Disrupted jobs: Big changes need Big Data
Published 22 February 2022
The updating of crucial labor market information in real time online stood in contrast with government efforts to collect traditional labor market data. We now have an opportunity to connect the private sector with the public sector looking to use big data for policymaking. To remain competitive for global investment and trade, investing in Big Data is an investment in the future.
As the Asia Pacific Economic Cooperation (APEC) convenes virtually for the first official meetings of APEC 2022 – with Thailand as host – the impact of Covid-19 will remain prominent in the discussions. As the region’s economy recovers along with the labor market, policymakers and workers alike examine questions surrounding jobs in a digitalized economy.
One of the consequences of the Covid-19 pandemic has been its impact on work. As economies shut down and reopened, imposed quarantines, and struggled to vaccinate the population, governments around the world found themselves scrambling to respond to the economic pain of lost jobs and suspended careers.
Yet while factories shuttered and ports became backlogged, e-commerce and digital services were picking up speed, and improved the resilience of the broader economy.
Within days and week, the disruption to trade, firms, and livelihoods was pervasive. While firms adversely affected by Covid-19 measures were terminating or furloughing workers, job opportunities were accelerating in the growing digital economy. In virtual job-listing platforms like LinkedIn and Indeed, millions of firms and people posted real job openings, developed competencies, and updated resumes.
The updating of crucial labor market information in real time online stood in contrast with government efforts to collect traditional labor market data, which policymakers rely on to inform labor policies.
Clearly there is a disconnect. Due to their considerable costs, regular labor force surveys – which include information on employment and unemployment trends, educational attainment of the workforce, and wages – are often conducted on a quarterly or monthly basis. The surveys are comprehensive, but the results trickle in slowly.
On the other hand, big data for the labor market include:
- Online job ads and employee work history data, such as online CVs, which shows employer demand for skills and jobs and workers’ supply of those skills
- Human capital management data sourced from payroll and HR systems
- Online learning platform data demonstrating skills that workers are learning
- Online gig economy data that shows where gig workers work, who takes jobs, and the types of jobs workers will accept for pay rates
- Knowledge sharing and communication platform data
This ‘big data’ is more granular, updated frequently, and can quickly capture emerging skills, such as those needed in response to new technology. As a result, compiling traditional and big data can give policymakers timely, accurate, and reliable information to use for evidence-based policymaking on labor market regulation, skills development, and social protection.
Indeed, labor market regulation, skills development, and social protection are among the biggest challenges facing policymakers as they grapple with the future of work. This nexus of challenges was discussed in the recently published report, the APEC Economic Policy Report (AEPR) on Structural Reform and the Future of Work.[i]
According to the report, economies need to address economic security for workers even as dynamic technological and environmental landscapes require new skills and new rules to match evolving economic realities. Thus, timely information will be crucial to help policymakers understand the fast-paced changes that are happening all around them. This information will also be useful to ensure that an economy remains competitive and strategically positioned for transition to a digital age.
Using big data for policymaking and strategizing is nothing new. The private sector has embraced big data for years, helping the businesses make investment decisions, develop new products, target advertising, and deliver goods more efficiently.
Using big data for developing public policy, however, is not as ingrained. This is partly because big data is neither cheap nor easy. The private and academic sectors have had to invest significant amounts – on collecting data as well as on digital infrastructure and technology, and on building and sharing technical skills to collate, clean, and analyze big data.
We now have an opportunity to connect the public sector with the private sector. There is no need to reinvent the wheel. Instead, governments can work in partnership with private firms, universities, international organizations, and other research institutions to bring big data to bear for public policymaking. Governments and policymakers looking to use big data could start with three small steps:
- Understand and assess the full scale of costs. In any partnership, there are upfront costs as well as dynamic costs. It is important to consider the costs of initial creation and set-up, people and analytical resources, and maintenance of taxonomical and data updates.
- Begin with a small-scale pilot project. This pilot project should aim to solve a very specific problem; for example, how to determine the top skills required for each occupation in the economy. Initially, the government may face some hesitation from stakeholders accustomed exclusively to traditional data. It is important that the first project starts small to gain trust in the data.
- Once trust is gained, start a larger project. After the initial data scoping to ensure the usefulness of big labor market data, the government can consider larger scale projects. Further projects can encompass work such as the examples described earlier, including identifying labor shortages, emerging skills, or growing occupations.
The digitalization of production, trade, and supply chains was underway before the pandemic. Yet the Covid-19 crisis accelerated the process. With borders closed and offices shuttered, even the most tech-averse firms and bosses found themselves forced to work with logistical apps and remote working tools.
The same is true with how we monitor jobs and skills in the labor market. Traditional labor market data have served employers, investors, and policymakers well. But it is challenging for economies to navigate workplace disruptions in the digital age and remain competitive for global investment and trade. Investing in Big Data is an investment in the future economy.
Layla O’Kane is a research manager at Emsi Burning Glass and Emmanuel A. San Andres is a senior analyst at the APEC Policy Support Unit (PSU). This article is based on APEC PSU’s Issues Paper #13 on Big Data for the Labor Market: Sources, Uses and Opportunities (https://www.apec.org/publications/2021/12/big-data-for-the-labor-market-sources-uses-and-opportunities).
i APEC Economic Policy Report (AEPR) on Structural Reform and the Future of Work (https://www.apec.org/publications/2021/11/2021-apec-economic-policy-report)
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