Statistics Under Pressure: informing decision-making at pace
The Covid-19 pandemic highlighted the importance of data being used to inform decision-making at pace. For statisticians working under pressure, it can be challenging to judge when imperfect data is good enough to inform decisions, and which trade-offs can appropriately be made.
This project aims to foster an environment in which statistics, data and modelling that are good enough to inform time-pressured decisions can be used with confidence, especially in cases where the data is not perfect and decisions might otherwise be made in the absence of data.
Statistics Under Pressure aims to support statisticians to provide the best possible statistics under pressure, including consideration of when and how to make suitable trade-offs. It aims to raise awareness around the need for trade-offs in real-world circumstances, along with the merits of such an approach. It also aims to support decision-makers and the public to interpret and use data that is associated with limitations or uncertainties.
- Deepen understanding on how trade-offs can be employed in line with good practice among statisticians and analysts
- Improve the ability of non-analysts to interpret statistics and data that are presented with uncertainties and caveats, and to use them to inform decisions
- Strengthen resources and structures (eg data platforms, team structures) to promote statistics that are produced at pace and feed into decision-making rapidly, including capacity to ramp back up in the event of another crisis
- Increase cross-team communication, including between decision-makers and analysts, and between analysts and external stakeholders/data users to increase understanding of user needs and data context
- Raise awareness of the need for and value of an approach that involves trade-offs among the wider statistical community, end users of data, and the public, to increase understanding and explain the necessity and merits of such an approach
The following individuals form a Steering Group
that helps to direct and advise on the project:
- John Aston (Chair) - Professor of Statistics at the University of Cambridge, previous Chief Scientific Advisor at the Home Office (2017-2020), non-executive director on the board of the UK Statistics Authority
- Paul Allin - RSS Honorary Officer for National Statistics, Chair of RSS National Statistics Advisory Group, visiting Professor in the Department of Mathematics, Imperial College London, previous roles chairing the UK Statistics User Forum and at the Office for National Statistics and Government Statistical Service
- Christl Donnelly – RSS Vice President for External Affairs, Chair of RSS Campaign Advisory Group, Professor of Applied Statistics at University of Oxford and Visiting Professor at Imperial College London
- Clare Griffiths - previously Head of the UK COVID-19 dashboard, currently Population Health Surveillance lead at the Department for Health and Social Care
- Sarah Walker - Chief Investigator of the Covid Infection Survey, Professor of Medical Statistics and Epidemiology at the University of Oxford.
In the first instance, we are looking to develop and publish a series of case studies to illustrate instances in which compromises were made in order for data to best inform decision-making.
The case studies will highlight which trade-offs were made, and explain why these compromises were necessary to allow data to feed into decision-making. We aim to cover a range of topic areas (eg health, finance, public statistics), and a range of sectors (eg government, business, academia).
We plan to produce a range of outputs and helpful materials during the course of this project, to support statisticians, decision-makers, and the public with providing and interpreting data in fast-paced circumstances. This could include, for example: guidance for decision-makers on how to interpret data with limitations; guidance for analysts on how to communicate the limitations of data; circumstances in which the RSS supports making trade-offs to allow data to inform decision-making; accessible wording that statisticians can use to help defend decisions in which trade-offs have been made; policy recommendations on structures and resources to support fast-paced data-informed decision-making; or opinion pieces and campaigning activities to raise awareness of the need for and value of making trade-offs to allow data to best be used to inform decisions.
We welcome your thoughts on this project, including feedback on what you would find helpful to support you to produce, communicate, use, or interpret statistics and data in high-pressure fast-paced circumstances.
To date, we have held scoping discussions with a range of RSS members and external stakeholders, as well as circulating surveys to gather feedback and shape the project plans.
We plan to consult with stakeholders throughout the project. Please do get in touch if you are interested in feeding into this project; please email firstname.lastname@example.org.