The PEPTalk of June 2018 focused on Profiling, which allows us to divide people into target groups based on predetermined rules and to subsequently provide these groups with more targeted matches, guided by an AI-driven knowledge model. In the upcoming PEPTalk of March 26, you will learn how VDAB, in close cooperation with WCC, has put advanced AI techniques to use in their daily practice, with the aim of taking their job matching to a higher level.
Using AI techniques in order to improve job matching is not simply a matter of using an off-the-shelf algorithm and then expecting miracles – VDAB uses highly targeted AI techniques for very specific purposes, in a process in which there is also close collaboration with domain experts. Ria Deketele will present how VDAB is now using data analysis and machine learning to determine relevant target groups of jobseekers that require more tailored matching strategies. You will learn how by means of a qualitative tuning process, specific rules and matching criteria have been applied in order to improve these jobseekers’ chances in the job market. You will also learn how the effects of this tuning can be quantitatively evaluated by means of data analysis. Finally, you will learn how talent expectations and company culture information can potentially enrich the match process even further.
Below you can watch on-demand our PEPTalk on ‘How advanced technology improved job matching at VDAB’.
PEPTalks are live & interactive: we encourage you to ask questions during the web
Self-service skills assessment using a smart app based on ESCO and AI!
Apart from MySkills in Germany, there is another new approach to help refugees finding a job quickly. It is an app that helps them in their own language to assess the skills they have gained through past experiences. It uses the ESCO taxonomy including over 13,500 individual skills and nearly 3,000 occupations, as well as state of the art artificial intelligence to match individuals to occupations and generate job-specific applications.
The resulting skill profiles can then be used by individuals, employment services, education institutions, and others, and integrated into existing career and education services. Mr. Ulrich Scharf, Managing Director of Skilllab will explain how it works and how a PES can use it to improve the chances of refugees in finding suitable work more quickly and efficiently.
PEPTalks are live & interactive: we encourage you to ask questions during the webinar.
Click below to see the webinar on demand.
For more information on the skilllab application please contact Ulrich Scharf at firstname.lastname@example.org
ESCO is the multilingual classification of European Skills, Competences, Qualifications and Occupations. ESCO is part of the Europe 2020 strategy.
The ESCO classification identifies and categorises skills, competences, qualifications and occupations relevant for the EU labour market and education and training. It systematically shows the relationships between the different concepts.
The morning session will focus on MYSKILLS. This German PES project helps people with a distance to the labor market find work by creating an objective record of their professional skills. The workshop will be presented by the PEPTalk’s guest speaker, Anja Block from the Bundesagentur für Arbeit.
The afternoon session is about using AI and segmentation to improve match results. An AI-driven approach enables PES to influence jobseeker advice, resulting in more fitting matches.
You can read more about these topics or re-watch the PEPTalks here:
Imagine an 18-year-old and a 55-year-old with the same skills.
A job matching algorithm might offer them the same job. But we all know that they should each get different advice. Advice that takes into account their differences as well as their similarities.
There is a way to provide fitting advice without having to hand-tailor it for every single jobseeker. WCC calls this Perspectives. Here’s how it works:
Target Groups for tailored advice
During enrollment, the system registers data such as age, gender, location, education, and experience level. Based on this knowledge, each jobseeker is assigned to a well-defined target group. The advice people in this target group receive is based on a sophisticated AI-driven labor market knowledge base.
Now here’s the most interesting part: Public Employment Services can influence this advice. For example, because they want to align the advice for a specific target group with an ALMP, or because the jobseeker is in a geographic area that needs a different approach than the average.
In the 45-minute PEPTalk webinar on June 25, WCC’s Marcel Bakker will discuss PES-influenced AI-driven job advice in more detail and explain how to implement this approach. He will be joined by Ria Deketele from the Belgian PES VDAB, who will discuss the matter from the PES point of view: what is VDAB already doing in this area, and what are their plans?
The Australian employment services industry is unique. No other country in the world has managed to build a Public Employment Services sector in which the front-line work is entirely carried out by non-government organizations contracted by government. Australia’s innovative system was praised by the OECD and incites the interest of government organizations around the world.
Australia’s innovative outsourcing of Public Employment Services in the late 1990s initially attracted some criticism. Were the Australians converting the plight of the unemployed into a private money-making opportunity? Was their government abdicating responsibility? Such fears proved unfounded and unjustified.
Australian employment services are one of the most closely monitored industries in the world, with market competition forces simulated by stringent and relative performance standards upon which the continuance of an individual provider’s contract entirely depends.
Contracted employment services providers are held accountable to a strict compliance framework. Contract cycles are short, with under-performing companies losing the right to re-tender. In the first 20 years, the market condensed from over 300 providers to under 50. A ‘Star Ratings’ system determines the relative success of providers in achieving employment outcomes through a complex calculation that takes into account size and geographical location of allocated sites, characteristics of the local job markets, and characteristics of the provider’s jobseeker case load. Providers scoring 2 or less out of 5 are deemed ‘under-performing’.
Remuneration for the provider also mostly depends upon successfully placing jobseekers in work, and in most cases the placed client must remain in employment for at least 26 weeks. The administrative burden for providers is considerable, and the rewards are hard-earned.
An advantage of this system design is that it focuses provider efforts at a local level on achieving successful employment outcomes. It is responsive to changing labor market conditions and attracts a mix of innovative service models delivered by small and large organizations, not-for-profit and private companies, and specialist and broad-based services. The system’s effectiveness depends on information conduits between government and providers, as well as on sophisticated data and analysis of labor markets.
Read more about the unique Australian PES system in this free chapter of Managing Workforce Development:
The environment in which PES operate is being reshaped by fundamental changes resulting from demographic shifts, new technologies, and globalization. Workers can now expect many job transitions throughout their careers, meaning they will have to continuously develop their skills. In many emerging and developing economies, these structural transformations are occurring against a backdrop of high levels of underemployment and informal types of employment. Poor labor market outcomes contribute to rising inequalities not only in terms of income, but also in terms of access to quality employment opportunities. In addition, labor productivity growth has tended to decline in both advanced and developing countries since the mid-1990’s, partly as a result of demographic change and mismatch between the supply and demand for skills.
To tackle these complex labor market conditions, PES must widen the range of their responsibilities. While job brokerage and the provision of labor market information remain core activities, PES must evolve if they are to contribute to the broader objectives of boosting labor market participation, stimulating job creation, promoting inclusive growth, and raising labor productivity. The best way to do that is by connecting jobseekers, employers, and other labor market actors.
Recently, PES have had to operate under continued austerity measures, which means that services have to be delivered more efficiently without compromising quality. At the same time, PES often only have a small market share in terms of vacancy coverage and access to key labor market information. This means PES need to engage with a range of actors to share know-how, expertise, and resources, and to offer complementary services to jobseekers and firms.
In this context, the real question is not so much why, but how PES should cooperate with other actors such as government departments, regional and local authorities, private firms, employer’s associations, unions, and non-profit organizations.
This free chapter of Managing Workforce Potential will review how these forms of cooperation can be most effective. It argues that the local level is often the most pertinent for setting up partnerships, and that the adoption of appropriate governance mechanisms is a key success factor for such partnerships.
Reshaping National and Global Employment Services Markets
The modern Public Employment Service no longer functions as a single national operator. Public-private partnerships are reshaping employment services markets around the world. Why should PES work together with private partners, and more importantly, how should they form and build these partnerships?
This free chapter of Managing Workforce Potential provides at least 4 convincing arguments for PES-private partnerships, explores the many possibilities, and ends with an inspiring business case in the ‘Mayan Riviera’ in Mexico.
What is the sharing economy, and what are its implications for employment services? Also referred to as the ‘gig economy’ and ‘Uberization’, the sharing economy is a system of business models that bring individuals together to share their resources with strangers, all of whom are – and this is the key – enabled by a third-party digital platform.
Today, sharing economy architecture can be found for almost anything. We are most familiar with structures such as Airbnb (accommodation) and Uber (transportation), also known as the ‘rides and rooms’ industries. However, locally and globally, people are also sharing “meals, power tools, dog kennels, boats, driveways, bicycles, musical instruments, even excess capacity in their rucksacks” (McLean 2015). The Internet, mobile technology, and social media platforms have brought about this economic and cultural shift. From one’s living room, global markets can not only be accessed, but participated in fully.
If this is altering our traditional business models, then certainly it is changing the nature of work. How are we to understand ’employment’ in the social economy? The disruption in traditional business structures raises practical questions for Public Employment Services and their partners. Does employment in the sharing economy fit the usual “supply and demand” scenario we have served over the years? And if the sharing economy is a dimension of the labor market, are conventionally-designed Public Employment Services and partners evolving to successfully place and support people in this new world of work?
There’s no shortage of research attempting to find answers. In this free chapter of Managing Workforce Potential, Natalie Branosky, explores and explains the sharing economy’s impact on Employment Services:
Competence-based matching provides an interesting answer to the significant increase in bottleneck vacancies. PES want to offer opportunities to unqualified young jobseekers (NEETs: not in employment, education, or training), to young people whose diploma does not offer a good connection to the labor market, to refugees without a recognized diploma, and to people aged 55+, whose acquired competences are more important than their outdated diplomas. There is pressure from both the demand and the supply side to substitute diploma- and profession-centered matching with a broader, more modern matching system.
Competence-based matching is the best alternative. On the one side the system doesn’t exclude diplomas, because they are an attestation of acquired competences. But on the other, the system also allows for including prior/elsewhere/otherwise acquired competences in the matching process. In addition, because competence-based matching allows for fine-grained mapping of possible competence gaps, it is a better guide for (re)orienting jobseekers and allows for a more effective specification of training needs.
Find out more in this free chapter of Managing Workforce Potential: Compentence-Based Matching – The Holy Grail? by VDAB CEO Fons Leroy
Around every 18 months, our collective computing power doubles. New innovations erupt from the technology volcano ever faster. These open up vast areas of possibility for PES: new channels to serve their clients, new tools for matching and managing the workforce, new systems to increase productivity…
But technological innovations are also getting increasingly complex and changing ever faster.
How can PES harness the power of IT and big data to improve their efficiency and effectiveness? Find out in this free chapter of Managing Workforce Potential: