We often hear that growth is the answer to all our problems. However, growth alone will not suffice. Resolving the current challenges society is facing is not just about economic vigor: it is about elevating the human condition. In a world increasingly driven by behavioral economics, we must leverage big data analytics for inclusive growth, so everyone can make contributions toward growth and all sectors of society can benefit from the dividends and sense of purpose that result. Economic growth corresponds to an increase in GDP. However, to avoid leaving part of the population— indeed the entire population of the Global South (Africa, Central and Latin America, and large parts of Asia)— out of the growth equation, we must add a qualitative measure that we describe by using the term inclusive. In considering what inclusive growth looks like, we note that it encompasses three essential components:

  • Education that allows people to participate in disruptive industries and expanding markets, particularly data-driven services, whereby entirely new skill sets will be the catalysts to redeploy traditional ones.
  • Jobs created by the free movement of goods, services, capital, data, and people, with all sectors of society able to add value to the economy.
  • Well-being, consisting of prosperity, good health, and longevity, in an environment of public health and safety, sound policymaking, and prudent allocation of taxpayer resources for the public good without fraud, waste, or abuse.

The three pillars of inclusion are highly interdependent: we need a higher proportion of the population contributing to society, and to achieve this we need to improve education and well-being while simultaneously creating more jobs. Fortunately, technology is an enabler, a catalyst, and a propelling force that makes it possible to take action. We can now process huge volumes of data, and we now have enough affordable processing capacity to build the complex models that allow us to ask previously unimaginable questions as well as to answer those that were not previously answerable. The combination of these abilities — big data analytics — makes truly inclusive growth a genuine possibility for the first time in history.

Expanding access to education

During times of transformation, it is inevitable that society will experience a gap in the type of skills needed to remain competitive. For example, as the Industrial Revolution began, when more farmers than factory workers were available, it took time for the populace to be retrained and catch up to the needs of the age. The same is true in our current digital revolution—over time, these new digital jobs will be the catalysts to redeploy the more traditional roles. But at the moment, we are experiencing a lag because a digital economy requires people versed in science, technology, engineering, and math—STEM skills, precisely the skills that are currently lacking.

When it comes to education, the need is global but the greatest potential for transformative change is in the Global South. The populations and emerging markets of these countries offer immense untapped potential for economic growth and investment—but they are the same regions often lacking in educational and information infrastructure.

One solution lies in using online curricula and other forms of distance learning, which can spread proven techniques across borders. But online learning is not the only application of analytics in education. Big data analytics can also be employed to improve educational outcomes in brickand-mortar schools. For example, educational value added assessment systems (EVAAS) use multivariate, longitudinal modeling to go beyond mere classroom level analyses: they assess the effectiveness of districts, schools, and teachers, and provide continually changing projections of future student performance and needs. EVAAS is flexible enough to account for factors such as student and teacher mobility, team teaching, and changes in educational policies and assessment standards. EVAAS also balances the role of school and home factors in educational success.

Expanding access to jobs

In this time of economic transition, new jobs are being created. But are we ready to fill them? If data are the new oil—the fuel of the information economy—the new oil barons will be the data scientists and knowledge workers, and the world will need plenty of them. By 2018, the United States is projected to have 190,000 unfilled analytics positions and a shortage of 1.5 million managers and analysts skilled in big data.

Pôle emploi, the social service agency for employment in France, must comply with national legislation while also taking regional and local needs and requirements—such as industrial, agricultural, or service industry zones, seasonal employment, and so on—into account. Managing risk and quality across this complex web of factors is a problem well suited to big data analytics. By permitting highly localized approaches to serving the unemployed, Pôle emploi is using its limited resources more effectively, offering greater flexibility and personalization along the pathway to employment and fast-tracking their clients’ re-entry into the workforce

Enhancing well-being

Big data analytics has much to offer in advancing the practice of healthcare toward the triple aim of better health, better care experience, and lower costs. The potential is mind-boggling. Masses of genomic data, clinical trial data, electronic health records, claims data, research study data, and more—terabytes and petabytes of data—can be brought together to reveal important discoveries and support better operational and medical decisions in both private and public healthcare.

After the SARS outbreak of 2003, the Department of Health in Hong Kong modernized its analytics to link many different systems for a better flow of information. In essence, the department took massive amounts of diverse data and linked them together in a social network that took into account how people interact and where. Once these social networks are mapped, the department can identify hotspots to forecast where disease is likely to spread next. Where an outbreak originates determines how it will affect the population, so predicting infection paths shows where and how to deploy resources for maximum effectiveness. The department is now better prepared to fight the next health emergencies, including a more recent outbreak of Dengue fever.

After Typhoon Haiyan devastated the Philippines in 2013, analytics helped aid workers prioritize assistance levels and supply distribution. The International Organization for Migration incorporated social media data with geographic and real-time data to better understand the unique needs of each region hit by the typhoon. As a result, they could pinpoint what locations were hardest hit and what supplies were needed most, learning, for example, that hospitals in the badly damaged coastal city of Guiuan were running out of diesel for their backup generators.

Big data and inclusive growth

Fortunately, big data analytics can empower public sector organizations to use their data to “predict to plan” and “predict to prevent” rather than “fail and fix.” In other words, rather than patching holes and closing loopholes, big data analytics allows us to proactively identify the conditions that can give rise to fraud, risk, and security breaches—as well as to many other public welfare challenges. If social programs that promote well-being are to be adequately funded, stopping leakage caused by fraud and waste is essential.

In summary, big data analytics can transform public sector services into the proactive and effective programs citizens deserve. Early and proactive interventions have proven to save substantial tax dollars while at the same time improving the quality of life. Ultimately, big data analytics will drive inclusive growth by enabling more people to join in adding value to the economy.

This is an edited version of a full-length article that first appeared in the Forum’s 2015 Global information Technology Report.

Author: Mikael Hagstrom is Executive Vice President at SAS and vice chair of the Global Agenda Council on Data-Driven Development at the World Economic Forum.

Image: A villager goes through the process of a fingerprint scanner to register for the Unique Identification (UID) database system at an enrolment centre at Merta district in the desert Indian state of Rajasthan February 21, 2013. REUTERS/Mansi Thapliyal