How to evaluate youth employment programmes

But monitoring and evaluating such programmes poses a challenge for many.

SAD Project Manager Katharina Wespi is an expert in the field. In April, she met with other specialists in Turin. On her return, we asked her to talk about common mistakes and about what lessons she could learn herself during these three days of exchange.

You were part of the Taqeem “Community of Practice Peer Learning” event, which took place in Turin in April. What was the primary aim of the workshop and who was it aimed at?

The workshop brought together experts in evaluation practices and organizations active in youth employment in the Middle East and North Africa. The objective was to create a space to share knowledge: the experts provided technical assistance to the practice-oriented organizations. Together, they developed concrete steps to improve the evaluation of youth employment programmes. Among the experts, the workshop was also a good opportunity to share experiences.

What was your role?

I worked with a Jordanian governmental organization which is responsible for the evaluation of all youth employment programmes that are implemented in the country. I provided them with tools and ideas to further improve their evaluation practices. Apart from that, I presented on questions of data collection and corresponding tools, both qualitative and quantitative ones. I focused on problems that occur in the area of youth employment in particular.

…for example?

Well, the first problem concerns data collection. One way to facilitate primary data collection is the use of information and communication technologies such as mobile phones or e-mail. These technologies allow us to reduce the costs of data collection. But: very often, people just don’t respond to surveys they receive by e-mail.

Another source of errors is the formulation of the questions. To cite just one example: the question “Do you work?” seems to be a simple one. But our experience shows that the meaning of «to work» is not obvious. We see a lot of programme participants who say they don’t but indicate having a regular income. This inconsistency can be explained by the fact that people who carry out a job that does not correspond to their education level, for example the university graduate who works in a grocery store, do not consider this work a “real job”. That’s why we must be very careful when formulating standardized questions for quantitative analyses.

Looking back at these three days of exchange, what are the most important lessons you have learned?

I suppose having a chance to share experiences with other experts in the field was one of the most important aspects for me. Besides that, I was able to benefit from information on new tools, platforms and apps for managing data – thanks to a colleague who introduced us to new web based tools of data management. And in a sense, it was also good to hear that my colleagues experience the same struggles as me, notably with regards to data quality and data return.