Next year, David Caplan will be stepping into the shoes of Honorary Officer for Public Statistics, at a time when official statistics are taking centre stage. We had a chat to find out a bit more about him and what the next few years might bring...
Congratulations on your appointment! What are you most looking forward to as the Honorary Officer for Public Statistics?
Thank you. I’m looking forward to working with colleagues to influence the UK statistical system and ensure its continued relevance. I see the public statistics project as being about ensuring that we have a statistical system that delivers quality statistics that can be used for the widest range of decision making. And statistics that help the public and others hold government at all levels to account.
The RSS has a key role to play with its public voice and access to key players in the system.
Can you tell us a bit about your professional journey and how it has prepared you for this role?
Sure. I spent the first half of my career in official statistics mostly working on national accounts. I then moved into the wider public sector as Director of Research at the now defunct Audit Commission and then different things including co-running a small consultancy and a couple of roles working in or with local public services. I am now back in my original comfort zone working as a research associate at the Economic Statistics Centre of Excellence.
This experience is quite broad. I’ve worked both as a producer and user of official statistics and as a producer of non-official statistics. I’ve worked across a range of domains including economics, health and local public services giving me a very broad view of challenges for both the producers and users of statistics in different environments. I like to think that I’ve absorbed something from every role I’ve had - and certainly I have gained an appreciation of the public value of statistics.
Have there been any particular projects or roles in your career that especially shaped your view on the importance of public statistics?
I am tempted to say “all of them”. Working on high-profile economic statistics you see how statistics impact on big decisions by Government and the Bank of England that affect everybody. At the Audit Commission, I developed a greater understanding of statistics as an accountability mechanism - and deeply regret that the abolition of the Commission means that there is less transparency on the performance of local public bodies. Working with smaller councils has shown me that there is potential for more use of statistics - but that there are considerable barriers to doing so in terms of costs, skills and culture.
All of this has reinforced my belief that a strong, well-resourced public statistics system is essential for democracy and effective public services.
Do you have any particular priorities for your first year in the role?
The Official Statistics system, particularly the ONS is going through a very challenging time. The Devereux report was scathing in its criticism and when PACAC report later in the year, they may be even more damning. There are too many issues with key data series and the basic data. This points to two priorities. First, we need to be a supportive but critical friend of the ONS. We should work with them, for example in holding round tables and bringing in a range of voices for them to hear. But we should also hold them to account by asking questions and expecting answers.
Second, there is a potentially worrying development that ONS may focus on the needs of its key customers in government and the Bank of England. I joined the old CSO in the post-Rayner days and do not want to see a return to a statistical system focused almost exclusively on government users. We must continue to advocate for the wider public statistics agenda
How do you see the role of public statistics evolving over the next decade, especially with the rise of AI and big data?
Interesting question. I’ve actually been a bit disappointed by the impact of big data and AI so far. Promising data sets seem not to have delivered. But we can continue to hope that large data sets can be interrogated to provide useful statistics. And some of the hype is unjustified - yes we have more computational power and tools but the underlying statistical methods aren’t all particularly new.
I think generative AI might change some user perceptions - and it is now much easier to do AI assisted data analysis which might increase the number of users and the demands on the system. ChatGPT will write your R code and might provide a sensible interpretation of the output.
For producers, I think there may be scope to improve outputs. Time is often a constraint when producing statistics and intelligent use of AI tools in the quality assurance processes might be a way of improving quality without reducing timeliness.
Finally, do you have a favourite statistic or piece of data?
Not really - I tend to have a favourite dataset at different times depending on what interests me. At the moment, it’s tracking performance on an indoor rower!
Perhaps my one constant is weather records — no idea why. But, as someone with a South African wife, I enjoy pointing out that Cape Town has more rain than London.