Richard Hamblin, 2018 LDC Fellow

In the last ten years, our ability to analyse vast amounts of variable forms of data at great speed has, for some, opened up a brave new world of a government of services micro-targeted to individuals; policy devised, implemented and evaluated in real time; “data commons” empowering and freeing individuals and communities; even the very paraphernalia of public service itself replaced with algorithms! 

In my first blog I set out a view that we’ve been using data wrongly to report performance rather than generate insight. The need to make this shift is the starting point for all else that follows in what I am trying to achieve with this fellowship. So, it’s kind of incumbent on me to justify this position.

In undertaking the fellowship, numerous public and private sector leaders and academics have generously given me their time to answer all manner of questions over the last two months.  I’m profoundly grateful and my thinking has clarified considerably as a result. One question that I have asked, in a range of different ways is “Why do I find it relatively easy to recruit bright, excited graduates with great ideas about what we might do with the data available to us, but comparatively hard to find people with same passion five to ten years into their career?”

Of all the “inspirational” little vignettes that disfigure management literature and LinkedIn streams, few are as hackneyed as the tale of JFK touring NASA headquarters in 1961 and on asking a janitor what he did for NASA, receiving the reply “I’m helping to put a man on the moon”. So far, so Dilbert.

So down to brass tacks: what skills do we need in our data teams and how do we get ‘em? 

Exploiting data as a resource for insight not only needs high levels of skills and subject matter expertise, it requires the bringing together of a number of distinct roles – not all of which are tied up with statistics or computer science abilities.

This fourth prerequisite links to both higher purpose and the ability to influence the system.  It is somewhat tricky to define tightly, but encompasses a range of related issues:

The worry about investing heavily in data and the people to use it is that we create a Rolls Royce engine that is not connected to the “wheels” of delivery.  This seems an odd thing to say as government departments are increasingly concerned to be (or at least say that they are) data-driven. Certainly, agencies that provide services to government increasingly complain about the burden of data collection (which creates an opportunity cost that limits their capacity to provide the service that they are being paid to provide).