1887

Big Data Intelligence on Skills Demand and Training in Umbria

image of Big Data Intelligence on Skills Demand and Training in Umbria

The COVID-19 pandemic had a severe impact on the Umbrian economy, and despite recovery of labour demand, the region faces challenges related to digitalisation, tight labour markets, and volatile demand for low-skilled jobs. To address these issues, the OECD and the Umbrian regional agency for active labour market policies (ARPAL) have collaborated to investigate the labour and skills demand of the region using big data techniques applied to online job postings. This report provides new insights into the alignment between labour and skills demand and the training options available in the training and education programmes contained in the Umbrian Regional Training Catalogue. This report builds new indicators to measure the alignment of course content with employer demands in Umbria, with results showing that alignment is relatively good for some occupations but that this can be strengthened to provide job seekers with up-to-date training options that match the demand of the labour market.

English

The Regional Training Catalogue and its supply of training: A descriptive analysis

This chapter offers an overview of the courses provided in the Regional Training Catalogue (RTC) by the Umbrian regional agency for active labour policies (ARPAL). The analysis shows for which occupations training is available, and the corresponding number of training hours. Furthermore, leveraging Natural Language Processing (NLP) techniques, the chapter utilises algorithms and computational models to process and analyse the content of the courses described in the RTC in order to identify the skills that are provided in the training options available therein. Additionally, the chapter presents information on the cost, duration and class-sizes for the courses listed in the RTC, also highlighting the differences between the provinces of Perugia and Terni.

English

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error