Today’s changing world places many complex challenges to labor market governance and management: the slowdown of the global economy, the structural shifts and evolving skill demands connected to widespread digitalization, as well as increasingly dynamic career paths with more frequent job switching, geographical mobility and flexibility, and multiple transitioning between education/training and employment.
Advanced labor market information systems are key to improving labor market efficiency
To address these challenges, many governments have established active labor market polices (ALMPs) and public employment services (PES) to help workers find jobs and firms fill vacancies. However, due to the complexity and individual set of challenges in any given labor market, there is no simple answer as to how public employment services should be set up and organized. But a well-thought-out information strategy and infrastructure is certainly critical to the success of any PES. If nothing else, the most recent disruptions have shown that effective ALMPs and PES require agile and flexible frameworks to successfully adapt to rapid and at times dramatic shifts in their labor markets. But even the most agile of frameworks is only useful if it includes a system to identify labor market issues as they arise.
Identifying such issues relies critically on the availability and quality of data, information and analysis. Therefore, establishing an advanced labor market information system (LMIS) is an integral step towards more efficient and targeted employment and labor policies by delivering accurate, relevant and timely information to inform design, implementation, monitoring and evaluation of policies. According to the World Bank, advanced LMIS encompass institutional arrangements between key stakeholders (e.g. policy makers and the education system), collaborative partnerships with private sector actors and advanced technology solutions to gather, validate, analyze, and distribute information related to the labor market that is relevant, reliable, useful, and as comprehensive and up to date as possible.
Combining traditional labor market information with real-time data
Traditionally, labor market information (LMI) was primarily gathered from censuses, surveys, case studies, and administrative data. However, this traditional LMI has a disadvantage that is increasingly cumbersome: lag time. In an ever-faster changing world this carries risks such as policies being outdated before they can be implemented, rendering them ineffective if not obsolete. Therefore, an effective LMIS should also incorporate real-time (big) data from additional sources such as online job portals and networking sites. This type of data is not only much more up to date, it also typically contains more detailed information including job activities and requirements regarding education and skills. However, real-time LMI based on online job advertising data also has significant shortcomings: Apart from the challenges of duplicates and inconsistent levels of detail, it tends to be incomplete. Not all jobs are posted online, in particular, this type of data rarely captures the informal sector and is also often biased toward certain industries or occupations. In addition, the data may be distorted by ghost vacancies posted by non-hiring companies that want to cast a broad net for talent. Accordingly, real-time LMI is a complement to, rather than a substitute for traditional LMI.
Empowerment through interoperability
In addition to supporting policy makers and researchers, a strong LMIS should also provide additional services such as job matching, career and skills guidance and government support services through a government-managed online platform with interconnecting subsystems tailored to the different users. In this way, the LMIS strengthens the functioning of the labor market by helping all stakeholders in the labor market including workers, students, firms, and practitioners to make informed choices on a variety of topics such as job search and hiring strategies, curriculum design, career planning and training investments, and more.
International examples of modern LMIS
Worldwide, several countries offer examples of advanced LMIS incorporating LMI from traditional and big data sources and where the information feeds both into and from multiple interconnecting public interfaces to provide comprehensive, verified LMI for research and policymaking as well as job-matching, career guidance and skills development services. These sophisticated services include state-of-the-art tools and technologies such as AI/ML and big data analysis.
For instance, in Korea, information in the LMIS is used by the Korea Employment Information Service (KEIS) to monitor and evaluate public policies and generate analyses and forecasting for stakeholders such as job seekers, employers, researchers, and policy makers. Data is drawn from national statistics, surveys related to employment and skills, and databases from various interconnected KEIS networks, including HRD-net, a job-training platform, and Work-net. Originally established in 1998 as a publicly managed job-search portal by Korea’s Ministry of Employment and Labor, Work-net now provides comprehensive employment information and support services, including job matching and information on occupational outlooks, working conditions, and skills demand, as well as feeding user-generated data back to KEIS. With the progress of technology, it has added mobile services (2010), big data services (2018), chatbot services (2019) and AI-based job matching services (2020). 
The Norwegian LMIS also comprises interconnected subsystems that combine services for labor market supply and demand with data for decision makers and policy makers. The Norwegian Labor and Welfare Administration’s (NAV) online platform for job search and matching services, Arbeidsplassen.nav.no, has been using AI technology since 2019. It contains job advertisements both posted directly on the platform by employers and imported from external, privately managed job portals, as well as a CV database of job seekers, providing a comprehensive overview of the labor market. The system also has access to extensive information on the Norwegian education landscape to enhance the accuracy of job matching and career planning services. This modern digital platform provides automated and highly user-friendly services, and continuously self improves thanks to sophisticated machine learning algorithms in the backend. During the first wave of the pandemic, the system proved scalable by a factor of 8–10 within just a few days to deal with the surge in registrations caused by the dramatic disruptions in the labor market.
The technology behind the semantic search and matching engine and the underlying ontology of Arbeidsplassen.nav.no is provided by JANZZ.technology. JANZZ has been collaborating with several public employment services across the globe to assist their LMIS development. Our services range from state-of-the-art AI-based solutions to gather real-world labor market data and transform it into smart labor market intelligence – including job and resume parsing and automated classification and contextualization of job and skills data – over intuitive and powerful analysis and dashboarding tools that generate actionable insights including skill or workforce gap analyses, training and career guidance or semantic job matching, to designing entire system architectures from scratch. Visit our website and discover the advanced solutions we have created for public employment services or watch the explainer video for our integrated labor market solution JANZZilms!.