Top 5 Benefits of Integrating AI in Logistics
Top 5 Benefits of Integrating AI in Logistics

Top 5 Benefits of Integrating AI in Logistics

At this point in 2021, it is no secret that Artificial Intelligence (AI) has deeply seeded itself into our society. From finishing our sentences through automated suggestions to drone-delivered packages from Amazon, all the way to automated groceries… AI has demonstrated its extreme innovative potential for helping to maximize efficiency in many different areas of our lives.

AI’s innovations have advanced the world of business across many industries as well. For the supply and demand chain and logistics operations, AI has been a game-changer. In fact, many reports predicted that AI will create an entirely new “logistics paradigm” by 2030 as it continues to outperform humans at repetitive but mission-critical tasks. With unforeseen challenges in shipping currently taking place, solutions for advancing logistics technologies are more and more needed. It is not wrong to assume that: “Logistics is setting about its journey to make its way as an AI-driven industry”.

Let’s look at the top 5 benefits of integrating Artificial Intelligence in Logistics:

Enriching Data Quality

First and foremost, the primary benefit of AI’s application in logistics will always be the quality of the data it helps to ascertain. Capacities within AI, such as Natural Language Processing (NLP) and Machine Learning (ML), help accurately obtain and organize information that pours into logistics companies at insurmountable volumes every day. NLP can understand terms, phrases, and even jargon that is commonly repeated, and ML can draw connections between these key points—creating context and learning as these words evolve.

Better, faster global connections allow AI to be more accurate than ever before, and when applied to logistics, it will enable optimal data usage within shipping. Avoiding risks and creating more efficient solutions, AI maximizes resources and slashes costs. With synergy between man and machine, enriched data can help tell a company where they need the precise amount of people and assets when they need them, and for how long even in multiple locations.

With improved information authenticity and consolidation, more insight is gained, and logistics companies can make needed refinements across the board for day-to-day operations in a high-demand era.

Improved Predictive Analytics

The capabilities of AI are seriously ramping up company efficiencies in the areas of predictive demand and network planning. Having a tool for accurate demand forecasting and capacity planning allows companies to be more proactive. By knowing what to expect, they can decrease the number of total vehicles needed for transport and direct them to the locations where the demand is expected, which leads to significantly lower operational costs.

An example of this is seen through the international transportation leader DHL, whose platform monitors more than eight million online and social media posts to identify potential supply chain problems. Thanks to ML and NLP, the system extracts information out of online conversations and identifies potential material shortages, access issues, and supplier statuses. With an ability to accurately see what’s coming, logistics companies can remain ahead of the demand curve helping them glean a competitive edge in the transportation industry and cut down on unnecessary costs.

The tech is using data to its full potential to better anticipate events, avoid risks and create solutions. This allows organizations to then modify how resources are used for maximum benefit – and Artificial Intelligence can do these equations much faster and more accurate than ever before.

Better Transportation Forecasting

It was projected that AI would increase productivity in logistics by more than 40% by 2035. Efficient output in the supply and demand chain is especially make-or-break now, with E-commerce exploding up 33% to $792 billion in 2021 alone.

AI can be linked into a multitude of databases along the transportation chain, procuring information on all available components and opportunities, and providing a roadmap to enhanced feasibility.

AI-driven software can provide demand forecasting per asset type and location up to 12 weeks in advance, giving logistics companies insight to route rail and vehicles more efficiently, optimize storage on ocean shipments, and potentially avoid any bottlenecks at ports or areas of common production delays.

This is vital during an increasingly chaotic era in the transportation industry: shortages of vehicles and shipping containers… add delays to the transport route.

Strategic Asset Positioning

With it costing more than $20,000 to ship a standard 40-foot container from China to the east coast of the US in 2021, up from less than $3,000 only two years ago, it is imperative that logistics companies fortify all of their available assets.

An AI analysis can increase visibility into fleet performance, help planners and logistics professionals strategically position their assets and safeguard against unnecessary risk. AI algorithms support companies in the utilization of predictive capacity matching decreasing the nonessential shipment of empty containers and trailers and even mitigating the number of vehicles on the road.

By decreasing the total number of vehicles needed for transport and directing them to the locations where the demand is expected, asset positioning can ensure efficiency while also achieving significantly lower operational costs. This helps to ensure that a shipping company always has the correct number of assets at the optimal location, at all times.

Last Mile Planning

In 2021, there was a 24.3% increase in the parcel and last-mile segment of transportation from growth in E-commerce and home delivery. Rather than subscribing to subjective guesswork, logistics companies need to apply AI to linehaul planning in order to streamline and enhance overall operations.

With a capacity to predict forthcoming volumes on the most granular level, every leg of a shipment’s journey can be solidified. By understanding all the external factors that might occur along the arduous line of a shipment, AI can help logistics technology companies plan around unnecessary roadblocks and remain efficient especially in the last mile of transportation. Unlocking informed data for linehaul planning through AI will set companies apart from their competitors because they can prove in real-time that they can both literally and figuratively deliver.

How to leverage AI for Logistics?

2021 has been a game-changing year for logistics service providers. AI is due to grow from 12% to 60% within logistics over the next five years showing the important in accessing these innovations.

In order to stay competitive and leverage physical assets and infrastructure to the fullest logistics businesses need to find a digital technology organization to consult and deploy AI to digitize operations.

TSL is proud to be a connection between the world’s leading logistics solutions and Vietnamese enterprises. We offer a total comprehensive solution related to barcode and RFID devices. Solutions that TSL provides which has been applied  the development of automation and computer science, bringing a comprehensive and seamless management system to help businesses operates in transportation service, warehousing and goods in a timely, accurate and economical manner.

TSL is currently an official partner in Vietnam of Blue Yonder (former as JDA) and SOTI  – the world’s leading brands in the field of logistics with solutions: Warehouse Management System (WMS), Transportation Management System (TMS), Category Management System (CMS), Demand Forecasting, Enterprise Mobility Management (MobiControl). Besides, TSL is also as the authorized partner of Honeywell and Zebra.

*Source: Reference

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