Tag: AI

OM in the News: Navigating Supply Chain Disruptions

“Historically, supply chain teams react to crises only after they have already begun,” writes Material Handling & Logistics (Dec. 19, 2024). A crisis starts and the team goes into fire-fighting mode. After the situation is remedied, teams return to business as usual, only to await the next crisis. Balancing strategic imperatives with solving these short-term crises is the key to effective supply management.

For years, supply chain professionals have been forced to play defense, constantly reacting to minimize disruptions as they arise. This approach not only diminishes employee productivity by forcing them to constantly switch between projects and contexts, but it also undermines the perception of the function’s strategic importance.

The Panama Canal is no stranger to challenges and complexities brought about by natural disasters, geopolitical tensions, or technical failures

But new technology is transforming the way supply chains are managed. Instead of addressing problems as they arise, procurement professionals can identify opportunities for strategic value early and often, developing proactive response plans for dealing with predictable disruption events. While the specific timing and severity of disruption events like hurricanes, port closures, labor strikes, or country shutdowns are difficult or perhaps even impossible to predict, there are a finite number of event types each year that can disrupt supply chains, and thus a finite number of response plans that can assure resilient continuity of supply.

With the advent of new predictive procurement tools like those we discuss in Module G (Applying Analytics to Big Data), supply planners and purchasing teams now have the capacity to reduce the chaos of unexpected disruptions.  AI-driven tools are now helping to streamline and automate labor-intensive tasks, allowing procurement teams to quickly identify alternative suppliers and manage spot-market opportunities when unexpected challenges arise. By analyzing data trends, such as historical supplier performance metrics and environmental factors, these predictive procurement systems enable businesses to make more informed decisions proactively.

Identifying alternative sources of supply within a company’s existing supplier base is key, since qualifying new suppliers can be time-consuming, and expanding the total number of suppliers may introduce unnecessary complexity. Also,  securing carriers with secondary capacity is equally important, as logistical challenges often arise when transport routes are disrupted.

Classroom discussion questions:

  1. What tools do AI provide supply chain planners?
  2. What canal issues have companies faced the past two years, and how have they dealt with them?

OM in the News: Amazon’s New Robotic Warehouse and Humans

Amazon just opened its most-automated warehouse yet. But underneath the robotics and artificial-intelligence technology at the site, the facility will still rely on thousands of employees, writes The Wall Street Journal (Dec. 7, 2024). The 3 million-square-foot building in Shreveport, La., is Amazon’s first warehouse to use automation and AI at every step of the fulfillment process and be able to handle one million orders a day.

Amazon’s Sparrow device uses suction cups to lift items and artificial intelligence software to identify objects by color, shape and size

The facility shows how companies are spreading automation through their distribution centers to get online orders to consumers at an ever faster pace. The sprawling site also demonstrates the challenges Amazon and other companies face as they seek to turn over some of the most physically demanding and repetitive warehouse tasks to robots.

Amazon hired more than 1,400 people at the Shreveport distribution center and plans to eventually employ 2,500 workers picking orders, loading and unloading trucks and managing the robotics systems. The idea is to speed up operations, save on labor costs and make warehouses safer for the workers that remain. Amazon has been the subject of government scrutiny over the treatment of the workers at its facilities. The warehousing sector had one of the highest rates of injuries and illnesses in the U.S., with 4.7 cases recorded per 100 workers compared with the national average of 2.4 cases per 100 workers.

Some traditional warehouse roles have proved too difficult for Amazon to fully automate, however, partly because the company sells more than 400 million widely varied products that range in size, weight and fragility, from dog toys to toaster ovens. Humans can easily look into a storage container packed full of goods, identify a particular item and know how to pick it up and handle it, whether it is a bottle of shampoo or a sweater.

 “The tactile grasp that the human hand has, and the situational awareness and the perception of the human brain, is unmatched,” said Amazon’s chief technologist. Instead, robots at the facility carry storage containers full of merchandise to human employees who look inside and pick out the item a customer ordered, then place that item into a tote box that goes onto a conveyor belt and is taken to be packaged.

Classroom discussion questions:

  1. What are the advantages and disadvantages of automating warehouses?
  2. Why do warehouses have high injury rates?

OM in the News: Junk Is Needed for the New Electric Era

Circuit boards from thousands of different products arrive at Glencore’s Rhode Island facility, where the company determines the copper content and the value of the waste.

One of the world’s largest miners is digging into America’s junk drawers, old phones and landfills. The quarry: bits of copper to meet the needs of the energy transition and data boom.  Shredded cellphones, obsolete computer cables and chewed-up cars are heaped 30 feet high outside Glencore’s 97-year-old copper smelter deep in Canada’s boreal forest. There, the scrap is melted with copper concentrate from mines to produce fresh slabs of metal.

Shifting from fossil fuels to more renewable electricity promises to remake commodity markets, writes The Wall Street Journal (Nov. 21, 2024). If America requires less crude oil and coal, it will in turn need copper for everything electric. “In the next 25 years we will consume more copper than humanity has consumed until now,” says Glencore’s  recycling head.

Data centers being built to facilitate AI and store smartphone videos are full of copper. So are the phones. Even if rich mine deposits are found, it takes decades to bring them online. That prevents miners from responding quickly to new demand, which leaves scrap to balance the market. Copper never goes away and is infinitely recyclable.

Miles worth are strung through homes and cars and along rights of way, carrying electricity and drinking water. But a lot sits in junk yards and landfills. When prices rise, there is more incentive to get it. Copper prices are currently among the highest ever. Nearly half of demand will be met with recycled copper by 2050, up from about a third today.

Germany’s Wieland began construction in 2022 on a $100 million recycling facility in Shelbyville, Ky. Another German firm, Aurubis, is building an $800 million recycling facility in Augusta, Ga. Glencore recently bought a failed electronics recycling facility in Arkansas and will use it, too, to gather scrap. Glencore found that the concentration of copper in landfilled auto fluff can be more than twice that found in geologic mines.

Classroom discussion questions:

  1. Why the demand for copper?
  2. What makes copper recycling attractive?

OM in the News: Reducing Manufacturing Waste

With inflation keeping the cost of raw materials high, it has become more important than ever for manufacturing companies to reduce waste as much as possible. Not only is this strategy good for the environment, and the company’s bottom line, but it can also boost employee well-being and morale, writes Industry Week (Nov. 12, 2024). Here are five approaches:

  1. Use Less Material. One obvious solution is to cut down on the amount of materials used. To help identify where waste is coming from – whether it is using more energy or thread than needed to produce a shirt, or printing reports that could easily be shared digitally – a thorough examination of a company’s practices is the first step. Recycling should be prioritized, including printer cartridges, old computers, monitors and batteries from small devices. Recycle containers should be near every workstation.
  2. Save Time. Time management can help cut down on waste substantially by reallocating unnecessary work to more important tasks that will help boost profit. Real-time tracking using radio-frequency identification (RFID) uses radio waves to follow a product from the beginning of manufacturing all the way through to shipping. This helps identify how to potentially streamline and speed up the production process.
  3. Embrace Artificial Intelligence. AI has the potential to discover new areas for improvement that humans may not be able to identify on their own. For example, it could be used to analyze the motion of workers and products throughout the manufacturing process. Cameras can be placed throughout a factory to capture the necessary information for the AI system to review and analyze.
  4. Optimize Workflow. Another type of waste that is important to a manufacturing company’s success is excess movement. When an employee is able to produce more without having to work as hard physically, there is less wear and tear on their bodies. This results in less injuries and sick time needing to be taken, happier employees and ultimately an increase in worker productivity.
  5. Utilize Talent. Initiating training programs to educate employees on best practices can also reduce waste. When employees perform work that unnecessarily squanders both materials and time, they need to be taught there is a better and often easier way to complete those jobs.

Classroom discussion questions:

  1. In addition to these 5 ideas in Industry Week, provide several others to reduce waste.
  2. How else can AI be used in a manufacturing process?

OM in the News: Manufacturing and Early AI Adoption

Manufacturers are betting artificial intelligence (AI) can help address pressing challenges, from supply chain volatility to the shortage of skilled workers. Three-quarters of  manufacturing executives say that adopting emerging technologies such as AI is their top priority in engineering and R&D, says Industry Week (Oct. 4, 2024)

AI is a broad term that encompasses basic data analytics (Module G in our text), machine learning, deep learning, and generative AI. Adopters are using AI to solve key problems in procurement, assembly, maintenance, quality control, and warehouse logistics. Some are deploying generative AI to synthesize huge volumes of unstructured data. Others are experimenting with AI service bots that partner with field technicians, for instance, to recognize more quickly when maintenance is required and to improve the quality of that work.

AI can also report supply chain bottlenecks in real time and predict potential disruptions in advance. In manufacturing it can include: minimizing assembly defects and improving quality control; boosting productivity; and streamlining warehouse management.

For example, one manufacturer adopted AI-based video processing to track manual assembly activities and automate quality checks of those activities,. This reduced failures in the assembly process by 70%, while also cutting down efforts for quality checks by 50%.

Another firm adopted an AI-powered industrial copilot that converts natural language into code and translates old programming languages into natural language, completing both tasks faster and better than human developers. Engineers using this AI solution were 5% more productive.

AI can also help ensure that warehouses operate at top efficiency, carrying items that meet demand and minimizing extra inventory. One company adopted an AI-based inventory management system that helped it minimize overstock while still fulfilling all orders. AI also provides more flexible job production planning so that companies can allocate specific assembly activities to the most relevant assembly expert at a given time to maximize productivity.

As a growing number of companies experiment with and deploy new AI solutions, they are raising the industry bar for productivity and performance. The article suggests that  companies that defer investing will need to run twice as fast to keep pace.

Classroom discussion questions:

  1. Summarize the AI advantages noted in the Industry Week article.
  2. Provide additional examples of potential AI use in manufacturing. In services.

Guest Post: Using AI to Decrease Food Waste and Combat Food Insecurity

Temple University Professor Misty Blessley raises an interesting issue in her Guest Post today.

The Supplemental Nutrition Assistance Program (SNAP), overseen by the U.S. Department of Agriculture (USDA), plays a crucial role in combating food insecurity across the U.S. SNAP offers monthly benefits through an Electronic Benefit Transfer card, enabling food- insecure individuals and families to purchase food at authorized retailers.

Food insecurity, defined as a lack of consistent access to adequate and safe nutrition, affects about 13% of the U.S. population. Delaware recently became the first state to pilot an AI-powered app aimed at linking surplus food with SNAP demand. With over 30% of food wasted during production and distribution, food insecurity is increasingly viewed as a supply chain challenge.

This new AI-powered app is instrumental in combatting food insecurity by addressing the potential for waste along the supply chain.

How it works: The app, called the Smart Shopper app, allows producers and retailers to offer SNAP-approved items at discounted prices in locations where surplus inventories and unmet SNAP demand overlap. SNAP recipients can download digital coupons to purchase food that would otherwise be wasted. Developed by the creators of Priceline, the app operates similarly by offering discounted goods, much like Priceline offers unused hotel rooms and airplane seats. One key advantage is its ability to predict food surpluses at their source, rather than merely reacting to food approaching its expiration date.

The benefit: The app extends the value of SNAP benefits, helping recipients make fewer compromises when deciding which foods to purchase. It also creates a win-win situation.
Delaware noted that “when we help our most vulnerable buy locally grown products, they receive the most nutritious, freshest food Delaware has to offer, and we support small farms, boosting and growing the local economy.” Additionally, the app addresses a $250 billion food waste issue at the retail level. The app is expected to become available nationwide.

Classroom discussion questions:
1. Refer to Introduction to Big Data and Business Analytics in Module G of your Heizer/Render/Munson text. In what ways does the Smart Shopper app move decision-makers from information to optimization?
2. Why is inventory record accuracy important to the proper functioning of the Smart Shopper app?
3. How are agricultural products the same as/different than hotel rooms and airplane seats?

OM in the News: Gary, The Hospital Robot

Gary works in a hospital. He does a lot of fetching and carrying. He cleans and sanitizes. He also chats to patients, acts as a translator and records and transcribes doctors’ consultations. He works every shift available, he never calls in sick, and he doesn’t stop for a coffee, a cigarette or a bathroom break. But he does need time to recharge his batteries – literally.

Gary is even being trained to clean toilets.

Gary is a robot, designed and built by Israel-based Unlimited Robotics.  Since the start of this year a dozen Garys have been working at two of Israel’s largest hospitals. And 10 Garys just began working at a hospital in Philadelphia. The US is a huge target market for the company.

Gary is one answer to a global recruitment crisis in healthcare facilities. There simply aren’t enough people willing to work in a hospital when they can get a job in Starbucks, Dunkin Donuts or McDonald’s for the same money. By 2030, writes Israel21c (July 25, 2024), the problem will be so acute that there will be a shortfall of 18 million health workers globally. 

Gary costs around $30,000, which is less than a year’s salary for a typical US hospital worker. Except that Gary works a 140-hour week with no vacations.

There are many opportunities for Gary, but Unlimited Robotics decided concentrate on the huge demand from hospitals both in Israel and the US.

Gary is autonomous, which means he takes “initiative” rather than relying on minute-by-minute instructions. He also has two arms, whereas most robots have just one because coordination of two simultaneously is exceptionally complicated. And he’s adaptable. Most robots are designed for a single task, but Gary can quickly pick up new skills thanks to an open-source platform that allows software developers with no prior experience of robotics to build applications.

Gary provides a range of services in healthcare facilities, for example meeting the constant demand for bed linens, water, medical devices and other items so that medical personnel can spend more time treating patients.  Gary also engages selected geriatric patients in conversation, to maintain or improve their cognitive capabilities. He recognizes them and (using AI) personalizes every conversation. Eight out of 10 patients say they are happy to chat to a robot. (Clicking on the article link allows you to watch a video of Gary in action).

Classroom discussion questions:

  1. What other tasks can Gary be eventually trained to do?
  2. What non-hospital opportunities exist for Gary?

OM in the News: Artificial Intelligence vs. Sustainability

Google just released its environmental report. It doesn’t make for comforting reading. Despite the tech giant’s best efforts to operate its business sustainably, GHG emissions rose 13% from a year earlier and are up almost 50% compared to a 2019 baseline.

The reason? Artificial Intelligence. Or rather the expansion of data centers required to service the needs of its insatiable appetite.  But as The Wall Street Journal (July 8, 2024) writes, Google isn’t alone in this. The sustainability reports of other tech firms tell similar stories. 

Of course, it is not just the power demands of data centers that are driving up the emissions numbers. It is the construction of the infrastructure that is also carbon heavy. So we won’t know if any of the efficiencies AI brings truly offset its environmental costs until those centers are all up and running.

Google and Microsoft have vowed to slash emissions by the end of the decade, but new disclosures show their numbers are moving in the wrong direction. The AI boom is substantially responsible for the lack of progress. Large language models like ChatGPT are powered by energy-intensive data centers, and AI is projected to increase electricity demands from data centers by 50% by 2027.

To address the issue, they’re getting creative. Amazon Web Services is pursuing a deal to buy energy directly from a nuclear power plant on the East Coast. Microsoft has eyed small-scale nuclear, too, and unlike many of its peers, it is an enthusiastic purchaser of carbon offsets. Google’s sustainability report was accompanied by an announcement that it had partnered with BlackRock to build a one-gigawatt pipeline of solar capacity in Taiwan. The company also touted its data center efficiency metrics, saying Google-owned data centers are 1.8 times more energy efficient than average.

Despite these efforts, now that the numbers are trickling in, it’s becoming clear that the growth of AI has presented real challenges to tech companies that have long sought to position themselves as climate leaders.

Classroom discussion questions:

  1. High tech firms have long promoted their sustainability goals. What can they do now that AI is demanding massive new sources of power?
  2. How is this an operations management issue?

Guest Post: Helping Your Students Land a Job

 

Charlie Render is CEO of Render Analytics, a Florida-based consulting firm. One of his AI software packages is described in this post. ApplyGenie just won a recent contest as the best  product to invest in by the Orlando Business Journal. 

It is nearing graduation day and the job market has been tight for new grads. Finding a new job can be a time consuming and demoralizing process. Applying for jobs is a full-time job itself, and finding the right job has never been more competitive or difficult. Here is a new AI tool that can help your students. ApplyGenie  (ApplyGenie.ai) automates the first round of their job hunt by applying to jobs online on their behalf while they can spend their time elsewhere. Students can send out hundreds of personalized job applications for relevant roles at the click of a button!

Applying for a job is a numbers game. Applying to 100 jobs is more likely to generate a job interview or job placement than applying for two or three.

The first 25 applications are free. After that ApplyGenie charges $19.99 for another 25 applications, $59.99 for 100 applications, and $99.99 for 200 applications.

OM in the News: AI is Taco Bell and Pizza Hut’s “Secret Sauce”

Since the pandemic, fast-food chains have increased investing in technologies like digital ordering and more drive-throughs, betting those trends will last, reports The Wall Street Journal (April 2, 2024). Now, pressured by higher labor costs—including California’s new $20 minimum wage law—and inflation-weary customers, more fast-food operators are banking on AI to drive sales and help lower costs.

Yum Brands has worked to consolidate customer data for its four brands.

The explosive growth of generative AI, which has already made its way into sectors like healthcare and retail, is further accelerating the pace at which fast-food chains embrace cutting-edge technologies. While these restaurants have traditionally lagged behind other sectors in technology adoption, that is quickly changing. The chains are finding they must keep pace with increasingly tech-savvy consumers, while keeping labor and other costs in check.

Yum Brands’ “AI-powered”  artificial intelligence shapes nearly every aspect of how its Taco Bell, Pizza Hut, KFC and Habit Burger Grill restaurants are run. The fast-food giant has been increasing its investment in technology and automation. About 45%, or about $30 billion, of Yum’s sales are digital, double the level in 2019.
Yum’s SuperApp, a mobile app for restaurant managers to track and manage operations—Yum calls it “a coach in your pocket”—is testing a generative AI boost. Team members can ask the app questions like “How should I set this oven temperature?” rather than turning to training materials or tapping through an app interface.
The goal is for SuperApp, now in use in more than 8,700 Pizza Hut and KFC locations, to connect technology systems so managers can order ingredients and schedule shifts without leaving the app. SuperApp can also be updated as features are developed, such as with an augmented reality tool for teaching employees how to make new products like Pizza Hut Melts.
Like its competitors, Yum is also testing generative AI’s use for customers, such as voice AI for drive-through orders. The company is also looking into image-recognition AI to count cars and waiting times in a drive-through, as well as digitally linked and managed kitchen appliances
.
Classroom discussion questions:
1. How else could AI be used in managing a restaurant?
2. What is generative AI?

OM in the News: AI in Manufacturing

Manufacturers are increasingly evaluating and adopting AI solutions to leverage their data, writes Industry Week (Feb. 13, 2024). Here are some key areas that stood out in how manufacturers are adopting the technology:

Quality control enhancement: AI can improve manufacturing quality control through vision systems trained on images and videos, accurately detecting complex product defects. Real-time monitoring identifies issues promptly to prevent future defects, and AI’s continuous learning enhances defect detection.  (See Ch. 6)

Supply chain visibility: Manufacturers deal with enormous amounts of data in their operations, and the integration of AI technology allows real-time observation, quicker trend identification and more accurate forecasting to meet demand effectively. AI algorithms analyze historical sales data, market trends and external factors, enabling more precise demand forecasts and aligning production and inventory levels. In logistics, AI optimizes routes by analyzing transportation costs, delivery times and traffic patterns, enhancing efficiency and cost-effectiveness. The strategic use of AI in the supply chain offers benefits like improved visibility, increased agility and better planning, enhancing overall resiliency and responsiveness. (See Ch. 11)

Energy efficiency and resource utilization: Companies are using AI to optimize energy consumption and resource utilization in manufacturing processes. These capabilities analyze real-time data from sensors, production equipment and other sources to identify patterns and trends in energy usage. This can inform predictive recommendations to optimize energy consumption, reduce waste and enhance overall resource efficiency. (See Supp. 5)

Predictive maintenance improvement: The use of AI in predictive maintenance enables a shift from reactive to proactive strategies, leveraging data-driven approaches. AI algorithms analyze real-time data to predict maintenance needs and failures. AI identifies patterns on the factory floor, detecting anomalies and potential malfunctions. This proactive approach minimizes unplanned downtime, extends equipment lifespan and allows manufacturers to optimize resource allocation through scheduled service activities during planned downtime, enhancing overall productivity and reducing costs. (See Ch. 17)

The use of AI in manufacturing operations in coming years is expected to accelerate. Investment in AI technologies is forecast to rise among 96% of companies by 2030.

Classroom discussion questions:

  1. How will AI become a common tool for operations managers?
  2. Using a search engine, describe a real company example for these applications.

 

OM Podcast #15: Automation, AI, and Operations at Frito-Lay

In the latest podcast, Barry interviews Tom Rao, Senior Vice President of US Field Operations for Frito-Lay, a division of PepsiCo.  Tom and Barry discuss various operations improvements at Frito-Lay, general plans for how Frito-Lay plans to utilize AI to support the business, and how Frito-Lay is addressing the challenge around labor shortages.

 

Transcript

A Word document of this podcast will download by clicking the word Transcript above.

Instructors, assignable auto-graded exercises using this podcast are available in MyLab OM.  See our  earlier blog post with a recording of author and user Chuck Munson to learn how to find these, or contact your Pearson rep to learn more!  https://www.pearson.com/en-us/help-and-support/contact-us/find-a-rep.html

OM Podcast #14: Feeding the World Through Complex Supply Chains

In our latest podcast, Barry speaks with F. Scott Fein, Vice President of the Northeast Region of Robinson Fresh, a company that aims to “feed the world through complex supply chains.”  They discuss cold food storage supply chains and operations, the effects of AI, sustainability, and product variety and customization.

 

 

Transcript

A Word document of this podcast will download by clicking the word Transcript above.

Instructors, assignable auto-graded exercises using this podcast are available in MyLab OM.  See our  earlier blog post with a recording of author and user Chuck Munson to learn how to find these, or contact your Pearson rep to learn more!  https://www.pearson.com/us/contact-us/find-your-rep.html

Guest Post: Hershey’s $1 Billion “Sweet Spot” Supply Chain Investment

Dr. Misty Blessley is Associate Professor of Supply Chain Management at Temple University.

The Hershey Company, a confectionery and salty snacks giant headquartered in Hershey, Pennsylvania, struggled to meet heightened customer demand for Halloween candy last year because of limited production capacity. Due to a new Hershey’s line and three new Reese’s lines, the problems of last season are now behind the manufacturer. As recently reported in Supply Chain Dive, the firm views its $1 billion investment “as a growth enabler rather than an expense to manage.” Hershey considers their “Sweet Spot” as being nimble enough to react to demand growth, while having the capacity needed to meet customers’ needs.

Hershey’s investment is expected to be a multi-year undertaking, which will allow the candy giant to balance existing capacity with future flexibility. Plans include an additional chocolate factory in Hershey, 13 new production lines and upgrades to 11 existing lines. Core brands will be in focus, with 60% of the investment allocated to the Reese’s brand. With flexibility and agility as an objective, Hershey’s is implementing modular advanced technology lines that use robotics and automation. These lines allow for smaller production runs and shorter changeover times.

Reese’s candies funnel through a Hershey production line

In addition to adding capacity, Hershey’s has also found hidden capacity by using advanced analytics and AI. For example, an evaluation of the network of six KitKat production lines resulted in finding $35 million of capacity that could be leveraged without a substantial investment. The company also considered underutilized production lines and what products might be suitable to outsource to a co-manufacturer, rather than being made in-house. As a result, Hershey recently outsourced its production of Zero candy bars, and used that to free up capacity to make PayDay candy bars.

When determining what products to use a co-manufacturer for, Hershey had two considerations. If it’s a core product with intellectual property Hershey wants to protect, production is kept in-house. If it’s a product at the end of its lifecycle or a new product the company doesn’t want to commit a large investment in yet, Hershey will consider shifting production to an outside manufacturer.

Classroom discussion questions:

1. Refer to Supplement 7 of the Heizer/Render/Munson text. Which of the tactics for matching capacity to demand is Hershey applying?
2. How has Hershey benefitted from taking a multi-faceted approach to manufacturing capacity, beyond simply adding capacity?

OM in the News: Dancing Pods at Amazon’s Warehouse

“At Amazon’s fulfillment center in Carteret, N.J., the workers don’t walk to and from shelves,” writes The Wall Street Journal (Sept. 5, 2023). The shelves come to workers. (Click on the 7 second video below).  About 45,000 pods—the name given to the four-sided shelving units—are shuffled around the 1.3-million-square-foot facility on self-driving units that hoist and carry them to workers in a kind of choreographed waltz. Those workers either fill the pods with arriving goods or empty them to build packages for shoppers.

Most of the facility’s 3,000 employees, including the top manager, aren’t allowed to enter that area, even to lean over to retrieve an item they have dropped. The specialists permitted to move amid the shuffling units must don a specialized vest that syncs up via radio and acts almost like a sort of electric force field, helping direct the pods around them. An AI system situated in the cloud helps oversee the pods’ movements.

Amazon calls the approach of moving the shelves a “goods-to-person” strategy. The design, which uses artificial intelligence and sensors, is meant to promote a mix of efficiency, ergonomics and safety, with the thinking that it is ultimately better to have shelving units, rather than employees, scurrying around its cavernous facilities. Globally, Amazon has about 750,000 autonomous robots to move around its shelving pods. Though most operate in specialized zones, its newest design is intended to mingle with workers and move around them as though navigating a cocktail party.

Amazon said its lost-time injury rate has fallen 69% from 2019 to 2022. Last year, lost-time injury rates were 21% higher at sites that didn’t use robotics technology. Proponents of the technology say it can help prevent injuries that can be ruinous for workers and costly for employers. Some workers say they find the technology creepy, but others say it can keep them out of harm’s way, preventing some of the costs—financial and otherwise—associated with a workplace injury.

Amazon has ample resources to put toward safety initiatives—the company has about 8,000 staff who work on safety matters.

Classroom discussion questions:

  1. Why is Amazon changing the warehouse order-filling process?
  2. What are the advantages and disadvantages of this new “moving shelves” approach?