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Towards efficient data collection at Statistics Sweden

Towards efficient data collection at Statistics Sweden. Johan Erikson Data collection , process owner johan.erikson@scb.se. Data collection today. Two main data collection departments Individuals and households Interview surveys Questionnaire surveys

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Towards efficient data collection at Statistics Sweden

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  1. Towardsefficient data collection at Statistics Sweden Johan Erikson Data collection, process owner johan.erikson@scb.se

  2. Data collection today • Twomain data collectiondepartments • Individuals and households • Interviewsurveys • Questionnairesurveys • Enterprises and public sector • Enterprises and Enterprise relations – Örebro • Enterprises – Stockholm • Public sector • Coordination and Largeenterprise management • Process owner at process department • Register data collection at subjectmatterdepartments

  3. Roles in data collection • Process owner • Establishcommonroutines • Build and maintaincommontools • Process users • Runcollection on a daily basis • Demands on commonroutines and tools

  4. Commontools in use • Web data collectiontool • Interviewcollectiontool • Hand-heldcomputers for CPI collection • Scanning system • ”Funnel” for administrative data • Triton – commonproduction system

  5. Effects of centralised data collection • Expert functions • Resourcepooling • Learning by experience • Implementation of new tools and routines • Addressingnon-survey-specificissues • Internal tension, ”us and them” • Resourceplanning in largeunits

  6. Ongoinginitiatives • Triton project – expectedgains • Planning and metadata haveeffect on IT tools • Built-inqualityassuranceactivities • Easier to pool resources and work on manysurveys • Moreefficientinterview data collection • Contact strategies • Common set of cases • Data warehousing • EDI initiatives (XBRL)

  7. Futurechallenges • Decliningresponse rates • Difficult to reach respondents • Pressure to reduceburden • Combiningsurvey data and administrative data • Data sharingbetweengovernmentagencies • More on EDI • New technologicaladvances • Social media? • Optimisingresourceplanning with new contactstrategies

  8. Reflections / conclusions • Centralisation of data collection has beensuccessful so far • Internal tension tends to decline over time • Some of the futurechallenges that face us are meteasier with a centralised data collection • Demand for expertise on collection-specificissues – collection is a general knowledge, not onlysurvey-specific, e.g. contactstrategies • Demand for technicalexpertise • Demand for central roles (persons) to negotiate with data providers and othergovernmentagencies

  9. Reflections / conclusions (2) • Some of the futurechallengesprobablyrequireevenmore of centralisation, and new thinking • Manyissues are the same for householdsurveys and business surveys – combinedexpertisenecessary (mixed mode, decliningresponse rates) • Technicalchallengessuch as direct data feeds • Combining administrative data and survey data • Administrative data are used for both registers and surveys • Are todayssurveys and their limits the mosteffectiveway to collect data? • A single ”data capture” departmentcould be an effectiveway to deal with data sharingissues

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