A system that guides, motivates and invests in workers near term skills and future capabilities can help build long-term organizational growth and resilience.

It has been well known for the past decade that organizations need to train and reskill their workforce to remain competitive. Larger organizations have dedicated programs and consultancy firms to take care of this training, but in a rapidly changing world, where learning has become a key driver, the investment has still been too small - and opportunities have often only gone to the selected few.

We need a system that goes beyond internal training, government-funded programs, and slow-to-adapt educational institutions. A sort of a learning community - not the ones that we know today, which is based on communities of interest, where we meet and hang out together, share knowledge and then go back to our normal lives - but more a sort of impact community where we have a desire to act together and learn through creation.

Impact communities are often formed around a particular domain where the participants are highly motivated and passionate about the domain. You can find these communities formed around extreme sport, online gaming, and activism. Groups within impact communities often create extreme results by discovering new approaches, supporting and motivating each other - all to find ways for more impact with less effort and fewer resources.

Companies that create internal impact communities are often the ones at the forefront of their industry, they are the ones reinventing quickly during times of crisis and whose employees have embraced the habit to unlearn and reskill to optimize for impact - it has just become a natural capability of them.

Over the last few years at 123abc we have collected data and experimented with models and algorithms that work to match people with people to create impact communities.

We’ve tried to understand how to speed up learning to close skills gaps and prepare people for the future of work. Our findings show that skills training isn’t the challenge, either is the future of work.

Shorten the loop

We have to shorten and close the information loop between what skills and capabilities there are in demand to the workforce, motivate and guide reskilling, and then easily connect to create impact. The speed and closeness of the loop will change both over time, by industry, and by location.

To shorten the information loop, companies will have to embrace and invest directly in learning both in and outside of their organisations. Individuals within the workforce must embrace learning and make it a habit to acquire new knowledge. We measure the willingness to invest and learn, and the interplay between the actors with a Learnability score.

What We Believe

To ensure more economic growth and organizations that are more resilient to constant change we need a  truly open Career Network that is human-focused but machine-assisted. We call this system the Open Human Cloud Network.

The Open Human Cloud Network will connect the workforce directly with companies in a way where they anonymously exchange data, companies invest in skills and capability training when reaching out in the network and connections are machine-assisted.

The Open Human Cloud Network is a set of standards and rules on top of existing decentralized network protocols and is open for everyone.

In a series of blog posts, I will go deeper into the mechanics of the Open Human Cloud Network, tell you why we believe it can increase companies economic growth, create a more resilient workforce, transition casual and low-income labor into more stable job roles and how 123abc can play a part in building an Open Human Cloud Network in the coming years.

At 123abc, we are passionate about building an Open Human Cloud Network for the world. We think this is the way to bring economic freedom to more people, more growth to workplaces, and equity of opportunity in the world.

Building a matching engine to pair talent with jobs is an exciting challenge. How much should we weigh proven success over clusters of indicators that predict upcoming talent?

This is one of the many questions asked when developing the initial matching engine at 123abc for the human-cloud network. To ignite the brainstorming process and let technical bios stay out of the first drafts we use storytelling. Our favorite story to discuss the assessment of talent [current vs upcoming talent] and how we should measure the success of our matching engine is the story taken from an interview with Stephen Francis.

A sports coach’s insight into talent scouting

Stephen Francis, the world's most successful sprint coach and founder of MVP Track & Field Club, has excelled in finding and developing talent that most other people have overlooked.

‘I love to work with people who are hungry for a second chance - I love to prove that people made a mistake. That other stuff bores me. I stay clear of those I call “can’t miss” athletes as a matter of principle. Instead, I look for those with the greatest development potential,” he explained in an interview.

According to Stephen Francis, one of the great misconceptions about talent identification arises from our conviction that current high performance automatically equals a great potential and that current average performance equals low potential. Current performance can certainly be a good indicator of potential but this is not always the case.

What is important to him is not performance in itself, but what caused it and the story that lies behind it. Because of this, one of the key areas Francis looks at when trying to assess talent is training history. This is based on the idea that if you know an athlete’s past, you’ll have a greater chance of evaluating the possibilities for the future. As Francis explains: ‘Imagine that you see a guy running the 100 meters in 10.2 seconds as a nineteen-year-old. Then you see another nineteen-year-old running the distance in 10.6. Everything seems to be screaming at you that you should choose the one who runs 10.2. But if you’re good, you will know that the guy who ran the distance in 10.6 may have even greater potential. Imagine, for instance, that the 10.2 guy comes from a very professional and qualified training environment, while the 10.6 guy basically trained on his own. I look very closely at athletes’ training histories. The better an athlete is without having a good training history, the greater the potential that exists.’

Looking beyond the surface to the story

Looking beyond the obvious result is a key principle when spotting talent in a business environment too. Don’t judge potential using numbers alone. Dig below the surface to learn how the numbers were achieved or what stood in the way that might have prevented them from being better. Was a manager successful more because of favorable market conditions than because they were a competent decision-maker? Did a salesperson deliver good numbers because he had an amazing product that sold itself or because he systematically worked on building a strong pipeline?

As Stephen Francis puts it: ‘It’s not about the performance – it’s about the story behind the performance.’

Understanding Potential with the Human Cloud

The Human Cloud gives you a way to examine a candidate’s whole career story - the story behind a CV. The network gives you the tools to understand and evaluate a candidate’s ability to adapt to change, their commitment to learning, and the soft skills that help them problem-solve and create.

Hire for potential to create a learning-focused and adaptive workforce that brings evolving value to your company and mission.

Learn more about the Human Cloud project and our vision for the future of work by signing up at 123abc.com >>>

At 123abc, we are passionate about building an Open Human Cloud Network for the world. We think this is the way to bring economic freedom to more people, more growth to workplaces, and equity of opportunity in the world.

Long-life learning is about anticipating that we will all need to navigate a longer, more turbulent work life. If early baby boomers are already experiencing 12 job changes by the time they retire, we may have to prepare for 20 or 30 job transitions in the future.

Long-life learning isn’t about education for “those people over there.” The future of workers is about us. To stay competitive in the workforce, we’ll all need to think of ourselves as working learners, always flexing between working and learning or juggling both at the same time. We are the ones who will be affected, and so we must get to the business of building the infrastructure for us to harness the power of education over and over again throughout a longer work life.

We need to design a new learning ecosystem that is fundamentally more navigable, supportive, targeted, integrated, and transparent.

  • Navigable. Job seekers don’t have the technologies and tools they need to analyze their talents, bring them to the surface, and assess their skill gaps. They want information about how to choose the right career pathways—the type real-time labor market information and consumer reviews provide. They need a bird’s-eye view of the current and future job market, including all of the career pathways open to them based on their interests, skills, past training, and experiences. Navigation will give adults better information to guide them through complex systems, and better assessments to help them make sense of their skills and experience and figure out how to translate and transfer their capabilities into better jobs.
  • Supportive. Job seekers want guidance on which pathways will be most effective, targeted, and affordable in helping them grow and thrive in the labor market. To stay focused on their education and career goals, learners need comprehensive wraparound supports, be they person-to-person or tech-enabled, to help them overcome hurdles and manage multiple commitments and competing priorities. Better support services will foster the success of all working learners, from the beginning of their explorations all the way through their new working lives and subsequent career transitions.
  • Targeted. Job seekers need access to a precise and relevant education tailored to their needs: the right skills, the right pathways, at the right time.They also need to know that the education they choose will be worth the investment—and clearly signal value to a prospective employer. More precise or targeted learning experiences must provide not only the knowledge but also the human and technical skills, professional networks, and hands-on practice that equip learners to be ready to work.
  • Integrated. Working learners need the time, the funding, the confidence, and the resources to integrate education and training with their existing responsibilities. A new learning ecosystem will reduce education friction and make advancement achievable by offering better funding options, new opportunities to learn while earning, or in the flow of work.
  • Transparent. The hiring process must be transparent, open, and fair—and enable job seekers to prove their competence and skills.When skills become the primary currency of the job market, employers will be able to access a more diverse pool of qualified candidates who have proved they have what it takes for the work ahead.

source: Dr. Michelle R. Weise, Long Life Learning

About 123abc

Our Mission is to build an Open Talent Economy there provides more economic freedom for every person and business. Our first step is to enable access to the Open Talent Economy by creating the Human Cloud Network and make it easy for people to find the right skills to develop, for businesses to indicate what skills they need, invest in people development, and invite people into their teams.