‚ÄėThe public good‚Äô is a phrase which you might not have come across before. When I first joined the Office for Statistics Regulation (OSR) nearly two years ago, I had no real idea what it meant, but I knew that it was something very important to OSR; something which was mentioned in nearly every meeting I went to. What I know now is that OSR‚Äôs vision ‚Äď that statistics should serve the public good ‚Äď is fundamental to all that my colleagues and I do. ¬†

So what is serving the public good? It means that statistics should be produced in a trustworthy way, be of high quality, and provide value by answering people’s questions: providing accountability, helping people make choices, and informing policy. As statistics are part of the lifeblood of democratic debate, they should serve a very wide range of users. When they meet the needs of these users, they serve the public good. 

But¬†needs can¬†change¬†quickly,¬†and statistics can be used in ways that also do not serve the public good¬†–¬†precise numbers can be used to give a misleading picture of what the statistics¬†actually say,¬†too much weight can be put on statistics,¬†or they can be described incorrectly.¬†¬†¬†

At OSR it is our job to support confidence in statistics. Having a really strong understanding of what it means for statistics to serve the public good is crucial to this.   

Over the last 22 months, I’ve been leading a research programme aimed at doing just this, as existing research on understanding public good is relatively sparse.  

My first step in exploring public good was to publish a literature review which explores the current evidence on public good. We have also analysed how researchers think their research will provide public benefits and we are currently running studies to explore what members of the public and our own team think about the public good.  

A key theme coming from this research is the importance of being able to communicate statistics in a way that is understandable to everyone who is interested and needs to be informed by them. This is not an easy thing to do. Statistics potentially have many different audiences Рsome people may confidently work with statistics, whereas others may not have much experience of statistics, but want to be able to understand them to help make decisions about their lives.  

Differences in¬†how¬†people¬†understand¬†statistics¬†are¬†often¬†attributed to¬†an individual‚Äôs¬†literacy¬†or¬†numeracy¬†abilities¬†‚Äď we often hear the term¬†‚Äústatistical¬†literacy‚Ä̬†when this¬†type of understanding is being talked about.¬†¬†¬†¬†

We think it is¬†wrong¬†though¬†to think of statistical literacy¬†purely¬†in terms of a deficit in knowledge.¬†Rather,¬†we think¬†that¬†producers¬†of statistics¬†need to understand what people find easy to grasp and what they find counterintuitive and think, ‚ÄúHow do we work with that to make sure that the real message of the statistics lands properly?‚Ä̬†It is our role¬†in OSR¬†to guide producers to do this.¬†¬†

To help us with this, we will be kicking off some new projects this year aimed at increasing our understanding of how different segments of the public regard statistics. 

The public good may seem like a mysterious concept¬†but, by working to¬†build the evidence sitting behind the phrase ‚Äėpublic¬†good’ and¬†understand¬†how the statistical system needs to respond to meet it, we are hoping to make it¬†much¬†less so.¬†¬†

We hope that our research work, which we are undertaking in collaboration with others, will not only highlight the role that statistics play in the choices that people make and the risks to the public value of statistics in a changing environment, but also that publicly researching this area will stimulate others with the capacity and expertise to work in this area.