Common Flow is a research and engineering project building a shared mathematical reference frame for human skills
Why we're doing this
We know that there's a skills gap, and we think the solution could be a skills map. Employers and industry tell us that they can't find workers with the right skills, while schools and individuals say that they don't know how to describe or demonstrate the skills they have. We start from a different position: the gap is not primarily a deficit in people, it is a mapping problem in the systems we use to recognise what people can do.
Skills are real, transferable, and broadly distributed. They are built through paid work, education, military service, sport, caring roles, cultural practice, volunteering, household labour, and a long tail of unstructured experience. The frameworks which employers, educators, governments, and credentialing bodies use to talk about those skills are strong, but they rarely speak to each other, and it's difficult to translate skills across countries and contexts. A skill recognised by one system is invisible to the next.
Cross-sector moves, military-to-civilian, care-to-management, trades-to-tech, international-to-local, lose information at every boundary. The cost of that lost information falls hardest on the people who can least afford it. Common Flow is the long-form attempt to fix the mapping layer, not to replace any of the existing frameworks but to let them speak to each other.
The hypothesis
The research rests on three propositions:
Skills can be mapped
We believe that skills have geometry, and that when skill taxonomies are reduced to their underlying structure, they converge on a small number of shared dimensions. A skill is locatable in a continuous space, not only as an item in a list.
The skills gap is a recognition gap
Most of what is framed as a population-level capability shortfall can also be explained by translation failure between systems. When skills are mapped into a shared reference frame, the apparent gap shrinks.
A shared map can change behaviour
When people, employers, and policymakers work from the same reference frame, recognition, hiring, mobility, and self-perception all shift in directions that are observable and worth studying.
The Methodology
The project runs along three lines of work.
- Build the map. A mathematical layer that encodes existing skills frameworks into a shared geometry, validated against published taxonomies and standards. This is the engineering core of Common Flow and the substrate everything else depends on.
- Test the map across sectors. Applied studies that take the map into specific recognition problems: cross-sector career transitions, qualification translation, hiring practice, workforce-planning instruments. Each study asks the same underlying question in a different setting: does a shared reference frame change what is seen?
- Test the map with people. Research with the humans whose skills the system is trying to recognise. Current strands inside this work explore the impacts on young people and self-perception, competency mapping, and cross-sector skills translation.
Head of Research
Lucy Sattler leads research at Common Flow. Her working background crosses the military, educational and instructional design, innovation, and social enterprise leadership, and she is the founder of , a career development organisation that has spent more than two decades working with young people, schools, and employers internationally; that practitioner work is where the project's central questions came from.
Lucy is currently a PhD candidate at Queensland University of Technology. Her thesis is one research strand inside Common Flow, focused on whether collaborative skills mapping changes how young people perceive their own capability. Her broader published work spans career development, vocational identity, and socially just career practice, with peer-reviewed articles in Career Development International and the NICEC Journal, and includes the Cluster Approach to the Development of Identity (CADI) framework.
Find Lucy on LinkedIn and on Google Scholar.