Commentary: Eliminating the "tunnel vision" approach to supply chain optimization
"Micro-optimization" of individual processes for cost and efficiency produces only isolated benefits. "Macro-optimization" brings widespread improvement to the enterprise as a whole.
Supply chain and logistics executives have been focused on traditional supply chain strategies for far too long. Approaches such as mechanization (for example, pallets and pallet lifts); physical distribution (warehousing, material handling, and freight transportation); logistics automation (automated machinery); and enterprise resource planning (ERP) systems have relegated the traditional, siloed supply chain to a role as a cost center. This "tunnel vision" focuses on optimizing operational processes in order to achieve greater efficiencies and thereby drive down costs.
While that may have been a successful strategy in the past, leading many to take an "if it isn't broken, don't fix it" attitude toward their supply chain management (SCM) solutions, that kind of thinking could doom them to the same fate as once-successful industries that have failed or are in trouble today. Think about companies like Sears, Blockbuster, Life Magazine-all experienced a time as premier brands, but they struggled to adapt when faced with a "perfect storm" of disruptive technologies, an expanded competitive marketplace, new consumption models, and changing consumer expectations. They and others like them focused on cost containment instead of adapting and leveraging new technologies and business models to drive growth.
In our industry, this kind of disruptive change is exemplified by the "Amazon effect," the phenomenon that has raised customer expectations with respect to the speed and visibility of goods in-transit and the demand for same-day delivery. In contrast to the old-line businesses like those mentioned above, modern supply chains are adopting new technologies and business models championed by innovation leaders like Amazon.com. We now have a global marketplace that offers easy access to a broad variety of products and satisfies customer expectations regarding the speed and visibility of goods in transit, while also focusing on innovation with an eye toward growth and consumer satisfaction. Nevertheless, if companies continue to view their supply chains as a linear, static cost center, the result will be a dead end. Those embracing a model that relies on cooperation and collaboration across the industry rather than siloed, internal operations are and will be the winners.
In this new world, the key to successful supply chain strategies that will meet increasing customer demands revolves around one concept: macro-optimization.
Micro- vs. macro-optimization
Traditionally, organizations have run their orders and shipments through an optimization engine based on a siloed network, resulting in their SCM solutions being "micro-optimized."
When supply chains are driven by micro-optimization strategies-that is, they are treated as a cost center instead of as an asset, and they are inwardly focused on a single existing network-they become static and inflexible. As a result, models, prices, and agreements become outdated as soon as they are put in place, and companies are unable to react to changes in the market.
For example, in the micro-optimized approach, no matter how efficient the optimizer is, it will always leave some portion of a shipment un-optimized because it is working with slightly outdated information, therefore there is a finite amount of opportunity in that data set. On average, users of optimization software will find that this lag time results in 4 to 10 percent suboptimal output from micro-optimization.
Comparatively, macro-optimized approaches embrace a new supply chain model, one that relies on cooperation and collaboration as well as the connection of many supply chains, as opposed to focusing on an organization's own supply chain. In a macro-optimized model, companies are able to adapt to customer demands because this approach allows for modifications within supply chain processes; for example, they can adjust to fluctuations in available capacity and have visibility into optimization opportunities that may be available through multiple networks. Micro-optimized approaches cannot allow for modifications, because there is a limit to its effectiveness, as it is inherently limited to an organization's own orders, rates, and carrier capacity.
When organizations adopt macro-optimization, two essential elements are required for success:
1. A global trade network (GTN): A connected, collaborative network enables companies to have access to a broader, deeper community of shippers, trading partners, carriers, freight forwarders, and so forth. The power of a network lies in its ability to bring clarity and certainty to a volatile situation and its ability to offer "on-demand" connections to thousands of potential carriers.
2. A single-instance, multitenant environment: This environment allows for the aggregation of data from multiple companies, where real-time visibility is a reality. Data is captured, analyzed, and operationalized to an organization's advantage.
Here are two real-life examples:
Capacity constraints can be a daily concern for shippers. In a micro-optimized approach, a shipper ends up overpaying for a less-than-truckload (LTL) pick-up, because the individual shipper has no ability to take advantage of the additional empty space in the truck. With macro-optimization, shippers can share capacity on less-than-truckloads or on backhauls. Additionally, in macro-optimization, if a shipper always moves freight on a particular lane but never has a return load, another shipper could use that empty capacity on the backhaul for one of its difficult lanes. In this scenario, both shippers saved money, and the carrier didn't waste "empty miles."
As another example, a group of small-parcel shippers located in one major city can use macro-optimization to pool their freight while also engaging in the cost-saving option of "zone skipping." In this situation they pool and move their freight by local carrier several zones away, and then tender their parcels for delivery to a major carrier like UPS to avoid expending the time and resources required to complete the shipment themselves. This option is not available to them if they stay in their own, siloed operations. But with macro-optimization through a global trade network and a single-instance, multitenant environment, the power of the network takes hold and provides new cost-saving opportunities.
Our industry can leverage such disruptive technologies to compete in an expanded competitive marketplace. Taking a macro approach helps companies engage in new consumption models; adapt to natural disasters and other causes of damage that are out of an organization's control; adjust to changing trade agreements and customs requirements; and meet changing consumer expectations driven by the Amazon effect. Changing from tunnel vision to a wider view will be key to the future of our industry. Macro-optimization is the strategy that can make it happen.
Doug Surrett is Chief Product Strategist for the technology and supply chain services company BluJay Solutions (www.blujaysolutions.com).
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."