Towards efficient data collection at Statistics Sweden Johan Erikson Data collection, process owner

Data collection today Two main data collection departments Individuals and households Interview surveys Questionnaire surveys Enterprises and public sector Enterprises and Enterprise relations – Örebro Enterprises – Stockholm Public sector Coordination and Large enterprise management Process owner at process department Register data collection at subject matter departments

Roles in data collection Process owner Establish common routines Build and maintain common tools Process users Run collection on a daily basis Demands on common routines and tools

Common tools in use Web data collection tool Interview collection tool Hand-held computers for CPI collection Scanning system ”Funnel” for administrative data Triton – common production system

Effects of centralised data collection Expert functions Resource pooling Learning by experience Implementation of new tools and routines Addressing non-survey-specific issues Internal tension, ”us and them” Resource planning in large units

Ongoing initiatives Triton project – expected gains Planning and metadata have effect on IT tools Built-in quality assurance activities Easier to pool resources and work on many surveys More efficient interview data collection Contact strategies Common set of cases Data warehousing EDI initiatives (XBRL)

Future challenges Declining response rates Difficult to reach respondents Pressure to reduce burden Combining survey data and administrative data Data sharing between government agencies More on EDI New technological advances Social media? Optimising resource planning with new contact strategies

Reflections / conclusions Centralisation of data collection has been successful so far Internal tension tends to decline over time Some of the future challenges that face us are met easier with a centralised data collection Demand for expertise on collection-specific issues – collection is a general knowledge, not only survey- specific, e.g. contact strategies Demand for technical expertise Demand for central roles (persons) to negotiate with data providers and other government agencies

Reflections / conclusions (2) Some of the future challenges probably require even more of centralisation, and new thinking Many issues are the same for household surveys and business surveys – combined expertise necessary (mixed mode, declining response rates) Technical challenges such as direct data feeds Combining administrative data and survey data Administrative data are used for both registers and surveys Are todays surveys and their limits the most effective way to collect data? A single ”data capture” department could be an effective way to deal with data sharing issues