Latvia’s public employment service, the State Employment Agency (SEA), is undertaking a modernisation of its service delivery. This review discusses the SEA’s digitalisation needs and strategy to guide its modernisation efforts. It provides a detailed assessment of the SEA’s digital infrastructure and key recommendations concerning its IT system, analytical capacity and digital tools for jobseekers and employers. This report on Latvia is the fourteenth country study published in this series.
The State Employment Agency (SEA), Latvia’s public employment service, plays a crucial role in connecting people with jobs, but tight budget constraints make efficiency a priority. Many public employment services in OECD and EU countries are increasingly harnessing digitalisation to meet the needs of their clients better and more efficiently. This report assesses the SEA’s existing digital infrastructure and makes key recommendations for how the SEA could make better use of digital technologies.
Latvia allocates relatively little to active labour market polices (ALMPs) compared to other EU and OECD countries (0.14% of GDP in 2021 compared to 0.45% and 0.53% in the OECD and EU, respectively), as ALMP expenditures rely largely on project-based EU funding. Low levels of resources for ALMPs limit the SEA capacity, resulting in challenges to attract and retain staff due to low wages, a high number of jobseekers per counsellor, and low availability of ALMPs even though previous evaluations of these have shown them to be effective. This low level of resources underlines the importance of the SEA making the most efficient and effective use of them, highlighting the opportunity to harness digitalisation. However, harnessing the potential gains from digitalisation requires up-front investment that can be difficult to resource when funding is stretched.
The SEA recognises that its IT backbone is a key enabler to deliver good services to its clients, and its IT system is indeed able to support most of its current needs, such as registering jobseekers, managing services and measures, registering job vacancies, and matching jobseekers and job vacancies. However, the IT system does not include sufficient data management functionality, particularly in terms of data analytics to support evidence generation, but also in terms of data quality management and data sharing solutions with external parties. In addition, the architecture of the current IT system is not fully future‑proof and some practices in the SEA exhibit data and system security concerns.
The SEA has a dedicated tool to profile jobseekers to generate a better understanding of their needs for support, as well as a tool to match jobseekers and job vacancies. While the vacancy matching tool is fully digitalised and largely covers the needs of the SEA counsellors, jobseekers and employers, the jobseeker profiling tool requires manual processing and raises some issues regarding its efficiency, accuracy and usefulness. Digital tools to assist jobseekers in career management are only at a very initial stage in the SEA, the first tool to guide an understanding of jobseekers’ abilities being just adopted.
The key policy recommendations emerging from this review include:
Adopt a dedicated digitalisation strategy for the SEA. Develop a dedicated digitalisation strategy that lays out the objectives, principles and frameworks for the SEA’s digital transformation clearly and comprehensively. This should cover ensuring sustainable resources for digitalisation, establishing frameworks to maximise the value‑added of digital solutions, monitoring and evaluating digital tools, and managing risks associated with such tools.
Fine‑tune the operational IT system, its security and related practices. Move to a more modular architecture, introduce network-level segmentation and systematically upgrade outdated software. Implement continuous and systematic processes throughout system security management, such as in monitoring vulnerabilities, monitoring system access, auditing access rights and risk assessment and management.
Introduce a modern data analytics system involving a data warehouse and a Business Intelligence tool to better meet the knowledge needs of internal and external stakeholders, as well as comply with data protection regulation.
Refine the design and implementation of the jobseeker profiling tool. Refine the objectives and possible use cases of the profiling tool. Integrate the jobseeker profiling tool into the SEA digital infrastructure to use data from external registers automatically, facilitate data inputs from users and retain profiling information for future use. Adopt a modern statistical profiling technique or an AI-based profiling model to improve its accuracy, learning from the best practices of other countries.
Introduce a skills profiling tool to support jobseeker profiling efforts that consists of skills testing modules and generates a better understand of jobseeker skills to provide better job matching and career management services, as well as measures for upskilling and reskilling.
Enhance the performance of the job matching tool to better and faster identify good matches between jobseekers and job vacancies. Move towards a competency-based matching algorithm and consider enhancing it with AI technologies in the future to further facilitate using skills taxonomies, and increase its performance and user-friendliness. Consider supporting the job matching tool with other (advanced) digital solutions to better help employers to fill vacancies for bottleneck occupations and strengthen career management services.
Invest in the SEA’s digital tools and staff capacity. In particular, invest in the IT department of the SEA to ensure sufficient capacity to steer the digital transition and manage the projects with the external contractors.
Increase the capacity of the ALMP system. Increase ALMP funding from the national budget to expand the reach of evidence‑based ALMPs across the different types of services and measures, such as counselling, training and employment incentives.
