The Transformative Potential of AI in Logistics

When we talk about the fascinating potential of “AI” technology, we visualize a future of self-driving cars, robots performing high-precision surgeries, blockchain-powered fin-tech revolution, e-commerce, and much more. We seldom notice that Artificial Intelligence is already altering our daily lives. Suggesting commute route based on real-time traffic, completing sentences in emails, recommending what to watch on YouTube based on our history are instances of AI irreversibly impacting our lives for the better. The subtle, incremental benefits of AI applications in supply chain business does not get enough coverage, despite the huge potential. Business intelligence solutions tailored for the logistics industry can make use of modern technology stack (AI, Machine Learning, Data Science and Predictive Analytics, Cloud Computing) to optimize legacy operations.

The logistics and supply chain sector is a prime candidate to undergo revolutionary changes. It provides an opportunity to disrupt at scale and deliver immediate results by delivering process efficiency, accurate forecasting, optimized route planning, inventory management, view real time dashboards, and much more.

Logistics Industry Pain Points

Many supply chain operators are still relying on manual, decades old logistics processes while the nimble, new-age start-ups are eating into their customer base. They need to realize technology adoption is no more an option to attain a competitive edge – it is fast becoming a necessity to stay relevant.

Before exploring the use of AI in logistics, let us highlight the prevailing problems causing unexpected time and cost overheads.

• Under-utilization of existing data
• Manual workhouse management processes
• Inaccurate transportation and route forecasting
• Inaccurate demand prediction
• Manual re-routing of misplaced packages
• Fragmented customer experience

84% of supply chain managers outline a lack of network visibility as the primary reason for inefficiency, which covers all the points listed above. The need of the hour is to adopt both strategic and tactical approaches – the former will yield long term results while the latter will give short term benefits and confidence to continue along the digital transformation journey.

AI Use Cases in Logistics and Supply Chain

Here are some of the solutions that can leverage modern technology solutions such as AI, ML, Cloud Computing, and Data Analytics to lead them on their path to digital transformation and compete with digital native businesses.

Inventory Modernization

A warehouse has items from different product categories spread across acres of floor area. It is easy to lose track of them relying on manual monitoring. Inventory data is time-sensitive in nature, with a need to be constantly updated in order to deliver value. Today’s data may not hold any value tomorrow, creating a need for leveraging AI and automation to update it frequently.

A drone with an on-board camera passing the shelves every day can address this need. The data would be fed into an AI powered video processor that can read barcodes and accurately determine an item’s location and quantity. It offers the following recurring benefits:

• Faster, with lower error rate
• Long-term cost savings
• Streamlined order processing
• Workplace safety, as employees no longer need to work at heights

Automated Sorting

Parcel sorting is a critical, time-consuming process with little scope for error. You need automated, scalable solutions to scale up on-demand and keep up with e-commerce growth. With AI-enabled sorters, the need to divert more manpower towards sorting during festive season would be a thing of the past.

Combining optical readers with AI powered bots can automate the entire process. Sorters will automatically arrange packages according to pre-defined algorithms. Functioning at its full potential, the solution can make the entire cycle more efficient – from receiving inventory, order processing, picking, packaging, and dispatch. Optical scanners can even determine vital characteristics of each package, i.e. weight, dimensions, destination pin code, etc. to achieve better results, delivering these key benefits:

• Better productivity
• Reduced manpower demand
• Better accuracy
• Lower cost of operations

Transportation and Delivery Route Optimization

Travelling Salesman Problem is one of the oldest and most challenging logistics problem. There have been different approaches to solve it. The last step of Supply Chain – delivery – is one of the most complex problems to solve, due to unexpected events that can occur at any time. Traffic jams, road accidents, road closure, customer not available, etc. are real life situations that cannot be predicted. The need of the hour is to have a self-learning, flexible algorithm that can adapt itself as per conditions.

When a delivery agent leaves your facility with a set of 20 boxes to be delivered at 20 different addresses, the supervisor gives him a route map to help save time and fuel costs. What (s)he does not (and cannot) account for at that time is the changing traffic conditions and roadblocks throughout the day. This is where AI powered route optimization can help you stay ahead of the game. The routing application can read real time traffic and weather data to continuously work out the best route and course correct when possible.

Conclusion

As a logistics business owner, you need not solve all the legacy problems at once. You can adopt technology in a graded manner, where you start reaping the benefits of one solution before investing in another. At AI Superior, we help you channelize technology to modernize all stages of your business – from order creation to delivery and everything in between. Our customized solutions will help you compete and navigate the waters through a continuously evolving business environment.