Data Collection and Data Sharing at Statistics Netherlands

Prof. dr. Ger Snijkers*

UNECE CES 2011- seminar IGeneva, 14 June 2011

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Overview

• Organizing data collection activities:• Yesterday • Today

• Process-and-knowledge driven approach• Challenges we face today• Data Collection Strategy• Developments over the years

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Data Collection over the years

3

Stove pipes Data Collection 2000

Partial Centralisation Data Collection Now

< 1994 1994 - 2000

2000 - 2007

Present

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Drivers for centralizing data collection:

Achieving efficiency by:• Abolishing redundant processes, workflows, and

activities for social and business surveys• Monitoring processes, workflows, and activities

• Abolishing redundant systems and tools• One data collection management system• Maintaining as less systems and tools as needed

Spin off• Clear and professional external focus• Reducing response burden

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Organizing Data Collection

Front desk:• Client relations• Survey design

Design:• Questionnaire• Sampling• Training

Survey deployment:

• CAPI / CATI Interviewing

• Planning & control• Fieldwork logistics• Support• Special services

Clustering of practices and knowledge• Focus on how knowledge is being used

12 fte

35 fte

240 fte

• Fte’s:• 375 (2008)• 277 (2012)

• Budget:€ 18.5M

• 145 surveys

92 26 118 fte

122 fte

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Process-and-knowledge driven approach:

Survey deployment

CATI unit• Interviewing R• Telephone

CAPI unit• Interviewing R• Face-to-face

Help desk• Support R• Telephone

• Technology driven: use of telephone• Processes, workflows and skills are different• Processes, workflows and skills are comparable

Re-organising Telephone and interviewing units

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Process-and-knowledge driven approach: Introducing home-based interviewing

• Phase 1: for CATI agents €100k• Phase 2 (ongoing): for CAPI interviewers €400k

Revenues:• Flexible cost efficient CATI / CAPI workforce• Remain nationwide CAPI coverage• Improved communication• Prevent slack demand – supply CAPI workforce

Survey deployment

CATI unit• Interviewing R• Telephone

CAPI unit• Interviewing R• Face-to-face

Help desk• Support R• Telephone

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To be ready for the future

• Reliable statistics:• relevant• more & integrated information• faster

• Less money• improving cost-efficiency

• Less compliance costs• reduction of response burden

• Implementation of Data Collection Strategy

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The 2011 Data Collection Strategy:Retrieving and returning

3 steps:1. Re-use of available data

• Data sharing & data warehousing

2. Use of new registers and other secondary sources • Traditional government-based registers • Information from private businesses

• Data on the internet (web-crawlers)

3. Primary data collection:1. EDI technologies, like XBRL

2. Web surveys 3. traditional modes: paper, CATI, CAPI

• Using new social media technologies • Reciprocity: report back to respondents

Multi-source designs

Mixed-mode designs

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How to achieve this?

• Data Collection Division: • Coordinated data collection for social and business surveys• Mixed-mode designs

• Data Service Centre & Social Statistical Database: • Data warehousing

• Research (in collaboration with Methodology Division):• Statistical methods for combining data sources• New sources • EDI techniques • Web survey methodology, mixed-mode surveys, pre-testing • New media

• Survey-based projects:• Re-designing chain of Economic Statistics:

- using more register data / XBRL / Web questionnaires • Re-design of Social Surveys: - developing web questionnaires

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Data collection:Developments over the years

• From stove-pipes to a coordinated system of data collection

• From single surveys to multi-source/mixed-mode data collection designs

• From single-survey managers to managers of integrated sets statistics

• From local decision making to corporate decision making

• From data collection to data retrieving and returning

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Thank you