CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Statistical Business Process in the Czech Statistical Office Joint UNECE/EUROSTAT Workshop on Metadata (METIS) Geneva October 2011 Session IV: The GSBPM and Process Quality Management Ebbo Petrikovits

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 2 Content of the presentation  I. Statistical business process implemented in the CZSO  II. Process quality management  III. SMS modules used in the CZSO  IV. Lessons learned  V. Conclusion

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic I. SBP in the CZSO Brief History (1)  2005 – 2006  SMS Vision approval by the top management of the CZSO; SMS Project launched;  CLASS specifications prepared and accepted;  VAR specifications prepared and accepted;  Preparation of the CZ-SBPM and its approval;  TASKS specifications prepared and accepted (based on the CZ-SBPM);

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Brief History (2)  2007 – 2010  The TF 2006 Project for the TASKS sub- system was launched (design, development and implementation);  Development and tests of the CLASS and VAR applications;  The CLASS and VAR applications have been set up in production regime;  The IOP Redesign of SIS Project launched  Development and tests of the TASKS application

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Brief History (3)  2011  Regular use of the CLASS and VAR applications  Description of statistical tasks of STS and SBS  Description of other statistics (energy, culture, science and technology development, etc.)  Description of administrative data from the CNB  IOP Redesign of SIS Project specification preparation

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Content of the CZ-SBPM  Developed in spring 2006  Proposed 6 phases of the SBP:  A – Requirements  B – Preparation of statistical task  C – Elaboration of technical and organizational specifications of a statistical task  D – Preparation of statistical task processing  E – Data collection and data processing  F – Dissemination of statistical information

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic CZ-SBPM – GSBPM Comparison CZ-SBPMGSBPM A – Requirements1 – NEED B – Content preparation of ST 2 – DESIGN C – Technological preparation of ST D – Preparation of ST processing E – Collection and processing 3 – COLLECT 4 – PROCESS 5 – ANALYZE F - Dissemination7 – DISSEMINATE 8 – ARCHIVE 9 – EVALUATE

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Differences  Time of development  CZ-SBPM - in beginning of 2006  GSBPM - in 2009  Aim of the development  CZ-SBPM - to prepare base for design of metadata for the SMS module TASKS  GSBPM – to prepare a comprehensive handbook on statistical business process  Authors of the SBPM  CZ-SBPM – the CZSO experts  GSBPM – statistical community under the METIS WS of the UNECE  Users  CZ-SBPM – users inside the CZSO  GSBPM – statistical community under the umbrella of the UNECE

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic Our conclusions from the comparison (1)  On one hand (advantage)  we have had the first complete document describing SBP, officially accepted by the top management  the SBPM has introduced common terminology, which would be used by statisticians and IT experts  the SBPM has been used for derivation of metadata for the sub-system TASKS specifications  the SBPM has helped us in discussion on administrative data transformation for statistical purposes

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 10 Our conclusions from the comparison (2)  On the other hand (disadvantage)  phases of our model were not well balanced  we focused mainly on Design and Build phases (due to using for TASKS specifications)  we underestimated the Collect and Process phases (we put them in one phase)  we did not solve the Archive phase as an independent phase  the Evaluate phase we (knowingly) left out (opinions on this phase were controversial)

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 11 Final conclusion  We revised our CZ-SBPM and made the decision to replace our model with the GSBPM  For further activities we would use the GSBPM  But we still see a need for incorporation a part handling administrative data into the model  This sub-process becomes more and more significant in statistical processing, it will replace surveys in many statistical tasks  The content of this sub-process contains completely different activities against survey activities, especially when we work with metadata from the beginning of the SBP

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 12 Use of the GSBPM in our practice  Feasibility study for the IOP Project Redesign of SIS was based on the GSBPM  Design of the SIS architecture according to the GSBPM  Based on the phases and sub-processes of the GSBPM the SIS sub-systems and their functional blocks were designed  Next several slides show practical use of the GSBPM

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CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 14

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 15 Sub-system INPUT

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 16 II. Process Quality The CoP Principles of process quality (1)  Principles/criteria for institutional environment  Professional independence  Mandate for data collection  Adequacy of resources  Quality commitment  Statistical confidentiality  Impartiality and objectivity

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 17 Process Quality Institutional Environment  The statistical act comprises the principal answers to the IE criteria  Comparing the Czech act on state statistical service we may give positive answers to all six criteria  It means that institutional conditions for official statistics are primary provided by law  Nevertheless we should examine what is the quality of our communication of the IE conditions to the users a and respondents

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 18 Process Quality The CoP Principles of process quality (2)  Principles/criteria of individual sub-process  Sound methodology  Appropriate statistical procedures  Non-excessive burden of respondents  Cost effectiveness

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 19 Process Quality Sound Methodology  Basic sources of statistical methodology are  Official documents of the UN  Regulation of the EU/EC  Internal official document of the NSI  We should examine  Quality of correct transformation of the official documents into internal instructions, handbooks and manuals for the NSI staff responsible for preparation and processing of a statistical task  Quality of instructions for respondents  How  organize internal surveys on documentation quality  Organize inquiries at respondents on the understandability of the instructions for filling in the questionnaires

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 20 Process Quality Appropriate statistical procedures  This criterion expresses the rate of transformation of sound methodology into right described procedures for preparation and processing of a statistical task  For measurement it we can specify for example following attributes  Manuals ant tools for questionnaires design and creation  Manuals for description of statistical tasks  Manuals for validation rules specifications  Procedures for transformation of administrative data for statistical purposes (transformation of administrative variables into statistical variables)

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 21 Process Quality Non-Excessive Burden on Respondents  Very important criterion in time being  We use in our practice following attributes for measurement the response burden  On questionnaires  Number of approached respondents  Percentage of entrepreneurs  Amount of filled-in items in the questionnaire  Estimated time for filling in a questionnaire  Periodicity of submitting the questionnaires  On statistical task (rate in %)  Category A - content and form defined by the EU regulation  Category B – content defined by the EU regulation, form set up by the NSI  Category C – content and form defined by the NSI

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 22 Process Quality Cost Effectiveness  Proposal of suitable characteristics (attributes) for measurement cost  Rate of automated and manual operations  Recording of scheduled start/end time and actual start/end time of all activities  Recording of time consumptions of  staff for selected activities  applications or sub-processes

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 23 III. SMS modules in CZSO practice Statistical Tasks – brief description  Goal of the TASKS sub-system: full description of a statistical task via metadata from the various aspects:  content (variables, statistical units, code-lists)  functions (validation rules, response duty, aggregation algorithms)  structures (questionnaires and their components)  outputs (specifications, layout)  organization (workplaces, timetables)

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 24 Statistical Tasks - Objects  Objects  Statistical task  Data structure components (DSC)  Validation rules  Reporting duty specification  Timetable  Document  Program module  Program run 24

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 25 Statistical Tasks – DSC  DSC:  Super-questionnaire  Combined questionnaire  Simple questionnaire  Annex  Enclosure  Section  Section variant  Super-section 25

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 26 STATISTICAL TASK HIERARCHY Statistical Task Super-Questionnaire Combined QuestionnaireQuestionnaire EnclosureAnnex Q-headingSectionSection variant TimetableProgram run Document Timetable stepProgram module Validation Rules Report. duty Super-section Computational dimension Computational object Aggregation types

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 27 Use of the TASKS metadata  For sub-system INPUT  Graphical editor for questionnaire design  Validation rules translator  Technical documentation compiler  Data entry application compiler  For sub-system CENTRAL  Output table definition translator  Generator of table aggregates

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 28 IV. Lesson learned (1)  GSBPM  Useful and practical guidance supporting  Implementation of concrete statistical process  Analysis of individual phases and sub-processes  Is an open model allowing extension with additional more detailed levels  Is not a dogma, it allows selection of needed phases, sub-processes or activities for practical use in concrete statistical task

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 29 Lesson learned (2)  GSBPM - areas of use  Analysis of sub-processes  Derivation of suitable application needed for implementation  Derivation of metadata for description of various features of sub-processes or activities (including process quality) and metadata for application descriptions  Effectiveness analysis of sub-processes or activities and procedures specifications for their interpretation

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 30 Lesson learned (3)  Process Quality  We should focus on four criteria specified by the CoP  Find out adequate metadata describing individual criteria  Specify the right locations in sub-processes (in applications) for automated recording of the attributes values  Design of appropriate procedures for evaluation of measured attributes on process quality

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 31 V. Conclusion  The GSBPM we consider it an useful and practical handbook for statisticians and IT experts  The model describes in detail main phases and sub-processes of the statistical business process  We recommend it for practical use in everyday statistical practice

CZECH STATISTICAL OFFICE Na padesátém 81, CZ Praha 10, Czech Republic 32 Thank you for your attention