- Skills anticipation studies help identify future labor market needs, enabling education and training systems to better prepare workers for emerging occupations and in-demand skills.
- Combining quantitative data with qualitative insights produces more robust results, making it easier to identify priority sectors, skills gaps, and training needs.
- Recent experiences in Ecuador and Honduras show how skills anticipation studies can inform training policies, helping align workforce development programs with the needs of employers and productive sectors.
Imagine you are the director of a technical training institution. You have to decide which programs to offer over the next few years. How do you choose a training portfolio that will help people find better jobs in a labor market that is changing faster than ever?
This is a real and urgent challenge across Latin America and the Caribbean (LAC). A recent Inter-American Development Bank (IDB) analysis based on online job vacancies from 15 countries in the region found that demand for digital and technological skills grew from 16% to 19% in just three years, while vacancies related to artificial intelligence surged in 2025. Yet many institutions continue preparing workers for occupations and skill profiles designed for a labor market that has already changed.
To help address this challenge, the IDB works with countries to design and implement labor market information systems that support better decision-making by students, job seekers, employers, and training providers. In this blog, we explore one of the key components of a strong labor market information system: skills anticipation studies. We explain what they are, why they matter, and highlight good practices for developing them.
Unlike a traditional labor market assessment, which provides a snapshot of current conditions, a skills anticipation study looks ahead. It analyzes trends to identify which occupations and skills are likely to become more important, which are expected to decline, and where future training gaps are likely to emerge.
Across several IDB publications, we have emphasized the importance of aligning what education and training systems teach with the skills people need to build successful careers. Without that alignment, training becomes less relevant, and the workers who are already most vulnerable bear the greatest costs.
As discussed in our book Making Labor Markets Work, although countries across the region have made progress in identifying skills demand, they still face the challenge of collecting this information systematically and channeling it into training systems so that it informs the design and updating of curricula.
There is no single way to conduct a skills anticipation study. The most appropriate methodology depends on the context, the quality of available data, the resources available, and the level of detail required.
Quantitative methodologies. These rely on data from multiple sources, including household surveys, employment records, online job portals, and labor intermediation platforms. For example, online vacancy platforms can be analyzed through web scraping—a technique that automatically collects information from websites—to reveal, in real time and at relatively low cost, which occupations employers are seeking and where skills shortages exist. Sector-specific surveys can also be used, such as Costa Rica's Digital Talent Survey, which maps demand for digital skills. These approaches are comparable, scalable, and can be updated regularly, but they also have limitations: they tend to underrepresent informal sectors and emerging skills that have not yet appeared in administrative or online records.
Qualitative methodologies. These gather information directly from people with in-depth knowledge of specific sectors, including employers, business associations, labor unions, public sector officials, and academic experts. Their main value lies in understanding the strategic direction of the economy, identifying sectors with growth potential, and anticipating the human capital they will require. Their main limitation is that results depend on participant selection and are less comparable across countries or contexts.
Mixed methodologies. These combine both approaches. Quantitative evidence provides the analytical foundation, while stakeholders validate and enrich the findings through their expertise and experience. According to the OECD, about half of all skills anticipation exercises worldwide use this combined approach.
International and regional experience points to several recommendations for strengthening the design and implementation of skills anticipation studies:
- Combine methodologies. Studies that integrate quantitative evidence with qualitative validation tend to produce more robust and credible results.
- Engage multiple stakeholders. Employers, business associations, labor unions, and training institutions should all contribute their perspectives. This increases both credibility and relevance.
- Prioritize strategic sectors. The energy transition, digitalization, agribusiness, and sustainable tourism are creating new occupations across nearly every country in Latin America and the Caribbean.
- Define the scope and level of detail from the outset. Broader studies identify overarching trends, while more targeted exercises generate information that is more useful for designing training programs.
- Generate actionable information for training systems. A well-designed skills anticipation study should identify priority sectors, critical occupations, in-demand competency profiles, and existing skills gaps. Its role is not to design curricula—that comes later—but to provide sufficiently detailed evidence to support that process.
With support from the IDB, skills anticipation studies are increasingly informing training policies across the region.
In Ecuador, for example, the Ministry of Labor conducted a Labor Skills Demand Survey in 2024, which found that 41% of firms struggle to fill vacancies. The country has also carried out skills anticipation studies on sustainable transport and renewable energy to better understand current and future demand for skills in these sectors. Together, these findings will help improve the relevance of training courses delivered through the Employment Commitment Support Program.
In Honduras, the Ministry of Labor and Social Security is developing a skills anticipation study covering manufacturing, construction, agribusiness, tourism, and financial and business services. The results will help align training activities under the Labor Market Insertion Support Program with the needs of the productive sector.
Skills anticipation studies do not predict the future with certainty. Rather, they strengthen institutional capacity to anticipate change, adapt to evolving labor market needs, and ensure that workers—especially those in vulnerable situations—enter the labor market with the skills employers actually demand.
Significant challenges remain. Data availability and quality continue to vary across countries, coordination between public institutions and private sector stakeholders is often difficult, and financial and technical resources are limited. Yet the cost of inaction may be even greater.
Without tools to anticipate future skills demand, training systems risk preparing workers for jobs that are disappearing, while employers struggle to find the talent they need.
More than a planning exercise, skills anticipation is an investment in higher productivity, greater worker adaptability, and training systems that are better equipped to meet the demands of the future.