Submitted
Last Updated July 19, 2018
Work of the Future
Brave Venture Labs LLC
Team Leader
Jessica Colavbo
Basic Information
Our tagline:
Talent sourcing software for identifying and matching high skill people to growing companies hiring in Africa.
Our pitch:
Global companies are aware that teams will be distributed globally and that talent can and will be hired everywhere in the world. However, they are also unprepared to unlock the strongest fit, and highest performing folks in those new talent markets. The most effective high growth companies spend 6 weeks and $5000 sourcing every new hire they make in Africa. And after all that, nearly 50% of those hires wash out in 18 months. In most case, the driving factor behind a higher expense and lower success rate is data. LinkedIn isn't rich enough in most emerging cities to quickly surface optimal talent. The data that does exist isn't always reliable or relevant to the hiring company's needs. We are developing a revolutionary tool for team leaders to build a customized talent pipeline at the click of a button. By uploading a job description and answering a few questions, leaders can auto-generate a list of talent to interview that is uniquely aligned to their team in both culture and skill. Companies using our software can source talent in days instead of months. At the same time, talent can use Brave's software to understand their skill gaps and possible career trajectories based on what the market actually demands.
Where our solution team is headquartered or located:
Nairobi, Kenya
The dimensions of the Challenge our solution addresses:
- Other (Please Explain Below)
- Upskilling, Reskilling, and Job Matching
About Your Solution
What makes our solution innovative:
Global recruitment is growing at 10% and online players are growing at 15%. And while companies are launching solutions for megacities like London, very few are designed to support data fragmented, emerging cities like Nairobi and Lagos.
How technology is integral to our solution:
Our core technology is intelligent tagging. We add an enriched layer of predictive variables to companies and talent, and simulate who will thrive in specific roles, teams, and companies. We use computational psychology and complexity science to identify soft and social tags, informed by organisational behavioural sciences. Our natural language processing machine learning tools continuously study emerging work areas to sort out how demand for skills are changing. We lightly monitor work performance to obtain data for improving our ability to match people to different situations. These technologies can identify new roles and and match people into those positions.
Our solution goals over the next 12 months:
Goals:
First, build a sustainable business within the African continent.
Second, advance our methodology for predicting potential in data environments.
Third, partner with 5 world class companies in 3 African countries to to test the efficacy of our latest predictions and the internal value of our service.
First, build a sustainable business within the African continent.
Second, advance our methodology for predicting potential in data environments.
Third, partner with 5 world class companies in 3 African countries to to test the efficacy of our latest predictions and the internal value of our service.
Our vision over the next three to five years to grow and scale our solution to affect the lives of more people:
Africa especially suffers from privilege and bias in the economy. The right methodology mixed with machine automation will allow us to scale a more deliberate evaluation of the many relevant variables about each person. When each individual's skills are clearly measured in every emerging city, companies will be able to make strategic choices about where to build their next office and who to hire. When talent knows which jobs are in demand and the soft and technical skills required, they will be able to envision how they might fit into the global economy long before it leaves them.
Our website
http://braveventurelabs.com
The regions where we will be operating in the next 12 months:
- Sub-Saharan Africa
How we will reach and retain our customers or beneficiaries:
Our beneficiaries are mainly young professionals among the estimated 70% that comprise the youth in Africa who cannot find a job matching their qualifications. We also serve people ill-suited to their current roles and ambitious companies struggling to find great talent. Our solution makes invisible talent visible and desirable to local and international companies like GE and IBM.
How many people we are currently serving with our solution:
Our company supports companies hiring product teams. Roles include engineers, analysts, data scientists, and product leads, which make up 25% of all professional jobs in Africa. In the last year, our African talent pool for these professions has grown to over 500,000. Currently our candidates get an average of a 30% increase in salary through a Brave job. And over half of them are moving from informal or self employment to full time employment. A major investment fund recently achieved a diversity success by hiring a senior role from a global region where they have never hired from before.
About Your Team
Explaining our organization:
Brave was founded in November 2015 to help unleash the best in people. After speaking with 100s of companies in East and West Africa, Europe and the US in early 2016, the team identified an opportunity to radically improve the meritocracy of hiring. Brave sources job candidates for companies in a dozen countries around the world hiring in Africa. Our team of 12 scientists, engineers, designers, and recruiters are based in San Francisco, London, and Nairobi. Half of our team is in Kenya and is expanding quickly. We currently serve over 50 clients hiring in 5 African countries.
The skills our solution team has that will enable us to attract the different resources needed to succeed and make an impact:
Our company was founded by three leaders:
-Jessica Colaco: CRO and Head of Growth, is a computer scientist, TED Fellow, and founder of iHub, Africa's first technology hub.
-Daniele Orner, Chief Scientist and Head of R&D, specialises in artificial intelligence, including agent-based simulations and high complexity predictive modeling.
-Ibanga Umanah, CEO and Head of Strategy, is a political psychologist, product designer, and innovation strategist who grew up and worked in Nigeria, Egypt, India and the USA. He's conceived and built over 20 new ventures for Fortune 500 corporations including GE, FedEx, Samsung, Lowe's, and Aetna.
-Jessica Colaco: CRO and Head of Growth, is a computer scientist, TED Fellow, and founder of iHub, Africa's first technology hub.
-Daniele Orner, Chief Scientist and Head of R&D, specialises in artificial intelligence, including agent-based simulations and high complexity predictive modeling.
-Ibanga Umanah, CEO and Head of Strategy, is a political psychologist, product designer, and innovation strategist who grew up and worked in Nigeria, Egypt, India and the USA. He's conceived and built over 20 new ventures for Fortune 500 corporations including GE, FedEx, Samsung, Lowe's, and Aetna.
Our revenue model:
Our data pipeline includes physical and digital talent acquisition. We seek to integrate our assessment and matching solution with internal HR systems, career websites, and applicant tracking systems to improve talent pipelines within organisations. Using our data enrichment and comparison tools, companies will be able to compare and select talent to interview from inside and outside their organization. Our machine improves each time we code a company's goals and skills request against their final hiring choices and candidate performance over time.
We expect to increase the quality of people in a company's interview pipeline with less investment of internal staff time and advertising. Our model already lowers average sourcing cost by 20% and we expect savings to increase to 80%.
As more people are placed in the right jobs for their skill we will see significantly lower underemployment rates among skilled talent in emerging cities. As well as an increase in per capita income. Currently our candidates get an average of a 30% increase in salary through a Brave job. And over half of them are moving from informal or self employment to full time employment.
We expect to increase the quality of people in a company's interview pipeline with less investment of internal staff time and advertising. Our model already lowers average sourcing cost by 20% and we expect savings to increase to 80%.
As more people are placed in the right jobs for their skill we will see significantly lower underemployment rates among skilled talent in emerging cities. As well as an increase in per capita income. Currently our candidates get an average of a 30% increase in salary through a Brave job. And over half of them are moving from informal or self employment to full time employment.
Partnership Potential
Why we are applying to Solve:
With Solve's support, we'd invest in R&D and Product Development to automate more aspects of our scoring model, matching simulation, and user experience. We will also accelerate our talent data acquisition. And finally, we'll invest in account leads in 3 African cities outside of Kenya to expand our reach and impact for talent.
The key barriers for our solution:
-Operating in low-middle income countries.
-Education is still far below employer expectations. To mitigate this we provide pointed feedback to candidates on specific growth areas which will advance their career, and direct them to learning resources online.
-Networks for information exchange are still in emerging economies, and companies are closing open sources for personal data. We've developed a low-data approach to predicting matches.
-People change. For our matches to maintain their quality, we need to continuously understand talents preferences and goals. We are rapidly innovating on our user interaction experience to maintain our data quality.
-Education is still far below employer expectations. To mitigate this we provide pointed feedback to candidates on specific growth areas which will advance their career, and direct them to learning resources online.
-Networks for information exchange are still in emerging economies, and companies are closing open sources for personal data. We've developed a low-data approach to predicting matches.
-People change. For our matches to maintain their quality, we need to continuously understand talents preferences and goals. We are rapidly innovating on our user interaction experience to maintain our data quality.
The types of connections and partnerships we would be most interested in if we became Solvers:
- Other (Please Explain Below)
Solution Team:
Jessica Colavbo
Co-Founder, Head of Growth
Co-Founder, Head of Growth