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Draft Statistical Capability Framework

This draft Statistical Capability Framework (SCF) is currently out for consultation with stakeholders, including State, Territory and Federal government agencies, other National Statistical Offices (NSOs) and Institutions, academia and the Australian Public Service. Feedback gathered from these sources will directly influence future development of the SCF.

If you would like to provide feedback on the draft SCF or would like further information on it, please email The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.


The Australian Bureau of Statistics (ABS) recognises that to achieve a more statistically capable workforce, wherever that workforce may be, it is important to have a framework to understand what statistical capabilities are required and to offer a common language to describe those capabilities.

An increase in statistical capability both domestically and internationally will help transform the way users and producers communicate, manage and use statistical assets to support informed debate and decision making in the research and/or policy arenas.


To achieve this, a draft SCF has been developed. The purpose of the framework is to provide a standard set of capabilities and offer a common language to describe those capabilities. This will enable discussions to occur around statistical capability needs analysis and future development requirements.

The SCF has been designed to be applicable and relevant to not just other NSOs, but to all users, producers and leaders in the wider domestic and international statistical community. The goal is to have the SCF adopted as an international standard by the UN Statistical Commission.


The SCF defines and articulates the full spectrum of capabilities required by users and producers when undertaking any kind of statistical work. It does not attempt to define the capabilities associated with statistical infrastructure or systems.


The SCF consists of three tiers:
    Tier 1: Capability dimensions;
    Tier 2: Main statistical processes attached to each dimension;
    Tier 3: Capabilities required for each statistical process.


This tier shows the three dimensions of the Statistical Capability Framework: Statistical Use, Statistical Production and Statistical Leadership.

Image: Statistical Capability Framework logo. Subtitle: Understand Statistics, Understand our World.


This tier outlines the main processes required to undertake work in the capability dimensions outlined in Tier 1.

Statistical Capability
Statistical Capability Framework - Tier 2
Statistical Use
Discovering & Assessing - finding sources of information that can help you better understand the issue being studied, and determining whether that information can appropriately inform your analysis or research and/or policy need.
Analysing and Interpreting - using appropriate techniques to find key messages in the data that will help to inform your research and/or policy need.
Communicating - presenting the key messages you have found in the data in a clear and accurate manner. This includes articulating the purpose of your analysis and research and/or policy need and any quality issues or limitations you may have found in the data.
Applying – using the statistical information that has been discovered, assessed, analysed and interpreted to inform the outcome of the research and/or policy need.
Statistical Production
Specifying - articulating the research and/or policy need in detail and then scoping what information is required to address that need and how the necessary data will be obtained and/or collected.
Designing and Building - designing and building the statistical methodologies, IT systems, and business processes that will be used to produce the required statistical information.
Acquiring and Processing - obtaining and/or acquiring the relevant data and applying all processing requirements. This includes documenting associated metadata and assessing data quality at all stages of collection and processing.
Validating and Disseminating - preparing the data outputs for publishing. It involves validating the accuracy of data outputs, ensuring any privacy requirements are adhered to, and statistical outputs are accessible to all relevant stakeholders.
Evaluating - undertaking an evaluation of the end-to-end statistical production process to consider if it was successful, how it may be improved, and/or whether it should be undertaken again.
Statistical Leadership
Positioning - ensuring the ongoing relevance of statistical information by understanding the broader national and international research and/or policy environment and identifying emerging statistical needs and their solutions.
Influencing - shaping the national and international environment in which statistical information and assets are valued to better inform research and/or policy decisions.
Enabling - ensuring the appropriate foundations (including capabilities) and infrastructure are in place to support the generation, management, availability, and use of high quality statistical information.


This tier outlines the capabilities required to undertake work in the areas outlined in Tiers 1 and 2.

Statistical Capability
Statistical Capability Framework - Tier 3 – Statistical Use
Statistical Use
Discovering & Assessing
  • Clearly articulate the aim and purpose of the research and/or policy need.
  • Formulate research questions based on the research and/or policy need.
  • Locate relevant information sources and assess their ability to be linked and/or integrated.
  • Assess the quality of available data sources and determine if they are fit for the users' purpose.
  • Compare quality attributes for different data sources in the context of the research and/or policy need.
  • Negotiate access to administrative or transactional data sources that may or may not require payment, formal agreement, or have other accessibility requirements.
Analysing and Interpreting
  • Understand and apply appropriate techniques to link, integrate or extract relevant information from data sources.
  • Identify the main contributors, relationships, and trends in data.
  • Transform data into tabular or graphical format.
  • Reach a conclusion or prediction based on the extracted information.
  • Understand any relevant statistical models and frameworks used to produce statistical information (e.g. System of National Accounts, Price Indexes, System of Environmental-Economic Accounting, Generic Statistical Information Model, Aust. Statistical Geography Standard, Australian and New Zealand Standard Industrial Classification).
  • Describe key information in both written and visual format.
  • Relate key messages to the research and/or policy issue under consideration.
  • Apply statistical reasoning to support your conclusions/decisions.
  • Describe any data linking or integration that has been undertaken to inform the research and/or policy need.
  • Clearly articulate the limits of the data due to quality implications.
  • Communicate complex concepts and technical issues using easy to understand language to ensure stakeholder understanding of the research and/or policy issue being explored.
  • Develop risk mitigation strategies based on data gaps, or quality issues identified in the analysis.
  • Communicate the decision to be made and/or recommendations to be implemented, including the relevant statistical justification.

Statistical Capability
Statistical Capability Framework - Tier 3 – Statistical Production
Statistical Production
  • Engage and partner with relevant stakeholders to understand the research and/or policy aims of key data users, the concepts to be measured, and the ways the outputs will be used.
  • Negotiate access to administrative or transactional data sources that may or may not require payment, formal agreement, or have other accessibility requirements.
  • Conduct quality assessments on datasets derived from administrative sources.
  • In consultation with stakeholders and using knowledge of available data sources, determine if a statistical project is necessary and feasible.
  • Identify and understand any relevant statistical models and frameworks required for production of information (e.g. Generic Statistical Business Process Model, System of National Accounts, Price Indexes, System of Environmental-Economic Accounting, Generic Statistical Information Model, Aust. Statistical Geography Standard, Aust. and New Zealand Standard Industrial Classification).
  • Develop a collection strategy, prioritise content, establish methodological and quality parameters, and agree on a dissemination strategy.
  • Apply knowledge and understanding of statistical business processes, methodologies, and technologies to ensure fit for purpose outputs.
  • Identify potential quality issues and articulate any impacts on the collection process.
Designing and Building
  • Understand the relevant methodologies and processes required to:
    • Develop a sampling strategy (e.g stratification, frame, coverage, and scope of collection).
    • Design and build collection content (i.e. questions, data items, variable descriptions).
    • Design, build, and test a collection instrument.
    • Develop an editing strategy (e.g. micro- and macro-editing, editing methods and techniques).
    • Develop an imputation strategy (e.g. identifying data items to impute, imputation methods).
    • Develop a data quality strategy (e.g. quality gates).
    • Define and document relevant metadata.
    • Design and test training materials and instructions for the statistical collection.
    • Build and test statistical processing systems.
Acquiring and Processing
  • Initiate contact with providers and obtain access to, or collect data using relevant methods.
  • Document and assess all metadata relating to the quality of the administrative data set or data collection.
  • Extract datasets and apply appropriate data pre-processing tasks.
  • Apply micro- and macro-editing techniques to data to identify potential errors.
  • Identify and resolve inconsistencies between datasets before linkage/integration.
  • Match and clean administrative data records and apply appropriate data linking techniques and methodologies.
  • Apply relevant statistical models where necessary to obtain standard outputs.
  • Derive new data items from existing variables.
  • Apply weighting criteria to sample data to create estimates for the target population.
Validating and Disseminating
  • Identify key issues in the data and dissect or isolate its components to investigate further.
  • Apply analytical techniques to view data from a range of perspectives and/or detect and test relationships between variables.
  • Understand and explain movements in key variables over time and between different subgroups.
  • Confront key statistics with other data sources and explain any differences.
  • Understand and articulate any associated data limitations (i.e. sampling and non-sampling errors, data gaps).
  • Create summary indicators to communicate the statistical stories present in the data.
  • Produce standard outputs informed by any relevant statistical models used.
  • Transform output datasets, commentary, and statistics into dissemination formats.
  • Use relevant metadata to support the evaluation of systems, processes, and procedures.
  • Identify key statistical issues in the collection process and potential impacts on data quality.
  • Assess the business processes of administrative data producers and identify steps in the collection and/or processing stages where data quality can be improved.
  • Test new or updated processes and systems to identify and resolve potential quality issues.

Statistical Capability
Statistical Capability Framework - Tier 3 – Statistical Leadership
Statistical Leadership
  • Undertake environment scanning to understand the broader research and/or policy context, and utilise this understanding to set and review relevant statistical programs with key national and international stakeholders.
  • Apply economic, environment, or social knowledge to manage, implement, and innovate within the statistical process to support improved research and/or policy decisions.
  • Conduct statistical work aligned to the Fundamental Principles of Official Statistics (set out by the United Nations).
  • Establish, maintain and leverage good working relationships with key stakeholders in relevant fields.
  • Contribute to the development of national and international statistical standards, classifications, frameworks, and protocols, and promulgate their use within the wider community.
  • Champion data access and facilitate data sharing across relevant statistical and non-statistical government agencies and organisations.
  • Negotiate agreements on the provision of data (including administrative data) and technical services to agreed timetables and budgets.
  • Assist data custodians to improve data quality at the source by improving metadata standards and implementing relevant classifications to increase coherency.
  • Lead and connect with networks, seminars, and groups of experts across the national and international domain to ensure consistency, coordination and collaboration of activities.
  • Develop and leverage relevant networks.
  • Build the statistical understanding and knowledge of data custodians.
  • Assess and actively develop the statistical capability of users and producers of statistics and facilitate the development of necessary learning resources.
  • Ensure stakeholders know what data is available, understand relevant statistical concepts and simple statistical analyses, and can communicate statistical information effectively.
  • Facilitate the delivery of important national and international statistics to users along with related information to help them understand and apply the data effectively.

If you would like to provide feedback on this draft SCF or would like further information on it, please email The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.

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