Those responsible for supply chains, secure package management, and contactless package management, are pressured to deliver an ever-increasing volume of eCommerce shipments. But they do have an ally in the form of AI and computer vision to improve efficiency and streamline the fulfillment process. These two advances are literally transforming the supply chain and improving “customer-to-merchant” engagements. 

As originally posted at Toolbox, this must-read blog details how new technology advancements are automating and improving eCommerce to benefit merchants and enhance customer experiences–like never before!

Supply chains need to get smarter to deliver an ever-increasing volume of ecommerce shipments. AI and computer-vision can improve efficiency, streamlining the fulfillment process and how shoppers engage with merchants.

The path along the logistics chain needs to become more efficient to streamline an ever-increasing ecommerce volume, elevate shopper satisfaction, and promote repeat business. Even with the COVID-19 vaccines rolling out in 2021, consumers will remain guarded in their buying habits and continually rely on ecommerce more and more.

This statement is underscored by a Mckinsey report that says ecommerce underwent ten years of growth in just three months to overtake physical channels. Whether it’s retail, residential, or enterprise, supply chains need to get smarter and evolve to deliver this ever-increasing, massive volume of shipments.

A critical component of this supply chain evolution is leveraging AI to help ease the load of delivering and managing these shipments. Artificial Intelligence (AI) and computer -vision technologies are good examples of new ways to improve the efficiency of processes that are critical for the movement and storage of goods.

For example, large metal package lockers were a reasonable approach to be used as a holding area for deliveries in the past. Over time, these bulky lockers proved to be inefficient due to the amount of space they occupy as well as the fixed physical dimensions of each individual storage locker space; often too small to accommodate larger items or too large making smaller items occupy more space than necessary.

AI and computer-vision systems are now replacing lockers, allowing organizations to use open shelving systems where items are tracked and securely monitored more efficiently, improving staging, space utilization, and retrieval. Computer vision also provides a digital breadcrumb trail that drastically improves visibility and, as a result, item management.

This new form of managing deliveries is a welcomed change that brings more flexibility to a rigid retail model.

Nextgen Tracking

A critical aspect of package management involves reading labels with unique tracking numbers or identifiers to identify each item. These labels are placed on every item, and reading these identifiers, either by handheld scanners or having a person physically entering the label information into a computer database, dramatically slows the entire delivery process.

However, utilizing the unique capabilities of computer vision will enable systems to automatically read and record these labels, eliminating the need for handheld scanners or manual data input by staff. This automated label registration process offers one hundred percent item visibility across the entire chain while reducing human intervention and costs.

Billing and Auditing

Logistics companies can also use computer vision to audit the package dimensions traveling through their hubs, enabling senders to easily and accurately measure package dimensions before shipping them.

The lack of understanding on how to properly measure package dimensions can lead to misaligned expectations on how much shipping will cost vs. how much a sender actually gets billed. By automating the manual task of measuring package dimensions, logistics companies can streamline and enhance the customer experience and reduce costs.

Reverse Logistics

The growth of ecommerce continues to increase,  causing additional challenges beyond home deliveries. Barclaycard research found that 30% of shoppers deliberately over-purchase and subsequently return unwanted items, and nineteen percent of those surveyed admitted to ordering multiple versions of the same item so they could make their mind up after delivery.

Today’s agile supply chain has to manage the delivery of online purchases to distributors and in-store pickup along with the reverse fulfillment process from the consumer to distributor to store. It’s no longer linear—the supply chain is now circular.

Retailers are now desperately trying to manage returns and where to send them—whether they should go back to inventory, be donated, recycled, or possibly sent to a distribution center. Some large retailers such as Amazon and Walmart are making progress with reverse logistics by leveraging AI algorithms that can make a cost analysis to determine whether the item should be returned or remain with the shopper.

AI and computer-vision technologies are helping reduce reverse logistics inefficiencies by creating a same-day chain-of-custody trail that identifies a purchase and the subsequent return back to the store for an exchange. A reverse ecommerce fulfillment process, where shoppers can order online, bring unwanted merchandise back to a physical store location, and simply place it on the return shelf, is both a huge challenge and a major opportunity for retailers.

In an optimized reverse fulfillment process, AI takes over to automatically identify and tag the item as returned, and computer vision monitors it until it’s processed or placed back in inventory. Items don’t even have to be returned in the original packaging. Systems such as the iPickup center can recognize and record the item placed on a shelf and send the customer a picture as proof of the return.

In the future, it will automatically be able to determine if it gets restocked or sent to a discount store. This “packageless return” streamlines the entire reverse logistics process and simplifies it for the shopper because it removes the “arts and crafts” hassle of packaging up and shipping out a return. Automated AI-enabled in-person, packageless returns produce more economic value and are a more eco-friendly option for this new reverse logistics opportunity.

Conclusion

Computer-aided logistics are transforming the entire supply chain and streamlining not only the fulfillment process but also how shoppers engage with merchants pre and post-purchase. With the increase of ecommerce and the enormous volume of returned merchandise, the human element has now become the weakest link in the distribution chain.

By embracing technologies such as AI and computer vision, steps can be improved or taken out of the customer journey, streamlining the shopping experience while helping retailers transform their own logistics process and focus on customers, not fulfillment.

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