Shortlist

The Problem

Kenya’s workforce has yet to benefit from the growth of the digital economy and catch up with the growing labour demand in cloud computing, artificial intelligence, and the Internet of Things. Despite employers’ clear interest in hiring Kenyans to conduct cloud-based work, there is a lack of trained people and market linkages that connect youth with jobs. Many Kenyan youths could engage in cloud work today; however, they lack the necessary training to equip them with the right skills and access the opportunities in the digital job market. There are significant challenges on both the demand and labour side that hold youth back from participating in the digital workforce. Additionally, many youth cannot access these jobs because they do not have a device on which to perform their work. This systemic bottleneck is the single greatest barrier to further scale of the sector.

Moreover, female job seekers in Kenya face especially severe challenges in finding work that matches their skill-sets and potential and pays them equitably. Historically, the job matching process has favoured male applicants, from the user interface that candidates experience to the wording used in the application questions and the signals recruitment teams give employers.

The Solution

Shortlist’s initial project design addresses the structural bottlenecks that have prevented the industry from unlocking its growth potential so far and requires a consortium approach to address both the labour infrastructure and talent pool gaps that currently limit job creation. The consortium will tackle these complex challenges through sourcing talent, training candidates, and matching and placing candidates. The validated demand by employers underpins Shortlist’s proposed approach.

As a result of initial market traction, Shortlist is scaling up this project to create an additional 3,500 jobs, on top of their initial target of 5,000 jobs. This scale up builds on the strengths of the existing work while introducing a new focus on scalable and sustainable approaches to address key labour infrastructure gaps.

In addition to maintaining the operating model of our existing project withy CFYE, Shortlist is adding three layers of innovation to increase job creation at the county level:

• Partnering with corporates (including Microsoft) to provide access to digital skills training to youth jobseekers to support career growth. We will also partner with county-level governments to help provide appropriate physical locations in which young people can access the internet and conduct cloud work.
• Adding additional employer partners to our consortium with strong existing  demand to create jobs. We will prioritise employers that have a mission to hire female youths in rural locations.
• Increasing the scale of our device financing facility to provide high quality, low-cost devices to more cloud workers who can’t afford a basic laptop or smartphone. Without steady and consistent supply of devices to perform work, youth (in particular rural and female Kenyan youths) will be unable to access these jobs due to the lack of this necessary productive asset.

A significant part of Shortlist’s objective is to encourage more women applicants and eliminate gender biases in the job matching process through gender-sensitive practices.

Additionality 

The support by CFYE will provide immediate and catalytic impacts on our ability to achieve this program’s objectives. CFYE’s increased grant support unlocks the key infrastructure necessary to find, equip, and place youths into these jobs. It allows us to build an innovative financing facility needed to enable another 3,000 youth to afford a device required to conduct cloud work remotely.

CFYE’s technical assistance will help bring best practices from around the world to develop meaningful and lasting partnerships with local governments and improve the way we monitor and evaluate results. It will also support our consortium to take feedback more effectively from youth in Kenya and around the world to adapt our implementation tactics based on ground-level inputs.