Capturing Opportunities with the Internet of Things

BY STEPHEN SU

Throughout 2014, the hottest buzz words about industry opportunities have had to do with the Internet of Things (IoT). There are also variations on the wording such as the Internet of Everything (IoE) and Internet of X-factor (IoX) that simply underscore the abundant but still elusive future opportunities in products and service applications.

IoT is not just another technology innovation awaiting market adoption, but rather a paradigm shift that will lead to another industry revolution. Over the next 10 years, most likely no single consumer product will enjoy a larger sales volume than mobile phones, which will serve as a gateway enabling many IoT devices and sensors of different forms and functions to be connected to the internet network. According to most market forecasts, collectively these devices and sensors may add up to some 30-50 billion units by 2020 – about 6-8 times the number of mobile phones. The global market for IoT is projected to increase to more than US$300 billion annually by 2020. Smart applications for IoT show multiple promising business opportunities: healthcare, sports and leisure, energy and the environment, manufacturing, security, transportation and logistics, education, etc. Among different IoT product types, smart home sensors and smart wearables like mobile watches will be leading the way.

International Data Corp. (IDC), the global market intelligence firm, defines IoT as a “network of networks of uniquely identifiable endpoints – or ‘things’ – that communicate without human interaction using IP connectivity.” In other words, for IoT it is not enough simply to have connection between people and devices with internet data. The key is to have sufficient artificial intelligence so that no human interaction is needed for value-added applications.

While the future seems highly promising for business opportunities for all these IoT applications, at the moment no one is in a position to predict what the killer applications might turn out to be. Due to this uncertainty, Taiwan companies now have a chance to be at the same starting line with other global players–unlike the PC and mobile-phone eras during which Taiwan mainly took the role of follower behind global market leaders.

Since many of the emerging IoT applications and systems will require both hardware and software integration, Taiwan’s traditional strengths in ICT hardware design and manufacturing will favor industries like IC design, IC foundry, semiconductor packaging, mobile phones, sensors and other electronic components, precision mechanics, etc. Both large and small companies will have equal opportunities in selecting emerging IoT applications to build ecosystems. However, Taiwan needs to strengthen its position in industries involved in system software, branded consumer products, and service exports. In addition, as IoT applications will cover a wide spectrum of traditional industries like healthcare and tourism, Taiwan also needs to leverage its ICT strengths in forming cross-disciplinary industry alliances between traditional industries and ICT industries.

Data Economy vs. Energy Economy

For more than a century, the key factor in the world economy has been energy, with oil and gas as the most valuable natural resources, powering industrial growth and even influencing global politics. However, the leading oil and gas company, ExxonMobil, has not generated growth in its market cap since 2011. Its global ranking among companies by market cap has dropped from first place to second, overtaken by Apple, and three other oil and gas companies have dropped out of the top 10 in terms of market cap in the same period. While energy companies’ ranking has been declining, three of the top 10 companies by market cap are now in businesses related to the internet and software: Apple (1st), Microsoft (3rd), and Google (4th – up 20 places since 2011). Apple’s market cap has increased by 60% during that time, Microsoft’s by 75%, and Google by 129%. These trends indicate the coming of the Data Economy, consisting of value-added integration and applications of emerging technologies like IoT, big data, and the cloud – and show that the Data Economy is beginning to command higher value from investors than the traditional Energy Economy.

IoT-economy_2014-12
Similarity: Value-add from exploration, drilling, processing, application of resources Difference: Data explosion, borderless, open, multi-usage

 

There are similarities between the Energy Economy and the Data Economy. In the Energy Economy, value-add is generated from four stages of activities: exploration, drilling, processing, and applications of natural resources like oil and gas. In the Data Economy, value-add is generated from similar activities but through data processing. While natural resources are limited and will be depleted in the Energy Economy, the Data Economy’s resource – data–will never run out but rather will continue to expand in volume. Furthermore, data is not restricted to physical country borders, can be openly accessed, and can be re-used multiple times for value-added applications.

In the Data Economy, therefore, big data analytics – analyzing data, combining domain knowledge, and translating these resources into customized services – becomes the most important tool for generating value-add. Just as shale gas/oil is one of the most important game changers for the next 100 years in the Energy Economy, big data analytics will be a huge game changer for the foreseeable future. Since the infrastructure of IoT basically consists of a centralized system and distributed devices connected through internet communication, big data analytics can have an enormous impact on the value of businesses engaged in the Data Economy.

As an example, one of the early applications of IoT currently is the use of smart watches for healthcare monitoring. Since personal data can be collected from a smart watch for many hours a day, seven days a week, the volume of data collected can greatly exceed the amount traditionally analyzed by medical professionals. Without the use of some type of big data analytics to digest such a large amount of data and formulate medical recommendations by artificial intelligence, the vast data collection from wearables such as smart watches will not add any value to end users.

Internet of the Minds

IoT is usually divided into three forms of interaction among different entities via a communication network: People-to-Machine (P2M), People-to-People (P2P), or Machine to Machine (M2M). Among these entities, data is being transmitted and processed either by centralized computing or distributed nodes. Supporting this data communication is a wide spectrum of technologies encompassing cloud computing, communications protocols, human-machine interface, wireless sensor networks, big data, cyber-physical systems, artificial intelligence, flexible displays, and many others.

While most market forecasts focus on how big the device-related opportunities will be for smart watches or smart home meters, less attention is being paid to how to collect and analyze data. In this regard, all companies pursing IoT-related business opportunities need to be reminded that “People-centric” should be the focal point of all business models and technology development. “Machine-centric” or “Data-processing” are important elements in the IoT value web, but should be utilized only to support the provision of innovative services to satisfy the unmet needs of “People” in Business-to-Consumer (B2C) or Business-to-Business (B2B) business models. By emphasizing People-to-Services (P2S) and integrating it into the offering of IoT applications, the Internet of Minds (IoM) will be established as a critical success factor for IoT.

IoT graph2
Internet of Minds (IoM) as a critical success factor for IoT

 

As a case in point, iRobot is famous for developing household robots for vacuuming and floor-washing purposes. These products already have certain user-friendly features that users find appealing, such as automatic return to the home-base charging dock when running out of battery life, and sensors to detect when the robot is approaching a wall. In the future, similar new household robots will be connected to the internet via a wireless network to enable them to carry out IoT functions such as allowing caretakers to monitor the security of elderly patients or making it possible for the robot to carry on small talk with lonely elderly users. These are appropriate P2S features that connect the minds of people (unmet needs, wish lists) with the minds of machine (artificial intelligence, friendly user interface) to establish IoM.

As mentioned above, since no one knows which of today’s many emerging IoT applications will become tomorrow’s killer apps – thus putting Taiwan companies on an equal footing with all global competitors – it would be best for Taiwan to adopt an approach similar to that of a Special Operations Force (SOF) in unconventional military operations. Special Ops usually refers to a small, elite military force trained to perform unconventional missions. The U.S. military has many such units for different purposes, such as the Army’s Green Berets, Rangers, and Delta Force, the Navy SEALs, and the Air Force’s Special Operations Squadrons. Unlike conventional warfare, a Special Ops unit often needs to conduct operations with quick deployment and surgical precision around targets. Rather than involving synchronized massive planning across different military units, it requires comprehensive support within the same military unit for self-sustaining operations. It is designed to quickly establish defendable beachheads for later battles to be won.

The Taiwan government and industries should form similar “Special Ops Teams” for selected IoT applications. Each such application would be strategically chosen for its high impact with regard to potential market size, yet also carrying a high degree of uncertainty in terms of risks associated with technological maturity or potential substitution by other technology. As a result, it would be preferable to make a small but early investment in technology or business-model exploration for each IoT application, rather than making a massive effort that requires complex coordination and often slows down development speed. The aim is to fast-develop some IoT applications to pilot test in a new ecosystem, then adjust the design of the product or service based on early feedback. While not all selected IoT applications will become winners, hopefully a select few would attain early success.

The “Special Ops” units should be cross-disciplinary, public-private partnership teams consisting of representatives from both private industry and research institutes like the Industrial Technology Research Institute (ITRI), but championed by a single government ministry to minimize bureaucracy. They should concentrate on strategic IoT applications that already have a degree of established lifestyle-related ecosystems in Taiwan. Some examples of such applications could be smart transportation based on Taipei’s YouBike or Mass Rapid Transit system, smart retailing based on the 24-hour convenience store infrastructure, and smart healthcare leveraging the existing National Health Insurance system and community culture of volunteerism. Hopefully more of these lifestyle-related ecosystems will soon transform Taiwan industries’ innovation focus from “Manufacturing in Taiwan” to “Lifestyle in Taiwan.”

In sum, Taiwan can capture the emerging IoT opportunities through the IoM and Special Ops Teams. By focusing on “People-centric” products and services while leveraging traditional advantages in technology and products, Taiwan could quickly build pilot ecosystems that could cultivate new business models, develop high value-added innovations, and integrate system solutions in IoT applications.

— Stephen Su is General Director of ITRI’s Industrial Economics and Knowledge Center (IEK). He holds an MBA from the Kellogg School of Northwestern University and a master’s in Electrical Engineering from Caltech

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