Mastering Winter Sales in Retail: How to Leverage AI-Driven Solutions for Streamlined Logistics

The AI market in the supply chain is expected to reach $41 billion by 2030, growing at a CAGR of 39% from 2023. [1] The reason behind this tremendous growth in AI utilization across the supply chain is pretty straightforward – the supply chain is full of inefficiencies.

By leveraging AI-powered solutions, businesses can improve the efficiency of their supply chains by up to 67%, making AI not just a perk but a must-have in an increasingly competitive market. [2]

This article will explore the role of AI in the supply chain, particularly around how it could help businesses avert risks and maximize sales by streamlining logistics.

Leveraging AI-driven solutions for streamlined logistics

AI applications and use cases have permeated nearly every industry, offering cutting-edge solutions for a myriad of problems, and the logistics sector is no exception. When utilized correctly, AI could significantly improve logistics operations and eliminate bottlenecks throughout the supply chain.

Here are some of the most notable ways AI can improve logistics operations for retail businesses during the winter sales bonanza.

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Logistics planning

Logistics processes require significant planning. The process is even more intense at busy times of the year when businesses need to coordinate between suppliers, store managers, customers, and other essential elements of the supply chain.

AI-driven technologies and machine learning solutions can facilitate logistics planning operations through numerical analytics and scenario analysis. [3] AI can also streamline logistics planning through:

Demanding Forecasting

Traditional forecasting methods like exponential smoothing methods and AutoRegressive Integrated Moving Average are barred with a huge margin of error. They also rely on historical data, which may not apply in heavy sales periods like the winter sale.

Demand forecasting, on the other hand, utilizes real-time data from the business’s CRM software to make accurate demand forecasts, leading to improved sales, reduced holding costs, and a reduced probability of stockouts.

Supply Planning

By analyzing product demand in real time, businesses are better able to update their supply planning parameters, thereby optimizing the flow of their supply chain. Ultimately, this helps reduce the amount of resources required to supply the various branches and minimize wastage.

Read more about Benefits of Artificial Intelligence in Supply Chain Management: optimization and cost reduction

Analytics

Any business that seeks to remain competitive in this dynamic market must leverage data analytics capabilities to make use of collected data for more effective intelligent decision-making. AI-powered analytics can also improve logistics by:

Route Optimization

Freight management is an important aspect of logistics operations. By analyzing existing routes, businesses can better determine the best routes based on distance and traffic situations. For instance, by utilizing shortest path algorithms in graph analytics, businesses can identify the best routes, thus cutting shipping costs and speeding up the delivery process.

Dynamic Pricing

Optimizing logistics operations isn’t just about making sure freight gets to its destination on time; it’s also about cutting costs in a bid to offer more competitive pricing. Dynamic pricing takes this up a notch by actively analyzing supply, demand, subsidiary product prices, and competitor pricing changes to automatically respond to price and demand fluctuations.

Intelligent, automated warehousing

Warehousing has several bottlenecks, including inventory management issues, unoptimized processes and workflows, and seasonal demand fluctuations. These bottlenecks are more pronounced for large retailers who deal with tons of varying goods.

In a bid to improve warehousing efficiency and eliminate some of these bottlenecks, several large retailers, including Amazon, are adopting intelligent warehousing solutions that utilize AI and robotics to substitute human tasks, thereby reducing errors and improving operational efficiency.

For instance, Amazon’s intelligent warehouses[4] that utilize robotics for order fulfillment have benefited the company greatly by cutting costs, minimizing errors associated with order pickups, and accelerating the picking and packing of orders, thus improving the overall efficiency of the company’s warehouses.

Other AI-driven technologies like computer vision can also benefit businesses greatly. When utilized in conjunction with robotics, computer vision can aid in damage detection of stored products, thus reducing the possibility of delivering damaged goods.

It might be also interesting for you: Scenario-based supply chain optimization with AI

Streamlined back-office processes

Logistics processes don’t just end at the supply chain; they also transcend into everyday back-office operations where tons of structured data like bill of lading forms have to be manually extracted, stored, and analyzed to facilitate and enhance business operations.

In that regard, AI can help streamline back-office processes through:

Automated Document Processing

Important documents like bill of lading forms and invoices help businesses communicate with their suppliers, storage providers, and customers. Unfortunately, processing these documents manually can prove rather daunting, not to mention the amount of time and human resources it takes. By leveraging AI-powered automated document processing, businesses can effectively streamline various document processing tasks, including data input, error reconciliation, and report generation.

Autonomous vehicles

Over the past few years, several companies, including some major vehicle manufacturers like Tesla, have developed autonomous vehicle technology that’s poised to revolutionize how people travel and deliver goods.

Although current technologies are primarily focused on driverless cars, driverless trucks might be hitting the road anytime now. When incorporated into other AI-powered technologies like smart roads, driverless trucks could be much safer than human-operated vehicles, leading to safer roads and faster delivery of goods.

In 2022 alone, the number of automated vehicles produced was 17,000 units. As businesses continue to see the limitless possibilities of fully automated delivery vehicles, this number may grow to reach 127,000 units by 2030, marking a significant shift in the logistics sector. [5]

Wrapping up

The winter sales season is one of the busiest times of the year for most retail businesses. The holiday shopping craze presents an excellent opportunity to get rid of the year’s dead stock and introduce new products.

However, to facilitate all this, businesses need an elaborate, streamlined logistics process that can easily handle the increased flow of goods. To this effect, any company leveraging AI technologies like analytics, robotics, intelligent warehousing, and other business-oriented AI-powered technologies is bound to have an operational advantage over their counterparts still relying on traditional means.

References

[1] Intellias.com. AI in Supply Chain. URL: https://bit.ly/3tTlxST. Accessed on January 5, 2024
[2] Ctmfile.com. AI is Set to Transform Supply Chain Management Industry. URL: https://ctmfile.com/story/ai-set-to-transform-supply-chain-management-industry-roundup-13-april. Accessed on January 5, 2024
[3] Sciencedirect.com. Scenario Analysis. URL: https://www.sciencedirect.com/topics/earth-and-planetary-sciences/scenario-analysis. Accessed on January 6, 2024
[4] Aboutamazon.com. Amazon Introduces New Robotic Solutions. URL: https://www.aboutamazon.com/news/operations/amazon-introduces-new-robotics-solutions. Accessed on January 6, 2024
[5] Statis.com. Projected Number of Automated Cars Worldwide. URL: https://bit.ly/3TV9mQe. Accessed on January 6, 2024