Opening address at the Regional workshop on pilot projects to develop practical capabilities for analyzing demand for skilled workforce and enhancing TVET delivery in Region VI

By Mr Khalid Hassan, Director, ILO Country Office for the Philippines at the Regional workshop on pilot projects to develop practical capabilities for analyzing demand for skilled workforce and enhancing TVET delivery in Region VI, 11 November 2022, Iloilo, Philippines

Statement | Iloilo, Philippines | 11 November 2022
  • Secretary Danilo Cruz, TESDA Director-General;
  • Mr Lloyd Cameron, British Embassy - Manila, Economic and Climate Counsellor;
  • Mr Erel Evalle Lim, Chief Employment Promotion and Workers Welfare, DOLE Region 6
  • Ms Arlene Bagoning, PSA Region 6
  • Regional Director Jerry Tizon and officials at TESDA Region 6;
  • Partners from industry and tech-voc institutions in the region;
  • Ladies and gentlemen, good morning!
The ILO appreciates everyone’s presence and the Technical Education and Skills Development Authority (TESDA) strong partnership in enhancing the system to improve employability. We value everyone’s commitment to improve labour market information and use it to develop responsive policies amid changing skills demand.

ILO sees this on-going partnership as very relevant to the administration’s eight-point socio-economic agenda, especially in formulating policies to achieve its “jobs agenda” or “creating more jobs, creating quality jobs, and creating green jobs.”

This agenda complements the Decent Work Country Programme of the Philippines and the ILO’s Global Call to Action for an inclusive, sustainable and resilient human-centred recovery from COVID-19.

This “jobs agenda” highlights the significance of a mechanism that provides detailed labour market information on in-demand skills.

This mechanism should complement industry or business stakeholders’ consultations and maximize Labour Force Survey (LFS) data availability in the country.

Since March 2021, ILO through the UK-funded Skills for Prosperity Programme and TESDA have been working with international and national experts to analyze major statistical surveys in the Philippines, identify the LMI to be used, process and interpret, provide introductory training to TVET staff primarily in the pilot regions of 6, 7 and 8.

Today’s presentation will include findings, challenges, lessons and recommendations for enhancing TVET and LMI systems in Region 6.

Using a method developed by our international experts, we examined 2019 and 2020 LFS data to analyze demand and, partially supply of skilled labour. In this workshop, our experts will share indicative results and recommendations for Region 6.

Today’s discussions may be complex, causing some apprehensions on use of analytical methods.

Let me assure you that initial presentations on the pilot results, such as in Region 7, have generated a lot of interest among stakeholders and a realization that the country’s advanced statistical system allows for more detailed analysis of demand for and supply of skilled workforce tailored to the TVET system’s needs.

Our partnership with TESDA supports the method’s applicability to area-based training delivery. For instance, TESDA Region 6 may combine qualitative industry stakeholders’ consultations with LMI-based data for establishing regional skills priorities.

We understand that using the LMI-based method at the regional level has certain constraints, which are addressed in the recommendations for enhancing the country’s statistical system.

The pilots helped us improve the system and determine areas for TESDA, DOLE, DTI and industry stakeholders’ capacity building in the regions.

We urge everyone to share insights and future perspectives so we can enhance the analytic system together.

As we do so, note that the Philippines is in a good position to use analytical methods given its relatively advanced labour market information and complementary systems for collecting data from the Public Employment Service Offices (PESOs), tech-voc and higher education institutions, and even from big data collected from public and private job sites.

Maraming salamat po (Thank you very much)!