Ladder

There are over 3.9 million Black and LatinX professionals in the US labor market struggling to be gainfully employed because they have limited access to quality guidance, do not have access to trusted career information and have limited resources to take a trial-and-error approach to upskilling for the future.

Ladder is a software application that uses leading database technology and analytics to transform real-time job data, pulled from a variety of sources, into career insights that helps them take their best step forward.

This solution enables these marginalized groups achieve the best ROI for the time and money they invest in developing their careers, make more informed career planning decisions, and gain access to experienced professionals who can provide much-needed guidance.

At scale, this solution has the potential to improve their quality of life, increase their representation in high-growth industries in the US and empower the communities they live in.

As of 2019, 10.7 million people in the United States are looking for work or at risk of losing their jobs in rapidly declining industries by 2029. About 43% (3.94 million) of that population are Black and LatinX aspiring professionals with/without higher education degrees. These candidates struggle to choose a fit career path or adequately position themselves for jobs within a path for three main reasons:

1. Candidates have limited access to quality guidance. They are less likely to have access to mentors who provide such guidance due to relatively less access to experienced networks.

2. There is no single, trusted source of consolidated career information. Candidates have no means of viewing all careers available to them, a situation which is exacerbated by the fact that industry needs keep changing, new job functions are added to the labor market and demand for job functions fluctuates.

3. Candidates have limited time and funds to take a trial-and-error approach to planning their future.

Ladder is a software application that enables individuals to access the information and guidance they need to take the best step forward in their career. It does this with features that fall under three main categories.

“Research” features give an answer to “what is out there and worth pursuing?” by using data science and machine learning methods to regularly mine & share a comprehensive list of all possible job titles, and how they map to functions, industry, demand, wage, and location. 

Premium “Research” features give an answer to “what might be a good fit for me?” by using statistical methods and machine learning to identify the top 5 combinations of skill, education and experience that yield the highest chance of entry into each career path, the cost of each scenario, and the fit of candidates against each pathway.

“Engage” features allow users to create a feasible plan and find mentors that are best suited for pathways that they choose. Users can view and set relevant upskilling milestones, and find and connect with relevant communities of practice.

“Growth” features allow users to view progress made against their commitments and get alerts on new pathway recommendations based on their upskill progress.

Our solution aims to primarily serve Black and LatinX college graduates with 1-8 years of professional work experience, ranging in age from 23 to 31. 

This group relative to their counterparts are likely to be impacted when unemployment rates increase, on average receive lower wages, and disproportionately lack access to a knowledgeable network who can demystify potential career pathways.

They work in a white collar environment, mostly in declining or stagnant industries and positions, and are looking to make a change and achieve more professionally.

We are focused on helping them achieve the best ROI for the time and money they are investing in developing their careers. We can empower them to make more informed decisions, backed by data, and provide them access to those with experience who can provide much-needed guidance. 

We will also calculate the cost and estimated financial return that will likely come with certain decisions to make it as straightforward as possible. With this, they can decrease the number of false starts, stop investing in unproductive and costly degrees and certifications, and overcome stagnation, all of which would contribute to lessening the persistent wage gap and career dissatisfaction affecting this community. 

Our solution is aimed at providing the direction Black and LatinX professionals need to make the best decisions for their careers. 

As highlighted in The Challenge, the nature of work is changing. There are multiple paths to get to a specific destination, which can be a positive change, but when you come from a community where there is little leeway to take the wrong turn, this can end up being complicated and costly. 

We aim to build a platform Black and LatinX professionals can rely on to better navigate this labyrinth of options and empower them in this current landscape.

Yes. We plan to pilot the app in New York, California, Florida, Georgia, Massachusetts, Louisiana and Maryland. 

These states not only hold a high proportion of the Black and LatinX population in the US but also have a high proportion of Black and LatinX professionals with post-secondary degree attainment. This makes them the preferred states to pilot this platform, validate target customer profiles, use cases and the ideal value proposition.

The varying technology laws and regulatory landscape in these states will also give us a diverse perspective on how to approach other states with similar regulations in our wider go-to-market efforts.  

Expansions to all other states within the USA will follow after the beta rollout is finalized.

We have currently have 2 people (Lilian Anumba & Vanessa Williams) working part-time on this solution.

In the next year we plan to bring on data engineers and software development talent working as part of the founding team or contractors.

We consider building a diverse, equitable, and inclusive organization on 3 levels:

1. Team Makeup: Our founding team consists of 2 Black women who come from backgrounds similar to the people we hope to serve. We will seek out people from traditionally marginalized communities to make sure their voices are heard as we build this product.

2. Company Values: We want to ensure that everyone on the team is treated in an equitable and inclusive way. The company is built on the idea of service and we aim to carry that value into how it operates. Team members will be encouraged to take a selfless approach to their work, team relationships and service of the communities.

3. Product: With our reliance on AI, we must ensure the product that we are building is not plagued by the same biases many others deal with in the tech space by utilizing inclusive product frameworks.

Four major things make Ladder innovative:

1. UX design that optimizes for clarity, speed to answer and usability by these marginalized groups regardless of their education level or native language. Candidates typically scour hundreds of sites and thousands of profiles on sources like Payscale and LinkedIn over an extended period to get a tiny fraction of the data and analyses Ladder will provide.

2. Comprehensive and customizable career research tools that provide quality and current information in the right format, that answer pertinent career planning questions, and computations that candidates might not be equipped to do. Competitors like PAIRIN and the US Department of Labour Statistics provide some career exploration tools and occupation insights but the data that fuels this is updated once a year, exploration is focused on soft skills and none provides the analytics Ladder does.

3. Lower cost of service for a lot more value. Players in the professional development space like LinkedIn and WayUp have some raw data and resources to produce a competing product. However, they are 3.8 times more expensive, do not consolidate this data in a meaningful way even for their premium customers, and still need additional data sources to develop the analyses that Ladder does.

4. Operating in markets that are currently underserved and poorly penetrated by indirect competitors in the US and beyond.

At its core, Ladder is powered by an intelligent decision support system (IDSS) that relies on statistics, AI (artificial intelligence), machine learning and database technology to convert vast amounts of unintelligible career data to visually appealing career pathway insights and planning tools. This is only fitting as this product aims to displace or augment the need for human career advisors who provide recommendations without access to all the data, without the skill needed to form a factual opinion, or know all the options that are possible.

This IDSS leverages augmented data management methods to efficiently mine relevant career data from various sources, link data from external sources to preset fields, and load them into appropriate data lakes to create a foundation for predictive modelling to begin. 

The IDSS uses statistical methods, machine learning and AI engines to build, train, deploy and scale predictive analytics models that sort data into a holistic view of career pathway information, analyze predictors of success for a pathway, and propose top combinations that ensure entry into a pathway, and the cost of each scenario. 

Ladder uses leading Server-Side Scripting technology to engineer features that allow users to create a dashboard of their career pathway goals, find mentors, join communities of practice, and keep track of their progress. 

Being a new venture, Ladder will also leverage leading cloud computing technology that allows the business to scale the cost of model building, training, and deployment only as its user base, product innovation and operations grow.

Robo-advisors have become increasingly popular in the investment management space and they run on the first principles and technology that Ladder’s core features are based.

Robo-advisors are automated financial advisors that build and manage client portfolios for a small fee. They analyze vast amounts of complex stock market data to select high-yield investments for a client’s portfolio based on their risk tolerance and financial goals. Just like Ladder, in times of market uncertainty, users can rely on data-backed recommendations to choose high-yield investments that rebalance their portfolio. 

Betterment and Wealthfront are the pioneer robo-advisors in the market. Both, like Ladder, rely on winning theories to drive their predictive models and aim to provide access to expert advice for those who can’t afford expensive, sometimes uninformed, human advisors.

Wealthfront has an intuitive personalized financial planning tool called “Path” that is designed to grow with customers and help them understand how life changes impact their future needs. Path mildly mimics some functionalities of Ladder’s “Research”, “Growth” and “Engage” features which provides a career landscape that is based on real-time dynamic career/job information and gives users the ability to revise milestones and track progress against their goals. Like Ladder, Path also uses relevant third-party data to more accurately calculate the cost of each scenario and its impact on the client’s future.

Hedge funds and investment management organizations also use intelligent investment platforms - like Venn - that function like robo-advisors to build data-driven investment portfolios and increase their stock returns. 

If ladder is successful, it will influence 3 major outcomes:

1. Improved quality of life for Black and LatinX professionals: The career landscape information, pathway analyses and access to communities of practice that it provides allows users to get a clearer direction on what upskilling investments are needed to land a job of choice, choose the most effective and efficient upskilling scenarios, and get the coaching they need to be gainfully employed in a career they choose. Having gainful employment is proven to increase the income they need to care for themselves and their families. Additionally, gainful employment gives them a sense of purpose, belonging and increases their satisfaction with life.

2. Increased representation of Black and LatinX professionals in high-growth industries: The transparency Ladder provides into emerging job functions in all industries (including those with high-growth rates), the income value of these roles, the skills that increase a candidate’s chances of successful entry, and the cost implications and fit of each scenario should expand the world-view of this historically marginalized group and equip them with the information they need to prepare for and apply to more roles they typically might have overlooked.

3. Empowered Black and LatinX communities: The upskilling recommendations, access to communities of practice, and deployment of Ladder in target communities should lead to more people in those marginalized communities pursuing traditional and non-traditional opportunities for higher learning, skill and experience building which should lead to more skilled people capable of filling high-wage jobs in the places they live in and beyond.  

Within the next year, our goal is to get our first paying customer and grow our paid subscription base to at least 3,500 users by focusing on:

1.   Getting additional user data that validates the need for Ladder: we aim to develop concierge MVPs and establish routine interactions with early adopters that enable us to tailor a wider go-to-market strategy. We will validate the target customers, feature set that best addresses their needs, barrier assumptions, value proposition, pricing model and gain more understanding of the market/competitive landscape during this process

2.   Gaining at least 1 vital partner for career data: we aim to gain a no-cost but high volume data partner with little to no reuse/resale restrictions then subsequently build up to data vendors with more restrictive reuse/resale agreements who might require more engagement, higher cost and new formal legal agreements.

3.   Getting a working version of Ladder in the market with technical help: we aim to expand our R&D team by adding data science/engineering talent to the leadership team and onboarding software development talent or vendors to support the build of the early releases of Ladder.

Over the next 5 years, we aim to increase our Y1 paid subscription base by at least 10,000%, gain more career data partners, expand the solution set to address the career planning needs of creatives & aspiring entrepreneurs, and be operational in countries outside the US that have predominantly Black and LatinX professionals with similar low employment rates.

A major barrier to our goals next year is the COVID-19 pandemic that has significantly impacted the current labour market in the US. Job cuts are steadily increasing and affecting a significant proportion of the population. This means that Ladder’s target customers are potentially operating more in survival mode – trying to get any job to keep the lights on, than in a mode where they are looking to conduct an in-depth exploration of career options and make long-term plans.

Additional barriers to our first-year goals include limited access to resources to get a working version of Ladder up-and-running by Day 90. Our team has limited funding to build the MVP and make the investments required to build, train, and deploy early versions of our predictive models. Efforts to also get skilled data engineering talent has proved difficult as prospects require some funding to build the data systems Ladder needs to scale.

Over the next five years, the major barriers we anticipate are legal restrictions that limit the use of partner data outside the US.

We plan to overcome the pandemic barrier by putting more emphasis on testing, building, and scaling the “Research” and “Engage” features that more directly help job seekers land a job. We will focus on providing information that allows them to view all possible job roles, see career pathways of best fit and connect with relevant communities of practice tied to each pathway. This will enable them to increase their application pool and upskilling priorities during this downturn in the economy and get the coaching they need to land the jobs they are a good fit for in the next year.

We aim to overcome the funding and data engineering talent barriers by relying on the skillset of the current leadership team and low code tools to generate insights we can use for feature validation and user testing. Some of these low-code tools make it possible to mine preliminary training data, conduct predictive analytics without investing in an IT infrastructure, and build concierge MVPs that can display relevant information to users and collect product performance data.

Long-term, we plan to overcome potential reuse/resale restrictions in other countries by choosing partners with global subsidiaries that make it easy to get agreements in place when we want to scale and also partnering with local data vendors in the countries we aim to serve.

A key outcome data that will be relevant to measuring the success of Ladder is the decrease in Black and LatinX professionals with higher education seeking part or full-time employment. The US Department of Labour Statistics doesn’t currently provide information on the employment status of each race by education level.

Other key outcomes data that we would like to measure is the increase in representation of Black/LatinX professionals in high-growth jobs and the demand of high-growth jobs in their predominant locations. There is not enough data to know the race and education level of the candidates who fill high-growth roles.

We aim to partner with the Department of Labour Statistics to conduct custom analyses that help us plug these data gaps. We will also work with data partners to collect proxy data that allows us to estimate the profile and educational background of people who fill roles on their platform.

• We have a close proximity to this community. We are both Black women who have suffered from many of the same drawbacks as those we are looking to serve. A lot of our career journey was driven by happenstance and luck. Lacking sufficient knowledge and networks ourselves, we’ve made flawed decisions and invested both time and money in areas that did not serve us. Knowing this problem so intimately and being close to the network of professionals who need this will help us grow this business. While others might also be able to build technology, truly being successful will take a human element because so much relies on trust. We can create the best tool but the people using it must feel they can rely on it and the team behind it to drive the decisions that change their lives. Therefore, our personal connection to this problem and community will be key.

• Our professional backgrounds in bringing complex tech solutions that utilize big data, AI, and machine learning to market in both B2B and B2C spaces have provided us with the tools to develop and scale this business. Both of us have experience working on Product teams, at technology incubators, taking part in entrepreneurship fellowships at Columbia University, and more, through which we took ideas from 0 to 1. Most importantly, we have built and grown solutions that have successfully delivered socio-economic change in low and middle-income countries and communities that mirror our target group.

Ladder’s primary customers are Black and LatinX professionals who are:

• Employed part-time for economic reasons

• Unemployed and looking for part-time or full-time work

• At the risk of losing their job in rapidly-declining industries

These customers currently make up 3.9 of 10.7 million people in the US currently facing the same issues which creates a pipeline to generate over $374 million in annual revenue in the short term and ramp up to ~$1.02 billion dollars if the US market is maxed out.

Ladder generates revenue through paid subscriptions and impressions. All active users generate impressions when they use Ladder’s basic features which include the holistic career landscape by location, company, and industry and its “Growth” features. Paid subscribers gain additional access to features that show job fit analysis, predictors of successful entry into a pathway, scenario cost calculations, and access to “Engage” features.

Subscriptions cost $8 per month and impressions cost $8 per mille (1000 views). The aim is to have over 13,300 active users contributing to its impression-based revenue and ~3,690 users paying for subscriptions by the end of the first year. This assumes 16,649 installations, 80% conversion rate of installations to active users and 20% conversion rate of active users into paid subscriptions by the end of the first year.

We will convert installers into active users and subscribers by providing new users with limited access to both free and premium features and rewarding users who refer people to the platform and engage in community development with subscription discounts.

In the first year, based on a conservative revenue model, Ladder is expected to generate $26,648 in annual revenue from impressions and subscriptions. However, it will cost over $61,000 to produce a working product and an additional $48,900 to market and operate the business within that year. The business does not become cashflow-positive until its third year of operations.

We plan to use a combination of revenue generated from selling products and services, sustained grants, and sweat equity to get through the first two years of operations. Further details on the month-to-month projections are available on request.

We are estimated to spend about $110,000 in 2021. These expenses are largely driven by research and development for the MVP, marketing, and general administrative costs – start-up licensing, registration, logistics and connectivity costs - within that first year. Cost of goods sold include cost of third-party data mining, hosting and support for the web application.  A detailed cost breakdown is available upon request.

Firstly, we are applying to the Challenge because our solution addresses the focus of the challenge as it:

• Provides an innovative way for aspiring professionals in the US to drive career self-management and gain the insight and guidance they need to build their future in its workforce

• Positively impacts the lives of marginalized groups the challenge aims to solve for and has the potential to successfully scale to other professionals facing similar challenges in the US and beyond

• Is feasible and capable of financial sustainability in the short and long term

Secondly, the challenge enables us to overcome our resource barriers by providing grant funding to build and test our MVP and the opportunity to partner with leading AI/ML experts  - IBM - to build data systems/models that are based on the most current and innovative theories. Gaining access to US workforce boards also gives us the opportunity to continuously  iterate our solution with additional knowledge of proven interventions that really fuel systemic change in this space.

We need partners for funding, solution technology and talent recruitment to overcome our resource barriers in record time and build a good foundation to build, train and deploy scalable predictive models. We also need partners for legal and regulatory matters to avoid mishaps and oversights as we obtain the right business licenses, registrations, intellectual property (IP) protections, non-disclosure agreements, employee contracts and operating policies that our business needs to operate effectively and stay compliant in the nest year. 

IBM - Talent recruitment (data engineering and analytics software development) & Solution Technology (data systems, AI & machine learning models)

Linkedin, Indeed, PayScale, Google for Jobs, Glassdoor - Solution technology (job and employment data)