Modernization Working Group (SAB-AP Meeting)

Transcription

1 Modernization Working Group (SAB-AP Meeting) Applying GSBPM in the National Enterprise- Wide Statistical Systems (NEWSS ) DEPARTMENT OF STATISTICS MALAYSIA 2 December NEWSS - Vision An integrated statistical system framework for common system across DOSM BEFORE AFTER Silo Environment Obsolete Technology Non Integrated Environment Non Uniform Platform & Application Integrated Statistical System Framework Information Support System New Technology Centralized Repository Slide 2 1

2 Integrated Statistical Systems Framework Source : DOSM 3 NEWSS INTERFACE 4 2

3 1 Census/Surveys Profile 2 Pre Data Collection 3 Data Collection Modules in NEWSS Access project profile details for the planned/ implementing/ implemented census/surveys with their details activities. Access pre details i.e. scope of coverage for establishment census/surveys and sampling details. Access process details including the assignment of officers and field enumerator to sample case, capturing the operational control and operational visit information. Capturing the census/survey data, secondary data, process the batch file with census/survey data from offline data entry module. Access the link to enable (first installation) the offline data entry module on local workstation. 4 Data Processing Configure the data cut off date for economy surveys and survey data cut off period for monthly manufacturing survey. For surveys with probability sampling, capturing the related data required for weighted data processing and processing of the weighted data. 5 Modules in NEWSS Manage product, catalog, advance release calendar, customized request, data request, customer services, external user account, subscription and feedback. 5 Dissemination 6 Sampling 7 Enterprise / Establishment Frame Track the total transactions, delivery on hardcopy/cds, notification recipients. Log the notifications sent on subscription expiry and catalog release. Maintain the related reference of products, delivery zone and cost table, currency exchange rate, service charge and government service tax. Perform the details process on sample generation. Perform the selection of living quarter for field work. Maintain the enterprise/establishment frame, screening information, other agencies information (ROC, ROB, CIDB, KWSP). Manage the duplication of enterprise/establishment and duration of the new establishment. 6 3

4 8 Report Access to the ISSF reports and KMS reports. 9 Code & Classification Modules in NEWSS Maintain the standard code and classification for social demographic and economy. 10 Metadata Maintain data dictionary that describe the data available in DOSM Central Repository and Other Agencies Database. Generate the review tables for SSE and Monthly Manufacturing survey. 11 Business Intelligence 12 Knowledge Management System (KMS) 13 Evaluation Generate the tabulation for publication on SSE, MM and PTB. Provide the dynamic analysis capabilities on the data available, used to serve the data request. Access to the forum, Q&A, FAQ and Contact Us information. Performance management solution in measuring the performance of the objectives on strategy map via the Key Performance Indicators. 7 Mapping to GSBPM Pre Collection Processing Analysis Pre Collection Processing Analysis Specify Needs Build Collect Process Analyse Dissemination Monitoring & Quality Assurance Dissemination Monitoring & Quality Assurance Disseminate Archive Evaluation 8 4

5 Survey Process in the NEWSS environment A Pre-Collection E Dissemination B Collection A PLATFORM Statistical Environment D Analysis C Processing The technically capable The professionally informed Everyone else 9 Specify Need Build Identify requirement from user Users and stakeholders requirement taken into account Concepts identified are internationally comparable, revised when necessary to ensure align with international standards. These include definitions, codes (MCPA, MSIC) and manual (e.g. SNA) Variable descriptions determined by user, follow international standards data Population of interest is identified Frame sources from Malaysia Statistical Business Register (MSBR), Malaysia Statistical Address Register (MSAR) Build data instrument based on specifications. Multiple modes of data used questionnaire : face to face interview, mail, CATI and e survey. Workflows configured include all activities from data, right through to archiving the final statistical outputs. Testing of computer systems and tools conducted thoroughly to ensure the interactions between modules involved works as a coherent set of modules. 10 5

6 Collect Process Analyse Sample selected from sampling frame Strategy, planning and training activities prepared and conducted in compliance with MS ISO procedures Data collected stored automatically in the system for further processing phase Input data classified and coded within the system Errors and data discrepancies (outliers, non response & miscoding) identified and validated within the system Imputation routines done automatically by the system for non response cases, according to pre defined methods. Estimation of the sample survey using sampling weight to be representative of the target population. Data collected transformed into statistical outputs Validating the outputs produced, in accordance with the quality check procedures described in the MS ISO 9001:2008 Improvement in carrying out indepth statistical analysis to assess how well the statistics reflect the initial expectations Output finalized after the completion of relevant processes (consistency checks, determine level of release, collating supporting information, etc) and reached the required quality level 11 Disseminate Archive Evaluate System updated regularly parallel to the completion of data processing at time stipulated by user Press release of the products uploaded to the website at the embargo time and also on stipulated date in the Advance Release Calendar (compliant to SDDS) Promotion of the products is done through website (latest statistical release) Customer queries and satisfactions are monitored based on quality assurance document to ensure responses are provided within agreed deadlines and follow specified workflow. Standard archive rules need to be determined and established in order to ensure data and metadata resulting from the statistical business process are archived systematically and efficiently. Archive repository for data and metadata is currently not available. Data and metadata are stored in the system, but in two (2) different modules. Sub process 8.3 and 8.4 are not yet fully implemented for Monthly Manufacturing Survey data. Evaluation inputs include feedback from users, staff suggestions and also internal audit. which is conducted periodically by internal auditor Audit Committee was formed to monitor the quality of all statistical business process involved in producing the outputs. The evaluation report will become the basis for decision in monitoring the quality of the outputs. 12 6

7 CHALLENGES 1. Metadata management i. database environment ii. stored together with data iii. availability based on users needs iv. exchange and use infrastructure 2. Strengthening and empowerment of statisticians skills and ability in scrutinizing and analyzing the statistics produced. 3. Needs to define and determine archive rules/procedures for statistical data and metadata resulting from a statistical business process. 13 CONCLUSIONS Department of Statistics Malaysia is committed to standardize its production environment and will continue to expand and improve its common toolbox based on the needs of the surveys carried out. Personnel from all SMDs will be included in the initiatives of modernization of statistical products and services, particularly in adopting the GSBPM in every statistical business process 14 7

8 Thank You Terima Kasih Specify Needs 2 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 8 Archive 9 Evaluate 1.1 Determine needs for information 2.1 outputs 3.1 Build data instrument 4.1 Select sample 5.1 Integrate data 6.1 Prepare draft outputs 7.1 Update output systems 8.1 Define archive rules 9.1 Gather evaluation inputs 1.2 Consult and confirm needs 2.2 variable descriptions 3.2 Build or enhance process components 4.2 Set up 5.2 Classify and code 6.2 Validate outputs 7.2 Produce dissemination products 8.2 Manage archive repository 9.2 Conduct evaluation 1.3 Establish output objectives 2.3 data 3.3 Configure workflows 4.3 Run 5.3 Review, validate and edit 6.3 Scrutinize and explain 7.3 Manage release of dissemination products 8.3 Preserve data and associate metadata 9.3 Agree action plan 1.4 Identify concepts 2.4 frame and sample 3.4 Test production system Impute 6.4 Apply disclosure control 7.4 Promote dissemination products 8.4 Dispose of data and associated metadata 1.5 Check data availability 2.5 statistical processing 3.5 Test statistical business process 5.5 Derive new variables and statistical units 6.5 outputs 7.5 Manage user support 1.6 Prepare business case 2.6 production systems and workflow 3.6 production system 5.6 Calculate weights 5.7 Calculate aggregates 5.8 Generic Statistical Business Process Model Version data files 16 8

9 1 Specify Needs 1.1 Determine needs for information 1.2 Consult and confirm needs 1.3 Establish output objectives 1.4 Identify concepts 1.5 Check data availability 1.6 Prepare business case Needs for information identified and determined by Subject Matter Division (SMD) concerned, align with international practices Users and stakeholders requirement taken into account. Main stakeholders for MM statistics MITI, EPU, SMIDEC, MIDA, BNM Concepts identified are internationally comparable, revised when necessary to ensure align with international standards. These include definitions, codes (MCPA, MSIC) and manual (e.g. SNA) Checking and assessment on data gaps and availability done regularly based on user requirements Business case prepared align with the monitoring and quality assurance policy (Malaysia Standard (MS) of ISO 9001:2008) outputs 2.2 variable descriptions 2.3 data 2.4 frame and sample 2.5 statistical processing 2.6 production systems and workflow Detailed design of the statistical outputs to be produced - Functional Specification (FDS). Variable descriptions determined by SMD, follow international standards Sub-processes identified and determined by SMD questionnaire (face to face interview) and e-survey (online data entry) Population of interest identified and specified by Methodology Management Division. Frame sources from business registers, census and sample surveys. Sub-process 2.5 specifications prepared by SMD Production systems and workflow implemented and documented align with MS ISO 9001:2008 requirement 18 9

10 3 Build 3.1 Build data instrument 3.2 Build or enhance process components 3.3 Configure workflows 3.4 Test production system 3.5 Test statistical business process 3.6 production system Data instrument built based on specifications created during phase 2 (). Multiple modes of data used questionnaire : face to face interview, facsimile, and e-survey. Enhancement of existing system occurs in NEWSS Phase III, includes Force Accept Report, Question 2 Layout display, time out session for e-survey & Flow Registration for e-survey. Workflows configured include all activities from data, right through to archiving the final statistical outputs. Testing of computer systems and tools conducted thoroughly to ensure the interactions between modules involved works as a coherent set of modules. Comprehensive documentation (URS, BP, FDS) accessible easily by users through intranet. Training on how to operate the system conducted for all users (internal and external) Collect 4.1 Select sample 4.2 Set up 4.3 Run 4.4 Sample selected from business frame established in sub process 2.4 ( frame and sample ). Compliance with MS ISO procedures : Technical Instructions (JPSP-AK-PP-02) Strategy, planning and training activities prepared and conducted in compliance with MS ISO procedures (JPSP-PK-04 & JPSP-AK-SPB-01) Data Collection monitored through Operational Information Control (MKO) module where response rate and data mode reported at real time basis. Records of when and how providers were contacted are also included. Data collected stored automatically in the system for further processing phase. However, metadata are stored in different module. Data entry either done manually or via e- survey

11 5 - Process 5.1 Integrate data 5.2 Classify and code 5.3 Review, validate and edit 5.4 Impute 5.5 Derive new variables and statistical units 5.6 Calculate weights 5.7 Calculate aggregates 5.8 data files Data collected via paper questionnaires and e-survey are matched and linked automatically in the system. The process takes place at real time based, regardless of whether the data has been completed or not. Input data classified and coded within the system, where coding routines done according to a pre-determined classification scheme prepared by the SMD. Errors and data discrepancies (outliers, non-response & miscoding) identified and validated within the system, run iteratively based on predefined edit rules. Imputation routines done automatically by the system for non-response cases, according to pre-defined methods. Imputed cases are flagged by the system Process (cont d) 5.1 Integrate data 5.2 Classify and code 5.3 Review, validate and edit 5.4 Impute 5.5 Derive new variables and statistical units 5.6 Calculate weights 5.7 Calculate aggregates 5.8 data files Arithmetic formulae applied in the system to derive new variables from variables already present in the dataset, i.e. principal statistics (Sales Value of Own Manufactured Products, Number of Employees and Salaries & Wages) The calculation method of weights and aggregates are provided in the system in order to gross-up sample survey results to be representative of the target population. Final data files stored automatically in the system and ready to be used as input for Phase 6 Analyze

12 6 Analyse Data collected transformed into statistical outputs, to indicate the latest trends of manufacturing sector and compiled for the production of Industrial Production Index. 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Scrutinize and explain 6.4 Apply disclosure control 6.5 outputs SMD responsible in validating the outputs produced, in accordance with the Quality Check procedures described in the MS ISO 9001:2008 quality document (JPSP-06-AK-SPB- 01 & JPSP-06-AK-SPB-02). Improvement in carrying out in-depth statistical analysis is an essential aspect to be taken into account especially in assessing how well the statistics reflect the initial expectations. Data Dissemination Policy and Statistics Act established for the purpose of protecting the confidentiality of the data and metadata released. Output finalized after the completion of relevant processes (consistency checks, determine level of release, collating supporting information, etc) and reached the required quality level Disseminate System updated regularly parallel to the completion of data processing at time stipulated by SMD. Data and metadata are stored automatically in the system for dissemination purposes. 7.1 Update output systems 7.2 Produce dissemination products 7.3 Manage release of dissemination products 7.4 Promote dissemination products 7.5 Manage user support In the case of MM Survey, products are disseminated in the forms of printed publications, tables and also charts in the web site (Statistical Release). Press release of the products uploaded to the website at the embargo time and also on stipulated date in the Advance Release Calendar (compliant to SDDS). Promotion of the products is done through website (Latest Statistical Release). Customer Queries and Satisfactions are monitored based on quality assurance document (JPPS-PK-07) to ensure responses are provided within agreed deadlines and follow specified workflow

13 8 Archive 8.1 Define archive rules 8.2 Manage archive repository 8.3 Preserve data and associate metadata 8.4 Dispose of data and associated metadata Standard archive rules need to be determined and established in order to ensure data and metadata resulting from the statistical business process are archived systematically and efficiently. Archive repository for data and metadata is currently not available. Data and metadata are stored in the system, but in two (2) different modules. Sub-process 8.3 and 8.4 are not yet fully implemented for Monthly Manufacturing Survey data Evaluate Evaluation inputs include feedback from users, staff suggestions and also internal audit. which is conducted periodically by internal auditor and SIRIM (Standards & Industrial Research Institute of Malaysia). 9.1 Gather evaluation inputs 9.2 Conduct evaluation 9.3 Agree action plan Audit Committee was formed to monitor the quality of all statistical business process involved in producing the outputs. Internal audit conducted periodically in accordance to Quality Procedures (JPPS-PK-06 & JPPS-06-AK-01). It involves the SMD concerned and all state offices. The evaluation report will become the basis for decision making power to form and agree an action plan. Corrective action and improvement plan must be included into consideration as a mechanism of monitoring the quality of the outputs