Data demonstrates the enabler to the future current and future employment by providing a catalog that decision-makers can use to fix the constraints within the workforce.

“We need to find new ways to collect data and use non-traditional sources like mobile phones,” Andreas Schaal, Director of Global Relations, OECD, adding that it is important to ensure that there is a middle way in terms of sharing data.

“We need to make sure that the data we are collecting combines accuracy, reliability, and consistency, this can be difficult,” Schaal explains during a panel discussion on data-driven approaches to the labour market during the World Government Summit held in Dubai.

The ability to use data in understanding employment helps create a variety of streams within the workforce. The national labour force data, company data, and industry-wide data should demonstrate patterns and business ownership and employer-worker by sector, gender, age, and nationalities at current and future levels based on economic trends. 

“How to harness this [data] is a challenge,” said Rafael de Medina Director and Chief Statistician, Department of Statistics, International Labor Organisation. 

Data can help recruiters and decision-makers forecast, anticipate future skills, and measure the efficiency of workers such as digital workers. By understanding the data, recruiters can understand the variety of skills and understand the mobility of labor within the market.

Data statisticians have been addressing issues with getting good quality non-biased data that can help decision-makers take the right steps. 

“We have this wealth but we have to be cautious about how to have strong governance at the country level,” explains de Medina who added that it is vital to have clear definitions and guidance to harness the quality of data. 

For example, there are challenges between gender equality and rights, “This can be from some something as basic as lack of consciousness, lack of conception on gender equality and women’s rights which then translates into the lack of understanding of the significance of the sex-segregated data,” said Jean D’cunha, Senior Global Advisor of International Migration, UN Women

Some of the challenges, she explains, include a lack of technical capacity and data collection within the interview process. It can be a simple process of asking men what they think the women’s priorities are. Moreover, there is a lack of coordination between data producers and affected women which affects the quality of data. 

“There are also in many spaces, many constraints, there is limited demographic space and women equalities have sensitivities around them, and so there are constraints to data collection or censoring of data,” D’cunha explains.

According to the panelists, there must be a new approach in terms of adopting data to face these challenges to be able to harness data to produce the right policies. Some of the challenges D’cunha talks about include the lack of knowledge and skills to be able to overcome them.

“Invest in the skills, skills, skills of your people,” said Schaal.