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Study of anticipation and forecasting models for international recruitment needs in Netherlands, Australia, Canada and Denmark

Ryhmä kavereita kävelee kadulla
07.11.2024 Olli Oosi Avainsanat: ,

On behalf of KEHA Center (a centralized governmental unit for service development in employment and economic services), we conducted a comparative analysis of practices related to international recruitment needs and labor demand forecasting in four different countries. The analysis focused on the Netherlands, Australia, Canada, and Denmark. In this blog, we summarize our main findings in English. Explore the study here (in Finnish).

The perspectives on labor demand and supply, as well as the consideration of immigration, focuses on professions or occupational fields. All the countries reviewed employ models for labor demand and supply forecasting, with some countries even using multiple models. However, perspectives on international recruitment vary. Discussions and planning around labor immigration, particularly at the employer level,  emphasize skills and competencies. Still, labor immigration forecasting mainly focuses on professions in which the country needs workforce. The need for international recruitment has rarely been central in model development, though there are future plans to integrate it more explicitly.

The forecasting timelines for labor demand and supply vary between countries, ranging from short- to mid-term (Netherlands, Denmark, and Australia) to long-term (Canada). Interviews suggested that the need for international recruitment is often perceived as a quick response to obtain skills and labor, which is why it is not directly reflected in labor demand and supply forecasts but appears indirectly.

Each country’s immigration strategies and practices related to visas, work, and residence permits shape immigration and the targeting of international recruitment. Employers or their representatives play a central role in defining international recruitment needs. Recruitment needs arise from employers, and international recruitment in all countries takes place largely on a “market-driven” basis, meaning that public actors have a relatively minor role in identifying and forecasting recruitment needs.

At the time of the study, the digitization of forecasting or the use of AI was not very advanced in the comparison countries; Finland appears to be a frontrunner in this area. The most common approach is to publish forecasting results on some form of interactive digital platform supported by database structures.

In labor demand and supply forecasting, qualitative information or interpretive collaboration processes are essential. A process perspective is one of the aspects that could be learned from the comparison countries and applied to the development work in Finland on this topic.

The perspective of international students is included in the labor supply in several countries. This is reflected in models as data on the number of international students in the country’s education systems and assumptions about how many of these international talents or individuals will stay in the country, as seen in the Netherlands and Australia.

Finland is capable of doing many things more diversely than the countries in this comparison. Finland has extensive data on matching situations across various timeframes. However, workforce immigration/international recruitment perspectives could be strengthened in matching modeling. Finland needs further processing of existing data and a regular collaborative analysis and interpretation process involving forecasting actors, labor market organizations, and regional entities to address acute international recruitment needs and set long-term goals and related actions.

The key lessons for Finland’s development work from the study are:

  • Recommendation 1: Finland’s international recruitment forecasting model should also include qualitative elements and collaborative interpretation with key employer organizations.
  • Recommendation 2: The perspective of international students should be incorporated into the forecasting model.
  • Recommendation 3: Country-specific analysis should focus on creating a process for generating country-specific information.
Olli Oosi

Olli is co-founder and senior partner at Owal Group. Tel. +358505304737 olli@owalgroup.com

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