When I was young, my father would tell me to focus on learning one skill and to become very good at it. This was the pathway to success in his generation, to become a specialist. However, he didn’t set me up for that. Growing up in Silicon Valley, speaking French at home, studying economics and literature, I found that I developed a more eccentric skillset, with some things that I could claim to be somewhat specialised, and some more general skills. And what I found since then—from technology research in the US and management consulting in Africa to founding a startup in Southeast Asia—is that the modern world is increasingly set up to reward such eccentricity.
McKinsey and Ideo popularised the T-shaped person framework since the 1990s, the idea that the future-ready professional should cultivate both a singular specialisation and a variety of other areas in which they could achieve competence. This reflects a general trend of the knowledge economy to move towards ever more inter-collaboration across teams, higher innovation, and greater time spent on projects that may require new skills and knowledge. The rise of Agile is the best testament to a workplace that needs multidisciplinary teams that can be flexible, pivot quickly, and execute efficiently in a complex stakeholder environment.
The key-shaped person might be the next iteration of the T-shaped person—someone who builds multiple specialisations and builds a broad base of competencies in order to build a unique value proposition for themselves to their employer. Some key-shaped persons have quite clear appeal—the expert in finance and video gaming could become an equities analyst for the games industry or competitively position themselves as the best candidate for the corporate finance team of a major games studio; the L&D specialist who dips into programming or machine learning could become an L&D analyst—while others may need to carve out for themselves the situations in which they shine. But what key-shaped learning has in common regardless of skillset is that it is preparing individuals to function in environments where constant learning, multidisciplinarity, and a constant interplay between expertise and collaboration are the norm.
The no-code revolution can deploy automation, data, and AI to make your work easier and more valuable.
These are all examples of how modern professionals can extend the value of the work they do and save themselves enormous amounts of time through automating the most manually intensive and tedious work.
In the past, this type of automation was only possible for software developers or statisticians with advanced technical knowledge. But the no-code revolution and a basic understanding of technology and data tools now makes this automation and value-adding analysis accessible to everyone, regardless of background or level of technical savviness.
In the wake of the Great Resignation, a greater focus must be placed on employee retention, wellbeing, and preparing existing team members for emerging responsibilities. Recruitment, particularly of scarce talent, has always been a challenge. But that challenge has only grown, which means the opportunity for People teams is to focus on Learning & Development to empower the existing company’s workforce.
Meanwhile, the COVID pandemic has triggered what is likely to be a long-term shift towards hybrid and remote work. How do teams maintain culture and performance in such a context?
Many companies worry that investing in L&D will only be training employees to seek work elsewhere. But in 2022, it is more likely that investing in L&D is an investment into retaining your current employees, supporting their wellbeing, and preparing them for internal value-adding opportunities. Learning opportunities in the company are vital to addressing skills gaps and filling in pivotal staffing gaps internally, but they are also important for team wellbeing. Employees want to be given room to meet their potential, to be set up to achieve and succeed, and to be ensured that their company is giving them a strong trajectory for growth.
15 years ago, the future of learning was associated with massive online video classes known as MOOCs, mobile learning apps, or even the promise of personalized AI algorithms that could curate assessments and learning content.
Taking stock now, how have those promises panned out?
Two trends in particular have grown since the launch of the first MOOC. Both trends are oriented towards addressing some of the challenges with the current landscape of MOOCs and workshops.
The first is the rise of the Cohort-Based Course, a reaction to self-paced learning that solves many of the completion and performance outcomes of MOOCs. Cohort-Based Courses are social courses that are typically a commitment of several hours per week over several weeks (although more accelerated options exist). This is similar to the original thesis of a MOOC. What is different; however, is that cohort-based courses typically support cohorts of 10-30 learners who go through it together, hosting live class discussions with strong personal connections between learners, and between learners and course facilitators.
This personal connection, sense of camaraderie, and group activities are precisely what set them apart from MOOCs and make them so much more effective in terms of retention and student completion. For companies, these courses are particularly interesting as they can serve the dual purpose of not just upskilling in new skills, but also reinforcing team bonds and team culture.
The second is Project-Based Learning. Many MOOCs and workshops remain plagued by limited relevance and applicability for learners, dominated by lectures and theory. Perhaps it is a hangover of a society that grew up in a lecture-based classroom.
Project-based learning turns this on its head—the focus in such learning experiences is on the learner working through a project, often with the help of a coach or mentor. As a more active form of learning, project-based learning provides superior educational outcomes. In the ideal state, project-based learning can be directly interwoven into a company's workflow, allowing employees to engage in "stretch projects" where they learn new skills and work on a real project for their team.
One of the oldest challenges in learning is known as Bloom's 2-Sigma Problem. Education researcher Benjamin Bloom, who is also famous for discovering Bloom's Taxonomy, remarked in a study that has since been replicated around the world that one of the most important determinants of learner success is the ratio of teachers to students.
In particular, students in a classroom of 30 students and one teacher performed two standard deviations below a one-to-one tutoring session. To put that into context, two standard deviations is like moving from the 50th percentile (scoring better than 50% of the class) to the 98th percentile (scoring better than 98% of the class).
This means that changing our mindset from large group workshops or large classrooms into individual coaching or mentoring could be the most significant intervention to improve learning outcomes.
This shouldn't be a surprise to anyone who has ever met with a coach or a mentor. My mother was a French teacher. She would teach both classes at the local college as well as private tutoring for business professionals and high school students. Her college classes, with twenty students or more, followed a clear lesson plan, with limited flexibility to accommodate those who wanted to go faster or slower.
Her private tutoring classes, by contrast, may have used a lesson plan as a starting point, but quickly deviated—focusing on areas that the learner found more challenging, zooming through topics that the learner found easier, taking side journeys into topics that connected more to the learner's individual interests, or translating explanations into the context of the individual.
It has been 40 years since Benjamin Bloom shared his finding, and technology companies, governments, training agencies, and many others have since tried to use this to create the silver bullet solution to learning. Unfortunately, the problem has not been solved.
Expectations for L&D have also changed over time. Whereas prior L&D initiatives were dominated by the needs of managers and leadership to upskill their workforce (needs which are very much still present), current L&D is just as driven by the demands of a workforce that increasingly expects to be given opportunities to grow and thrive as professionals.
For generations that grew up in a knowledge economy, the expectation of a workplace is not just that of an employer, but a place where their own intellectual curiosity, professional ambition, socioemotional wellbeing, and search for meaning can be fulfilled.
In many industries, employees may spend the majority of their waking hours at work—it’s no wonder then that self-conception of an individual's purpose and sense of value become enmeshed with their work.
In this context, developing personalized learner roadmaps, supporting individual pathways to grow, and encouraging employees to identify and work towards their idealized professional self, are all ways to set your company up to attract and develop star talent. In particular, providing learning experiences that treat employees as individuals, reorient skill gaps as opportunities, and build team well-being are the bedrock of turning L&D into an engine of team growth, the cultural success, and organizational performance.
Eskwelabs is one of a generation of new edtech startups pioneering Learning Sprints: short and social cohort-based courses that leverage the structure of a regular class with the personalized learning of a coach in the context of a team project.
Our Learning Sprints are modelled on Agile project sprints, introducing all teams to the general worklow of a data analyst as the team with the learning team to complete a backlog of curated deliverables that give learners a mock project setting for them to learn the skills of the future. Along the way, learners are split into small teams, each with their own learning scrum master and coach, who passes on the instructions of the learning manager, reviews the lessons, and provides personalized coaching to each member of the team to succeed on their deliverables.
In a corporate context, Eskwelabs works with companies to use the company's own data whenever possible to ensure that Learning Sprints are directly relevant to the teams involved. Think of it as a facilitated data apprenticeship in your own company! Unlike a real stretch project; however, this is a safe space for learners to try and fail and learn.
After the Learning Sprint, learners can then take the deliverables they made and use them as a replication tool for their own projects or to teach other teammates how to apply the same skills. Eskwelabs also supports teams to assess their own data maturity and constructs individualized learning roadmaps that help every learner chart out their own pathway through the future of work.