# **Conclusion**

**The SDS makes several contributions** . First, the SDS provides a comprehensive but also in-depth portrait of skill, task, and educational requirements for a set of detailed occupations in Vietnam. The SDS is among the first surveys to collect this information at the detailed occupational level in a developing country setting. The collection of information about detailed skills means that these skills can be flexibly grouped into different categories (for example, socioemotional skills, digital skills, routine skills, interpersonal skills) as needed. The use of a consistent scale anchored to the time spent using or performing a skill or task yields a measure of skill and task importance that is easily interpreted. The SDS approach also has some advantages over collection of skill and task data via online job vacancy data, which has become common in recent years. In developing country contexts, online vacancy data tends to be biased towards higher-skilled digital-intensive occupations and jobs at firms that use the internet (CSC 2019; World Bank 2021). The SDS avoids this bias by selecting the occupations of interest, including low-skilled jobs, first and using a sampling frame based on Vietnam’s Labor Force Survey. Finally, the information generated can be easily compiled into profiles that can be shared with labor market stakeholders in order to inform career and workplace decisions.

**Still, the SDS has some weaknesses** . The SDS requires outlays on administering a survey, and initial data collection covered only 30 of the hundreds of occupations in Vietnam at single point in time.

**Ensuring the sustainability of occupational profiling efforts will require ongoing investment** . To be useful to students, employers, training institutions, policy makers, and other labor market stakeholders, labor market information must be both comprehensive and updated. This means that the SDS would need to be expanded to eventually cover all occupations in Vietnam. Plans would also need to be made to periodically review occupations already covered by the SDS. These efforts would require investment in survey administration, analysis of data collected, and dissemination of the results. Complementing the SDS with online job vacancy data could help offset some of the costs of frequently updating the occupational information collected by the SDS. Online vacancy data on skills and tasks could help keep occupational profiles fresh in between rounds of data collection, which could likely take place at greater intervals if complemented with online vacancy data. For example, O*NET uses online job postings to identify tools and technologies, to inform task statement taxonomies, and to identify new job titles to update occupational profiles. Incorporating additional data sources into occupational profiles is also important to ensure that a complete picture is created. Labor Force Survey data, firm surveys, consultations with employers and other labor market stakeholders, and many other sources are useful complements to the SDS and online vacancy data. The SDS is thus part of a labor market information ecosystem with the comparative advantage of producing comprehensive, granular information about occupational skills and tasks.

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