e-Ubelong

An agile data-driven digital platform that fosters economic integration of marginalized and displaced workers.

If all the world's forcefully displaced people were in one country, it would be the 20th largest country in the world. Refugees, the internally displaced and returnees face countless barriers to re-entering local labor markets, from skills mismatch to lack of networks. Of the 63 million forcefully displaced, almost 24 million are refugees, living in another country (UNHCR).

Technological transformation is expected to further increase the pool of marginalized workers in the coming decades. McKinsey (2017) estimates that in the next 12 years, as many as 14% of the global workforce needs to reskill, upskill or adapt to new jobs, due to automation and artificial intelligence (AI) technologies.

Current platforms such as LinkedIn, ZipRecruiter and Monster are ineffective because they do not account for the specific needs and challenges of displaced and marginalized workers. Marginalized workers have incomplete skillsets, relatively short work histories, and lack of access to information or financing for upskilling. Their chances of finding stable long-term employment through these existing platforms are virtually nonexistent.

We believe that technology should not be a threat to workers, as it has the potential to create economic opportunities and facilitate labor market integration. The e-Ubelong platform uses an algorithm to match skills of marginally displaced workers with skill gaps in the local labor market to provide feasible employment opportunities. The platform also connects the workers to training paths and financing options for upskilling, reskilling and retraining to support their long term labor market integration.

Our solution aims to reduce the inefficiencies in the allocation of refugee and displaced labor by employing cutting edge technologies.

The e-Ubelong platform has 4 integral components:

1. Skill identification: measure skill availability of marginalized workers and the demand (need) for skills in local labor markets.

2. Training: personalized pathways for intensive training (incubator style, on-the-job training, online coursers etc.), partnerships with local language and vocational schools in the host communities etc.    

3. Placement: skills-gap assessment and preference-need matching algorithm.

4. Financing: seed-funding, financial planning, and long term financial sustainability (i.e. timeline and interest structure for paying back initial funding, insurance mechanism etc.).

e-Ubelong will empower marginalized and displaced workers to become future-proof by enabling them to break down employment barriers, providing them access to tools for continuously upgrading their skills, and forging partnerships that will guarantee a secure gateway for labor market re-integration.  

e-Ubelong builds on advanced technologies to provide an integrated, smart, and sustainable process specifically targeting the needs and challenges of marginalized workers. Our platform equips displaced workers with the right information, tools and network to obtain the necessary training and experience in order to secure stable long-term employment. 

We will be deploying adaptive cutting edge developments in data analytics/science, optimal algorithmic matching, cloud computing, and blockchain technology combined with professional mentorship to design a customized learning and employment path for each worker. 

Our digital platform will leverage data analytics and machine learning algorithms to create a skills repository, assess the skill gap in local labor markets, and provide an optimal employment match. By employing these latest technological advancements we will increase access to information and opportunities, improve accuracy and understanding of skill gaps in real time, and account for complicated factors as well as inputs to provide practical options for our beneficiaries.

Our solution's goals over the next 12 months include:

• Identify and establish connections beyond the pilot group of beneficiaries (30 refugee women in Baltimore) to reach a goal of 15,000 beneficiaries 
• Complete skill gap and mismatch assessment in the Maryland area and map the need for skills by industry and location
• Forge 15 additional corporate and public partnerships for job training and placement 
• Prototype a working version of the matching algorithm and digital platform
• Compile a comprehensive feasibility analysis and well-developed business plan for the next 2-5 years

Over the next three to five years we aim to:

1. Achieve a sustainable financing model for our solution

2. Expand beneficiaries beyond refugee women to include all marginalized workers in high-unemployment states in the US (including Mississippi, Georgia, Nevada, Michigan)

3. Expand the base of our corporate and public partnerships for financing, training, and employment 

4. Start piloting in other locations in the United States, Canada, Germany, and Jordan

Our beneficiaries will access the platform though a user-friendly web interface and mobile application available in multiple languages. We will leverage our existing community partnerships to engage in extensive A/B testing for the design of the platform and application. Our pilot group of beneficiaries will fully engage in providing input on developing targeted incentives for recruiting and retaining users.We will personally work with the initial beneficiaries to build success stories and enable them to mentor future beneficiaries. Additional features of the solution and incentives to increase the retention rate will be developed through design thinking, user interface and experience processes.

We are conducting direct interviews with 30 refugee women who are currently looking for employment or are in temporary employment situations, such as seasonal workers and replacement workers for full-time personnel (i.e. due to maternity or sick leave) in the state of Maryland in the US. These women were accessed through a partnership with the International Rescue Committee (IRC) and we interview them at 3-month intervals (total 12 months) to qualitatively monitor their difficulties and skills-mismatch in accessing more favorable employment conditions. Our solution will assist them in pre-identifying the skills needed to identify and retain longer term employment.

In the next 12 months we expect to serve approximately 7,000 women refugees living in the DMV area who are either in temporary employment or unemployed (of a total 50,000 registered refugees). e-Ubelong will connect them to training (certification programs, online and in-person training, on-the-job training etc.), and employment opportunities they would not otherwise be able to attain because they have incomplete skillset, short work history, and are unable to find suitable options though existing platforms (LinkedIn, ZipRecruiter, Monster etc.). We expect to observe initial results and impact within the first year of registering user data and deploying the platform.

Daniela has 4 years of experience as an empirical analyst and consultant in international economics and policy making. Her background includes mathematical and economic modeling, econometric techniques, machine learning, and experimental research design.

Lina has 3 years of experience helping integrate refugees though private sector solutions, including employment and education. She launched dafero to understand the unique needs startups have in integrating refugees into their business models.

Juna has over 3 years of experience developing data-driven products such as data dissemination platforms for policy analysis. She is skilled in full-stack development, machine learning, data wrangling, data visualization, and empirical analysis.

Our revenue model is a subscription-based recurring revenue strategy. We will provide access to the platform and our services based on a pre-determined periodic cost. The burden-sharing cost structure will be designed not to impose additional financial barriers to beneficiaries by subsidizing subscription fees leveraging alternate partner funding.

We aim to establish an additional Public Private Partnership (PPP) between corporate partners (SMEs and MNCs), government agencies (Department of Labor, local Chambers of Commerce), foundations and NGOs. Corporations will contribute to the program on a sliding scale based on revenue share. Other partners will contribute by providing supply-side input data and subsidizing subscriptions to the platform.This setup will enable us to achieve financial sustainability in the long run.

We expect an initial need of $250,000 for the costs for the first 12 months to pay for researchers to conduct in-person qualitative interviews with the subjects, software engineers to develop the platform and algorithm, and deploying a working version of e-Ubelong.

The Solve platform can guide us - through partnership and mentoring opportunities - in developing a dynamic business strategy. This would support scaling our solution throughout the United States, and subsequent target countries which will initially focus on major refugee-hosting hubs (Germany, Jordan, and Ethiopia). Solve can support e-Ubelong by:

1) Providing mentorship and forge new partnerships (corporate, public, community etc.)

2) Supporting with financing the development and deployment of the platform

3) Guiding the development of a smart, sustainable and dynamic solution for our beneficiaries

4) Suppling consulting expertise and advise in identifying and testing barriers for upscaling 

Solve can help address the following barriers:

1)  Connecting to technical experts and engineers to help design and prototype a working version of our platform

2) Securing seed funding to finance the prototyping of the platform

3) Designing incentives for the initial wave of beneficiaries, both refugee women and participating SMEs, for investing their scarce time and resources to help develop an effective solution

4) Providing a network of experts, startups, and partnerships which have experienced similar scaling barriers to aid us in scaling up in the US and internationally