Data’s role in propelling the public sector forward

The publication of the National Data Strategy was tremendous – it provided a timely framework for the public sector to start heading in a unified direction with correlated data infrastructures and services that will help drive efficiency and deliver better, more agile public services. Data-driven public service delivery can fuel innovation and job growth and the National Data Strategy will help unlock data’s true power and value.

We recently commissioned our public sector research in order to properly understand how important the Strategy is to key public sector thinkers – and we also wanted to know how best to continue working with our partner communities.

Our research showed that 75-80% of respondents thought it was imperative that the Strategy is adopted.

How are you seeing data change the UK public sector?

We’ve seen fundamental societal change in recent years - and we’re seeing the way society works drive the way public services need to be delivered.

In the pandemic we saw six years of digitisation happen in 12-18 months. We wouldn’t have dreamt of delivering apps to people’s phones with data about allergies and differing vaccination levels all in such a short time – but necessity dictated progress, and the technology sector as well as government learned a huge amount.

In part due to that, citizens now expect a better use of data – like how the world’s biggest online marketplace has the best set of delivery data. The next generation also have a different idea of security and simplicity when it comes to tech – whether it’s the covid app or We Buy Any Car – and the National Data Strategy has set a new high water mark for what public sector is capable of.

We’re seeing a lot of good work happening across sectors.  Data no longer needs to be connected to the application – it needs to be disaggregated, as with the insurance sector, where consumer efficiency for any form of insurance is now vastly improved.  

There are various different futures for data in the public sector. One leads to a more effective government delivering better services for citizens, and a more hospitable environment for business and civil society to thrive. Better data means a better understanding of the country we live in and better outcomes for citizens overall.  

An alternative future would be where we don’t get the infrastructure right – where we’ve papered over the cracks instead of fixing the plumbing, we’re not thinking about everyone needing to be data literate and the digital divide is exacerbated, and we’re wasting the huge potential for data sharing across government.

Can the current public sector infrastructure cope with the demands of the data economy?

There are good examples of excellent data use in the public sector – the covid 19 dashboard was an open data success story, and demonstrates one of the principles of open data where it gives others the opportunity to find things out as more eyeballs can lead to greater insight.

There are some good initiatives going on but there’s lots of work to do. There are challenges – fixing the infrastructure is not as sexy as some of the shiny applications we see, so how do you make the boring interesting? We also know there’s a problem with legacy IT in government and with data not being interoperable between departments – but the pandemic has really changed people’s attitudes and that could be a real driver for change.

Agile data infrastructure

Our report looked at how data infrastructure can help propel the public sector forward.

Five to ten years ago, organisations either built their own infrastructure or loaded it into a dark room somewhere. Then we saw the advent of public clouds and the ‘bottomless pit’ mentally. We wanted to look at government’s immense legacy and current infrastructure based in data centres. In our research we saw 30 per cent of organisations have adopted cloud. We’re now seeing a shift from cloud first to cloud appropriate – not being tied into one cloud, but having the freedom to choose cloud or on-premise where appropriate.

Government can be more agile and scale up or down where necessary with the cloud. We’re supportive of a blended cloud environment – we provide first party optimisation services across clouds and on-premise. Once you’ve thought about efficiency, you have to think about protection and security, and then legacy. Legacy infrastructure that is not cloud can be incorporated with a traditional environment storing cold data and the cloud storing hotter. 

Emerging data challenges

There are of course huge challenges around the sheer amount of data being created. The mobile world led us to believe in a data storage bottomless pit. Our survey showed us that data is expanding at immense rate – for example, in digital forensics, the police arrest small gang of criminals and they have to take all the data from all their laptops and phones.

68% of all data created is used once and never again. 8 per cent of world’s electricity by 2030 will be used storing data. We need to have conversations around storing data properly – cheap, cold and with low environmental impact. Data does not all need to be treated equally because it’s not all created equal.

Going forward, what’s key is retaining freedom of choice in data decisions you make – whether you’re cloud, multi-cloud or hybrid cloud; efficiency and avoiding waste need to be front of mind.

Data culture and jobs

There is also undoubtedly a technology skills challenge for both the public and the private sector, and a lack of diversity that needs to improve. But I’m enthusiastic about creating a culture where data is used to create better outcomes. That’s not to do with technology skills – our (data) industry needs an image revamp. The internet generation is focused on outcomes and showing that’s part of our culture will broaden the pool of people finding data roles more interesting and exciting.

Also, we’re seeing a boom in AI which is taking the value we can get from data to the next level. That’s also an attractive job vocation for a broader demographic. We need to get away from ‘scientist type’ roles to focus on roles driving data efficiency to achieve better outcomes.