From remote working to online shopping, the pandemic has been a great accelerator of long-term shifts. It has done much the same thing to the role of data and statistics within public life.
This was really brought home to me in late 2020 when the RSS’s panel of distinguished experts sat down to decide our Statistic of the Year. In past years, our choice had usually generated a quirky news piece, intended to highlight how statistics could make sense of the big stories of the year. But when we looked through the nominations for 2020, we realised things were different: the statistics before us were the big stories of the year. The news of the pandemic, its spread, and its impact on lives and on society were being understood through the medium of statistics.
In much the same way, statistics became a central tool of our collective efforts to understand and to tackle Covid. Crucial projects like the Coronavirus infection survey, the UK Coronavirus dashboard, and the RECOVERY trial were as central to the UK’s Covid response as Nightingale hospitals or the vaccine procurement programme, and each was, in its different way, an exemplary statistical undertaking. Statisticians were in demand across government, and proved their value time and again.
So it is extremely timely that earlier this year the Office for Statistics Regulation published its major review, Statistical leadership: making analytic leadership count. Others have written eloquently about several of the main themes of the report, such as the importance of statistical skills, and of transparency and trust. While these are dear to the RSS’s heart, there is another theme in the report that I think is especially important: empowering statisticians to provide leadership, and ensuring they have strong career prospects.
One way of thinking about the crucial importance of empowered statisticians is to consider the counterfactual. What happens when if the other conditions for statistical leadership – such as technical skills and transparency – are met, but if organisations fail to give statisticians the right organisational roles, access and opportunities?
When this happens, we see a very particular failure made. Statisticians are left out of the loop of strategic planning. Data is seen as a specialist function to be commissioned as an afterthought, often to justify rather than inform a decision. And the commissioning process breaks down: statistical projects are assigned by leaders with limited statistical background, sometimes with unrealistic objectives and little chance to iterate during the project. The near-term results are projects that are frustrating to work on and disappointing for users. The longer-term results is that skilled statisticians are demoralised and drift away. We’ve all seen organisations like this; we may even have worked at some. Sometimes statistics or statisticians get the blame, and we hear talk of mutant algorithms or statistical errors. But the root cause isn’t in the data or the methodology: it is a problem of organisation.
But the good practice of the past eighteen months have shown to the world at large that there is a better way. In our experience, this relies on a few elements.
First of all, putting statistics, data and evidence at the heart of the organisation’s strategy. This means those senior leaders who aren’t statisticians gaining the skills to be users of statistics and to work well with statisticians, and statisticians being supported and trained to take senior leadership roles, rather than existing as a permanent auxiliary function. This helps make statistics and data intrinsic to the organisation’s workings.
Secondly, it requires strong career development opportunities for statisticians. Technical skills are important, but for true statistical leadership these need to be complemented with opportunities to learn general management and other operational skills. Crucial to this is mentorship. (This is why the RSS runs a mentorship scheme for candidates for our Chartered Statistician designation.) One of the silver linings for some statisticians of the immense workload imposed by the pandemic has been the exceptional opportunities to try out new roles in other organisations, as statistical and data skills have been at such a premium. Wouldn’t it be good if the volume and quality of these opportunities continued once the burden of Covid-related work has subsided?
Thirdly, it requires managers and heads of profession to be mindful about the make-up of the profession and to ensure it is open, diverse and growing. Research has shown that lack of opportunity and diversity is a big barrier to society’s scientific potential; it is likely that the same holds true for our discipline. This means redoubling our efforts to increase the diversity of the statistical workforce when it comes to protected characteristics. It also means promoting non-traditional routes into the profession, building on the GSS’s apprenticeship and degree apprenticeship scheme, and making the most of in-work skills schemes like the RSS’s Data Analyst, Graduate Statistician and Chartered Statistician designations, and the competency framework we have designed for them.
Getting these vital human-level, organisational questions right is essential for a thriving statistical profession. And that in turn is indispensable for anyone who cares about rigorous, useful, trustworthy statistics.