Deirdre Giesen & Barbara Berkenbosch Managing perceived response burden: why and how

Actual and perceived response burden –Actual response burden: time and/or money spent on complying with statistical data requests –Perceived response burden: subjective evaluation of effort spent. E.g. ‐Did you find it quick or time consuming? ‐Did you find it easy or difficult? See also Dale & Haraldsen (2007) ‘Handbook for monitoring and evaluating business survey response burdens’. 2

Outline –Findings BLUE-ETS project: demonstrating need for management of perceived burden –Example of “Perception of Burden” project at Statistics Netherlands 3

Acknowledgements BLUE-ETS work CBS Deirdre Giesen, Vanessa Torres van Grinsven, Ger Snijkers et al. University of Ljubljana: Mojca Bavdaž, Irena Bolko et al. SSB Gustav Haraldsen, Øyvin Kleven, Tora Löfgren, Dag Gravem et al. SCB Boris Lorenc, Andreas Persson et al. SORS Rudi Seljak et al. University of Bergamo Sylvia Biffignandi Perception of Burden Project Barbara Berkenbosch, Daisy Debie, Lex Visser, Matthijs Jacobs,Vronie de Haan, Jos van den Heuvel, Max Storms, Deirdre Giesen, Vanessa Torres van Grinsven, Ger Snijkers et al.

BLUE-ETS research on burden and motivation Measurement and reduction of response burden in official business surveys NSIs practice Businesses’ perspectives on official statistics Case studies Analyses of data on burden and response behaviour in Sweden, Norway and Netherlands Studies on effects of actions to reduce burden and/or increase motivation: Experiments on improving motivation in Sweden and Slovenia, studies on effects of questionnaire design in Norway and The Netherlands BLUE-Enterprise and Trade Statistics project ( April 2010-March 2013) EU FP7 project See for all reportswww.blue-ets.eu

Slovenian experiment (Bavdaž & Bolko 2013)

Results BLUE-ETS case studies 1 Response burden related to response behaviour, e.g. more burden: lower and later response, more edits needed Perceived burden related to actual burden but also to perception of NSI and usefulness statistics

Results BLUE-ETS case studies 2 Experiments aiming at increasing motivation by better communication did not show many of the expected effects The two questionnaire studies showed that questionnaire redesign can reduce actual and perceived burden

Perception of Burden Project at SN –Ran from February 2012-August 2013 –Part of government policy to reduce burden caused by statistics –Main goal: further intensify and coordinate actions to reduce perceived burden (projects aimed at reducing actual burden ran in parallel) –Main goal: improve businesses’ and business organisations perceptions of response burden created by SN surveys 9

Assess needs by –Brainstorming workshop with representatives from various parts of bureau to 1) make inventory of current knowledge and initiatives and 2) prioritise actions needed to reduce business respondents’ irritiations about our survyes. –Additional research: telephone survey of SMEs in our samples, re-analyses of data customer satisfaction survey, analyses of sentiments regarding SN in social media 10

Actions taken –Improvement of letters –Show case approach: collaboration with businesses and business organisations in redesign of survey –Reduction of helpdesk waiting times –Improvement of service call center –Improvement of website 11

Plans for the future –Use ‘show case approach’ for future redesign projects –Develop permanent monitoring of perceived response burden –Redesign questionnaire systems to imporve uniformity and user friendliness of our questionnaires and to enable the production of survey calendars –Further professionalize our complaint handling 12

Thank you for your attention… … and please have a look at all BLUE-ETS deliverables at 13