Richard Hamblin, Director of Health Quality Intelligence at the Health Quality and Safety Commission was a 2018 fellow recipient.

Richard completed a number of reports and blog updates as part of his fellowship investigating how organisations can successfully drive delivery through data and analytics. 

In 2019, his presentation ‘Data, leadership and rabbit holes’ summarised his research, findings and tool he created.


Data, leadership and rabbit holes [PDF, 2.5 MB]


30 years down the wrong rabbit hole: how we got there and how we get out

"It’s all very well arguing that we need to use data in a different way and therefore we need data teams that look like this and are led like that, (and by the end of this fellowship process I may have some idea of what this and that look like), but a sceptic could perfectly reasonably ask 'why do we need to use data in a different way?' What follows is my answer, the reason why I embarked on this exercise." 

30 years down the wrong rabbit hole: how we got there and how we get out [PDF, 804 KB] 

So what? (and for that matter “how”?)

Richard's earlier paper suggested why we need to change how we view data in public services. Data should be seen as a source of insight rather than an instrument of control, and that where monitoring “targets” exist these should be locally relevant and mutually agreed rather than centrally imposed. What does that mean in practice, and how do we go about doing it?

 So what? (and for that matter 'how?) [PDF, 456 KB]

Blog updates

Post 1: Setting the scene

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! 

Read the full blog post

Post 2: Why shift? (part 1 – benefits for all)

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.

Read the full blog post

Post 3: Why shift? (part 2 – creating the cadre)

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?”

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Putting a man on the moon

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.

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Better stats than a programmer, better programming than a statistician – the skills upgrade

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

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Hunting unicorns

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.

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Where we belong - social positioning of the organisation

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:

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On the importance of driveshafts – influencing beyond the data bubble

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).

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