1. 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

2. 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.

3. 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.

4. 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).

5. NEWSS Vision
Integrated Statistical Systems Framework
Source : DOSM

6. NEWSS INTERFACE

7. 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

8. Modules in NEWSS Profil Banci/Penyiasatan1
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.

9. 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 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

10. 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.

11. Generic Statistical Business Process Model1
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 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

12. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.
1.6
Prepare
business case

13. 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 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.
2.6
Design production
systems and
workflow

14. MM PROCESS FLOW
MM1 :
Pre-Collection

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

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

17. Collection & Processing
MM PROCESS FLOW
MM4 :
Collection & Processing

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

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

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

21. Analysis & Dissemination
MM PROCESS FLOW
MM8 :
Analysis & Dissemination

22. 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, 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.
3.6
Finalize
production
system

23. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

24. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

25. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

26. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.
6.5
Finalize
outputs

27. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.
7.5
Manage
user
support

28. 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

29. 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

30. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

31. 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 It was developed by the Joint UNECE/Eurostat/OECD Work Session, over several years.

32. 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.

33. 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

34. Thank You Terima Kasih 34