Unemployment Zero

Bring the power of data literacy to the hands of young unemployed adults, by providing easy to access and curated materials that are aligned with in-demand jobs/careers. Our systems starts by understanding personal needs and desires and crafts a personalised curriculum to get to the desired outcome. With the right pathway created, our AI engine will tutor students to meet their goals. Our offer helps students starting at the right level, study the right materials, avoiding wasting time on non-relevant subjects. The alignment with in-demand jobs guarantees a fit between invested time in studying and increasing the likelihood of finding a better/new job.

By scaling this solution globally - for which there is this need in different countries - we can start shaping the culture and the decision-making process of the corporate world, leading to a sustainable education process of literacy - until we reach a global acceptable level. 

We are facing unprecedented unemployment in young adults, regardless of their education. Portugal (our community), young unemployment rate is 19.3%, Greece (36.1%), Spain (30.6%) and Italy (29.3%). Being young adults the workforce of tomorrow, the way we solve this problem today will inevitably impact the corporate culture and leadership in the future. There are plenty of factors for this problem: misfit between supply and demand in higher education degrees; some are students & workers at the same time. But one of the main root causes we found is that these individuals are missing the basic knowledge of data literacy. 

Considering that data is the new universal language, most of the world IS NOT able to read, write or understand data (basic illiteracy!). Providing Data Literacy will not only empower to solve a short term unemployment problem but it will also ensure that tomorrow's workforce will be equipped with this - saving billions of dollars to companies (e.g Australia estimates to lose $13.9 Billions every year on not having data literacy). 

With this, we are making sure our young adults will grow as educated and literate people, that will understand and use data in a more ethical and responsible manner. 

Our solution is a technological platform that builds a tailor-made educational pathway on data literacy, based on the student's desired outcomes, having into account in-demand job opportunities and trends. With a scalable approach to the unemployment problem, we can focus on bringing companies and individuals together, matching their profiles and needs.

Example: An unemployed with a business background can get an education might focus common pitfall of the decision making process, how to show proper visualizations, etc. After the process, his badge will recommend him for a Business Analyst position and suggest what opportunities are out there and how to apply for them. 

All this process occurs in a gamified process organized by levels and point system, where students can level up and "master the game" - reaching their goals. Different students are allocated to different levels, depending on their initial assessment. To keep our audience engaged, we are promoting healthy competitions amongst peers.

We use Machine Learning (Natural Language Processing) to understand how to create the best pathway for each student and a Classification system to help us determine if the student is ready to level up or not. 

Our solution serves the young adults that are currently unemployed as well as the companies and future co-workers that will benefit from the culture these young workers will bring.

Unemployment has multiple dimensions: we have different educational level, based cities, experience, mobility conditions, etc. We are focus on Lisbon unemployment and Lisbon startups and small and medium companies to host these individuals after training. 

Our focus is to understand their needs to build a tailor-made solution. We do this by analysing surveys about their preferences. As we are understanding these individuals needs while developing parts of the technology - under a  Lean Startup Methodology - we have a built in feedback system to provide feedback on content, applicability and overall quality. 

Although it might not be obvious, the main need of an unemployed might not be to get a job, but to get a good job. There's a wrong incentive where people tend to use unemployment benefits simply because ordinary jobs don't pay as much or are not worthy of the troubles of "getting to work" everyday. With this, we must focus on up-skilling and improving the odds of getting a good job or creating their own business.

Finding a good job or being an entrepreneur should be available to everyone that is willing to learn, specially the ones that are currently without a job. 

By understanding these individuals needs and desires, we can build an educational plan that will create the opportunities to have a better job - fulfilling one of the most urgent corporate needs - as well as to spot opportunities with their life experiences and personal pain points to become entrepreneurs. 

We take very seriously the reference in "A World of Three Zeros" book to entrepreneurship being the solution to bring unemployment to zero. 

The existing options to improve Data Literacy (just like courses on Coursera, edX, etc.) are not enough to make the difference among people and have been proved inefficient, mainly caused by the high rates of abandon (on average, 3/4 people abandon without finishing it). The causes for this problem appears because of the typical e-learning approach:

1) "one-size fits all" approach, when every single person has its own needs and existent skills;

2) passive learning methodology (read texts, assists videos and solve exercises), when it is proved that active learning (with group discussions, interaction with peers/mentors, peer-to-peer review, cross-evaluation) is the most efficient method, by increasing retention rates from 30% to 90%;

3) unpleasant and binary (right/wrong) evaluation systems, that most of times create an unnecessary pressure on students and doesn't give room to "learn by trying";

What makes us unique is that we are developing all parts with a holistic view and considering the presented issues. Thus, the innovation in our solution is split into three topics:

1) Curate teaching materials that have to be develop in a way that allows personalisation & learning path definition for an AI agent;

2) The technology that brings this reality to every individual and contains our internal learning system which understands how each students learns and what is the best next step for his/her specific learning path;

3) The innovative methodology with a mix of passive and active learning, a gamified evaluation (including peer review), team/peer projects and group discussions.

We are developing 100% of our technology in the Cloud (using Amazon web services), which gives us unlimited scalability, and using open-source tools (such as Python, React and MongoDB), which allows us to guarantee we have no fixed costs associated to it.

In terms of technological development, the product is splitted into two parts:

- The learning tech platform; and

- The AI algorithm.

The platform allows user interaction and navigation after logging in. While on it, people are able to attend classes, solve exercises, etc. while receiving instantaneous feedback, interact with peers / mentors in group discussions, check their performance, etc. The platform is able to collect real time actions/feedback provided by the user (telemetry). This data is then analyzed by the AI algorithm and suggests the user next steps to improve their Data Literacy.

The AI algorithm is based on graph theory and in two concepts: conceptual and procedural nodes; e.g.: for each course, exists a specific graph split in nodes (equivalent to each concept) that are connected by lines (representing the interdependence between concepts). This graph connected to the Bayes Theorem, which calculates the probability of a user knowing a concept, gives us the ability to diagnose the skills gap to determine his next step. Moreover, while moving to next steps, the user's confidence is continuously measured to create a redundant and important metric for the final decision of the algorithm.

Both parts have been developed from scratch by us.

Here are the references for the main book / papers / studies we have used and based our technology in:

- Graph Theory in Education - https://deepai.org/publication...

- Bayes theorem - https://www.springer.com/gp/bo...

- User Confidence assessment - https://help.area9lyceum.com/w...

The mission we are pursuing is to bring unemployment rates down through the usage of Data Literacy - to change not only individuals' lives and opportunities, but the corporate culture and future workforces. 

The main activity we are doing is teaching and certifying unemployed individuals in Data Literacy. The output we expect is to increase the skill set of these individuals.

The short-term outcome will be the increased likelihood of getting hired and the medium/long-term outcome is the ability to create a young workforce of entrepreneurs and intrapreneurs, able to change corporate culture and entire systems given the leverage they will have of understa. The overall impact is the quality of job each one of these individuals is now able to have as well as the entrepreneurship opportunities.

At this moment, we have already tested our methodologies and technology with about 200 people. Considering that in Portugal we have about 68 thousand unemployed young adults from which 38 thousand have a post-secondary, middle or higher level of education (pre-COVID numbers), our strategy is to tackle 5% of this population in the next year (around 2k people) and teach them the 21st century literacy.

In one year we want double the value we referred to (tackle around 4 thousand people) and start to expand our operations to Spain and Italy (where the unemployment rates are even higher than in Portugal and where the damages caused by COVID-19 were huge).

In these two countries, based on Spain and Italy governmental statistics, we estimate to have around 200 thousand people in the situation we referred to before. Thus, in the next five years, we consider to tackle 15% of that population, which means 20k people.

We know this target is not easy to accomplish, but we want to set our goals high to make sure we work hard every single day of our lives to accomplish it!

Within the next year, our main goal is to create a Pilot in Portugal and to give the opportunity to 2000 people to change in a significant way their careers and life - give this people a good and "with future" job.

For that, we need to create a strong partnership with the Institute for Employment and Vocational Training so we can get access to more people and scale even more the solution in Portugal.

For the next five years (i.e. expansion for Spain and Italy), we consider critical to create partnerships with governmental and education institutions, so we can have access to the highest number of people.

Barriers:

1) Technical: at this moment, we are in the prototype phase, which means we are still building the basis of our technology. Then, it is critical for us to finish it and make the final tests to start "spreading the word";

2) Financial: (i) To keep improving the solution (technically and business speaking), we need to hire developers and business managers so we can increase the speed and influence more people in the shortest amount of time possible; (ii) still on this topic, as part of our revenues comes from the services we are providing to companies, we need to create recurring revenues with some companies / partners;

3) Partnerships: the main barrier is to create strong partnerships with Institutes for Employment and other institutions to have access to our target in the different countries we want to work.

In the topic before we mentioned 4 barriers (1; 2; 3). We think to overcome each one as follows:

1) we have already set a partnership with a tech education school and StartUp Lisboa that will provide us internships to finish in a faster way our platform; regarding the testing phase, the partnerships we have with Católica Lisbon and Nova SBE give us access to a significant number of people that work as benchmark for us;

2) To create partnerships as we mentioned before will increase our workforce in a sustainable way; Apply and win awards (similar to this one) is also important for brand and finance; to create strong business relationships with companies and to implement our product into those companies guarantees us current revenues that will enable us to hire more people to keep improving our solution;

3) Using Startup Lisboa and other partners' networks, we have access to those institutions in Portugal; Surely, with MIT (hoping) we can access and get to those institutions worldwide.

At this moment, we have 3 people at full-time and a contractor to do Sales. 

Our team consists on highly multidisciplinary people, with a common fact: we are all lovers and dedicated and experienced teachers in data skills (from basics, as storytelling with data skills to Programming for Data Science and Advanced Data Science, in top notch universities / institutions in Portugal such as Nova SBE, Rumos, Lisbon Data Science Academy and ELU).

Our experiences in teaching have made the urgency to rethink education entirely clear to us to maximize the joy and results of learning. This common realization of the problem has created a strong motivation to revolutionize Data Literacy learning through technology as we have solved different problems by the means of technology before. As teachers as well as students ourselves, we experienced the difficulties that can arise from a non-personalized learning.

Regarding our background, skills and experience, we have two elements with an engineering background in the top-1 Engineering University in Portugal (Técnico Lisboa) and more than 10 years of experience on R&D, AI algorithms and software development. Moreover, our CEO, with a management & marketing background, is an experienced entrepreneur, who has already successfully launched two startups (including one non-profit for education in Data Science).

In sum, our expertise in starting up, highly valuable data and digital skills, and our personal stake and dedication to rethink education make us the perfect team to revolutionize learning and increase data literacy.

Currently, we have the following groups of partnerships:

- Startup Lisboa (top-1 Portuguese incubator), where we are incubated and receive mentoring and support regarding business development and strategy planning; through them, we also have access to networking activities and a community based on knowledge and sharing;

- Bright Concept, which is a highly experienced company in Digital transformation for companies and with a strong focus on Adults Education; with this partnership we are learning the best practices in Digital Literacy for Adults and get exposure to the target people of our project;  

- Center for Technological Innovation and Entrepreneurship @ Católica Lisbon Business School and Nova School of Business and Economics (the best business schools in Portugal), with whom we have been testing and developing some of the methodologies and activities we have developed on Digital Literacy for Adults.

Our revenue model is composed by two main revenue streams: by selling our product to (i) companies and (ii) to governmental institutes for Employment and Vocational Training (using lower prices) that have access to our beneficiaries. 

We are building a network and a sales team that serves our business model by promoting high rewards on success, with no fix costs. To approach Governmental institutions, we need to create strong partnerships and make them part of the product development. Apart from these two, we are applying for International grants. The main reason for building a business model like this is to lower the price on the end user (unemployed individual) by financing their access through companies, stakeholders on the latter hiring process, and governments, stakeholder with the highest cost with the unemployment problem. 

Regarding the costs structure, our fix costs are covering employers, office rent and development resources, such as Cloud Infrastructure. 

With the value proposition of increasing adult data literacy and up-skilling adults to make sure they have access to well paid and 21st century jobs, our impact measures are: # of beneficiaries helped; and % salaries increases on beneficiaries; # employment after completing the course rate; Average rate on life quality improvement with new job;  

Our key activities are (i) Building learning platform; (ii) Developing learning content for the courses; and (iii) Develop partnerships with stakeholders (Governmental Institutions for Employment and Vocational Training and top universities to develop best teaching/learning practices and metrics); (iv) Teaching and certifying unemployed individuals. 

Our path to financial sustainability comes from the strong revenue streams and reduced cost structure. As explained before, our main revenue streams are (i) sales for companies (at high prices) and (ii) sales for Employment and Vocational training Institutes (at low prices).

We are not looking at a typical Venture Capital investment but one where the stakeholders are also invested in solving the problem. We would hope to create some Social Impact Bond to further advance our mission and bring ownership from the Portuguese State and companies that are stakeholders of the process. 

As we move forward, we hope to shift the focus on B2B and create the right incentives to provide this straight to our customers by reducing the necessary fee through fair funding programs such as debt planing, governmental and company sponsored scholarships. 

Lastly, we are taking applying for some grants and awards given the innovation level of our solution as well as the benefits it can bring to our society. These types of funding are more relevant on the intangible value it brings to create brand value and giving us a good reference on unemployment problem solving and researchers. 

In sum, we create a combination of selling products to companies / governmental institutions, grants and, in the long term, revenues from individuals (with community support).

Applying to Solve has several benefits that are aligned with our strategy. The first and most important is to belong to the Solve's community. We believe in power of communities (we have been working hard to start different ones in Lisbon to solve different problems) as one of the main success drivers. This access is special for the following reasons: 

• Access to peers that are working through similar struggles and barriers 
• Recognition and product validation - having the stamp of a Solve's solver increases our credibility and makes it easier to approach companies and governments to finance the systems for the unemployed population.
• Mentoring from seasoned experts to help us overcome business model difficulties from mixing a social driven mission with a for-profit company. 
• Community to discuss innovative topics such as new ways of financing our business (social impact bonds) to creating new ways of financial sustainability.
• Network of partners to help us scale our global presence and facilitate with connections to companies and governments abroad. 

Specific barriers that we need help with: 

• How to create a sustainable business while building frugal innovation/technology. We are building technology that one of the main goals is to not have a financial entry barrier for the main users - the unemployed - while doing this at a large scale. Creating a sustainable business that allows our company to have man-power and fully focus on improving the system is where we need mentoring. 
• How to scale the scale the solution having a partnership network considering that we targeting Portuguese Government to start solving the problem. In our case, the Portuguese Gov. will help access our local community but to scale we need to start accessing others, and the network becomes hard to expand. 
• Creating a global network of companies that are already investing in Data Literacy at their core and involve them in the solution process. 

• We would like to Partner to MIT for credibility and technology review and feedback. 
• We would like to partner with B Corp organisation - firstly because we truly believe in the certification they are providing and secondly for the already social responsible corporate community already present. 
• Partner and get mentoring from Century Tech - given that they built a similar technological solution and could provide business guidance on how to avoid certain pitfalls they already found.

We are building a solution to provide access to better job opportunities to the unemployed. The skill set we are building is not just a technical one but a cognitive skill set as well! We are also doing this having into account the expectations and outcome desired from the most relevant stakeholder - the student. This guarantees a higher level of engagement, a tailor-made approach to his/her education and a fit to job market demands. 

Because we are focus on cognitive and technical, the skill set we are building is a fundamental piece that can serve as a stepping stone to many other professional fields - a company can choose to give further Analytic training, Sales, Marketing, Administrative, etc. To all of these, the education we are providing will make the barrier to get to this considerably lower while providing a differentiation level from the rest of the competition.

Usage of the GM Prize:

• Dedicate our resources and get more unemployed people through our learning system faster - without the struggle to financially survive, we can get more people onboard to test faster. 
• Hire instructional designers to help us designing a more pleasant experience and expand our network to scale the solution. 
• Invest and open source the gamification process and system that can serve plenty of educational problems (fair evaluation in Schools, lack of engagement in adult learning, etc).

We are based in Lisbon, Portugal and our solution is starting to solve the unemployed problems of the Lisbon community. As one can read in the application, we are tackling this problem precisely by educating people on basic literacy - in our case, Data Literacy. The importance of Data Literacy is not only relevant for today, considering the amount of job opportunities and money wasted by companies on the lack of this skill, but for tomorrow as the amount of data and data-driven decisions is only going upwards. 

By equipping our workforce with this we are providing them access to better jobs, giving them the capacity to go and solve some of the most relevant problems that our society is facing today - via entrepreneurship or intrepreneurship.

Usage of the Gulbenkian Award:

• Dedicate our resources and get more unemployed people through our learning system faster - without the struggle to financially survive, we can get more people onboard to test faster. 
• Hire instructional designers to help us designing a more pleasant experience and expand our network to scale the solution. 
• Invest and open source the gamification process and system that can serve plenty of educational problems (fair evaluation in Schools, lack of engagement in adult learning, etc).

We are using Artificial Intelligence to build the tailor-made curriculum for each student, track their records and predict their next step/level and learn with it's mistakes, we could use this prize to invest in researching the state of the art technology to open source this sort of solution. 

The applications of such technology are not restricted to our project. Universities could benefit to provide tailor-made curriculum, students in general will benefit of having a personalized education to allow them to go at their own pace and avoid the one size fits all kind of solution.