SkillsProfiler

Women in low-paid work have the problem that they are both more vulnerable to automation than men and are more likely to get stuck in unrewarding jobs. 

SkillsProfiler is helping workers find new jobs and identify relevant training, to lead better employment that mitigates against the risk of automation, kickstarts a cycle of lifelong learning and develops career resilience, by:

• Creating a skills profile based on our user’s skills, rather than job titles, to create an alternative to CVs and LinkedIn.
• Using real time job data to accurately match to the skills required in a potential role.
• Determining additional competences that are necessary to qualify for a new role.
• Signposting and providing access to relevant training resources that will augment their skills profile. Combining labor market statistics with job and training opportunities democratises career progression by giving the information and encouragement needed to maximise capabilities and transition into better employment.

There is a growing mismatch between the skills people have and the skills employers want, resulting in employers finding it increasingly difficult to fill roles. Globally, this accounts for 1.3 billion people; automation and digitization will only increase the scale of the problem.  

The problem is particularly acute for women in low-paid work, who find that they lack the skills to move into the jobs with greater demand and often get stuck in zero-hour, minimum wage employment or face long-term unemployment.
This is impacting business performance; 34% of businesses report that it is threatening growth while 55% report that it is hindering innovation (PWC 2019).  In total, it accounts for a 6% reduction in global GDP, amounting to $5tn (BCG 2020). In the UK, 63% of businesses are experiencing skills shortages (Open University 2019) equating to 850,000 enterprises.

• Low levels of in-work training opportunities, particularly for low-paid and older workers, .
• Low levels of self-study, with many people not knowing what is best from the huge range of training options.
• Lack of understanding of what skills will be valuable in the future (by 2030, 40% of workers may need to change occupation).

The skills mismatch is a major challenge for older women in low-paid work; automation will only increase the scale of this challenge.  Of the recently created occupations, only 16% were in job categories dominated by women, compared to 60% for men (McKinsey 2019). In the UK, women are significantly more likely to be paid only the national minimum wage and are more likely to get stuck in low pay.

We have worked with user groups across the UK to understand the challenges.  We found that the clustering of older women in some sectors means that they are unable to take advantage of the opportunities being created by technology; many work in retail where there is a high potential that roles will be automated while care-centric occupations are less easily automated but are typically low-paid.

SkillsProfiler enables women in low-paid work by finding commonalities between their existing skills and the skills requirements of alternative work, presenting options that may appear quite different to their experience e.g. school administrators have many of the core skills required for a role as an IT Business Analyst.  The result is to make it easier to discover alternative careers and make the move to another job.

We are building a platform that leverages job market data with predictive analytics, to enable low-paid workers to find better work.

Predominantly accessed over a responsive web interface, the platform will:

• Provide a low-friction tool for users to create their personal skills profile using an auto-generated list of skills based on prior job roles, against which the user self-assesses their relative capability.
• Enable users to message friends, associates and colleagues to contribute to their skills profile by providing an assessment of the user’s skills using a Likert Scale to measure the skills generated by the process above.
• Use labor market data to recommend potential career opportunities, based on commonalities between the user’s skill profile, as determined by their assessment and those of any nominated contributors, and an occupation’s skill requirements.
• Use real-time job data to identify and recommend work opportunities where there is a strong match.
• Use predictive analytics to identify where career opportunities could be improved by developing existing skills or learning new ones.
• Provide real-time training programs data, compiled by scraping data from multiple sites, to signpost our users to targeted training that will augment their skills profile.
• Improve the career prospects of low-paid workers in order to boost competitiveness (also validated by HBR 2017).

This will result in a marketplace being created that connects low-paid workers with new opportunities for better work (including better pay, flexible working, improved working conditions and/or less travel) or targeted training aligns to better work opportunities. By combining predictive analytics with behavioural insights, the objective will be to provide low-paid workers both the information and encouragement that they need to 

By working with our employer stakeholder group, we anticipate employers will use the platform to:

• Build talent pipelines to attract talent that is overlooked by their existing processes particularly in sectors that have major skills shortages.
• Optimise their existing workforce’s skills profiles in order to boost business performance.

 The user interface is being built in React Native, to enable users to open their personal dashboard both on mobile and web. The backend is built as a microservice infrastructure in Node.JS. This will enable the connection to external databases (including EMSI, Burning Glass and O*Net) through APIs while independently running computational processes (like profile formation and integration) with application tracking systems from our commercial partners.  We are using Python for the basic data analytics and considering R for certain predictive models.

We are targeting the older generation (50+) which is usually and marginalised in the workforce, although they account +15% (Statista, 2020) of the workforce, equating to more than 200M people globally in mismatched jobs. Yet this group provides a huge variety and pool of often overlooked and disregarded skills to the global economy. Our solution will not only work as a bridge to more fulfilling and safer jobs but also function as a lifelong career guide that takes into account day-to-day accomplishments, projects and trainings. Moreover, we apply machine learning to identify and tailor the best-fitting training opportunities sourced on- and offline. SkillsProfiler is the first holistic career guide that enables both companies and endusers to make the best decision based on advanced people analytics. 

In order for SkillsProfiler to elicit its full potential we need as much data as possible. Working with existing databases like BurningGlass, EMSI and O*Net enables us to develop a certain baseline understanding of the labour market and its dynamics worldwide. For a personal approach and understanding of individuals, we have to collect as many users as possible. This is the reason for a multimodal growth strategy considering both corporate partners as well as private users. 

Technically we are 

We started working on SkillsProfiler about 3 months ago. Our core market for 2020 and large parts of 2021 will be Germany and the UK due to our background and personal as well as professional network. 

We see SkillsProfiler as an intergenerational platform that can grow both B2B and B2B2C. A scale strategy similar to Slack by attracting individuals to use our solution is a valuable option we are very interested to explore. Additionally we are already in contact with globally operation businesses with both offices and employees overseas. 

We are currently a founding team of two working with external consultants and partners.

Experienced entrepreneur and business leader with a track-record in starting, building and operating businesses and not-for-profit organisations in the tech and apprenticeships sectors. Chair of several leading public sector and not-for-profit roles. Strong skills in strategy, planning, strategic partnerships and leadership, coupled with a thorough understanding of operations, finance and public policy. 

Experienced HR and Business professional with a background in building, growing and operating businesses. Strong skills in Recruiting, Employer Branding, Employee Development and Performance Management.
Recent partners and companies involve VCs and company builders like Zinc, b10 or Rocket Internet, traditional machinery businesses like Körber AG and startups like N26 or Lendico (now ING).

We are currently working with businesses across the UK and Germany like BT, Milk the Sun, Optimity or Hilton Hotels.