European Conference on Quality in Survey Statistics

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European Conference on Quality in Survey
Statistics
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Modernisation in Statistical Organisations (SMP)
Peter J Fullerton
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Aims

• Drivers for modernisation
• Objectives
• Benefits
• Initial approach
• New plans
• The way forward
• Examples

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Drivers for modernisation

• Creation of ONS in 1996
• - Diverse range of statistical tools and computer
  systems
• 2,000 pieces of software
• 400 500 live application systems
• 150 application development languages and
  software packages
• - Different methods, processes and practices

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Drivers for Modernisation

• Initial lack of integration and subsequent lack
  of investment
• Led to
• - Increasing costs through duplication, licence
  costs etc
• - Inefficiencies in production processes
• - Increased risk to quality of statistics

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ONS Modernisation

• To improve the quality, timeliness and
  efficiency of, and access to, the key statistical
  systems managed by ONS
• SMP, a key element of ONS Modernisation
• To create a metadata driven, corporate database
• To introduce a set of standard statistical tools
• To re-engineer key statistical systems
• To standardise and systematise the processing
  and presentation of statistical outputs

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Benefits to ONS

• Reduced risks
• Cash savings
• Improved quality
• Increased value of outputs
• Improved harmonisation of outputs
• Faster access speed of processing
• Reduced development time
• Reduced compliance costs

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Benefits for users of our data

• Datasets will be more robust and better suited
  to their purpose
• Errors and inconsistencies will be reduced
• Outputs will be more timely through reduced
  processing time
• New analyses of existing sources will be possible
• Access to a greater range of more coherent
  statistics
• Greater transparency as to the methodologies
  employed
• Improved responsiveness to new data needs

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Initial approach

• Generic data repository
• Configurable systems
• Several statistical tools operational
• Extensive metadata expectations
• Fully systematised processing
• Broad span of ONSs business
• 3 year delivery plan
• Business transformation

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Life Events
ADI
Business Surveys
National Accounts
Social Surveys
Labour Market
Prices/CSPI
Population Estimates
CPI
Business Surveys Framework
Social Surveys Framework
IDBR
Admin Data Portal
Collection Validation
Results Processing
Collection Validation
Results Processing
Dissemination
X12
GES
Canceis
Banff
Index No Constr
Analytical Tools
SAS
Superstar
Tau-Argus
ACTR
GRI
Metadata
C O R D
Unit Level Data
Aggregate Level Data
Longitudinal Data
Time Series Data
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New plans based on lessons learned

• More incremental approach to delivery of vision
• Extended delivery period
• Focusing on delivering production quality
  systems that deliver specific business benefits,
• At the same time contribute towards building
  infrastructure
• Build on the work done to date on key systems
  (Labour Force Survey and National Accounts)
• Business transformation

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The way forward (1)

• Labour Force Survey processing
• weighting and micro data outputs
• National Accounts
• - central systems
• - local systems
• Vital Events (births, deaths, etc.)
• - data portal

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The way forward (2)

• Survey Case Management
• work allocation
• telephony
• management information
• Business Data Collection
• Business Register
• Integrated Household Survey

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ADI
Life Events
Business Surveys
National Accounts
Labour Market
Prices/CSPI
Population Estimates
Social Surveys
CPI
Business Surveys Framework
Social Surveys Framework
IDBR
Admin Data Portal
Collection Validation
Results Processing
Collection Validation
Results Processing
Dissemination
X12
GES
Canceis
Banff
Index No Constr
Analytical Tools
SAS
Superstar
Tau-Argus
ACTR
GRI
Metadata
C O R D
Unit Level Data
Aggregate Level Data
Longitudinal Data
Time Series Data
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Contact details
peter.j.fullerton_at_ons.gsi.gov.uk pat.heymann_at_ons
.gsi.gov.uk
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Modernisation in Statistical Organisations (SMP)
Peter J Fullerton
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European Conference on Quality in Survey
Statistics