73 per cent of APS agencies identified employee skills and capability as a barrier to the use of data. Data analysts and scientists were identified as among the top 10 emerging job roles for Australia.
9 in 10 Australian companies are investing in and adopting big data analytics. Australian job postings for data science rose 58% in 2018 and are more than 5 times higher than they were in 2014.
23 per cent of Australians think that the Australian Government can be trusted to use data responsibly.
1 in 3 Australians think that the Australian Government could respond effectively to a data breach. Of the APS agencies that identified critical skills shortages 70 per cent identified skill shortages in data.
There are different agency types who utilise data, such as specialist data agencies, central agencies, policy agencies, service delivery agencies, regulatory agencies, finance and audit agencies, and justice and intelligence agencies.
Data may be about people, business, environment, and locations.
Data production includes the creation of data and managing data stages of the data use value chain. Examples of data roles under creation of data include data entry, cartography/surveying, questionnaire design and administration, interviewing, and observation. Examples of data roles under managing data include data engineering, database development, database administration, data management, and data governance.
Data use includes the analysing and presenting data and using the results of data analysis stages of the data use value chain. Examples of data role sunder analysing and presenting data include data wrangling and compilation, data science, statistical analysis, geospatial analysis, data visualisation and communication, and weather forecasting. Examples of data roles under using the results of data analysis include policy advice and development, service delivery and evaluation, research, performance and audit, and intelligence.
Long description: Descriptions of foundational data literacy, sophisticated data capabilities, and specialist data capabilities
Foundational data literacy. All APS employees require a foundational level of data literacy to perform their role. This includes using numeracy and basic statistics such as frequency and averages, visualising data effectively and producing evidence for decision making. Foundational data literacy ensures that all APS staff are able to effectively consume and communicate data or data outputs, and ensure the appropriate use of data.
Sophisticated data capabilities. Sophisticated data capabilities are required by employees who use or produce data on a routine basis. Intermediate to adept data capabilities are required across a variety of settings to inform policy or regulation development, to design more effective services, or to lead a unit or organisation that handles data.
Specialist data capabilities. Specialist data capabilities are required by employees who spend the majority of their time performing complex tasks with data. Data specialists include data acquisition officers, data analysts, data brokers, data scientists, or data infrastructure, management or methodology specialists.
The primary focus of the data profession is sophisticated data capabilities and specialist data capabilities.
Source, grow, and mobilise capability. Recruit specialist data graduates, develop existing data capabilities and enable mobility across data roles.
Share knowledge, expertise and better practice. Establish a Data Professional Network to share knowledge, expertise and better practice in the collection, analysis and reporting of data.
Senior leadership oversight. Oversight and championing by APS Senior leaders.
Collaboration. Collaborate across government with private institutions and with academia.
Long description: The four central themes of the APS Data Professional Stream Strategy with underlying practical initiatives.
Establishing the professional stream. Set up the professional stream: establish a senior reference group, identify the head of profession, develop a professional stream strategy. Collaborate and network: establish professional network.
Getting it right from the start. Attract the right skills to APS roles. Streamline recruitment across the APS, develop an APS profile, build inclusion into the professional stream. Ensure appropriate entry level qualifications, collaborate with the education sector to uplift entry level qualifications.
Developing sophisticated and specialist capabilities. Enhance capabilities, design job role profiles, identify and develop capabilities, identify and promote structured learning opportunities, encourage learning by immersion.
Embedding a professional workforce. Retain and grow workforce for the whole APS, define and promote career pathways, support professional communities, identify professional standards.
Outcomes for Australian citizens are that citizens have access to simple, reliable, tailored and timely programs and services. Citizens trust Government to collect and use their data appropriately. Outcomes for the APS are that the APS uses and understands data effectively to inform policy advice, regulation and services. The APS uses data safely, securely and ethically. Outcomes for government agencies are that agencies attract, develop and retain staff with sophisticated and specialist data capabilities.
Agencies build a more diverse data workforce, agencies foster a culture of data excellence, agency decisions are informed by fit-for-purpose data and sound analysis. Outcomes for APS staff are that Data Professional staff have appropriate entry-level data skills.
Data Professional staff become more confident and capable data producers and users throughout their careers. Staff access professional networks and communities of practice.
Data professionals are more mobiles and have access to data career pathways. Staff have a clear understanding of the competencies and behaviours expected of APS data professionals