New occupational codes: why good labour market data needs translation
The Federal Statistical Office is updating occupational codes for the statistics on vocational education and training. The technical list decides neither wages nor jobs – but it decides the quality of the figures that policy and companies build on.
An updated list of occupational codes looks like a minor technical announcement. For labour market monitoring it is more than that: codes determine whether many individual entries turn into reliable statistics. When training companies, schools and authorities name occupations differently, education paths, demand for skilled workers and transitions into the labour market can hardly be compared cleanly.
A code alone does not create an occupation
For the statistics on vocational education and training, the Federal Statistical Office maintains the Swiss Classification of Occupations and Functions (SBG-SFPI). It assigns data on training programmes systematically. The statistics are an annual full survey of people in a training programme that leads to a federal certificate of proficiency or a federal vocational attestation.
The new code is therefore not a new job title, not a wage category and not an admission requirement. It is a unique identifier. That sounds trivial, but it prevents identical or similar activities from appearing several times in datasets – or not at all. Especially in a working world in which specialisations and occupational profiles change, this ordering is the precondition for robust comparisons.
The critical point is the time series
An update also carries a risk: anyone who wants to compare today's data with earlier years must know whether only a name changed or also its assignment. If categories are split, merged or newly defined, an apparent increase in the statistics may partly be a consequence of the new system. Good official data therefore document changes and, where possible, provide bridges between old and new classifications.
That matters for cantons, industry associations and training companies. They base their planning on figures about apprentices, qualifications and the demand for skilled workers. Poor comparability can lead to wrong conclusions: an occupation might appear to be growing although only its assignment has become more precise. Conversely, real bottlenecks can remain hidden if new profiles are not mapped correctly.
What figures can do for vocational education
Switzerland bases its vocational education on close cooperation between companies, schools and authorities. Data can show where many apprenticeships are created, how specialisations develop or which transitions are particularly demanding. But they alone do not answer which training is "future-proof". That also requires information about working conditions, regional demand, further training and technological change.
For young people and parents, the update of the codes is no reason to reassess a choice of career. For public debate, however, it is a reminder: labour market figures are not natural events. They emerge from definitions, surveys and careful documentation. Anyone talking about skills shortages or the future of apprenticeships should therefore also ask what exactly is being measured.
The new list from the Federal Statistical Office therefore deserves less attention than a new occupational profile, but more than a mere footnote. It is part of the infrastructure that makes political debates verifiable. In a Switzerland that relies on differentiated vocational education, this translation work is the precondition for data actually becoming orientation.
