DEPARTMENT OF STATISTICS MALAYSIA 1st October 2014 Modernization Working Group (MSIS 2010) Applying GSBPM in the National Enterprise-Wide Statistical Systems (NEWSS ): Monthly Manufacturing Survey DEPARTMENT OF STATISTICS MALAYSIA 1st October 2014

Monthly Manufacturing Survey (MM) Objectives : Provide data on the latest trends in the principal statistics of the manufacturing sector, specifically on sales value, number of employees, salaries & wages and the main products manufactured, hence assisting users in policy formulation and decision making. Data obtained are used for the compilation of Industrial Production Index (IPI) and Monthly Manufacturing Statistics. IPI as an input for the compilation of quarterly Gross Domestic Product (GDP) and monthly Leading, Coincident and Lagging Indexes. To assist economists, academicians and public users in economic analysis.

SCOPE AND COVERAGE Geographically, cover whole of Malaysia. 120 industries out of a total of 197 industries covered Of the 120 industries covered, 102 are used in the computation of the Index of Industrial Production.

MM Statistical Environment (NEWSS) A PLATFORM A Pre-Collection E B Dissemination Collection Statistical Environment The technically capable The professionally informed Everyone else D D C C C Analysis Analysis Analysis Processing Processing Processing BI is often an area of friction between IT (who prepare the information) and the business users (who need it to do their jobs).

NEWSS Vision Integrated Statistical Systems Framework Source : DOSM

NEWSS INTERFACE

GSBPM MS ISO NEWSS Mapping to GSBPM Processing Collection Evaluation Archive Disseminate Analyse Process Collect Specify Needs Build Design Processing Collection Pre-collection Dissemination Analysis Monitoring & Quality Assurance Processing Collection Pre-collection Dissemination Analysis Monitoring & Quality Assurance

Modules in NEWSS Profil Banci/Penyiasatan 1 Profil Banci/Penyiasatan (Census/Surveys Profile) Access project profile details for the planned/ implementing/ implemented census/surveys with their details activities. 2 Pra Penggumpulan Data (Pre Data Collection) Access pre-collection details i.e. scope of coverage for establishment census/surveys and sampling details. 3 Pengumpulan Data (Data Collection) Access collection process details including the assignment of officers and field enumerator to sample case, capturing the operational control and operational visit information. 4 Prosesan Data (Data Processing) 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. 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.

Modules in NEWSS 5 Penyebaran (Dissemination) Manage product, catalog, advance release calendar, customized request, data request, customer services, external user account, subscription and feedback. Track the total transactions, delivery on hardcopy/CDs, notification recipients. Log the email 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. 6 Pensampelan (Sampling) Perform the details process on sample generation. Perform the selection of living quarter for field work. 7 Rangka Enterpris/Pertubuhan (Enterprise / Establishment Frame) 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. Monthly: Index of Industrial Production Salaries / Wages (manufacturing) Consumer Price Index Producer Price Index External Trade a specified embargo time for release

Modules in NEWSS 8 Laporan (Report) Access to the ISSF reports and KMS reports. 9 Kod dan Klasifikasi (Code & Classification) 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. 11 Business Intelligence Generate the review tables for SSE and Monthly Manufacturing survey. 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.

Generic Statistical Business Process Model 1 Specify Needs 2 Design 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 8 Archive 9 Evaluate 1.1 Determine needs for information 2.1 Design outputs 3.1 Build data collection 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 Design variable descriptions 3.2 Build or enhance process components 4.2 Set up collection 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 Design data collection methodology 3.3 Configure workflows 4.3 Run collection 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 Design frame and sample methodology 3.4 Test production system 4.4 Finalize collection 5.4 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 Design statistical processing methodology 3.5 Test statistical business process 5.5 Derive new variables and statistical units 6.5 Finalize outputs 7.5 Manage user support 1.6 Prepare business case 2.6 Design production systems and workflow 3.6 Finalize production system 5.6 Calculate weights This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 5.7 Calculate aggregates Generic Statistical Business Process Model Version 4.0 – 2009 5.8 Finalize data files

Generic Statistical Business Process Model Version 4.0 – 2009 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) 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 This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 1.6 Prepare business case

Generic Statistical Business Process Model Version 4.0 – 2009 2 Design  Detailed design of the statistical outputs to be produced - Functional Design Specification (FDS). Variable descriptions – determined by SMD, follow international standards Sub-processes 2.3 - 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 2.1 Design outputs 2.2 Design variable descriptions 2.3 Design data collection methodology 2.4 Design frame and sample methodology 2.5 Design statistical processing methodology This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 2.6 Design production systems and workflow

MM PROCESS FLOW MM1 : Pre-Collection

Pre-Collection (Cont’d) MM PROCESS FLOW MM2 : Pre-Collection (Cont’d)

Pre-Collection (Cont’d) MM PROCESS FLOW MM3 : Pre-Collection (Cont’d)

Collection & Processing MM PROCESS FLOW MM4 : Collection & Processing

Collection & Processing (cont’d) MM PROCESS FLOW MM5 : Collection & Processing (cont’d)

Collection & Processing (cont’d) MM PROCESS FLOW MM6 : Collection & Processing (cont’d)

Collection & Processing (cont’d) MM PROCESS FLOW MM7 : Collection & Processing (cont’d)

Analysis & Dissemination MM PROCESS FLOW MM8 : Analysis & Dissemination

Generic Statistical Business Process Model Version 4.0 – 2009  Data collection instrument built based on specifications created during phase 2 (Design). Multiple modes of data collection used – questionnaire : face to face interview, facsimile, e-mail 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 collection, 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). 3 Build 3.1 Build data collection instrument 3.2 Build or enhance process components 3.3 Configure workflows 3.4 Test production system 3.5 Test statistical business process This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 3.6 Finalize production system

Generic Statistical Business Process Model Version 4.0 – 2009  Sample selected from business frame established in sub process 2.4 (Design frame and sample methodology). 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 collection 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. 4 Collect 4.1 Select sample 4.2 Set up collection 4.3 Run collection 4.4 Finalize collection This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

5 - Process Generic Statistical Business Process Model Version 4.0 – 2009 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 Finalize 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 collection 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. This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

5 – Process (cont’d) Generic Statistical Business Process Model Version 4.0 – 2009 5 – 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 Finalize 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. This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

Generic Statistical Business Process Model Version 4.0 – 2009 Data collected transformed into statistical outputs, to indicate the latest trends of manufacturing sector and compiled for the production of Industrial Production Index. 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. 6 Analyse 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Scrutinize and explain 6.4 Apply disclosure control This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 6.5 Finalize outputs

Generic Statistical Business Process Model Version 4.0 – 2009  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. 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. 7 Disseminate 7.1 Update output systems 7.2 Produce dissemination products 7.3 Manage release of dissemination products 7.4 Promote dissemination products This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years. 7.5 Manage user support

I. Handling of Complaints Workflow Start Receive complaints Record complaints Refer to PB/TP/PP (BKKP) P/TP/PP (JPN) Justified? Examine complaints Close case and filed Forward to PYB(SKPA) Investigate Prepare report and response draft A B No Yes End Forward to PB/TP/PP (BKKP) Agreed? PYB receive report draft Inform the complainant Correction Record A B No Yes

II. Handling of Customer Satisfaction Workflow Start Received completed form from customer Analyze and prepare report Forward to PB/WP/PB (BKKP) Agreed? Send the form to main user Correction Receive result/recommendation and inform P(UKP) Take further action Present in MKSP No Yes End

Generic Statistical Business Process Model Version 4.0 – 2009 8 Archive 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. 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 This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

Generic Statistical Business Process Model Version 4.0 – 2009  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). 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. 9 Evaluate 9.1 Gather evaluation inputs 9.2 Conduct evaluation 9.3 Agree action plan This is the Generic Statistical Business Process Model, version 4.0, published in April 2009. It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

CHALLENGES Metadata management i. database environment ii. stored together with data iii. availability based on users’ needs iv. exchange and use – infrastructure Strengthening and empowerment of statisticians skills and ability in scrutinizing and analyzing the statistics produced. Needs to define and determine archive rules/procedures for statistical data and metadata resulting from a statistical business process.

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. Main focus for development in the next coming years will be on how information will flow and be transformed through the different stages of GSBPM. Higher level officers 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

Thank You Terima Kasih 34