ConHector: A community of opportunities for youth employment

Unemployment rate in Colombia at 13%, one of the highest in Latin America. Even worse so in urban areas, for young people, women and those with low-literacy rates. The young population makes up add up to 30% of  the working-age population, however low proficiency levels, education and skills along with barriers to access the labor market limits the opportunities of this population to improve their living conditions. Approximately 21% of young people (2,600,000) are “Ninis”, people who neither study nor work. We propose using ConHector as a virtual assistant that connects youth population seeking for jobs with employers and training through practical guidance tools, while leading to job insertion. Our strong data science approach gleans insights from structured and unstructured data providing valuable feedback and analysis to employers of the youngsters participating in the program and relevant stakeholder behaviour.

Unemployment rate in Colombia is 13%, and it's particularly worse in urban areas, and amongst young people, women, and people with low educational levels. Approximately 21% of young people (2,600,000) are NEET ( young people who neither study or work) and, “therefore, remain exposed to risks and are excluded from the country's social and economic progress, with the aggravating circumstance that 71 % of them are women and 85.9% of them are also poor and vulnerable”.

The vast majority of NEET are looking for jobs and/or are working in the un-paid sector (e.g. housework). They would like to work, but they are unaware of job opportunities, or, lack the skill set and training demanded by companies and/or the labour market. Even though technology can facilitate access to employment and training information it might be challenging to access it. On the other hand, there's a high mismatch of the skills available and those required by employees.

The increasing access to smartphones and strong adoption of WhatsApp, motivated us to use these instruments to provide the vulnerable and young crowds, a clear and curated job and training information opportunities catering to their needs.

We are serving youth population in the ages of 18 - 28 years who live in poverty, extreme poverty and vulnerability. They lack opportunities and are considered NEET. Fundacion Capital has already worked with vulnerable youth. In each initiative that we design and implement, we engage in a co-design process leading to a collaborative solution. We receive constant feedback during the design and implementation phases. In this way we are sure that the messages, information and counselling are fully understood. We engage with them in this process through focus groups and permanent observatories (permanent groups formed by project beneficiaries that provide constant  feedback throughout the process). On the other hand, because virtual assistance has machine learning, we are able to cater and personalize the interactions constantly learning and adapting.

The data analysis of these interactions, allow us to engage in dialogue with the private companies in order to understand their needs, requirements and to close the gap between potential employers and employees.

ConHector is a virtual assistant that informs youth about job and training opportunities that cater to their specific skills and characteristics, supporting them to access new opportunities. Additionally, it provides counseling and guidance for job insertion. ConHector is part of a broader intervention that builds the skills youth need to enter the job market with a strong data science approach to glean insights from structured and unstructured data to provide valuable feedback and analysis to employers, the youngsters participating in the program and other stakeholders.

How does it work? 

• ConHector creates a Community of Opportunities through the identification of allies that offer job placement programs or services for young people

• After profiling the users and, through data analysis, ConHector knows their job and training needs according to their skills and characteristics.

• Using non-industrialized machine learning models, ConHector makes personalized recommendations to users about job and training opportunities,  according to their skills, characteristics (e.g. age, sex, etc.) and geographical location.

• Through clear and relevant information, young people can make decisions about the job and training opportunities  available in their territories that they consider most relevant and apply to them. 

• Through coaches or local leaders, ConHector builds a network of users.

• ConHector monitors in real time the acceptance and access of users to the programs or services offered in order to accompany them throughout the process to access those opportunities.

• ConHector uses machine learning to glean insights from structured and unstructured data to provide valuable feedback and analysis to employers, the youngsters participating in the program and other stakeholders (including policy analysts and implementers)

• With data analysis it can provide advice on innovative ways to do policy design and practice while enhancing public value specifically on youth employment. 

Through the interaction with youth, the system will continuously capture data, which will enable us to continuously learn about the characteristics and needs of youth, allowing us to profile better, personalize, and improve the services. Potential employers can also learn about youth and strengthen their recruitment services. The more youth are using ConHector, the stronger the digital system will be, leading to a better service that will support youth in cost-effectively accessing the labor market.

ConHector can connect entrepreneurs with millions of job seekers around Latin America and narrow the gaps in poverty and inequality.

The innovation provided by ConHector is related to a new application of existing technology to tackle youth unemployment, strengthening the employment ecosystem with a much more precise data science approach. 

The solution is effective for the youth because:

• The information and services provided are accessible when and where youth needs them.

• It is relevant: Information and services offered respond to the specific characteristics and needs of the youth.

• Recommendations and engagements with the youth become smarter by adapting to their evolving needs (in their specific contexts and specific moment in life) 

• Reduce cost of service: Eliminate middlemen to directly connect providers of services to the end citizen through a platform at a fraction of today’s cost.

• Scalable: A process, network and software that grows in order to manage an increased demand, adaptable to the changing needs or demands of its users and/or clients in different contexts.

• Informs youth through WhatsApp about the opportunities available for them and how to access them. This virtual coach is complemented by an in-person support service that provides additional guidance when needed.

Key differentiators:

• Fast response

• High-Tech solution

• Optimized Services

• Customer-focused and computer coordinated

• The best end-user experiences

• Statistically optimized response

• Profitable by design

• Location-based goods and services

Our theory of change is as follows:

Activities

1. ConHector is fed with job market information (contacts employers and identifies opportunities.) 

2. Information is gathered from youth that are reinforcing their skills for the job market.

3. ConHector combines the information about employers and job seekers  and starts sending bespoke information to young beneficiaries (opportunities that suit their characteristics).

4. ConHector provides specific guidance to each young person to support their recruitment process

5. ConHector analyses data and provides specific guidance to employers in recruitment strategies. 

6. ConHector analyses data and provides personalized guidance to help job retention. 

Outputs

1. Youth learns about opportunities available for them,  to their skills and needs.

2. Youth gain confidence and knowledge in order to prepare and submit their CVs and prepare for interviews and recruitments process

3. Youth learn about training opportunities in topics required by the industry.

4. Increased job retention of youngsters

5. The companies increase their recruitment efficiency and job retention. 

6. Specific public policy recommendations to increase youth employment and job retention. 

7. Another regarding data analysis and management for public policy recommendations.

Short term outcomes

1. Young people  acquire skills required by the industry

2. Young people accesses jobs

3. Employers are able to find the talent required.

4.Employers receive valuable inputs to refine their job selection processes. 

5. Job retention is improved .

Long term outcomes

Improved physical and psychological well-being of youth while  strengthening and improving. the country’s employability ecosystem.

1. ConHector was tested with 300 families in rural and urban settings in Colombia, and was able to help people through personalised suggestions for them to get products and services to improve their life conditions, find accurate information about public services,  as well as emotional support. ConHector encourages its users to make their own decisions bringing them orientation and resolving questions through chat-bot interactions and data analysis.

2. We expect to improve at least 100 employer’s recruitment processes and job retention capacity.

3. If funding is available, we expect to reach at least 1,000,000 youth in the Americas.

We expect to customize ConHector to the needs of young people seeking jobs and economic opportunities while enhancing the country’s employability ecosystem. Next year we expect to launch a pilot with 1,000 youth. Then, we will start scaling up ConHector in Colombia, and then, in at least 5 countries in Latin America or countries where we have been already working such as Mozambique where we have existing networks and in-country experience. We expect to reach at least 1 million people in these countries, if the funding is available. 

If the necessary funding is available, ConHector can be customized to attend the needs of migrants and the poorest citizens looking for jobs, who have difficulty adapting into a new culture and social /economic context. ConHector can connect these population  with jobs and economic opportunities available for them, and support the integration of these people to the country.

The main barrier is to be able to access enough funding to scale up. At the beginning, ConHector needs to be funded by donors before it becomes self-sustainable and its service can be sold to beneficiaries, companies or governments who can pay for the placement of people in jobs.

We will continue looking for funding with international donors. Fundación Capital has already received funding from a large network of donors including the Ford Foundation, the International Fund for Agriculture Development (IFAD), the Citi Foundation, Co-Impact among others. Once the pilot yields results from the evaluations, it is possible to make a business case to some donors. In the future, once ConHector is strong given the data analysis of its scale up, it is possible to establish a business plan and it could be possible that companies and/or  young people pay once the job placement has been successful.

On the other hand, we have received several international awards such as the Skoll Award of Social Entrepreneurship, the Schwab Award of Social Entrepreneur, Ashoka and other international recognitions that place us in an strategic place in order to extend our network through potential partnerships with other stakeholders.

In the framework of the current global crisis generated by Covid-19 we have prioritized the use of the digital tools previously developed, as well as our capabilities in financial inclusion and economic education to provide accurate information and assistance to the population more vulnerable to this crisis. We activated our virtual assistant ConHector to continue promoting economic citizenship and deal with the issue of financial health, which due to the recession will be a pressing issue for thousands of families living in poverty in Latin America. ConHector will also provide official information on the subject of the pandemic, practical health and psychological advice, and relevant information at the local level. ConHector connects with the vulnerable population at the base of the pyramid in rural and urban areas with whom we have worked for many years. During the first phase, we are attending 2,800 families in Colombia, but we expect to continue serving more families in Colombia and Latin America in order to reach more than 250,000 users from Spanish-speaking countries.

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Our solution is part of the  Economic Citizenship as a Service (ECaaS) Unit at Fundación Capital. Fundación Capital is an international development organization that improves the economic and financial lives of people living in poverty around the world, combining different technological tools to design and implement effective social initiatives. For more than ten years, at Fundación Capital we have been promoting economic citizenship globally and at scale.

For more than ten years we have collaborated with governments and the private sector to design and offer solutions that increase the economic prospects of millions. Throughout these years we have impacted the lives of more than 6 million people: women, youth, migrants, refugees and vulnerable populations in rural and urban settings in more than 18 countries.

For our work, we have obtained the most important recognitions in the world for social entrepreneurship: Skoll Award for Social Entrepreneurship, Schwab Foundation’s Social Entrepreneur of the Year Award, USAID’s Million Lives Club, Ashoka Senior Fellowship and Katerva Award.

Full-time: 4 people

Part-time: 6 people

Contractors: 2 suppliers

At Fundación Capital we are an interdisciplinary team where social innovators work together with tech experts who are active listeners, focused on problem-solving and absolutely committed to the people that use our digital solutions. We combine more than 10 years working with those living in poverty as well as managing software projects to advance economic citizenship and boosting the local economy. 

• Tatiana Rincón - Vice President Livelihoods. In charge of integrating the digital solution with the social problematic of unemployed youth. Brings the experience in working with the population we are expecting to serve. 
• Rodrigo de Reyes - Director of the Digital Research and Development Department Director. In charge of digital solution design and strategic addressing.
• Carolina Duarte - Product Manager. Responsible of digital solution co-design and operations.
• Abraham Morales - Senior Tech Consultant. Facilitate processes for product design and development (UX, UI, scalability, reliability).
• Santiago Ruge – Quantitative Research Specialist. Data modeling and analysis.

At the moment we are working with Fundacion Carvajal, a recognized non for profit organization located in Colombia, with whom  we are identifying the gaps on employment process for people, and gathering data for knowing better the users, their behaviors and skills that must be enforcement or develop, and thus provide a more human-centered design solution.

As an organization we work along with local and international stakeholders all over the world. Some of the most important networks that we are part of are Catalyst 2030 (A Global Movement of Social Change Innovators; Schwab Schwab Foundation for Social Entrepreneurship, Skoll awardees, amongst many others. 

Some of the key stakeholders we work with are: MasterCard, BDO (Banco de las Oportunidades), GIZ, Universidad del Rosario.Some of the key stakeholders we work with are: MasterCard, BDO (Banco de las Oportunidades), GIZ, Universidad del Rosario.

The business model for our solution is as follows:

Government (National and Local): the benefit for this stakeholder is improving efficiency of social programs that target vulnerable youth. The source of income is a fee per user that was able to obtain a job.

Local private sector: the benefits for this stakeholder is increasing their job retention and improving their employment recruitment systems. The source of income is a fee per successful job placement and potentially increasing job retention rate.  

Users: the benefits for this stakeholder are learning about economic opportunities available for them, access to information, goods and services that impact their quality of life and increase their chances at ending the cycle of poverty. The source of income is a fee per successful intermediation (user able to access a job).

Social publicity (curated): the benefits for this stakeholder are social publicity by governments, local agencies, corporate social responsibility units, multilateral and bilateral organizations, NGOs and philanthropists. The source of income is a fee per bundle of publicity that reaches the user.

We are planning to seek sustained donations and grants from existing and potential partners. This is necessary to pilot the approach given that the concept and a first prototype has been developed, but it is necessary to customize ConHector for the youth, conduct evaluations, and  based on that, build a robust expansion and business plan built on stronger evidence. 

We see a lot of potential. A user fee for successful intermediation can be charged to the beneficiaries, also, and mainly a fee to the companies per successful job placement and increasing job retention rates. Last but not least, governments have social programs that seek the enhancement of economic opportunities for the youth. ConHector can be integrated in such programs and the government can pay for the services.

The funding, but especially, the mentorship to enhance and improve the digital solution are key for our work. Most importantly, the media opportunities will be key to connect with other donors that enabling us to scale up the solution and most importantly, access a broader network of potential allies.

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We would like to work with Data Kind for improving algorithms´s design.