Standard Process Steps in Statistics

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

2. Standard Process Steps • Why • Future situation • State of research • Example a function and a process • Relation IAF Outline of the Presentation

3. 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) Standard Process Steps in Statistics

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

5. 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 Standard Process Steps in Statistics

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

7. 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) Standard Process Steps in Statistics

8. Example of the data validation function Edit: IF marital status = ever married THEN age > 17 • Age [0,1,2,..120) • Marital Status (single, ever married) Q-indicator (passed, failed) Black Box (statistical method) 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 Standard Process Steps in Statistics

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

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

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

12. Thank You Standard Process Steps in Statistics