1.1

Position

These activities ensure that statistical organizations understand the environment in which they operate and the emerging issues they are confronted with, so it is clear where they can provide independent, evidence-based information, as well as statistical standards and infrastructure, for use by governments and the broader community. Based on this, statistical organizations determine their high-level goals and directions, including the values which will guide them, so they set their programmes accordingly. It also includes communicating the mission, values and expectations internally and externally, to lead and inspire staff and to increase government and community trust and confidence in the organization and in official statistics in general.

• Understand national & international directions & factors
• Determine organizational vision & values
• Determine organizational value proposition
• Determine organizational goals
• Communicate values & expectations

1.2

Govern

These activities cover the development of strategies to achieve the goals and directions set under Position. They include identification and prioritization of the statistical work programme, prioritization of the capital investment programme, and the allocation of resources (capital and labour) to implement the agreed programmes defined in the statistical and capability portfolios.

• Develop strategies for achieving organizational goals
• Prioritize statistical portfolio
• Prioritize capability portfolio
• Allocate portfolio & programme budgets
• Build & maintain internal statistical & professional excellence

1.3

Influence & collaborate

These activities cover liaison and coordination with other statistical organizations. They can include coordination within a statistical system, which may be based on a geographical hierarchy of entities (local, regional, national, multi-national), or a functional split of responsibilities between organizations. They also include activities undertaken to identify opportunities for data exchange or data integration. They also provide the statistical community with opportunities to exchange knowledge, improve statistical infrastructure and practices and influence statistical standards. These activities also help to build and enhance statistical capability in the external environment, leading to increased statistical understanding and improved application and use.

• Build & maintain strategic relations, nationally & internationally
• Build & maintain external statistical excellence
• Advance inter-agency & international collaborations
• Secure support for statistical & capability portfolio

2.1

Plan capability improvements

These activities plan the best way forward to improve an organization's capabilities. They require a thorough organizational view of possible improvements, supporting the prioritization of options through an efficient, iterative approval process until a work programme for capability improvements is finalized. These activities further coordinate the planning and resourcing of crosscutting / reusable capability improvement projects (both large and small), to ensure key improvement work is integrated across the organization, with interdependencies understood and the resources optimized across programme. These activities also monitor the ongoing progress of the work programme and report to the relevant governance fora to ensure all required change requests occur in an efficient and effective manner.

• Identify 'disruptive' & other capability improvements
• Propose capability improvement projects, including shared infrastructure
• Manage capability improvement programmes

2.2

Develop capability improvements

These activities progress approved improvement projects from the requirements stage through to their completion. The developers will undertake research, define the detailed requirements, coordinate the design and building, and finalize all aspects of the capabilities being developed, including their deployment for operational use. Whilst the development of capability improvements that concern multiple statistical business processes are included here, capability improvements in the context of a single statistical business process are included in 4.1.3 "Build"

• Undertake background research
• Develop detailed capability requirements
• Design capability solution
• Build & release capability solution, including shared infrastructure
• Manage capability development project

2.3

Manage capabilities

These activities take responsibility for managing organizational capabilities, ensuring the organization reaps maximum benefits from investments and can better manage quality. They involve maintaining capabilities, evaluating and improving them or suggesting where improvements are required. Data, metadata and process data (paradata) management are also included here. Staff undertaking these activities effectively become the custodians / reference persons for the capabilities, taking responsibility for their fitness for purpose.

• Maintain capabilities, including shared infrastructure
• Promote capabilities
• Evaluate capabilities
• Manage data, metadata and process data
• Manage quality

2.4

Support capability implementation

These activities provide the technical hands-on assistance required across the organization, in particular, supporting the Development and Implementation of statistical production. These activities also guide the successful operation of individual reusable business processes.

• Support design
• Support operations
• Support use externally

3.1

Manage business & performance

These activities manage how the organization conducts its business, including agreed changes to the business, in order to achieve planned outputs and outcomes.

• Manage business performance
• Manage change and risk
• Manage legislation & compliance
• Manage physical assets, including building facilities

3.2

Manage finances

These activities cover the organization's ongoing use of financial and accounting information to measure, operate and predict the efficiency and effectiveness of its activities, including procurement and contracts, in relation to the organization's goals and objectives.

• Maintain accounts (including assets & liabilities)
• Manage procurement & contracts

3.3

Manage human resources

These activities cover employee performance, recruitment, skills development, talent management and succession planning work.

• Manage employee performance
• Manage & develop skills
• Manage talent
• Manage recruitment
• Ensure succession planning

3.4

Manage IT

These activities cover coordination and management of information and technology resources and solutions. They include the management of the physical security of data, but not the management of statistical confidentiality.

• Manage IT services
• Manage IT & information security

3.5

Manage information & knowledge

These activities cover the ownership or custody of records, documents, information and other intellectual assets held by the organization and the governance of information collection, arrangement, storage, maintenance, retrieval, dissemination and destruction. They also include maintaining the policies, guidelines and standards regarding information management and governance.

• Manage documents & records
• Manage knowledge
• Manage information standards & rights

3.6

Manage consumers and suppliers

These activities cover the management of communication and exchanges between governmental institutions, the public and other stakeholders in direct or indirect support of organizational services. They therefore deal with the relationships between statistical organizations and the public, including those via the media. This includes measures to educate and inform users so that they fully understand statistical outputs, and to improve levels of statistical literacy in society in general.

• manage communications and media relations
• Manage stakeholder consultations
• Educate users and improve statistical literacy
• Manage cross-product user support

4.1

Develop

These activities define the detailed scope and solution for the production process or cycle, including sample and questionnaire design where relevant. They also cover the assembly and configuration of statistical capabilities and services and testing of the production system.

4.1.1

Specify needs

These activities are triggered when a new statistical need is identified, or feedback about a current statistical product or service initiates a review. They seek to understand the context around the identified need or change and user motivations. Specifically, the organization researches, confirms and documents user needs, and researches, assesses and proposes high-level options for addressing these needs, after assessing available data, methodologies, standards and frameworks and constraints. The scoping-related activities are generally sequential but can also occur in parallel and can be iterative. The scoping work is generally done to a level sufficient to prepare a business case, which presents arguments to proceed to the Design stage. The business case typically identifies the reasons for the proposed activity, its financial and social justifications, initial risks and issues, cost-benefit information, and the preferred high level solution and broad plan for proceeding.

• Identify needs
• Consult & confirm needs
• Establish output objectives
• Identify concepts
• Check data availability
• Prepare business case

4.1.2

Design

These activities describe development and design activities and any associated practical research work needed to define the statistical outputs, concepts, methodologies, collection instruments and operational processes. These activities include all the design elements needed to define or refine the statistical products or services identified in the business case. They also specify all relevant metadata, ready for use later in statistical business process, as well as the quality assurance procedures. For statistical outputs produced on a regular basis, these activities usually occur for the first iteration, and whenever improvement actions are identified in the Evaluate activities of a previous iteration. Design activities make substantial use of international and national standards, in order to reduce the length and cost of the design process, and enhance to comparability and usability of outputs. Organizations are also encouraged to reuse or adapt design elements from existing processes. Additionally, outputs of design processes may form the basis for future standards at the organization, national or international levels.

• Design outputs
• Design variable descriptions
• Design collection
• Design frame & sample
• Design processing & analysis
• Design production systems & workflows

4.1.3

Build

These activities build and test the production solution to the point where it is ready for use in the "live" environment. The outputs of the Design activities direct the selection of reusable processes, instruments, information, and services that are assembled and configured to create the complete operational environment to run the process. New services are built by exception, created in response to gaps in the existing catalogue of services sourced from within the organization and externally. These new services are constructed to be broadly reusable within the statistical production architecture. For statistical outputs produced on a regular basis, these activities usually occur for the first iteration, or following a review or a change in methodology or technology.

• Build collection instrument
• Build or enhance process components
• Build or enhance dissemination components
• Configure workflows
• Test production system
• Test statistical business process
• Finalize production system

4.2

Implement

These activities realize the designed production process (value chain) from the initial data sources to the statistical information products. Each step takes data and metadata as inputs and produces data and metadata as outputs.

4.2.1

Collect

These activities collect or gather all necessary information (data and metadata), using different collection modes (including extractions from statistical, administrative and other non-statistical registers and databases) and load them into the appropriate environment for further processing. Whilst they can include validation of data set formats, they do not include any transformations of the data themselves, as these are all done in Process. For regular statistical outputs these activities are undertaken for each iteration.

• Create frame & select sample
• Set up collection
• Run collection
• Finalize collection

4.2.2

Process

These activities describe the cleaning of data and their preparation for analysis. They include checking, cleaning, and transforming input data, so that they can be analysed and disseminated as statistical outputs. The activities may be repeated several times if necessary. These activities can apply to data from both statistical and non-statistical sources (with the possible exception of Calculate weights, which is usually specific to survey data).
. The Process and Analyse activities can be iterative and parallel. Analysis can reveal a broader understanding of the data, which might make it apparent that additional processing is needed. The Process and Analyse activities may commence before the Collect activity has been completed. This enables the compilation of provisional results where timeliness is an important concern for users, and increases the time available for analysis.

• Integrate data
• Classify & code
• Review & validate
• Edit & impute
• Derive new variables & units
• Calculate weights
• Calculate aggregates
• Finalize data files

4.2.3

Analyse

These activities produce and examine statistical outputs in detail and make them ready for dissemination. They include preparing statistical content (including commentary, technical notes, etc.) and ensuring outputs are fit for purpose prior to dissemination to customers. This activity group also includes the sub-activities that enable statistical analysts to understand the statistics produced. For regular statistical outputs, these activities are undertaken for each iteration. Analyse activities are generic for all statistical outputs, regardless of how the data were sourced.

• Prepare draft outputs
• Validate outputs
• Interpret & explain outputs
• Apply disclosure control
• Finalize outputs

4.2.4

Disseminate

These activities manage the release of statistical products to customers. They include all activities associated with assembling and releasing a range of static and dynamic products via a range of channels. They also support customers to access and use the outputs released by the statistical organization.

• Update output systems • Produce dissemination products
• Manage release of dissemination products
• Promote dissemination products
• Manage user support

4.3

Review

These activities review the production process to ensure it meets the expectation and needs of users and the organization

4.3.1

Evaluate

These activities manage the evaluation of a specific instance of a statistical business process, as opposed to the more general over-arching process of statistical quality management described in 4.4 – Manage. They logically take place at the end of the instance of the process, but rely on inputs gathered throughout the different activities. They include evaluating the success of a specific instance of the statistical business process, drawing on a range of quantitative and qualitative inputs, and identifying and prioritising potential improvements. For statistical outputs produced regularly, evaluation should, at least in theory occur for each iteration, determining whether future iterations should take place, and if so, whether any improvements should be implemented. However, in some cases, particularly for regular and well established statistical business processes, evaluation may not be formally carried out for each iteration. In such cases, these activities can be seen as providing the decision as to whether the next iteration should start from Specify Needs, or from Collect.

• Gather evaluation inputs
• Conduct Evaluation
• Agree an action plan