Context

Recently, estimates showed that the world could generate more data in the next three years than over the past 30. The explosive growth of data owes not only to “human” activities since as much as 40% of internet traffic is being generated by machines, between machines. However, this trend will likely continue and accelerate in the years ahead, with the number of networked devices in the world projected to reach a staggering 125 billion by 2030.

Analysis

What is a Data-Driven Economy?

• A data economy is a global digital ecosystem in which data is gathered, organized, and exchanged by a network of vendors for the purpose of deriving value from accumulated information.
• Data inputs are collected by a variety of actors including search engines, social media websites, online vendors, brick and mortar vendors, payment gateways, software as a service (SaaS) purveyors, and an increasing number of firms deploying connected devices on the Internet of Things (IoT).
• The gathered data is then passed to individuals or firms which typically take a fee. In the United States, the Consumer Financial Protection Bureau and other agencies have developed early models to regulate the data economy.
• Data collected and managed in the data economy must be stored on dedicated servers. These servers can be located on-premises for access from a single physical location, or off-premises.
• The data will reside in data centers and will remain available for access and exchange via internet-based applications, referred to collectively as the cloud. Storing and securing collected data represent a significant portion of the data economy.

Data economy categories

• Big data economy: Big data is defined as the algorithm-based analysis of large-scale, distinct digital data for purposes of prediction, measurement, and governance.
• Human-driven data economy: The human-driven data economy is a fair and functioning data economy in which data is controlled and used fairly and ethically in a human-oriented manner. The human-driven data economy is linked to the My Data Movement and is a human-centered approach to personal data management.
• Personal data economy: The personal data economy is created by individuals using personal data, which people supply either directly or indirectly. Consumers become suppliers and controllers.
• Algorithm economy: In an algorithm economy, companies and individuals can buy, sell, trade, or donate individual algorithms or apps pieces.

Data Paradox A recent Forrester survey of 4,036 high-level executives showed that 70% of data decision-makers are gathering data faster than they can analyze and use it, yet 67% constantly need more data. The massive opportunity brought about by data-driven decisions is being hampered by capacity constraints. Sometimes, this challenge is further amplified by the predominantly “defensive” narrative on data governance and policy, which rightfully places paramount importance on accountability, transparency, and privacy.

How to unlock and harness the current data opportunity?

1. Firms need to institutionalize data strategy at a human level

• Designing, implementing, and overseeing a holistic data strategy (from collection to analytics to monetization) that informs business decisions and units;
• Facilitating the free-flowing of data, data-driven insights, and data-related managerial decisions both internally and with external partners and regulators; and
• Supporting HR in recruiting or upskilling/reskilling employees.

2. Institutions need to rise to the challenge

• With data as a new strategic asset, present and future economy incentivizes the smart and responsible generation, exchange, and use of high-quality, interoperable data. To this end, institutions—including data-related rules, regulations, agreements, and governing bodies within and across national borders—must be modernized.
• The recently adopted global agreement on the Ethics of Artificial Intelligence led by UNESCO is among the most promising global effort to guide smart regulation towards the healthy development of this field.

3. All stakeholders in the data ecosystems must embrace and promote a truly data-oriented culture

• Data skill knowledge with training programs on digital and analytical skills now along with governments and educational institutions, who can deliver that should be encouraged more.

Way ahead

Transforming data from the raw material into a genuine factor of production and engine of innovation requires changes at the individual and organizational levels. It can flow among citizens, businesses, and governments. As 5G, AI, and other technologies reinforce both data supply and demand, this is the time to update our approach to data in a more forward-looking way. With the right people, institutions, and culture, we can build the economies of the future and use data as a driver of change for good.