In June 2023, the NHS published its Long Term Workforce Plan to retain existing talent, make better use of technology, and launch the biggest health recruitment drive in health service history.  

The plan failed to include anything to support workers in digital, data and technology roles.  

Lauren Bevan, Director of Consulting, outlines how the data analyst community can support each other in light of this omission and prove its ongoing value to the health service.    


As I write this, I’m barely keeping a lid on the simmering anger at the knowledge that the NHS’s omission of analysts and data scientists from its Long Term Workforce Plan was a deliberate decision. Andi Orlowski’s recent HSJ column echoed my frustrations perfectly. 

Data analysts have been left out of the Long Term Workforce Plan, they have been removed from the recommendations on the Cabinet Office pay deal for the wider Civil Service and there’s a move to regulate the profession.  

Those same data analysts, however, play a crucial role in the NHS. The NHS spends a huge amount of public money, at a local and national level, but the analysis that supports those investment decisions might be being done by people without professional qualifications. It’s almost certainly being done by someone who could get better pay, conditions, training and probably stands a fighting chance at finding a teaspoon at work and less chance of being dragged through right-wing newspapers.  

As people without the power to fix anything in the previous paragraph, what can we do?  I’m not very good at being a passive observer of a predictable disaster (which is a key reason I don’t really watch reality TV).  Here’s my thoughts of what we as a community of data analysts can do:   

  1. Share the shame – we are a community that shares methodologies, models, and results. I think we should share our failures, too. When we find an analytical barrier or a technical cul-de-sac, we should be less scared of telling others where the dragons are. We are proud (rightly) to trumpet our successes, but we should also tell others where we failed or, frankly, got stuck. No shame in it, just pass the baton. 
  2. Make it human – data doesn’t exist in a vacuum; we all have our perspectives, biases, and context. Much like the 90s TV hit ‘Catchphrase’, we can only see the full picture if we take off all the panels. And none of us have all the answers. I’m reminded of the Latvian mathematician Daina Taimina who discovered that the best way to articulate hyperbolic planes is by crocheting them. It was an issue that had literally been patched up by paper and tape until someone with a different skillset, from something completely unrelated, looked at it. Sometimes we all need that.  N.B. her book on the subject won the prize for the oddest book title of the year. Look at the list, there’s some good ‘uns. 
  3. Really get to the bottom of the question – it’s really tempting to analyse a question using the tools that we have at our disposal. But running into a solution without properly understanding the question (who’s asking, why they are asking, do they already have a hypothesis they want proven? etc) is why I’ve often ended up with version 132 of a model, which I then renamed based on time and date as I was too depressed at the number of versions (see point 1). Figure out the context of the question and it’ll save you some heartache (and probably some RAM, too). 
  4. Join a union (or a professional body) – regulation is coming. Most probably with whoever the next government is going to be. It seems likely that the stick is coming before the carrot but that’s fine. Pick an organisation that will help you with your development goals and feels like your flavour of people and get the most out of your membership.   

My final piece of advice is to those people who aren’t ‘data people’ but who work with them: please listen to us when we say it’s not possible in the time, with the data that exists, that there are limitations to what we can do with the data quality. Please believe us. We really want to give you an answer – that’s part of the reason we do the job that we do. We just want to give you something we can stand behind when asked to defend it (knowing that we will).  

The value of data to make good and responsible decisions on spend and priorities is immense. It’s clear this Government won’t support the role of technical experts in the way we would hope so we must create our own supports.  


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