For many retailers, omnichannel commerce is new and uncharted territory. But consultant Kerry W. Coin has been there, and now offers some guidance on how retailers can master a strategy that's fraught with supply chain challenges.
The advent of omnichannel commerce is changing almost every aspect of how retailers serve their customers—from the way they take customers' orders to how and when they fill and deliver those orders.
Omnichannel commerce refers to retailers' efforts to seamlessly integrate their store and e-commerce selling channels. By doing so, they enable customers to shop by any channel they choose and even use more than one channel to execute a single transaction. As retailers begin to simultaneously serve the Internet, catalog, and store sales channels, some are discovering that they must change their distribution operations to meet the unique supply chain challenges associated with that strategy.
Among the supply chain professionals who have successfully navigated those challenges is Kerry W. Coin. To restart his consulting practice, Coin retired from his position as senior vice president and chief logistics officer at Ann Inc. While at Ann Inc., a U.S. $2.5 billion fashion retailer operating more than 1,000 stores under the Ann Taylor and Loft brands, he worked on the development of a supply chain strategy for serving four retail store channels and two e-commerce sites.
Coin has a broad background in supply chain management. Over the course of his career he has worked in apparel, retail food services, consumer products, and management consulting. His consulting firm, The Kerma Group LLC, is dedicated to helping clients in the retail sector.
In a recent interview with Editor James Cooke, Coin discussed some of the issues facing retailers when they get into omnichannel commerce, and how they can adapt their supply chains to support an omnichannel strategy.
Name: Kerry W. Coin Title: Principal and co-founder Organization: The Kerma Group LLC Education: Bachelor of Science in mathematics and physics, Truman State University; Master of Science in applied mathematics and computer science from Southern Illinois University Business Experience: Senior vice president, chief logistics officer, Ann Inc.; vice president operations, AnnTaylor.com and vice president supply chain development, Ann Taylor Inc.; vice president retail and fulfillment, 1-800-FLOWERS.com; principal, A.T. Kearney CSCMP Member: Since 2013
Why are so many retailers pursuing an omnichannel commerce strategy these days?
One of the largest investments any retailer makes is product inventory. However, no matter how adept its planners are at planning and allocating this investment across the various points of sale, they will be wrong. Consequently, they will have too much at location A and not enough at location B, which causes two basic issues: First, a customer will be frustrated, and second, a sale will be lost. Omnichannel can serve as a "safety net," mitigating the risk of allocation error because it lets retailers service cross-channel demand from any source of inventory.
All inventory will be sold sooner or later, albeit at a successive series of markdowns, which erode margin. Given the fact that in many businesses a single percentage of margin can more than cover the cost of shipping and processing, omnichannel provides a means by which a retailer can provide the best possible service at the best possible margin.
The omnichannel strategy becomes even more compelling when you add improvements to customer service to these inventory management and margin benefits. The ability for a customer to buy anywhere and have product delivered anywhere or picked up in a store is a true customer-centric strategy that facilitates a win-win relationship between the retailer and its customer.
What changes must a distribution center (DC) make to its operations to serve both brick-and-mortar stores and online orders?
Depending upon a particular retailer's strategy for implementing omnichannel, a DC may not need to make many, if any changes. However, many retailers have not yet begun to balance inventory availability across selling channels—brick and mortar stores, Internet, and catalogue. Consequently, the migration to an omnichannel capability may highlight the need for a different cross-channel allocation of the retailer's inventory investment.
One approach gaining favor among retailers with seasonal stores is to migrate from a primarily "100-percent push" model to more of a demand replenishment model, where some percentage of seasonal product is held back for secondary allocations based upon local store or Internet demand during the season. The key question here regards inventory held at the DC for Internet sales. Since this channel is growing so much faster than the other sales channels, and it is less costly to fulfill a customer order from a DC than from a store, it may be tempting to allocate more inventory to this channel at the risk of cannibalizing store inventory to the point of diminishing store-level selections.
Some smart people have argued for a basic reduction in DC capacity by effectively replacing the traditional DC with a number of expanded brick-and-mortar stores equipped to service local demand for omnichannel orders. They maintain that this approach can mitigate the rapid growth in direct-to-consumer fulfillment. Although I can't see how to make that work out financially, there are indeed some real benefits to this approach other than those mentioned above. For example, parcel carriers can provide one- to two-day delivery to 97 percent of the U.S. population with as few as four well-placed fulfillment nodes. These nodes could be used to service retail locations more promptly with replenishment inventory as well.
What changes do retail stores have to make in their operations in order to pick items off the shelf to fill online orders?
Most retailers will need to reorient and train their hourly staff on a new set of operating procedures and systems. There will need to be a change in the processes utilized to accept an order and to assure the inventory is indeed available to fulfill the customer's order. This is the hardest part, operationally, of meeting the commitment to the customer. Retail store-level inventory accuracy is notoriously low due to a number of factors. Consequently, the inventory management system may indicate the SKU (stock-keeping unit) is available at a store when it is not actually available or may not easily be located at the store. In these cases, the retailer must have triage processes, which allow them to source the item from an alternative location.
Given even a modicum of success, there will need to be dedicated space for staging, packing, and labeling orders for shipment. Arrangements need to be made with parcel carriers to have systemic capability for processing moderate to large volumes of parcels and for reliable pickup times.
Does an omnichannel strategy require a retailer to work differently with its suppliers? If so, how?
Typically, there are a few strategic supply chain partners that need to be fully engaged in the retailer's omnichannel initiative. As described above, the parcel partner is integral to the effectiveness of the retailer's initiative. Similarly, on the software side, a few providers have emerged as leaders in the management of brokering and parsing orders to fulfillment locations. The near real-time availability of inventory by location being so essential, your systems integration partner—and, of course, your internal information technology team—will undoubtedly be called upon to help work through the synchronization of inventory views across the store and DC locations. If you utilize third- party logistics partners as part of your current fulfillment solution, they, too will need a seat at the table, as omnichannel will impact their operations, particularly where reverse logistics is concerned.
How do distributed order management systems help retailers gain inventory visibility? Are there any drawbacks to using this type of software?
The visibility to and management of cross-network inventory is essential to a successful omnichannel effort in a multiunit retailing network. Whether this capability is accomplished via purchased software or internally developed applications, it is a necessity.
I've always looked at the distributed order management application as a "user" of one's cross-channel inventory management application. Historically, multiunit retailers have had separate inventory management systems and practices, which for accuracy's sake are specific to the channel requirements. For instance, in the Internet channel, SKU-level, real-time accuracy is an absolute requirement for fulfilling a customer order, and systems and processes have evolved that routinely assure accuracy in excess of 99 percent. Not so in the retail store environment, where accuracy at the SKU level is far, far lower.
So, the dilemma comes when a retailer believes that there is inventory available at a location and it is not—or, just as bad, thinks there is no inventory and there is. This is one of the major reasons for the renewed interest in radio frequency identification (RFID) technology for retail locations. Retailers simply cannot rely on semiannual or annual physical inventories as the assurance of inventory availability in an omnichannel world.
And, a word of caution here: Please begin this journey with the end in mind. That is, carefully plan how to address the overall cross-channel inventory and order management requirements of an omnichannel strategy up front. This is not one of those initiatives you should undertake with a piecemeal design.
Can retail store workers be expected to fill orders with the same degree of accuracy as distribution center workers? Can store picking ever achieve "perfect order" metrics?
I may be a bit of a contrarian here. Those of us in supply chain operations frequently underestimate the abilities of store workers. Given the proper positioning of the initiative or customer focus; well thought-out processes such as scan and pack validation; incentives such as labor hours and bonus considerations; and training, store workers can certainly fulfill orders as accurately as DC staff—but not necessarily as cost-effectively.
How do you think retailers will handle same-day delivery for online orders?
Personally, I don't see the same-day delivery requirement as being as important as do some others in retailing. Of course, most of my experience is in the branded specialty retail sector, where seasonal allotment of inventory may preclude the feasibility of this capability.
What advice would you give a supply chain executive who has been assigned to set up an omnichannel strategy?
My advice would be, first and foremost, to make sure your entire executive leadership is aligned on the importance and necessity of the initiative. This starts with the chief executive officer (CEO), whose vision and support is essential. Given support from the top, make sure the initiative has the proper governance. Rigorous and candid project management through your project management office is a must. Since an omnichannel program by its very nature touches almost every functional area of the enterprise, a senior executive steering committee is a necessity. The project team must be built from the "best and brightest" from your supply chain operation, information technology group, store operations, change management organization, Internet operations, finance, and those key partners described above.
Of course, any initiative of this size and scope is best implemented incrementally, via a series of pilot projects before full rollout. It's always best to validate the business impacts of these sorts of strategic initiatives, and to confirm and refine plans based on the real-world impact of just how all the moving parts align. Experienced, outside support can be helpful.
Benefits for Amazon's customers--who include marketplace retailers and logistics services customers, as well as companies who use its Amazon Web Services (AWS) platform and the e-commerce shoppers who buy goods on the website--will include generative AI (Gen AI) solutions that offer real-world value, the company said.
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."