On August 2, 2016, Samsung unveiled its latest smartphone, the Galaxy Note 7, almost a month ahead of the launch of the new iPhone later that fall. The introduction of the Note 7 was an important event for Samsung, as the company was getting into a close contest with Apple to become the leading smartphone company in the world. Two weeks later, the company started selling the Note 7 in ten markets, including South Korea and the United States. The device received rave reviews from critics and fans, and initial demand was so high that it broke preorder records in South Korea and created supply shortages in some markets. However, within a week there were dozens of reports of Note 7 phones catching fire and exploding.
Samsung urged hundreds of its employees to quickly diagnose the problem, but none of them was able to get the phone to explode. After a frantic effort, Samsung engineers concluded that the defect was most likely caused by a battery that had come from one of its suppliers, and according to Samsung officials, “the problematic battery” had been installed in “less than 0.1 percent of the entire volume sold.”1
As news of the exploding phones continued to surface, the company—on September 2, 2016—suspended sales of the device and recalled almost 2.5 million Note 7 phones from the market. Samsung promised that within two weeks customers would receive replacement phones that would have batteries from a different supplier. However, the problem persisted, even with replacement phones, and most airlines banned consumers from carrying Note 7 phones onto the planes. Recognizing the severity of the problem and the potential impact on its reputation, Samsung, on October 11, 2016, decided to kill the Note 7 altogether. This news led to an 8 percent drop in Samsung’s share price, wiping almost $17 billion from its market value.2
While Samsung’s case is a cautionary tale for all firms, Siemens, in Amberg, Germany, would probably never face this problem. Using state-of-the-art technology, Siemens is ushering in the era of industry 4.0 and smart manufacturing.
In 2011 the German government conceived Industry 4.0, or the fourth industrial revolution, and since then the concept and the ideas behind it have caught the attention of many companies around the world. The first industrial revolution, during the eighteenth century, was powered by steam, which led to the mechanization of equipment and revolutionized a variety of industries, from transportation to textiles. The invention of electric-power generation and transmission in the late nineteenth century and the use of electricity in the early twentieth century in assembly-line processes ushered in the second industrial revolution, which saw the mass production and increasing affordability of everything from automobiles to household appliances. In the mid-twentieth century, electronics and computer technology led the third industrial revolution, which had a major impact on manufacturing through computer-aided design (CAD), computer-aided manufacturing (CAM), and automation through robots. Today, digital technology is leading the fourth industrial revolution, which allows the convergence of digital and physical products.
According to Germany Trade & Invest, an economic-development agency within the German government, Industry 4.0 represents a paradigm shift from centralized to decentralized production, where a machine no longer simply processes a product but where the product communicates with the machine to tell it exactly what to do.3 Through machine-to-machine communication, problems can be diagnosed and autonomous decisions can be taken without human intervention. The German conglomerate Siemens has set up a factory that, as a model of smart manufacturing, highlights the potential of Industry 4.0.
In Amberg, a small town in Bavaria, Siemen’s has built a factory of the future that produces programmable logic controllers (PLCs), devices used for automating industrial equipment and processes. Almost 75 percent of the operations in this factory are digitized and automated. Each component has its own marker—a bar code or an embedded chip—that communicates with a machine. This interaction then determines the precise action that needs to be taken by that machine. Data flows in real time between components and machines, and any changes—due to a new component, a new supplier, a new machine, or a new assembly process—can quickly be programmed to optimize the production process. At the end of production and for every product, Siemens has complete information on each component and each stage along the assembly process.
To understand the importance of digitization, it is helpful to distinguish it from automation. Eckard Eberle, CEO of process automation in the Siemens Process Industries and Drives Division, describes the classic automation process:
In manufacturing and process industries, people are running their plants deterministically. By this I mean they have a complete understanding . . . [of ] process . . . so everything operates under the assumption that the complete system is described. This is something that is very static, but also stable. It has the advantage that it is very robust.4
Stable and robust automation, as used by automobile companies, eliminates defects and speeds up operations. But it comes at the cost of limited flexibility. This is one of the reasons that it typically takes several years for car manufacturers to introduce a new car model. A digital factory, by comparison, provides all the advantages of automation in terms of speed and efficiency but also allows for flexibility and tracking. For many products, such as PLCs for Siemens or smartphones for Samsung, frequent innovations in electronic components and product design make classic factory automation less practical. Siemens has 99.99885 percent defect-free production even though its factory produces twelve million units per year, or almost one unit per second. Digitization of operations allows a company to quickly change any component, machine, or process. And this flexibility, again, has not come at the cost of speed and productivity. Through digitization, Siemens has increased its output 8.5 times without adding space or people.
As manufacturing gets complex, with potentially hundreds of components from scores of suppliers going into a product that is assembled in dozens of factories around the world, keeping track of changes and potential defects becomes increasingly important. This is how Siemens describes its Amberg smart factory and the future of Industry 4.0:
Here, products control their own manufacturing processes. In other words, their product codes tell production machines what requirements they have and which production steps must be taken next. This system marks the first step toward the creation of Industry 4.0. In this vision of a fourth industrial revolution, the real and the virtual manufacturing worlds will merge. Factories will then be largely able to control and optimize themselves, because their products will communicate with one another and with production systems in order to optimize manufacturing processes. Products and machines will determine among themselves which items on which production lines should be completed first in order to meet delivery deadlines. Independently operating computer programs known as software agents will monitor each step and ensure that production regulations are complied with. The Industry 4.0 vision also foresees factories that will be able to manufacture one-of-a-kind product without being unprofitable, as they will produce items quickly, inexpensively, and in top quality.5
Siemens’s digital factory provides a glimpse of the future of manufacturing, which will usher in a new era of improved productivity in a wide variety of industries.
The early growth of the internet was fueled by communications and consumer commerce. With the rise of connected devices, which are estimated to reach fifty billion in number by 2020, data can now flow among machines. Falling costs to connect, store, and process machine data are driving the growth of the industrial internet. By adding sensors into machines ranging from jet engines to wind turbines, GE is able to collect data on the performance of its assets, which allows it to do predictive maintenance and reduce down time. This increased efficiency of equipment can translate into huge savings for its clients. GE estimates that if predictive maintenance could improve efficiency for its clients by even 1 percent from reduced downtime and increased asset utilization, it could save the oil and gas industry $90 billion over fifteen years. Savings in other sectors, while not as great, are still impressively large (see figure 5-1).
Source: Karim R. Lakhani, Marco Iansiti, and Kerry Herman, “GE and the Industrial Internet,” Case 614–032 (Boston: Harvard Business School, 2014).
To realize this potential, GE developed Predix, a cloud-based operating system for industrial applications. It did so out of the recognition that the industrial internet differs from the consumer internet in several important ways. First, mistakes are costly in the industrial world. If Amazon makes a mistake in recommending you a book, the error is not very costly for you or Amazon. However, an error in a software algorithm for the industrial world could lead to the failure of a gas turbine, resulting in millions of dollars’ worth of damage. Second, security for industrial equipment, such as a power plant, is far more critical. Third, getting data from machines located in remote places, such as an oil rig in the Gulf of Mexico, is not possible using the consumer internet.
Next, GE built applications on top of its Predix platform. One suite of applications, for asset-performance management (APM), was designed to increase asset reliability and availability while reducing maintenance cost. This gave GE the ability to answer three critical questions: Will an asset fail? When will it fail? And what could GE do to prevent it from failing?
APM had a significant impact on GE’s clients, such as Gerdau, a Brazilian steel producer that was looking to cut costs to remain competitive with its Chinese rivals. One area where Gerdau asked for GE’s help was to reduce its $300 million annual maintenance costs by 40 percent. By doing an APM trial on fifty assets in one steel plant and monitoring their performance, GE was able to drive down Gerdau’s maintenance costs significantly within a year. This successful trial led Gerdau to expand APM to its eleven plants and 600 assets. It also prompted other major steel manufacturers to reach out to GE for predictive maintenance.6
Remote monitoring and automated predictive maintenance—some of the common applications of the internet of things—are even more important for industries such as oil and gas, where a majority of assets are located in remote locations such as the arctic, offshore, or in deep waters. Many of these industries have mature assets with declining productivity, and failure is not only costly but has serious consequences for the safety of employees. McKinsey Global Institute estimates that operational efficiencies in factories through the internet of things has the potential to add $1.2 to $3.7 trillion in value annually to the global economy by 2025.7
In 2015, MX3D, a robotic 3-D-print-technology company, started building an intricate steel bridge in Amsterdam using its 3-D printing technology.8 In February 2017, Apis Cor, a startup, used a mobile 3-D printer to build, on-site, a thirty-eight-square-meter (roughly four-hundred-square-foot) house in Russia.9 In April 2017, MIT researchers were able to 3-D print a domelike structure fifty feet in diameter and twelve feet high, in fourteen hours.10 Local Motors has built the first 3-D printed electric car, called Strati, which took only two months from initial design to prototype.11 Using human cells instead of ink in the 3-D printer, Dr. Anthony Atala at Wake Forest Institute for Regenerative Medicine is “printing cells, bones, and even organs on an 800 pound steel machine called ‘ITOP’, or Integrated Tissue and Organ Printing System.”12
In the last few years, 3-D printing has transitioned from being a mere curiosity for techies to prototyping for machines and printing large volumes of hearing aids and dental implants. It is now finding its way into the mainstream operations of companies. GE’s aviation group started investigating 3-D printing many years ago for fuel nozzles that go into its jet engines. To reduce fuel consumption and emission from its jet engines, GE had developed a fuel nozzle with a complex interior design in which twenty different components had to be welded and brazed together. These parts not only had to come together with a high degree of precision but also had to be able to withstand very high temperatures and extreme weather conditions while the engine was in operation. Traditional manufacturing efforts to build this fuel nozzle had failed several times, which led GE to investigate 3-D technology.
GE partnered with Morris Technologies, a pioneer in 3-D printing. By adding thin layers of metal powder, Morris Technologies was able to successfully create fuel nozzles that not only passed the stringent quality tests of GE but also were less expensive to produce, weighed 25 percent less, and were five times more durable than traditional nozzles. Mohammad Ehteshami, former head of engineering at GE Aviation and current head of GE Additive, recalled his reaction to this experiment: “The technology was incredible. In the design of jet engines, complexity used to be expensive. But additive allows you to get sophisticated and reduce costs at the same time. This is an engineer’s dream. I never imagined that this would be possible.”13 This successful attempt led GE to focus on mass production of 3-D–printed nozzles that would go into 12,200 units of its best-selling jet engine, LEAP. To achieve this goal, GE has “spent more than $1 billion to buy controlling stakes in two leading manufacturers of industrial 3D printers.”14
In his 2016 annual letter to shareholders, Jeff Immelt, GE’s CEO at the time, said that “the long-term market potential for additive manufacturing [is] huge at about $75 billion. We plan to build a business with $1 billion in revenue in additive equipment and service by 2020, from $300 million today.”15
Additive manufacturing provides many benefits and has several implications that go beyond manufacturing:
According to McKinsey Global Institute, the worldwide economic impact of 3-D printing from all the activities mentioned above could range from $180 billion to as high as $490 billion by 2025.23 However, some critics see this as hype and wonder if 3-D printing will ever be as economical as traditional manufacturing for mass production. Perhaps this explains why a 2016 report from Ernst & Young found that more than 76 percent of the nine hundred companies in its global survey have no experience with 3-D printing.24 While high-volume, standardized production for some products, such as automobiles, is unlikely to be replaced by 3-D printing in the near future, increasing numbers of other products will come to be manufactured in such a fashion, as the cost of 3-D printing comes down and the quality of the technology dramatically improves.
Developments in additive manufacturing are already moving beyond 3-D printing. In its self-assembly lab, MIT is experimenting with 4-D printing, in which an object can transform itself in a preprogrammed way in response to a stimulus such as a change in temperature or contact with water.25 With this technology, water pipes would be able to expand and contract in different temperatures to maintain water flow, and car tires would be able to change their tread according to changes in road conditions. In 4-D printing, the program is embedded in the material itself, allowing the material to transform its shape. Given the pace of technological change, it would be short-sighted for any product company not to investigate this exciting new area.
Virtual reality (VR), which immerses you in a virtual world, and augmented reality (AR), which overlays virtual elements on a physical product, have improved dramatically in recent years. In the past, many applications of these technologies have been in the consumer domain: Gaming industries have used VR for immersive games. The tourism industry has given potential visitors a real taste of, say, Venice or Paris without the would-be travelers having to leave their homes. Automobile companies are using the technology for virtual test-driving. And real-estate companies are allowing potential buyers to virtually walk through several homes in a short period of time.
These technologies are now being increasingly used for design, assembly, and training in industrial settings.
Goldman Sachs estimates that the market for AR and VR will be between $80 billion and $182 billion by 2025.31 It also suggests that VR and AR have the potential to become the next big computing platform that will have a major impact on many industries, similar to what we experienced with PCs and smartphones. Not surprisingly, all major digital players—Google, Facebook, Microsoft, Amazon—are investing heavily in these technologies. Once again, it will be wise for companies to understand the potential of these technologies and to take inspiration from the early users to create their own unique advantage.
Technology is transforming not just design and manufacturing. It is revolutionizing the entire supply chain, including warehousing, inventory management, logistics, and delivery.
Consumer-product companies are using sensors on shelves in retail stores to monitor real-time shifts in demand. Using computer vision (i.e., acquiring and processing images), sensors, and deep learning, Amazon can detect when a customer picks up a product from the shelf in its Amazon Go store. By using data analytics and monitoring real-time shifts in demand, Kimberly-Clark Corp., a consumer-goods company, has built a demand-driven supply chain that helps reduce the company’s forecasting error by as much as 35 percent for a one-week planning horizon and its finished goods inventory by 19 percent over eighteen months.32
Procter & Gamble, designated as one of the supply chain “masters” by Gartner in its 2017 report, links daily demand flows from point of sales to distribution centers and plants and even to its suppliers.33 Amazon, whose clothing and apparel sales were expected to grow to $28 billion by the end of 2017, has obtained a patent for on-demand apparel manufacturing that would dramatically cut down its inventory cost and enable it to avoid deep discounting of unsold products.34 Zara, the fast-fashion leader, is putting RFID chips into its merchandise. Each time a garment is sold, the chip sends a message to the stockroom to replace that item in the store. Not only does this free up employees from having to take frequent inventory to avoid stockouts. It also gives Zara an accurate picture of real-time demand and which fashion items are selling. Nestlé is exploring using sensors in vending machines with auto-replenishment capabilities. Demand-driven supply chains have an even greater benefit for high-tech companies that face shorter product life cycles and decreasing component costs over time.
Real-time information and data analytics are key to implementing demand-driven supply chains. Amazon uses these resources to predict the demand for various products near each of its fulfillment centers, to ensure that the correct (and correct number of ) items are stocked at each location. This capability enabled Amazon to launch Prime Now and to promise delivery within an hour. In a move that evokes images from Star Wars, Amazon has filed a patent for a “flying warehouse,” equipped with drones, that will move close to key locations based on their demand patterns.
According to Gartner, demand-driven supply chains are able to reduce inventory by 15 percent, increase order fill rates by 20 percent or more, increase revenues by 2 percent on average, and improve gross margins by 3 percent to 5 percent.35 If your company does not have these systems in place, you are missing out on a significant opportunity to improve your operations and supply chain.
Jeff Bezos’s mantra of “start with the customer and work backwards” drives everything at Amazon, including its warehousing and fulfillment strategy. In its customer surveys, Amazon found that speed remains the most important aspect of delivery (see figure 5-2).
Source: Amazon customer survey, 2017, courtesy of Rohit Sodha, Amazon’s country lead for transportation in Middle Europe.
Delivering individual packages to customers within a day or two (or an hour or two in the case of Amazon Prime Now), with close to 100 percent accuracy, when you have to pick, pack, and ship that package from a warehouse that stocks millions of items, is a nontrivial task. And it isn’t cheap. In the second quarter of 2017, Amazon’s fulfillment cost of over $5 billion was almost 14 percent of its total operating expenses. Not surprisingly, Amazon relies heavily on technology to increase speed and reduce fulfillment cost. Its acquisition of Kiva Systems for $775 million in 2012 transformed the way Amazon manages its warehouses using robots. One of the largest of Amazon’s warehouses—in Etna, Ohio—has more than a million square feet of space and stocks 50 percent more inventory than standard warehouses, since robots eliminate the need to have wide aisles.36 Locus Robotics, a startup based in Andover, Massachusetts, has developed the next generation of robots for warehouses. By using its robot, called LocusBot, Quiet Logistics—a third-party logistics company that does fulfillment for Gilt, Bonobos, and Zara—was able to increase its productivity by eight times.37
In addition to using robots, tagging individual items with RFID chips enables better and more accurate management of inventory. American Woodmark, a manufacturer of cabinets and vanities, is using nine million RFID tags to track material in its factories and warehouses, which has “reduced the labor for cycle counting—a regular inventory process—by 66% and improved accuracy from roughly 80% to 100%.”38 RFID tags on its merchandise has enabled Macy’s to inventory items in its stores every month instead of once or twice annually, and this has increased the accuracy of its inventory to 95 percent.39 Airlines are using RFID tags for tracking luggage so that a customer can be told about lost baggage ahead of time instead of waiting at the baggage area in frustration.
With the rise of e-commerce, delivery has become more critical than ever before. The last mile of delivery is perhaps the most complicated and expensive part of any delivery operation. With more than 100,000 trucks, cars, and vans, UPS delivers 19.1 million packages every day around the globe.40 Running this large fleet of vehicles is complex and expensive. Reduction of every single mile driven by its fleet can improve the company’s profitability by $50 million. Which route a driver takes can significantly affect his efficiency and fuel consumption of his truck. To design an optimal route to maximize efficiency and minimize fuel consumption, known as the “traveling salesman” problem in operations research, is a complex problem. The 120 stops that a driver makes on a typical day can be routed in trillions of ways. To solve this problem, UPS installed chips in its trucks to monitor their real-time movement. Knowing the location of a driver and the real-time traffic information, route-optimization software called ORION (on-road integrated optimization and navigation) directs the driver to take the optimal route. In the four years since its roll out, ORION has eliminated 1.6 million hours of truck idling time, and has produced an annual savings of 85 million miles in driving and 8.5 million gallons in fuel consumption.41 The company expects to save from $300 million to $400 million a year after the program is fully implemented (which it was scheduled to be by the end of 2017).42 With autonomous driving on the horizon, ORION can potentially maneuver a truck automatically, without any human intervention. DHL is also testing this idea with its SmartTrucks, which use RFID chips and route-planning software to ensure—respectively—that the right products are loaded onto the right trucks and that those trucks avoid city traffic jams during delivery.
Using technology to improve operational efficiency is not limited to product companies. Real-time data flow and automation are radically transforming service industries as well. For several years banks have been using online and mobile banking to reduce their transaction costs and the overall number of their bank branches as well as to enhance customer experience. In the health-care industry, the use of electronic medical records is enabling hospitals and doctors to have a complete view of a patient across hospitals and physicians.
Goldman Sachs is in the process of automating its IPO process. The company broke down a typical deal into 127 steps and then went on to identify that about half of these steps could be handled by algorithms. According to Bloomberg, “a computer interface called Deal Link has replaced informal checklists that were once tended and passed down between generations of rainmakers. It now arranges and tracks legal and compliance reviews, fills in forms and generates reports.”43 Goldman is now expanding this idea to other areas, such as mergers and acquisitions and bond sales. This change in Goldman’s strategy is reflected in a shift in the composition of its workforce. Approximately nine thousand of its employees, or one-fourth of Goldman’s current staff, are engineers.44
Auditing companies like Deloitte are using artificial intelligence and machine learning to identify high-risk accounting areas and to spot patterns in financial transactions. Like Goldman, Deloitte and other auditing companies can automate a large portion of their tasks. Such automation can reduce costs and increase reach to small businesses that currently can’t afford the services of Deloitte or PwC. Instead of waiting for quarterly statements, clients can receive automated, real-time information, which can be very helpful for managing their businesses. Effectively, auditing could shift from being a tool for reporting what happened in the past to being a valuable asset for helping clients figure out how to run their businesses in the future.
Technology is also making a significant impact in the legal industry. Companies like Rocket Lawyer in the United States and LawCanvas in Singapore and Malaysia are offering consumers and small businesses legal templates at affordable rates.45 Online marketplaces for legal services, such as Asia Law Network, are emerging to match demand and supply. A new service called LawGeex allows users to upload documents related to legal cases and to compare those against a database of documents from similar cases, eliminating hundreds of hours spent by junior associates in a law firm.46 IBM Watson has developed an application, ROSS, that allows lawyers to ask questions in plain English. LexisNexis developed Lexis Advance MedMal Navigator that allows malpractice attorneys to determine within twenty minutes whether a case is worth pursuing. Lex Machina has created a database for intellectual-property litigation that uses historical information to calculate the odds of winning a case.47
In conclusion, technology is making inroads in the operations of both product and service companies. Factories, warehouses, supply chains, and internal processes are poised for a significant transformation in the near future. Companies that position themselves to leverage these emerging technologies are likely to have a significant competitive advantage.
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