Agilent Technologies' "control tower"—an information hub linking the instrument maker with its suppliers to provide inventory visibility—has helped the company deftly model parts availability, manage order promising, and counteract parts shortages during a natural disaster.
In 2011, when the worst flooding in decades swamped Thailand, many of the manufacturing plants that produce electronic parts and components in that country were forced to suspend operations. That left many of their customers—mostly large international manufacturers—without critical parts needed to fill orders. But not Agilent Technologies Inc. Although Agilent's contract manufacturer in Thailand was out of commission, the testing-equipment maker was able to fill most of the orders that normally would have included items produced by that supplier. That's because Agilent had a resource its competitors didn't have: a "control tower" it had installed a year earlier for its Electronic Measurement Group (EMG).
The control tower is an information hub that links Agilent with its suppliers to provide visibility of the inventory in its supply chain, at both the company's own locations and at the sites of its contract manufacturers and their suppliers. The control tower's staff uses simulation software to model the impact of parts shortages on production and devise a plan to solve any problems. In the case of the Thai floods, the company used that software to rapidly identify shortages so that alternative sources for parts could be quickly found, or in some cases to permit the redesign of parts. "The control tower helps us to be able to capture all components during a shortage so we can come up with risk-mitigation actions," says Michael Tan, Agilent's EMG Supply Chain Operations Director.
Inventory unknowns
Agilent Technologies was created in 1999 when Hewlett-Packard spun off its test and measurement instrument business from its computer business. Headquartered in Santa Clara, California, Agilent Technologies reported US $6.9 billion in revenue in 2012. The Electronic Measurement Group (EMG) is one of four groups within the company, and it's the most profitable one, with US $3.3 billion in revenue in 2012. EMG sells products like oscilloscopes, spectrum analyzers, and network analyzers that are used in such industries as aerospace, defense, communications, and computers. The group has 9,000 customers worldwide. (In September 2013, Agilent Technologies announced plans to make the Electronic Measurement Group a separate, publicly traded company.)
To make 5,000 different types of electronic instruments, EMG works with 1,100 suppliers, 52 percent of which are based in Asia. Although the measurement group operates some of its own factories, it relies on strategic contract manufacturers to make 70 percent of its products. On average EMG ships 70,000 units each month to customers.
Agilent's inbound supply chain spans the globe and requires the coordination of parts flows between its own factories and those of its contract manufacturers. For example, Agilent technology centers in the United States and Germany make integrated circuits. Contract manufacturers in Asia incorporate those components into what Tan refers to as printed-circuit assembly boxes. But Agilent's main manufacturing plant, in Penang, Malaysia, also incorporates the integrated circuits into microcircuit assemblies found in electronic instruments.
All of those factories, both in-house and contract, keep their own inventories of parts to support production. Each plant also has its own suppliers, which keep their own stockpiles of inventory.
The whereabouts and availability of inventory in Agilent's extended global supply chain became a concern in 2009. That's when the economic downturn subsided and business began to pick up again. Cutbacks in production and the demise of some suppliers during the recession had led to parts shortages throughout the electronics industry. As a result, when Agilent needed to ramp up production, it "had some challenges" in locating parts that were in short supply, Tan says.
Compounding the problem was the fact that Agilent needed accurate information about parts availability from its suppliers in order to make delivery commitments to key customers and win business, yet it had no way to get that critical information quickly. One reason was that Agilent, its contract manufacturers, and their suppliers were using different information systems. While Agilent relies on Oracle's technology to keep tabs on production, many of its contract manufacturers and suppliers use enterprise resource planning software from SAP. Because the different information systems in the supply chain were not linked, if Agilent wanted to determine whether it had all the necessary inventory to make an order delivery-time commitment to a customer, it could take three to four weeks to get an answer from all the parties involved.
Simulation saves the day
To solve this problem, Agilent decided to construct a control tower that would give the instrument maker visibility into inventory holdings down to the supplier level in as many nodes in its supply chain as possible. For this vertical supply chain integration project, it bought RapidResponse software from Kinaxis, a vendor of enterprise supply chain software solutions. Besides facilitating supply chain visibility, the software handles demand, supply, and inventory planning as well as what-if analyses, among other functions.
In 2011, Agilent got the control tower up and running with three contract manufacturers and two of its own technology center facilities. Since that time, the control tower's scope has expanded in stages. Currently, it extends to five contract manufacturers and five Agilent-owned sites. Three of the contract manufacturers are in Malaysia, one is in Thailand, and one is in California. Agilent's own facilities linked to the tower include its plants in Penang, Malaysia, and in Santa Clara, California. The tower is also linked to technology centers located in California and Colorado in the United States, and one in Germany.
Staff members who oversee the control tower's operation work out of Agilent's main facility in Penang. There are two teams involved: one conducts the analysis, while the other manages data governance to ensure that all linked locations provide correct, high-quality information.
The suppliers transmit information to the tower on a daily basis. As of this writing, the control tower has visibility of more than 94 percent of all parts used in the EMG supply chain. The tower uses this information to create a complete picture of Agilent's supply chain, which the company employs to manage both daily operations and crisis situations. The information is displayed on computer screens formatted in customized worksheets that show purchase orders, plan, and supply allocation. Tan says the customized worksheets allow Agilent to monitor part-by-part shortages throughout different levels of the supply chain via weekly projected balances based on demand.
The control tower is routinely used to simulate the impact of a major sales event on production. "Our sales engineers want to be able within a half day to come back to a customer and say whether we can support them and get the product in a four-week shipment time," Tan explains.
Whenever a major customer deal is in the offing, the control tower helps Agilent to determine an accurate commitment date for product delivery. It does so by simulating the parts requirements. The simulation allows Agilent to check with its manufacturers and suppliers to determine parts availability, including whether production would encounter any parts shortages. If the simulation reveals possible problems with the availability of components, Agilent can then work with its suppliers to source the part on the open market or obtain it from other distributors. In some cases, the company has re-engineered the product to use an alternative part when the original version was unavailable.
Tan says that the control tower can very quickly predict the revenue impact from any possible deal as well as the company's ability to meet a delivery date before promising it to a customer. "Because of the wide range of products, it was quite a challenge to do this manually in the past within a short time," he says. "The control tower lets you know how much you have on hand and how fast you can get these parts into the factory that produces the product for the final customer."
Since setting up the control tower, Agilent has speeded up its response time for customer order promises. In the past, turnaround time for demand propagation took three to four weeks, as the instrument maker had to contact manufacturers and suppliers involved in a particular order and wait for their responses to determine parts availability for production. Now turnaround time is a week or less.
The control tower also helps Agilent with crisis management, such as when the floods in Thailand affected its contract manufacturer there. The tower simulates the constraints facing a manufacturer or supplier when an unforeseen event disrupts the supply chain. It enables a bottoms-up modeling through the supplier levels to identify the total impact of a disruption on sales orders, forecasts, and safety stock for the various products. It also lets Agilent prioritize the allocation of constrained materials to meet critical demand on the basis of the greatest business benefit. "Because of this tool we are able to quickly simulate gaps [in supply]," said Tan.
As a result of this capability, Agilent was able to minimize disruption for its customers during and after the floods. In some cases it found other sources for parts that it normally would buy from its Thai supplier. In other cases, it redesigned the product or engaged in "value engineering," a technique that involves identifying acceptable substitute parts.
A winning concept
For the control tower to provide inventory visibility, Agilent's supply chain partners must furnish clean, accurate data. The original owner of the data—whether it's Agilent's procurement team or a supplier—is responsible for accuracy and timely updates. "When new products are introduced, the bill of materials needs to be set up correctly at each level," Tan says. "That's why governance is important. Any change needs to be communicated throughout all levels of the supply chain."
Because the control tower needs accurate data for its parts calculations, Tan says, the company must work closely with contract manufacturers and their suppliers. For any data-sharing effort to succeed, he adds, all parties involved must benefit. "It is very important to collaborate to ensure that the data sharing will help [manufacturers and suppliers] as well," he says. "They have to realize that they are linking to systems to let them know their shortages. Then they can see the benefits of linking to the control tower."
Given Agilent's positive experience, would Tan recommend that other companies with complex supply chains consider the use of a control tower to manage inbound supply? He's a firm believer in the concept. For one thing, he says, end-to-end supply chain visibility on a single platform will give companies the ability to manage their supply chains across regions and across time zones. "This will help the company to perform proactive and effective collaboration with suppliers and also enable speed in decision making in the shortest turnaround time," he says. That's key for avoiding unnecessary inventory and expediting costs. But just as importantly, he adds, "it will enable the company to win deals as well as provide customers the best customer experience in terms of delivery responsiveness."
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."