1. Resources, plans and prioritisation

1.1 Sufficient resources

Indicator 1.1: Sufficient human and financial resources are provided to produce statistics that meet users’ needs.

The production of statistics that meet users’ needs is dependent on sufficient resources being available and these being deployed effectively. These resources can be in the form of human resources, such as people with the right skills and understanding to collect, process and disseminate the statistics, or financial resources, which enable surveys or data collections that meet users’ need to be conducted. Insufficient resources are likely to be detrimental to one or more dimension of quality and may result in user needs not being met. Insufficient people with the right skills and knowledge may increase pressure on the people that are available to carry out processes, resulting in risks to accuracy, for example through errors being more likely. Insufficient human resources may also lead to a lack of understanding of users’ needs and the quality required of statistics and whether this has been met. There may be a scarcity of staff with the technical knowledge necessary to produce niche statistics, such as National Accounts. It might lead to lack of time for the team to build skills and capability. Insufficient financial resources might mean sample sizes are cut below what is needed to meet required levels of accuracy. It might mean that additional expertise or data cannot be purchased. Finally, it could result in outputs being reduced or ceased altogether.

This indicator is derived from Code practice T4.3 with enhanced emphasis on statistics meeting user needs in line with the focus of this framework. The aspect of the Code practice around technological resources has been included in a later indicator. Both the IMF DQAF and ESS QAF include indicators around ensuring that resources are available to meet statistical needs.

1.2 Good business practices

Indicator 1.2: Good business practices are maintained in the use of resources. Where appropriate, statistics producers take opportunities to share resources and collaborate to achieve common goals and produce coherent statistics.

As well as sufficient resources being made available to meet statistical needs, it is also important that good business practices are maintained in the use of the resources. This will enable the best possible use of those resources to ensure that statistics are produced with the best possible quality. Taking opportunities to share resources and collaborate will enable maintenance and improvement of quality to take place as far the available resources allow. Examples of good business practices might include the use of staff on multiple annual outputs to manage peaks and troughs in resource demands or sharing technical expertise between teams. These practices can also help the coherence of statistics and statistical processes, which in turn enable greater contingencies when resources are constrained as staff do not need to learn multiple different processes for similar statistics.

This indicator is derived from the Code practice T4.4. The ESS QAF also includes indicators around the effective use of resources, cost effectiveness and efficiency.

1.3 Clarity of responsibilities

Indicator 1.3: The responsibility for collecting, processing, quality-assuring and disseminating the statistics is clearly specified.

By being clear on the responsibility for collecting, processing and disseminating data and statistics, it will be clear who is responsible for ensuring the quality of the statistics at each stage. These responsibilities could be split within teams, departments or other organisations or across them. Clarity on who is ensuring quality at each stage ensures the end-to-end quality of the statistics. Making reasons for collecting, processing, quality-assuring and disseminating statistics clear, such as through stating the legal basis for those activities, further ensures quality and supports public confidence in the use of the data. It also ensures that those activities are legal. Public confidence is important in ensuring that people respond to surveys and agree to their data being used, which in turn supports the quality of the data. The legal basis also allows for businesses to be mandated to respond to surveys, which improves response rates, and for data sharing agreements to be made, allowing access to the data for statistical purposes.

This indicator is derived from the IMF DQAF indicator 0.1.1, ‘The responsibility for collecting, processing, and disseminating the statistics is clearly specified’, with the legal basis added in line with indicator 1.2.2, ‘The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.’ Similar indicators are also included in the ESS QAF around the ‘mandate of the statistical authorities to collect and access information from multiple data sources for the development, production and dissemination of European Statistics is specified in law.’ Elements of this indicator are also captured in the Code under T4, Transparent processes and management, and T6, Data governance.

1.4 Suitable systems

Indicator 1.4: Sustainable, robust and flexible systems are used to produce statistics that meet current user needs and enable innovation and improvement.

As technology advances, there is an increasing need for sustainable, robust and flexible systems to ensure that statistics which meet user needs can be produced. As new, and ever-larger, datasets become available, new methods are developed, and new parts of the economy or societal trends need to be measured, it is important that systems are flexible enough to incorporate new data and methods to enable the best-quality estimates to be produced. With increasing use of reproducible analytical pipelines to safeguard the quality of statistics, it is important that the systems on which they are built are sustainable and robust. The move away from statistics being produced in spreadsheets is an important one in terms of quality, but that move is threatened when the systems are not robust, cannot be amended or are not understood by the teams using them.

This indicator is derived from Code practice T4.3 with specific emphasis on technological resources. This indicator arises from an emerging risk that we identified in the first pilots of the Spotlight on Quality programme. In the UK, we are seeing large transformation programmes to modernise the architecture underpinning statistics, but these programmes need to deliver across large numbers of statistical outputs to ensure statistics meet user needs.

1.5 Established development work programme

Indicator 1.5: A development work programme is established, published and regularly reviewed and includes planned improvements to quality.

A published work programme makes clear the plans for improvements to the statistics and helps users understand the developments that are planned for a set of statistics and when they might be implemented. These development plans should include any improvements to quality so that users are aware of the quality issues that are going to be addressed, can plan for any changes to the statistics and understand changes to quality over time and how the statistics meet their needs. Including longer-term quality improvements that will not be addressed in the short term can help users understand the quality of the statistics. A work programme can also support producers in identifying the improvements that need to be made and when they can be implemented. The work programme needs to be regularly reviewed to ensure that it remains up to date and achievable. The level at which the work programme is published will depend on the context. The work programme should be user focused. Sets of statistics with the same or similar user bases might be grouped together, and the development of new sources that will replace, or supplement, a set of statistics should be presented alongside the work programme for those statistics. Where data sources, processes and outputs cut across multiple teams, the work programme should cover the full end-to-end process.

This indicator is derived from the first part of the Code practice T4.2 with the addition of the need for the work programme to be published. Additional wording has been added to make it clear that the work programme should include planned improvements to quality. The IMF DQAF includes indicator 0.4.3, ‘Processes are in place to deal with quality considerations in planning the statistical program.’ The ESS QAF includes indicator 1.5, ‘The statistical work programmes are published and periodic reports describe progress made.’ The reporting of progress is included in a later indicator in this framework.

1.6 User involvement in developing plans

Indicator 1.6: Users and other stakeholders help develop and prioritise statistical plans.

Users and other stakeholders will often know most about whether the statistics are fit for their purpose and meet their needs. They will know the quality issues that have the most effect on them and their use of the statistics. Therefore, users and other stakeholders should be involved in developing and prioritising statistical plans. Different users may have different priorities, but understanding these different perspectives will help producers to understand the effect of prioritising some developments over others.

This indicator is derived from the last part of Code practice T4.2 with the addition of users and stakeholders helping in developing plans as well as prioritising them. The ESS QAF has a similar indicator, 11.2: ‘Priority needs are being met and reflected in the work programme’.

1.7 Transparency of progress towards plans

Indicator 1.7: Statistics producers are open about progress towards meeting development priorities and objectives.

As well as publishing development plans, updating them and involving users and stakeholders in their development, producers should also be transparent about progress towards meeting them. Transparency here will help users understand when changes might be implemented to statistics and the barriers to making them. Discussions around plans and priorities should be an ongoing dialogue to ensure that the statistics can best meet user needs whilst balancing resources and other constraints.

This indicator is derived from the second part of Code practice T4.2. It also features in Code practice V4.1 around being transparent in conducting development activities. The ESS QAF indicator 1.5 includes the requirement ‘periodic reports describe progress made’.

1.8 Transparency of prioritisation decisions

Indicator 1.8 Producers are transparent about prioritisation and how decisions on priorities affect quality.

Constraints such as resources, time, availability of data sources and systems mean that producers have to make decisions about what to prioritise. Sometimes these decisions will be within the team producing a set of statistics. Sometimes they will be across statistical outputs or even organisations. Each development will have different effects on quality and the ability of the statistics to meet user needs. Producers should be transparent about where they have taken prioritisation decisions, how those decisions have been made and what effect the prioritisation has had on all the statistics involved. This enables more-informed discussions with stakeholders about priorities in ensuring quality.

This indicator is derived from the third part of Code practice T4.2 and has been developed from learning from our pilot assessments and in discussion with stakeholders. It was apparent that it is not always clear what decisions have been made about priorities and the effects on quality. The effects on quality of these decisions were significant enough for us to include an indicator on this specifically.