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“One day, Sir, you may tax it” – Innovating in the Public Sector

 
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“Why, Sir, there is every probability that you will soon be able to tax it!”

As many of you will know, particularly if you work in the public sector, this is the response by Michael Faraday to William Gladstone, then British Chancellor of the Exchequer, in the 1850s, when the politician asked about the usefulness of Faraday’s research into an innovative phenomenon called electricity.

I think this aptly demonstrates some of the challenges and opportunities with new technology, data science and innovation facing Government and public sector bodies in the early 21st century.  Like Faraday’s time, we are living through a period of incredible technological change. For Faraday, it was the era of trains, anaesthetics and the advent of safe surgery, telegraphs and electric lightbulbs; for us, it’s self-driving cars and portable, or even implanted, health monitors, internet communication and artificial intelligence.  And yet, similar challenges also apply, especially when it applies to the application of these new technologies.  And this is a particular challenge when it comes to public services.

Faraday was talking about what he would have called “natural science”, and he dedicated his life to understanding electricity and electromagnetism, which are now the foundations for many other applications and scientific endeavours.  Gladstone’s point highlights that its success was by no means clear to everyone at the time.  Today, we might substitute “natural science” with “data science”, where the analysis of previously unmanageable or unmeasurable data sets offers to transform business and personal life.  And public services.

The point that Faraday’s quote demonstrates is that it’s not enough for a scientist, whether “natural” or “data”, to do analysis for the sake of it.  It always has to be “applied science” to make it successful or beneficial.  And so, it’s vital to put any innovation in terms of outcomes and benefits, rather than in any pure technical advance.

We already work with some Government Departments, who recognise how digital and data science can help transform the services they provide citizens.  But it’s also true to say that each government department is different, with its own objectives, and its own level of risk appetite and understanding when it comes to digital innovation, just like Gladstone was.  And some will need more convincing of the benefits than others.

So, Gladstone’s question, however boorish, is still relevant today, at least in relation to data science.  How would we describe the opportunities for applied data science for public services?

 

Traditional business case

As Faraday recognised, the strongest business case is always one that increases revenue or transactions or creates brand new revenue (or other forms of value) streams that hadn’t existed before.  This is the case whether the organisation is corporate or public, and so, in most ways, government is just like any other business.

This means that the objectives, and therefore the benefits, can be similar.  This is the case whether it’s increasing the booking flow on the MOT or HMRC tax submission online process, or increasing applications for new recruits to the Army.  These targets are very similar to those in the private sector, for whom Customer Experience, Media Attribution and Customer Insight are a known area of potential advantage and benefit.  For these types of public service, it’s important to recognise that there are clear parallels with other digital transformation programmes in other sectors.

 

Government focused, long-term business case

Secondly, and having made the first point, it’s important to recognise how some public services are not like other businesses.  For many digital businesses, it is normal to measure the impact of multichannel behaviour, but often in a relatively short measurement window, or with a fairly definable end metric.  For instance, calculating the impact of a new retail web site can be relatively rapid or short-term – if the sales come through, you know it’s working. 

Whilst these principles can still apply to digital citizen experiences, particularly ones that are more transactional in nature, many government services are more multi-channel, and long-term than that.  Most government services ultimately end up in an offline outcome of some kind – a behavioural change, or an efficiency gain in terms of time spent doing a job, or an even more difficult to measure attitudinal change, that makes people think about a topic differently.  And sometimes, as Faraday’s response implies, these can take years to come about.  So it’s important to plan out the full journey in order to understand the metrics along the way.  We have been providing multichannel insight since before the term “multichannel” became fashionable, so we are well placed to support public organisations to join up these disparate experiences.

 

Data science and innovation doesn’t have the answers at the beginning

But most of all, an insight programme can’t know what the answers are before it starts.  Gladstone didn’t realise this; for him, if it wasn’t immediately empirical, it served no purpose.  But that’s not how science - natural, data or otherwise – works.  Experimentation, as Faraday might have put it – in today’s business parlance, we often call it optimisation, or test and learn methods – needs time.

And this means it needs special circumstances to grow and develop, with a special type of management that can be difficult to foster in too rigid an organisational structure.  Test and learn strategies may not always provide better answers – in fact, they might not even mostly provide better results than control groups – but every now and again they might deliver insights into significantly better ways of doing things than had previously been done, or thought possible. This takes leadership, confidence in the long-term goals, not getting distracted by short-term effects, guidance, and trust in individuals to learn as they go.

Now, some might say that this flexible organisational structure doesn’t sound like a Government department, and so this sort of approach is not suited to public services.  But I would answer differently.  Firstly, the Government Digital Service has helped foster such a test and learn approach at the centre of UK Government, under the guidance of the Cabinet Office.  This has provided the senior stakeholder leadership to experiment with digital innovation in public services; this is permeating out to other departments.

And secondly, I would point to another famous Government organisation that was explicitly designed to experiment, and where management structures were deliberately flexible to accommodate the data scientists it employed.  It also happens to be our namesake – Station10, or Bletchley Park as it is now more commonly called, was the ultimate test and learn organisation, and it couldn’t have been more central to the UK Government’s strategy at the time.

And that’s why, in an admittedly somewhat long-winded way, is why we at Station10 are happy to announce that we are now officially a supplier on G Cloud 10, the public-sector cloud procurement framework. We are in the Cloud support category - suppliers provide services to help buyers set up and maintain their cloud services. Station10 services are now live in the Digital Marketplace where public sector organizations can search for cloud services.

The platform is transforming the government procurement and the digital government making it clear and simple, and enabling suppliers of all sizes to be in the government marketplace. Station10 is happy to this important framework to offer its services to the public sector; we think Michael Faraday, and perhaps even William Gladstone, would approve.

 

If you work in public services or Government in the UK, and are interested in investigating how insight and digital data science can help you, please get in touch, and we would be happy to discuss further.