The 21st century is ushering in digital and distributed tools that will further transform the way value is created and the job opportunities that result. In particular, emerging digital technologies, such as advanced sensors, and distributed capabilities, such as digital manufacturing and crowdfunding, are changing the process of value creation, the types of products and services that can be made, and the types of people who can commercialize them. It is not possible, of course, to predict exactly how these tools and technologies will evolve in coming decades, or what new tools may emerge, but it is clear that digital and distributed tools, broadly speaking, will become even more important to enable value creation. We offer some extrapolations and speculations based on some of the most dramatic changes so far.
Advances in software and data collection have opened up a wealth of possibilities for companies to better understand customers’ needs, optimize design and production processes, and discover new market opportunities. The rise of distributed approaches to everything from raising funds to hiring workers is changing the ways businesses operate. These capabilities are allowing companies to integrate systems of hardware and software and leverage data to provide new and improved solutions all along the value chain. They are making it cheaper and easier for entrepreneurs to develop new products and services and bring them to market.
Advanced Sensors and Cloud Computing
Developments in advanced sensors and cloud computing are allowing companies to collect vast amounts of information to monitor the performance of their products, provide new services to customers, and monitor their supply chains.
Advanced sensors promise to revolutionize a large number of fields. A traditional sensor—such as a thermometer, an accelerometer, or a detector
that senses the presence of a particular gas or chemical compound—produces an electrical signal that can be read by an observer or instrument. Today’s advanced sensors can be equipped with onboard computing capabilities that enable them to process the signal, carry out diagnostics, and even take intervening actions (e.g., triggering a warning or adjusting the system controls). They often have the capacity to communicate wirelessly, and tend to be both small and inexpensive to manufacture so that many can be used in concert (Spencer et al. 2004).
These advanced sensors are being used to monitor the structural health of buildings, bridges, and aircraft for signs of fatigue or impending failure. The ultimate goal is to create “smart structures” that not only monitor their status and report needed repairs but also, in some situations, make their own adjustments in real time in response to problems (Spencer et al. 2004).
Alongside the emergence of advanced sensors, cloud computing—the use of remote computing resources (typically accessed over the Internet) for computing, digital storage, and software programs—is also enabling “smarter” products and systems. With cloud computing an individual or business is not restricted to onsite computing resources: it is possible to store data and run software on remote computers. Thanks to the economies of scale enabled by sharing computing resources with millions of users and devices through the Internet, cloud computing has begun to provide better performance and more flexibility at a lower cost than can be achieved with a captive computer system.
The existence of large numbers of advanced sensors with computing and wireless communication capabilities raises the possibility of developing networks of thousands or millions of sensors that monitor large systems—such as a factory floor, a city transportation system, or a supply chain—to provide a real-time global picture of what is happening and respond automatically to a situation. At the same time, networking of the computing capabilities of various sensors could provide the systems with tremendous amounts of computing power. According to a report by the National Research Council, “These networked systems of embedded computers…have the potential to change radically the way people interact with their environment by linking together a range of devices and sensors that will allow information to be collected, shared, and processed in unprecedented ways” (NRC 2001, p. 1).
Digital and Additive Manufacturing
Developments such as digital simulation and additive manufacturing are enabling closer integration of design and production. Improved modeling and simulation are used to digitally represent and analyze prototypes, referred to as digital manufacturing, which saves time and money on the testing of physical models and specimens. Boeing, for example, has cut in half the amount of wind tunnel testing that it does by using simulations based on computational fluid dynamics.
Additive manufacturing, or 3-D printing (the process of producing parts by depositing and joining layers of material based on a digital model), is reducing prototyping costs by enabling production in smaller runs for lower costs. As a result, it has the potential to dramatically reduce production times and costs for full-scale production (Wohlers Associates 2011). It is also becoming important for the rapid and affordable manufacture of custom tools required for conventional high-rate manufacturing processes, such as casting cores and drill jigs (Cotteleer et al. 2014), the production of which requires considerable time and cost. Producing them with additive manufacturing can both significantly reduce costs and allow products to get to market much faster.
Distributed and Disintermediated Capabilities
New Internet-based capabilities enable new ways to solve problems and run businesses. For example, electronic communication methods distribute functions—such as raising capital, finding workers, creating products, solving problems—over a large number of entities, increasing the participation of people and businesses throughout the value chain. And they allow individuals to carry out these activities without the need for an intermediary institution. These approaches are already changing how companies form and operate, and the changes will accelerate in the coming years.
One important use of the emerging distributed and disintermediated capabilities is to raise capital for businesses and projects. Raising capital has always been one of the most difficult hurdles for startup companies or for existing companies with a new product or approach because they have no track record to convince backers of their likely success. Online crowdfunding sites now make it possible for individuals and businesses to seek funding for projects from anyone who would like to provide support. Perhaps the best known of these sites is Kickstarter, a platform for individuals seeking donations for creative projects; in March 2014 it announced that it had surpassed $1 billion in funding, provided by 5.7 million people.1 A number of other crowdfunding sites—Tilt, Crowdfunder, Somolend, appbackr, AngelList, and Quirky—have been created to raise funds for businesses.
There are two basic types of crowdfunding sites. One type (e.g., Kickstarter) relies on donations, although many recipients promise something in return for the donation—a copy of the resulting record or digital album in the case
1 “OMG. On March 3, 2014, Kickstarter passed $1 billion in pledges.” Kickstarter website, at www.kickstarter.com/1billion?ref=promo&ref=PromoNewsletterMar0314 (accessed April 21, 2014).
of funding for a music project, for example. These sites have funded new businesses developing consumer and technology products, designers offering custom fashion items, retail stores seeking to expand or open new locations, and many more projects. The appbackr site also relies on donations for, as its name implies, the development of mobile apps. The second model is “investment crowdfunding,” in which funds are provided either as loans or to acquire an equity position in the company. Somolend, for instance, provides loans to businesses that may have difficulty acquiring funding in more traditional ways. AngelList uses crowdfunding to provide angel investing to tech startups. And Quirky brings together people interested in invention to provide the funding and other support necessary to bring inventions to market (Barnett 2013).
In 2012 crowdfunding raised $2.7 billion for more than 1 million projects worldwide (the vast majority of the funding was for projects in the United States), and the total for 2013 was projected to be $5.1 billion—an increase of 81 percent (Massolution 2013). Thanks to this broad new array of potential funding sources, inventors and startup companies have many options for securing funding. It is still too early to know how widespread this phenomenon will become, but it illustrates the sorts of changes that the Internet is ushering in.
Uses of Social Media
In addition to funding, crowdsourcing has been used to provide businesses with various products and capabilities. Many businesses are using “social media” (a broad and somewhat amorphous term that refers to the group of technologies that enable people to interact remotely, generally in virtual communities or networks) to connect with their users and generate ideas for new innovations. The biotech company Genentech, for example, is using social media to collect information about the experiences of patients receiving cancer treatments. The information helps patients learn more about clinical trials while allowing the company to better integrate patient insights into its decision making for developing new medicines. It is likely that other uses of social media will emerge to assist companies in developing new products and services that people value.
Another example of an approach to crowdsourcing is TopCoder, a cloud-based community of computer programmers that companies can call on to produce software and algorithms for use in computer programs. Companies bring a programming problem to TopCoder, which puts it in the form of an open competition. Winning designs are licensed to the companies by TopCoder, which in turn pays royalties to the individuals who developed the designs. TopCoder also offers regular competitions in which programmers are given specific tasks to solve in a fixed period of time. These competitions allow programmers to sharpen their skills and allow TopCoder to identify talented programmers from around the world, and often the resulting programming solutions are valuable for use in various types of software. In April 2014 TopCoder reported
on its website (www.topcoder.com) that more than 600,000 people worldwide had registered at the site (although only a fraction had actually submitted programs or algorithms). TopCoder can be thought of as a global programming marketplace where companies find computer programmers to help them develop software and algorithms and computer programmers find jobs and career development.
oDesk, a third example of a novel use of distributed capabilities, connects businesses with freelance workers from around the world. It is the best known of a growing group of “online staffing platforms” where “contingent workers, contractors, freelancers can offer their skills and services for limited projects or even on-going assignments and where organizations and individuals can post their requirements or put tasks/projects out to bid” (Karpie 2012). oDesk provides online workspaces and communication channels for contractors and workers and handles payments for work done. Its website lists freelancers available in areas such as Web development, software development, writing and translation, administrative support, design and multimedia, customer service, and sales and marketing.
Cloud Computing Services
The emergence of cloud computing is important not only because it enables large amounts of data collection and analytics, but also because it is dramatically reducing the time and costs needed to scale up an organization’s computing resources. A number of companies, such as Amazon, Google, IBM, and several startups, have begun offering cloud computing services that allow individuals and organizations to rent “elastic” computing capacity—meaning that they can scale the capacity up or down in minutes—allowing them to acquire exactly the right amount of computing resources that are needed at any one time. This ability eliminates the need to purchase computing capacity for the maximum requirements needed at any time and radically reduces the time and costs required to scale up. For example, large pharmaceutical companies that want to acquire the computing infrastructure to support the development of a new drug can now gain almost immediate access to a 30,000-core cluster for $10,000, whereas previously it would have cost $5–10 million and taken about six months to build (McKendrick 2011).
Convergence of These Distributed Capabilities
The common thread among the emerging distributed capabilities is a broadening of opportunities along the value chain, both for businesses and entrepreneurs that can take advantage of them and for skilled individuals who can contribute to them. Together, these tools are significantly lowering the barriers to entry for entrepreneurship.
Launching a startup traditionally requires considerable capital and time to search for talent, acquire technology, and establish marketing and promotion. The convergence of crowdsourcing, cloud computing, and social media now allows potential entrepreneurs to easily access these capabilities at very low costs. And with the advent of digital manufacturing tools that improve product design, visualization, and analysis, as well as low-cost prototyping equipment such as 3-D printers, hardware startups can also build and test their product concepts more quickly and cheaply (Bradshaw 2013). As a result, startups such as Babybe, which develops products to improve the rehabilitation of premature babies, are able to reduce total development costs to less than $150,000 (Economist 2014).
A NEW SWEET SPOT FOR VALUE CREATION
As illustrated in the examples above, technological advances are giving rise to new opportunities for innovation and value creation. The committee refers to these opportunities as sweet spots and believes that many of the most promising such opportunities in the coming decade will arise from the integration of hardware, software, data, and people.
Recognizing that sweet spot opportunities are always a product of time and place—a sweet spot now would not likely have been one 10 years ago, nor is it likely to be one 10 years from now, and a sweet spot for the United States is not likely to be one for Brazil or China—the committee asked, Where can the United States focus its efforts over the next decade or so that will offer the greatest rewards in terms of creating value? The answer depends both on the directions that technology is taking now and on the particular comparative strengths (and weaknesses) of the United States now and in the near future.
Integrating Hardware and Software
One of the most powerful ways to create value in the emerging technological milieu is to integrate hardware and software to create products and services that are much greater than the sum of their parts. A good example of this is Apple’s development of the iPod.
The iPod: A Case Study
Introduced in October 2001, the iPod became one of the most successful consumer products in recent history. To create it, Apple combined innovations in hardware and software, integrating Toshiba’s 5-gigabyte hard drive, the FireWire serial bus, and software developed specifically for the iPod. The first iPod was simply a personal music player and, as such, just one more in a line of
devices that allowed individuals to listen to their music wherever they went, like the Sony Walkman and the Rio PMP300 MP3 player. But the iPod did its job in a way that was far beyond what other portable music players were capable of, and in a few years it completely dominated its market.
The iPod’s first and most noticeable advantage was the amount of music it could hold. Where the Sony Walkman played a single CD (or, in earlier versions, cassette tape) and the Rio held about 30 minutes of music, the iPod’s five gigabytes of storage were enough for about 1,000 songs. And FireWire made it possible to transfer music onto the iPod much faster than could be done with the Rio, which used the slower USB 1.1. But the real advantages were much broader and more lasting.
Other portable music players eventually caught up with the iPod on storage capacity and transfer speed, but the iPod had other characteristics that were not so easily matched (LePage 2006). The most important were Apple’s design of the iPod for ease of use, integration with its computers, and the software for the two. Suddenly it was simple to load music onto the player and organize it. Music transferred from a CD onto one’s computer would automatically load onto the iPod as well. Indeed, the music library on the iPod was automatically synced with the music library on the computer just by connecting the two devices. No one had seen anything like this before—it seemed almost magical. In addition, the design of the iPod was revolutionary. Apple had thought carefully about what was most important for listening to music and created a simple, intuitive interface that made it easy for users to hear exactly the music they wanted. The only controls on the first iPod were a click wheel and five buttons for navigating a simple menu that provided access to the music library. To people used to having many options on their music players, it might seem too simple, but the designers had created value by finding a way to connect users with their music in a way that was almost primal.
Yet another key to the iPod’s success was the development of the iTunes Music Store. By integrating the music player with a music listening and buying service, Apple amplified the iPod’s usefulness considerably. Now users could browse through thousands of songs, find the ones they liked, and easily load them onto the iPod. It was a totally new way of browsing and buying songs, and it changed people’s music buying habits.
Over time the iPod evolved, adding features and modifying the ways users controlled it. The hard drive was replaced with flash memory, the maximum amount of memory grew to 160 gigabytes, the ability to store and play videos was added, as were a video camera, a spoken menu, a touch screen, more powerful processors that increased speed and even allowed users to play video games, and so on. And every component was integrated seamlessly, not only in the iPod but across all the systems that interface with it.
By September 2010 some 275 million iPods had been sold.2 Simply put, Apple created tremendous value by integrating hardware, software, and services to allow people to listen to music and watch videos in a way that was far superior to anything that had come before.
Such integration is becoming increasingly common. A more recent example is the Pebble, a smart watch released in 2013. Funded by Kickstarter, the Pebble developers originally sought $100,000 but eventually received more than $10 million, making it the most successful Kickstarter project ever (Kosner 2012; Newman 2012).
The success of the Pebble watch was, again, due to the way it integrated hardware and software in a simple, appealing package that performed a number of tasks that people found useful. The watch has an “e-paper” display, a vibrating motor, a magnetometer, and a three-axis accelerometer, and it connects with iPhone and Android smart phones wirelessly via Bluetooth. Apps can be loaded onto the watch that take advantage of the different pieces of hardware to offer various capabilities, such as displaying emails, providing notifications of incoming calls on the smart phone, keeping track of pace and mileage while running or biking, and even providing a golf range finder that tells a golfer how far it is to a hole on any of 25,000 golf courses worldwide.
As Jon Rubinstein, former CEO of Palm, commented, the value is not so much in the hardware or even the software in such a device, but rather in the integration of the two to create services for people and the ecosystem around the device.3 He pointed to self-driving cars as another example of value that can be created through such integration. These vehicles will require the development of new hardware and, especially, new software, but their success will ultimately depend on the creation of systems in which cars communicate with each other in a way that smoothes traffic flow and avoids accidents while getting individual travelers to their destinations as quickly and efficiently as possible.
3 Remarks of Jon Rubinstein at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
Putting Data to Work
One way to enhance value with devices that integrate hardware and software is to add large amounts of data to the mix. This is the approach taken, for example, by Fitbit, a company that makes devices that keep track of users’ activity throughout the day and communicate that information using smart phones to a website where the activity data are analyzed. The devices integrate hardware (a 3-D accelerometer to measure movement, an altimeter to detect when a user is going up or down stairs, a clock, a display, and Bluetooth to connect wirelessly with a smart phone) with software (programs to calculate distance traveled and calories burned, various apps), but their real value arises from the data they collect. A user’s activity data are uploaded to Fitbit’s website, where they are analyzed to help the user track progress toward fitness goals, quality of nightly sleep, and even, with additional data, diet and nutritional plans. At least these are the initial uses of the data; as more and more users deposit data on activity patterns and related factors, it will be possible to use the information in new and unplanned ways, which will in turn increase the value of the data.
A less readily apparent example emerged from Google’s purchase in January 2014 of Nest Labs, a maker of smart thermostats and smoke detectors, for $3.2 billion. The purchase surprised many observers and had people asking why Google was interested in a company that made thermostats and why it would pay so much for a company whose annual revenues were probably only about $200–300 million (Rogowsky 2014). As Rubinstein pointed out, the answer seems to lie in the fact that these smart thermostats, when hooked up in millions of homes, produce a tremendous amount of data.4 Indeed, it is probably more accurate to think of Nest not as a manufacturer of thermostats and smoke detectors but as a data collection business. Its thermostats collect a large variety of data—not just a home’s temperature but information such as when people enter and leave a room, when the lights in a room are turned on or off, and the pattern of energy use throughout the day (Roose 2014).
Nest Labs cofounder and chief executive officer Tony Fadell previously worked for Rubinstein at Apple, where he was a major figure in the development of both the iPod and the iPhone. In an interview with the New York Times he described Nest’s philosophy this way:
We are a company that communicates to you, not just to your building contractors, about what you put in your home and why it’s important. It’s not just about turning up or down the heat, it’s about the other experiences that come with turning up or down the heat—what are we doing about energy, what are we doing about your health and safety. (Hardy 2013)
In particular, Fadell said, Nest’s smart thermostats and smart smoke detectors are very different from the traditional forms of these devices. They are no longer just for setting the temperature or detecting smoke; the way they collect, analyze, and communicate data opens up a world of new possibilities.
We came from the world of connected smart phones and apps. We don’t just see a thermostat with a better user interface; we see a smartphone that has thermostat functions. That is a very different thing. We don’t see a smoke alarm; we see a smartphone with a fire sensor. When you redefine the world that way, it opens it up to many more possibilities. (Hardy 2013)
The fact that Fadell and Nest see the world in terms of data and information, rather than in terms of devices, is likely at least part of the reason why Google—itself an information rather than a device company—valued Nest so highly.
Fadell went on to describe a future in which most household devices are smart and able to communicate with one another:
Every time I turn on the TV, that’s information that someone is home. When the refrigerator door opens, that’s another sensor, more information. Before, it was about one little brain and one little sensor, very tightly programmed. Now we have disparate things with an interconnection network, a brain that can evolve and sensor networks that can evolve, all interacting with these learning patterns. (Hardy 2013)
In short, these interconnected systems of hardware, software, and data offer a whole new area in which innovation can grow and evolve, presenting countless opportunities for creating value.
In addition to consumer and household goods, other sources are being explored for the use of integrated systems of devices and information. A great deal of data are already being collected and used for automobiles, as James Bonini of Toyota observed at a conference held by the committee. “It is already happening where personal devices are connected to automobiles,” he said. “The automobiles will collect a lot of information about how they are used. That will go back to manufacturers. It will go back to dealers.” Much of that information will end up in the cloud, where it will be processed and the results will be used for new types of innovation.5
5 Remarks of James Bonini at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
One car that is already collecting a tremendous amount of data about its use is the Nissan Leaf, which has been described as a “veritable smartphone on wheels” (Svarcas 2012, p. 169). Many of the data collected by the Leaf relate to use of the car’s battery and electric functions, such as the battery’s charging history, use management, and deterioration, and the functioning of the car’s electrical system. But the car can also collect many other data; it keeps track of the use of the headlights and air conditioning, for instance, and the GPS system tracks the vehicle’s position, speed, and distance traveled. The Leaf’s electronic data recorders (EDRs), the automotive version of the black boxes used in airplanes to provide information in case of a crash, are programmed to begin operation whenever the car’s airbags deploy and to record the vehicle’s speed, braking or acceleration, and the status of the airbags. The Leaf also has electronic modules that keep track of idling, acceleration, and braking and can be used to provide information about an owner’s driving habits (Svarcas 2012). Nissan’s warranty for the Leaf requires that customers visit a certified dealer annually to download information about the use of their vehicle and install software updates that improve performance based on aggregated customer data.6 Experts in the industry expect this sort of data collection and use to become more common.7
Another impetus for collecting data from cars is the push to develop self-driving cars. As automation plays an increasing role in the driving of cars—from systems that automatically apply the brakes when a car gets too close to another to full-fledged self-driving systems that require little or no input from the driver other than the destination—more and more data will need to be collected from the vehicles. In the beginning the data will likely be used for such purposes as analyzing drivers’ habits in order to develop ways to make cars and driving safer and more efficient, but as more cars become self-driving, roads and highways could become systems of cars interacting through the cloud. This is clearly an area in which there is tremendous value to be created.8
Healthcare Value Chains
The amount and types of health-related data are growing rapidly. Clinical trials for drugs and devices generate great volumes of data on responses to treatment, side effects, patient adherence to treatment, dropout rates, and the progress of diseases and other conditions in patients who are given placebos as well as those undergoing treatment. Basic research provides information on a broad
6 According to the 2013 Nissan Leaf Warranty Information Booklet.
8 Remarks of Jon Rubinstein at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
range of scientific and medical issues, from the biochemical pathways affected by different drugs to details on the mechanisms of various diseases. There is a tremendous amount of—mostly untapped—data in medical records in the offices of individual doctors and medical practices, and the growing use of electronic medical records promises to make these data widely accessible once methods have been devised to address privacy concerns.
Other types of health-related data can be collected from less organized sources such as social media and Internet searches on health-related topics. And the growing amount of genetic health-related data is opening up an entirely new front in the understanding, treatment, and prevention of disease. Genetic information is already used to determine which patients are most likely to benefit from treatment with a particular drug—an area known as genomic medicine—and as clinical researchers have access to more genomic data to combine with clinical and other health data, more applications will become possible.
In short, the healthcare industry is an area where it should be possible to create tremendous value by integrating hardware, software, and data to create new applications that promote health and the treatment of disease. For example, medicine is likely to become increasingly personalized as doctors and medical researchers become better able to analyze the effectiveness of treatments in terms of the individual characteristics of patients.
Paul McKenzie of Johnson & Johnson offered another example.9 The pharmaceutical industry, he said, is trying to move away from the simple model where a doctor provides a medical treatment along with instructions to the patient and leaves it up the patient to follow them: “Here is your pill; come back in 30 days and get another pill.” The focus is changing to a systems integration view of the patient, care providers, treatments, and their interactions. For instance, there is an effort to develop apps that help people understand when they should take their medicine in an effort in enhance their adherence to a treatment.
It is a matter of understanding where the source of value is. If it is seen as the discovery and manufacture of better drugs, then the effort will be placed there. But if one understands that patient adherence to medication schedules is a major problem—in neuroscience, adherence from 60 percent of patients is considered good, meaning 40 percent are not getting the prescribed treatment—then it becomes clear that value can also be gained by increasing the percentage of patients who adhere to the treatment schedule. What sort of system—of integrated medicine, software, and information services—would be necessary to get adherence rates of near 100 percent? How might apps and
9 Remarks of Paul McKenzie at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
social interactions be used to help people make the right choices for themselves? Answers to questions like these can create a great deal of value.10
Efforts to create value in the healthcare system in this way will require a very different mindset from the traditional one. Medicine has always been a very reductive field, with the focus on finding the cause of a disease or condition and treating that cause. And the way medical care costs are itemized and reimbursed in this country—with a specific code for each diagnosis and each individual action—only reinforces that approach. But a great deal of value can be created in the United States by integrating across medical records, clinical trial data, medical devices, pharmaceutical goods, apps, and social media to zero in on the best treatments for individual patients more quickly and more accurately and to help those patients (and perhaps their healthcare providers as well) adhere to those treatments.
TAKING ADVANTAGE OF OPPORTUNITIES
Opportunities accrue to the individuals, companies, and countries that have the capabilities to take advantage of them. If the United States is to continue to excel at creating value, it will have to recognize and promote the necessary skills and capabilities most applicable to the emerging sweet spots.
Individuals with certain skills will be most able to benefit from the integration of software, hardware, and data. Because software will be a core element of the sorts of integrated products described above, individuals who know how to design software and write code will particularly find their skills in heavy demand. Indeed, there are already shortages of computer engineers who can design apps for mobile devices, among others (Omojola 2013). Similarly, engineers who can design the devices to run this software, and those that can design the sensors and control systems necessary to operate machinery, will have little difficulty finding jobs. And people who know how to deal with large amounts of data—how to organize, analyze, and gain insights from it—will be increasingly in demand, as the amounts of data available for use continue to grow.
But perhaps the individuals who will be best positioned to take advantage of the coming sweet spots will be those who can work at the various intersections. For example, designers of user interfaces, both hardware and software, work at the intersection between technology and user and, to be successful, must understand user psychology as well as the engineering and design aspects of the product.
Another skill set likely to be in high demand is machine learning—the ability to design software and systems that can “learn” from the data collected. Software designers familiar with the challenges of dealing with large amounts of data and with the analytical skills necessary to extract meaning from the data likely will be increasingly valuable in coming years. In addition, systems designers—and, more generally, “systems thinkers”—will be needed to find ways to bring together the various interacting pieces in ways that extract the most value from the agglomeration.11
As with individuals, companies with skill sets most suited for dealing with the integration of hardware, software, and data will be the most likely to thrive. They will have the necessary skills among their employees—hardware designers, software engineers, data experts, and so on—and will be able to integrate across these domains, enabling disparate groups of people to work together in bringing integrated products to market. Apple set the standard, and many companies are following in its footsteps—Samsung, Google, Amazon, and Tesla, for example.
But few companies can afford to maintain all the capabilities needed for a major integrated project. Companies that thrive will be those most able to effectively coordinate with and take advantage of the expertise and capabilities of outside sources and actors along the value chain. For example, optimizing the system of pharmaceutical goods, medical devices, services, health monitoring apps, and information flow between doctors and patients to improve health outcomes requires aligning the activities of hundreds of companies. Businesses that are able to manage systems of this scale and coordinate across many stakeholders will have an advantage.
In addition, companies that can take advantage of emerging distributed capabilities will likely have an edge over those that cannot. For example, crowd-sourced data offer a nontraditional but very powerful source of information whose potential is just beginning to be tapped. With hundreds of millions or even billions of individuals posting information on Twitter, Facebook, LinkedIn, Pinterest, Instagram, Tumblr, Flickr, Google Plus, and multiple blogs, discussion boards, and rating and review sites, companies with the vision and know-how to take advantage of this information should be able to create value in ways not yet imagined.
There will also be opportunities to take advantage of more directed and deliberate contributions from individuals, such as the writing of software (an
11 Remarks of Jon Rubinstein at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
area that TopCoder is already exploiting) and the development of apps for valuable specialized tasks. As the world becomes increasingly interconnected, companies will be able to create great value by harnessing the creativity of individuals or groups of individuals who may have no connection with the company except a common interest in a subject or in solving a particular problem.
Advantages and Disadvantages for the United States
How well prepared is the United States to take advantage of digital technologies to make value?
One advantage that the United States has is that companies located here can generally find all the components needed for an integrated product or system without going out of the country. Paul McKenzie of Johnson & Johnson made this point when he spoke about his company’s decisions about where to locate production of biopharmaceutical products.12 In the case of older small-molecule compounds, where the science is well understood and manufacturing involves well-known processes, these are essentially commodities, so price dominates location decisions and the company looks for lower-cost sites. But the company is also involved in developing products that require a great deal of innovation, such as the use of stem cells to treat retinal degeneration. The process of making these products available to patients requires research and development; production; administration of the product, which involves surgery and must generally be done very soon after production; and then monitoring and feedback. The tight integration of these processes means that colocation takes precedence over cost in the selection of a site. Johnson & Johnson products such as biologics, vaccines, and stem cells require collaboration between research and development, clinical centers, and manufacturing, and so tend to be produced mainly in the United States and Europe.
More generally, McKenzie told the committee, the United States has an advantage in the way companies are able to collaborate with academia in both basic and clinical research. However, he added, at least in the pharmaceutical industry, he sees other parts of the world—China in particular—catching up with the United States in collaborations between academia and industry.
The United States has a similar advantage in the production of cutting-edge digital devices and services that integrate hardware, software, and data. Between academia and industry, the country has all the necessary skills and capabilities
12 Remarks of Paul McKenzie at “Making Value for America: A National Conference on Value Creation and Opportunity in the United States,” February 27, 2014, Beckman Center of the National Academies, Irvine, Calif.
to conceptualize, design, and operate these new technologies. Once the design has been tested and finalized, the manufacturing of the hardware may be done overseas at less cost, but the bulk of the value added will be in what the pieces have been designed to do and their integration with the software in a way that allows users to do things they had never been able to do before. As explained above, the value of the first iPod was not in its five-gigabyte hard drive or its FireWire components or any other of its individual components but rather in their integration, with the appropriate software, to create a music listening experience unlike anything anyone had seen (or heard) before.
The advantage of collaboration between academia and industry should also apply in areas such as software development, the design of user experiences with physical and graphical interfaces, new approaches to gaining insights from large amounts of data, and other areas that require thinking and integrating across multiple fields. The United States has the skills and capabilities required, as well as many companies with experience in integrating different components to create a useful, unified whole.
Yet another US advantage is difficult to quantify but nonetheless considered important by many businesses: Americans have a great, and deserved, reputation for being innovative. Innovators in the United States seem to be more creative, or at least more able—and perhaps more encouraged—to follow their creativity. For the past half century, US academics have dominated the recipients of Nobel prizes for physics, chemistry, medicine, and economics (see, for example, Bruner 2011). Similarly, over the past 40 years at least, the technologies that have been most transformative, from the personal computer and the Internet to smart phones and Google, have been mostly developed in the United States.
To the extent that its creative dominance can be maintained, the United States will have an advantage in areas of technological development that involve the creation of value through fundamentally new and creative innovations.
Yet certain disadvantages hinder the United States’ ability to take advantage of the opportunities posed by digital technologies. One notable shortcoming, discussed in more detail in Chapter 3, is the poor condition of US infrastructure for wireless communications. The infrastructure to connect novel products to digital networks and transfer data between them is critical to enable innovation in digital technologies and the benefits they can provide across the value chain. If the United States improves its digital infrastructure, especially in regions that have poor connectivity, it may be able to stimulate additional innovation and productivity gains.
Another concern is whether the US workforce is prepared to take advantage of digital capabilities and further develop them. The advent of open-source
software and the emerging development of open-source designs for objects through 3-D printing have created myriad possibilities to develop new products from building blocks that are readily available. Arguably, there are far more opportunities than people who know how to exploit them. Jon Rubinstein, who works with companies such as Amazon, Qualcomm, and many startups, commented that even in Silicon Valley there are not enough people with the right skills to do all of the work that should be done.13
With respect to the potential of data collection and analysis, another disadvantage is that, in some cases at least, it is more difficult to share data in the United States than in many other countries. In his comments to the committee, Paul McKenzie of Johnson & Johnson noted that, in large part because of privacy concerns in the United States, it is much easier to access clinical data in places such as China or India than it is in this country. At clinical sites in China every patient has an electronic medical record, which allows collection of clinical data much more quickly and with much less effort than if the records are on paper or in nonstandardized digital form. Although the technology for creating electronic medical records for all patients exists in the United States just as it does in China, there is a lack of collaboration between the healthcare system, industry, and the regulatory agencies. And broad concerns about privacy, and associated legal protections, have hampered such collaboration and prevented the implementation of standardized electronic medical records in the United States.
The result, McKenzie said, is that companies like Johnson & Johnson are more likely to conduct clinical trials in places where access to information in medical records is faster and easier. He explained that it is critical to have access to real-time data on clinical trial patients to be able to change the course of therapy during treatment if necessary, and the United States is at a clear disadvantage in this area.14
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