mindtalks artificial intelligence: How AI has become a powerful tool for the Shipping & Logistics Industry – Express Computer – picked by mindtalks

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By Pankaj Sachdeva, Vice President Innovation & India Site Leader, Pitney Bowes

Artificial Intelligence is providing visibility, optimization, analytical insights and improved decision to the Shipping & Logistics industry. Data is generated and captured during the entire lifecycle of shipping – right from a client profile to usage and behavior data, delivery and returns, tracking, billing and support. And this data is leveraged using artificial intelligence algorithms by shipping carriers and aggregators to add to revenue and optimize operations.

Here’s is how the Shipping & Logistics Industry is using AI tools to transform their business operations and enhance efficiencies.

New Client Acquisition: On the revenue and business development front, AI is helping acquire new customers by allowing providers to profile potential clients, analyze their shipping and logistics potential and understand and ease existing pain points, to pitch potential solutions. AI is also helping companies provide additional value to existing clients through segmentation, behavior analysis and targeted marketing campaigns.

Enhanced User Experience: Customer experiences are contingent on how intelligent your front-end is for customers. Recommendations in workflows is based on client segmentation, suggestions to make shipping cheaper and faster, and automated business rules are some of the use cases being deployed using artificial intelligence that help firms differentiate on experience.

New monetizable offerings: AI is helping companies deploy new monetizable services to clients. For instance, AI algorithms consider zip codes, real time climate and traffic data, coupled with historic data to estimate delivery dates for parcels quite accurately, and companies provide guaranteed delivery services. Similarly, data on theft and damage is used to offer the Delivery insurance services.

Operational Efficiency:
• Machine learning based Predictions:
o Volume prediction – Based on historic data and patterns such as on seasonality and trends, AI helps             forecast volumes into the future. Having a view of incoming and outgoing volumes enable business               forecasting and better planning of infrastructure and resources, both human and machine and                       return prediction.
o Returns prediction – AI is helping analyze the return potential of a package based on product                            reviews, quality of service in a zip code, and client historic behavior.
o Weight prediction – The weighted models used to determine the weight of the commodity and it                     helps to calculate the correct shipping charges.

• Cross border transactions and Tax/Duty calculators – Harmonized System (HS) code is a universally accepted method of classifying traded goods and is used to calculate the accurate duty, taxes, and restrictions. To fulfill cross-border transactions, HS code is required for each parcel, but it is not always available with the merchant or it may be incorrect. AI algorithms help predict the accurate HS codes for cross border duty, tax, and restriction determination. Data Science models on country of origin, which is required for custom clearance and parcel processing, help predict the country of origin of each parcel, and saves time of opening each parcel.

• Facility and Warehouse management – With a view of potential demand, providers are better equipped to take decisions on capacity utilization, labour, distribution of workload, and client demand prioritization. Freight management, and fuel efficiency – Real time data analytics allow route optimization of vehicles and freight for faster deliveries.

• Replicating or simulating the real world – Simulation techniques can help replicate the entire network of a Shipping firm, from client demand, to warehouse operations, to fulfilment, shipping, deliveries, and so on. Simulation gives an end-to-end view of how the network will perform under hypothetical conditions, which parcel journey leg could be a bottleneck or which ones can cause delay in shipments. For example: Information about a huge volume of incoming parcels, much above the capacity of parcel facilities or existing workforce, can help companies prepare to action the insights.

AI is becoming a vital technology to be competitive in the shipping industry. To build a strong AI team, it is essential to have a strong domain expertise and deep technical skills.

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