The specialist tasks are designed to describe day-to-day work within an occupation. While these skills can be transferrable across occupations and sectors, unlike core competencies, they are not universal.
We used O*NET’s Detailed Work Activities (DWA) as our starting point for technical tasks. There are approximately 2,000 Detailed Work Activities in the O*NET taxonomy. Each of these represent a distinct work activity performed in a job.
To bring the DWA into the Australian context, we manually removed or adapted tasks not commonly performed in Australia – for example we took out snow ploughing. We then modified the task to translate its academic descriptions to language that Australians are more likely to use daily. The modified tasks were called the specialist tasks thereafter.
It is important to note that several specialist tasks described the same or a very similar skill in different words. To facilitate the transferability among occupations, we clustered the specialist tasks into higher level groups using a mix of machine learning and human checking methods. The underlying intention is that if an individual can perform one task from a cluster, they can likely perform the tasks in the same cluster as well.
We used 3 different clustering algorithms, k-means, Affinity Propagation and Spectral Clustering algorithms followed by a customised cluster refining process. We then used a similar process to further group the specialist task clusters into families, to give us a true taxonomy of skills, rather than an occupation driven taxonomy which includes skills. We ended up with 29 task families, 279 task clusters and 1,925 specialist tasks.
Table 2. Example of top 10 specialist tasks for Cooks, by time spent
|ANZSCO Code||ANZSCO Title||Specialist tasks||% of time spent on task||Specialist cluster||Specialist family|
|221111||Cooks||Cook foods||26%||Undertake food preparation||Food services|
|221111||Cooks||Check quality of foods or supplies||9%||Monitor food or nutrition quality||Food services|
|221111||Cooks||Assess equipment functioning||7%||Inspect, test or maintain equipment or systems||Quality control and inspections|
|221111||Cooks||Cut foods||7%||Undertake food preparation||Food services|
|221111||Cooks||Prepare foods for cooking or serving||5%||Undertake food preparation||Food services|
|221111||Cooks||Coordinate activities of food service staff||5%||Coordinate food service activities||Food services|
|221111||Cooks||Clean food preparation areas, facilities or equipment||4%||Clean work areas or dispose of waste||Cleaning and maintenance|
|221111||Cooks||Inspect facilities, equipment or supplies to ensure conformance to standards||4%||Inspect products, equipment or facilities||Quality control and inspections|
|221111||Cooks||Arrange food for serving||4%||Undertake food preparation||Food services|
Working hours for specialist tasks: Task utilisation score
To analyse how specialist tasks are utilised by an occupation, we calculated working hours allocated to each task during a day. This also helped to rank the popularity of tasks according to working hours allocated to them.
While O*NET specifies each of the DWAs associated with an occupation, it does not provide a metric of the relative time spent in each activity for each occupation. In deriving the time spent for a DWA, we applied a similar method to that detailed in AlphaBeta’s ‘The Automation Advantage’ (2017).
We used the task ratings survey carried out by O*NET that asks respondents how often they perform each task in their role, ranging from ‘yearly, or less’, to ‘hourly, or more’. O*NET reports for an occupation the share of respondents and their implied frequency for a task. We derived a task utilisation score, or the working hour allocated to a task, for each occupation and task pair. This score is computed by taking the average of implied yearly frequency for a task weighted by respondent share.
Table 3: Task implied yearly frequency
|O*NET Frequency||Implied yearly frequency||Rationale|
|Yearly of less||1||Once a year (one time)|
|More than yearly||2||More than once a year (2 times)|
|More than monthly||12||Once a month (2 times)|
|More than weekly||48||Four times a month (48 times) (12 x 4)|
|Daily||240||At least daily, 5 times a week (240 times) (5 x 48 working weeks x 1)|
|Several times daily||480||At least twice daily, 5 times a week (480 times) (5 x 48 working weeks x 2)|
|Hourly or more||1,920||At least 8 times a day, 5 days a week (1,920 times) (5 x 48 working weeks x 8)|