[Viewpoint] Data and Business Value Creation

Key technologies of the 4th Industrial Revolution, such as the Internet of Things (IoT), Artificial Intelligence (AI), Big Data, robotics, drones, autonomous vehicles, and Virtual Reality (VR), create synergy through organic convergence. A core element in this convergence process is data. Data needs to be treated not only as a source of economic value creation as before but also as a means of business creation and as intellectual property subject to value assessment.

According to the International Data Corporation (IDC), the global data market size is expected to grow from $166 billion in 2018 to $260 billion in 2022, and the global data volume is projected to increase from 33 zettabytes (ZB) in 2018 to 175 ZB in 2025, with an average annual growth rate of 61%.

Data creates new business opportunities and jobs. Palantir, a representative U.S. company, is a good example. Founded in 2003 by Peter Thiel, well known as part of the PayPal Mafia, Palantir applied the fraud prevention program used at PayPal. Palantir generates business value by analyzing seemingly unconnected data sets. Its major clients include the U.S. CIA, FBI, and Department of Defense. As a business model that processes raw data and provides it to clients, Palantir's revenue reached $1 billion as of September 2020.

Among domestic companies, K-Weather is a representative example. Established in 1997 with the goal of "creating high added value through the weather industry," K-Weather currently provides weather content to about 4,000 companies. Weather and air are essential intangible assets inseparable from our lives, and K-Weather operates as an environmental data company covering all aspects of our living spaces by utilizing its weather expertise and 4th Industrial Revolution technologies to collect data.

Thus, data can be used in a wide range of fields, including intelligent-based industrial innovations such as customized precision diagnostics, cutting-edge smart factories, autonomous vehicles, and smart farms, as well as optimal traffic signal control, dementia prediction, AI-based crime analysis, and rational credit lending. Companies like Amazon, Alibaba, and SoftBank also recognize the importance of data and are leading the global market through research and commercialization.

Data Technology (DT), which generates and analyzes digital data to provide insights, is similar to Information Technology (IT), the foundation of the 3rd Industrial Revolution, in that both target digital data. However, as seen in IoT, DT differs in that the scope of data collection expands to things. Regarding the nature of data, DT does not distinguish whether data has value as information, whereas IT only deals with data that has value as information. This means that the value of DT can be considered in all aspects, including business value, contribution to human life convenience, and values related to disasters and life.

More data-based business models need to be created, and policy support for them should be more proactive. The United Kingdom is regarded as the most advanced country in data policy. In 2012, to create data value, it established the Data Strategy Committee under the Department for Business, Innovation and Skills and promoted a government-led open data strategy. The Data Strategy Committee decides whether to disclose data and reviews the potential for discovering business services through data utilization, serving as an advisor for disclosure and utilization.

Although our government recognizes the importance of data commercialization, progress has been slow. Even now, the establishment of a data agency similar to that of the UK should be actively considered. We look forward to more data-based business models being created and to economic growth and quality job creation through them. / Kyung-Hwan Kim, Dean of the Graduate School of Global Entrepreneurship, Sungkyunkwan University