open menu

The Administrative Data Research Network is an ESRC-funded project that ran from October 2013 - July 2018. It is currently at the end of its funding cycle and is no longer taking applications. Administrative data research will be taken forward in a new project, to be launched later in 2018.

Quality data and saving money

Research overview

People are less keen than ever to take part in social surveys these days. They may simply decline to be involved in the first place or they may drop out after taking part once or more. For large-scale household and cohort studies looking to collect data not just once but repeatedly over time from thousands of people, this is a major logistical, practical and financial headache. But research linking three major surveys run by the Office for National Statistics (ONS) with Census information has come up with new ways to overcome these problems and achieve good quality data whilst making substantial financial savings. It could also help secure the future of the UK’s rich and important data sets.

Key findings

The research shows that when repeatedly attempting to contact a survey participant:

  • Implementing a cut off point (between call 6 and 8) makes little or no difference to data quality
  • Implementing that cut o point (depending on the survey) can make savings of between 7 and 15 per cent.

It also shows that:

  • It could be profitable for the commissioners of social surveys to reconsider and reflect on current attitudes towards tackling non response
  • Instead of aiming for an overall response rate at the end of data collection, time and money could be spent more wisely after a certain point during it
  • This approach could result in better quality data even if response rates are not improved
  • Technology could be used to employ this approach in real time by prioritising people for removal from the data set.

How the research helps

There is increasing pressure on those running large-scale surveys to improve data quality whilst reducing costs. Every individual who declines to take part or drops out of a survey represents both a financial and a data quality blow in respect of the time and effort spent trying to contact individuals and in trying to deal with any bias caused by them not participating.

Traditionally, the approach to this problem has been to try to find new and better ways of maximising response rates, but this research points to potential benefits of an alternative approach. This focuses on monitoring subgroups of surveys to ensure they are properly represented and points to major potential savings from a more flexible and adaptive approach during the data collection process.


The research is the result of a positive and productive working partnership with ONS which has made the data available. 

The findings have attracted considerable interest, especially from within ONS, which is looking to make substantial savings on the surveys it manages. There is also interest among the wider research community especially those working on and with large scale social surveys.

Findings from the project have also been presented to the Treasury, the Government Economic Service and Government Social Research teams, members of the UK’s Household Longitudinal Study (Understanding Society) based at the University of Essex, the Royal Statistics Society, the World Statistics Congress in Brazil and an International workshop in Norway.

The research

ONS made the linked data set available to the research team via the Virtual Microdata Laboratory (VML) secure research environment. Each time a call was made to a participant, (up to as many as 20) in the first wave of data collection, the representativeness of the dataset was checked.

Further information and links

Dataset representativeness during data collection in three UK social surveys: generalizability and the effects of auxiliary covariate choice – Statistics in Society

Fieldwork e ort, response rate, and the distribution of survey outcomes: A multilevel meta-analysis – Public Opinion Quarterly

Using linked survey-census data to monitor survey non-response – You Tube video

The data

The research uses administrative data collected in three ONS household surveys:

Labour Force Survey (LFS), providing official measures of employment and unemployment - largest household study in the UK

The Life Opportunities Survey (LOS), providing data on how disabled and non-disabled people participate in society

The Opinions and Lifestyle Survey (OPN), providing quick and reliable information about topics of immediate interest

Those surveys are then linked to the UK Census, which provides a detailed snapshot of the population and its characteristics, and underpins funding for public services.

The research also made use of paradata, notes written by survey interviewers about the numbers of attempts they had made to contact survey participants.

Project team

Professor Gabriele Durrant, ADRC-E, University of Southampton

Dr. Jamie Moore, ADRC-E, University of Southampton

Professor Peter Smith, ADRC-E, University of Southampton

Download this case study (PDF) (760Kb)

Page last updated: 06/09/2017