1. Standard Process Steps in Statistics Robbert Renssen rrnn@cbs.nl Statistics Netherlands Robbert Renssen and Astrea Camstra, Statistics Netherlands

2. Outline of the Presentation 1.Standard Process Steps i.Why ii.Future situation iii.State of research iv.Example a function and a process v.Relation IAF

3. Standard Process Steps in Statistics 2 Why Management of ‘long-term’ changes From business targets to ‘ideal’ situation (represented by architectural principles) From ‘ideal’ situation to project targets From project targets to (physical) solutions (e.g. standard tools, process descriptions)

4. Standard Process Steps in Statistics 3 High level architecture of SN  GSBPM Statistics Production Chain Management Design Central Storage of data to be exchanged

5. Standard Process Steps in Statistics 4 Process modelling in practice Process models are very diverse (specific problems and solutions, terminology and so on) Applications of statistical methods are not recognized Applications of statistical methods and/or tools need preparatory activities Re-use of data and mixed mode strategies complicate the activities in a process Happy and unhappy process flows are entangled

6. Standard Process Steps in Statistics 5 Future situation (happy flows) Data Service Centre Legend Business service Standard process step Statistical dataset IT-tool Alignment Desision step

7. Standard Process Steps in Statistics 6 The state of research The current process models of a (large) number of processes have been collected (and studied) A general framework is formulated The process of the Short Term Statistics has been modelled in accordance with this framework The data validation function is worked out and illustrated by practical examples The error localisation and matching function are under construction (also a few non-statistical functions)

8. Standard Process Steps in Statistics 7 Example of the data validation function Black Box (statistical method) Edit: IF marital status = ever married THEN age > 17 Age [0,1,2,..120) Marital Status (single, ever married) Q-indicator (passed, failed) Distinction between the nature of a function and its use: domain edits, hard edits, soft edits, systematic edits (signs, 1000, Euro), relation edits, macro edits, and so on

9. Standard Process Steps in Statistics 8 Example of a (small) process Input population (a) Unit (a) Apply Data Validation Function Apply Variable Derivation Function Population (a,q) (in progress) Unit (q) Population (a,q) (in progress) Unit (a  q) Population (a,b,q) (in progress) Unit (b) Ready? Output population (a,b,q) Yes No, next unit

10. Standard Process Steps in Statistics 9 Examples of Statistical functions Data Validation Function Variable Derivation Function Error Localisation Function Error Correction Function Imputation Function Matching Function Estimation Function

11. Standard Process Steps in Statistics 10 BusinessInformation Systems Technical Infrastructure Contextual Conceptual Logical Physical Technical facilities Functionality & Usability Information needsBusiness concepts Hardware & System Software Components Application Components Communication patterns Organisational Structure & Procedures Products & Tools Bespoke Software & Settings Information Storage and Exchange Operations IAF Vision & Strategy Principles Standards Trends & developments Governance Security

12. Standard Process Steps in Statistics 11 Thank You

13. Standard Process Steps in Statistics 12 Statistical Method Design of Statistical Process Design of Process Flow Statistical Function Planning Set of Conceptual Attribute Variables Statistical Target Set of Physical Attribute Variables Statistical Strategy Glimpse of our framework Set of Operational Attribute Variables