Commentary: Why liquidation is worth worrying about
Traditionally, retailers have considered the benefits of liquidating unwanted merchandise to be too small to warrant much attention. But there are ways to go about it that can make a significant impact on the bottom line.
Howard Rosenberg is CEO and co-founder of B-Stock Solutions, a technology-enabled service company powering a network of private-label B2B liquidation marketplaces.
Though most organizations would rather not admit it, when it comes to the handling of returned, excess, and otherwise obsolete merchandise, liquidation—the quick disposition of assets for a fraction of their original price—is the rule in retail. Around 95 percent of returned and unsold merchandise will end up slated for the secondary market (a post-retail channel where unwanted and liquidated goods can be bought and sold). Although this is the most common way to handle returned and unsold goods, many companies fail to get as much value from their liquidation process as they could.
Given how competitive retailing is today, the ability to squeeze margin out of every area of the business—including merchandise slated for liquidation—is crucial. Yet many retailers still manage their liquidation programs the same way they did decades ago: They let excess inventory pile up in a warehouse, and then, only after the chief financial officer (CFO) says, "we need to get this off our books by the end of the quarter," they sell it to one or two liquidators at a rock-bottom price. This can result in billions of dollars lost over time—a huge hit to companies with already skinny margins.
Do the math
Historically, companies have viewed strategic liquidation planning as a money-losing investment; a 30 percent increase in pricing only impacts revenue by a fraction of a percent—so why pay much attention to it? But there is a better way to look at it: Increasing the recovery (pricing) on liquidation is like raising the price on a product. For example, if you are selling an item this week for $50, and next week you find you can sell it for $75, that incremental $25 drops straight to your bottom line. (This assumes there are no additional associated costs involved.)
This is exactly what happens when a company increases its recovery rate on liquidated products. Consider the following illustrative scenario:
1. A retailer has $100 million in revenue, and $3 million of that comes from liquidation sales.
2. This is a relatively well-run retailer with an operating margin of 6 percent (or $6 million).
3. If the company increased pricing on its liquidation sales by, for example, 20 percent, and assuming there are no additional associated costs, then that extra $600,000 ($3 million x 20 percent) goes right to the operating margin—turning $6 million into $6.6 million.
4. The retailer has now increased its operating profit by 10 percent.
What would the company have to do in order to increase sales of "A" stock product enough to have the same impact on its operating profit? Assuming the same 6 percent margin, it would have to generate an incremental $10 million in top-line sales—in other words, 10 percent growth, which is no easy feat—to generate $600,000 in incremental operating profit.
The benefit of achieving a higher recovery for customer returns and other overstock merchandise slated for liquidation seems clear. But conventional methods for dealing with customer returns and excess inventory may not be up to the task. For companies that sell inventory to one or two liquidation partners, recovery value will remain low because liquidators are experts at negotiating prices down in order to maximize their own profits. They make money by buying at lower prices, not by selling at higher prices. The traditional approach has another drawback, too. Selling directly to a liquidator can mean a lack of control over who is eventually buying a company's inventory and how its brand enters the secondary market.
How can organizations today update their liquidation programs in order to achieve higher recovery along with greater control over the entire process? The answer involves something they may already be doing in their forward supply chains: By applying technology and data-driven analytics to their liquidation programs, they can increase recovery by 20-80 percent and sometimes more, in our experience.
Time to rethink liquidation
Over the past few years a shift has taken place in how organizations manage returned and overstock inventory. Many are bypassing layers of middlemen and incorporating technology-based liquidation programs into their overall business strategy. This might include launching a private marketplace platform that can be customized, integrated, and scaled based on a company's unique needs, or leveraging an established business-to-business (B2B) marketplace, making that merchandise available to thousands of buyers who will compete for it via online auctions.
Applying this type of online marketplace platform not only delivers the highest price a buyer community is willing to pay right now, but it also automates the sale process, delivers a faster sales cycle, and generates proprietary market intelligence in the form of accurate data on market prices. Automation reduces overhead, and it may offer other advantages as well, such as the ability to sell from multiple locations, a practice that reduces the need to consolidate inventory and eliminates extra transportation costs. And some marketplace models allow retailers to increase their recovery without paying added out-of-pocket costs.
Rethinking a liquidation program is a must in today's competitive business climate in light of the slim margins most retailers are fighting to maintain. Any increase in prices you can achieve on liquidation volume—assuming there are no additional costs associated with the sale—falls 100 percent to the bottom line. If you do the math on your company's liquidation volume and assume a 20 to 80 percent improvement in liquidation pricing, you will see that the impact on operating and net profit can be quite meaningful.
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."