Pakistan does not effectively connect blue-collar job seekers and blue-collar job providers 

 

In 2017 3 out 10 Pakistanis were classified as ‘youth’ (15 – 29 years of age), and the country will remain ‘young’ for the coming three decades1 . World Bank data categorizes Pakistan as a substantially underemployed country; almost 3.5 million working age individuals are currently unemployed across the country (5.9% unemployment rate) with a further 4 million youth attaining working age every year . This presents great opportunities for economic progress if the potential of our young working population is harnessed and put to use wisely. 

 

Of the unemployed population in Pakistan, a substantially high percentage have received work experience or training in vocational trades, and can be broadly classified as being ‘blue-collar’. There are numerous hurdles that a job aspirant in the blue-collar market faces while searching for a suitable work opportunity. Additionally, employers face severe challenges in sourcing the ‘right’ employee for a vacant position. Since there is no formal platform where these jobs can be advertised, and no data repository to which all workers have access, the information about these work opportunities is often only available through word of mouth. While services like Rozee and BrightSpyre have been able to use these advancements to facilitate employment in the white-collar sector, technological advancements have not yet had a substantial impact on employment in the blue-collar sector. 

 

This lack of connectivity offers a unique opportunity for us to provide the market with a sustainable and evolving employment ecosystem where blue-collar workers can be connected to relevant employers effectively and viceversa. 

 

Kamayi will offer connectivity in bulk and intelligent usage capabilities to the blue-collar sector 

 

In order to bridge this gap in the market and effectively exploit this opportunity, Kamayi was created. It aims to be the largest database of blue-collar jobs for job seekers, as well as the largest marketplace of potential blue-collar jobseekers looking for relevant work opportunities. By applying advanced algorithms to this data, we will be able to provide optimized matching and create an online marketplace where candidates are recommended their ‘ideal job opportunities’ and employers are recommended their ‘ideal candidates’. Furthermore, by connecting these two types of users with employment solution providers (transport linkages, accommodation linkages, benefits linkages), we can overcome employment barriers in a cost-efficient manner and incentivize individuals to actively pursue employment. Our primary targets are to:

 

 1. provide a platform for employees to be informed about job opportunities relevant to them;

 2. provide a platform for employers to post jobs and source candidates relevant to them;

 3. provide solutions to overcome barriers in the employment process 

 

By using a blended approach of tech and human resource (‘placement’ and ‘call-centre’ teams), we aim to facilitate positive employment outcomes. Keeping the portal registration and onboarding process simple will encourage individuals to become part of our database, and ease of user experience and process will encourage individuals to be retained as users. This will be particularly tailored to users with low levels of smartphone literacy.

 

Using a web-based portal and a mobile app, for both employers and employees to use, our team intends to enable working-age individuals to search and apply for employment opportunities with ease, and for employers to post vacancies with a single click. The job-matching process would source best-fit jobs for candidates (and candidates for jobs) using the following four factors: 

 

1. Geographical Proximity - The distance between a potential candidate and an available vacancy, 

2. Skill Category Preference - The relevance of the candidates existing skill-set to the requirements of the available vacancy, 

3. Education & Qualifications - The relevance of the candidates existing educational/vocational training level to the requirements of the available vacancy, and 

4. Work Preferences - The working conditions preferred by the candidate (timing, industry preferences, salary requirements, benefits requirement) and how they match with the available vacancy.