actions in case of deviations from planned logistics tasks. 

At the same time, real-time monitoring allows customers to be aware of their order status, and have complete information about who is handling their package and how. Data analytics certainly increases transparency in supply chains and improves customer trust in brands.

In Conclusion

Efficient logistics and transportation are the need of the hour for Indian supply chain enterprises. Logistics technology is capable of improving routing, scheduling, and end-to-end supply chain optimization, with the added value of speed, cost-effectiveness, and overall supply chain efficiency. NITI Aayog’s vision of a digitized and modern logistics system across India’s varied territories is an achievable dream with the help of Data Science, Machine Learning, and Artificial Intelligence.

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