• Tech News
    • Games
    • Pc & Laptop
    • Mobile Tech
    • Ar & Vr
    • Security
  • Startup
    • Fintech
  • Reviews
  • How To
What's Hot

Elementor #32036

January 24, 2025

The Redmi Note 13 is a bigger downgrade compared to the 5G model than you might think

April 18, 2024

Xiaomi Redmi Watch 4 is a budget smartwatch with a premium look and feel

April 16, 2024
Facebook Twitter Instagram
  • Contact
  • Privacy Policy
  • Terms & Conditions
Facebook Twitter Instagram Pinterest VKontakte
Behind The ScreenBehind The Screen
  • Tech News
    1. Games
    2. Pc & Laptop
    3. Mobile Tech
    4. Ar & Vr
    5. Security
    6. View All

    Bring Elden Ring to the table with the upcoming board game adaptation

    September 19, 2022

    ONI: Road to be the Mightiest Oni reveals its opening movie

    September 19, 2022

    GTA 6 images and footage allegedly leak

    September 19, 2022

    Wild west adventure Card Cowboy turns cards into weird and silly stories

    September 18, 2022

    7 Reasons Why You Should Study PHP Programming Language

    October 19, 2022

    Logitech MX Master 3S and MX Keys Combo for Business Gen 2 Review

    October 9, 2022

    Lenovo ThinkPad X1 Carbon Gen10 Review

    September 18, 2022

    Lenovo IdeaPad 5i Chromebook, 16-inch+120Hz

    September 3, 2022

    It’s 2023 and Spotify Still Can’t Say When AirPlay 2 Support Will Arrive

    April 4, 2023

    YouTube adds very convenient iPhone homescreen widgets

    October 15, 2022

    Google finishes iOS 16 Lock Screen widgets rollout w/ Maps

    October 14, 2022

    Is Apple actually turning iMessage into AIM or is this sketchy redesign rumor for laughs?

    October 14, 2022

    MeetKai launches AI-powered metaverse, starting with a billboard in Times Square

    August 10, 2022

    The DeanBeat: RP1 simulates putting 4,000 people together in a single metaverse plaza

    August 10, 2022

    Improving the customer experience with virtual and augmented reality

    August 10, 2022

    Why the metaverse won’t fall to Clubhouse’s fate

    August 10, 2022

    How Apple privacy changes have forced social media marketing to evolve

    October 16, 2022

    Microsoft Patch Tuesday October Fixed 85 Vulnerabilities – Latest Hacking News

    October 16, 2022

    Decentralization and KYC compliance: Critical concepts in sovereign policy

    October 15, 2022

    What Thoma Bravo’s latest acquisition reveals about identity management

    October 14, 2022

    What is a Service Robot? The vision of an intelligent service application is possible.

    November 7, 2022

    Tom Brady just chucked another Microsoft Surface tablet

    September 18, 2022

    The best AIO coolers for your PC in 2022

    September 18, 2022

    YC’s Michael Seibel clarifies some misconceptions about the accelerator • DailyTech

    September 18, 2022
  • Startup
    • Fintech
  • Reviews
  • How To
Behind The ScreenBehind The Screen
Home»Tech News»Data-driven government needs practical steps
Tech News

Data-driven government needs practical steps

September 5, 2022No Comments7 Mins Read
Facebook Twitter Pinterest LinkedIn Tumblr Email
Brits say social media must do more to block harmful content
Share
Facebook Twitter LinkedIn Pinterest Email

Data-driven government is not new, or innovative – but it is essential to underpin policy and operational decision-making. Despite this having been central to government digital strategy for years, we are still struggling to see the outcomes, especially outside pockets of the pandemic response.

We know the problems – legacy technologies, a skills gap and cultural blockers – but what practical steps can we take today that will actually move the needle so that all public services are designed in a way that truly benefits citizens?

We talk a lot about user values in digital transformation, and working with data is no different. It is slightly astonishing how much money is put into building data platforms without applying the same techniques that we use when creating a digital system. For instance, if you were building a website, you would use user research to identify problems, test ideas and validate solutions, and only then deliver to those requirements.

Across the public sector, a lot of expensive data platforms are created with a “build it and they will come” mentality. This ignores what people really need, so the systems are not adopted and, as a result, those platforms are deemed failures.

Instead, we should build data platforms with the same techniques we use when creating anything digital. If you fix problems that people have, you make things easier for them, and a data platform will become sticky because there is a reason to use it.

Finding balance is critical for both the creation of a data platform but also the use of it. The data space moves fast, and it is worth remembering that what you are building will only last so long. This means you must balance this new-thing-versus-old-thing mentality. But, equally, you don’t want to just keep adding new tools to the toolkit. Iterate for as long as you need to really deliver value for the people you are designing for. Creating space for innovation is crucial – but don’t underestimate new tech fatigue.

See also  U.S CFTC charges South African company over $1.7 billion bitcoin ponzi scheme – DailyTech

Create a shared language  

One significant blocker to the adoption of data-driven practices is a lack of a common language. It is too easy for one term to have numerous meanings within an organisation. Moving to a domain-driven, product view of data can help.

We have found domain-driven development to be a great starting point. It’s an idea that allows you to view your organisation as a set of bounded domains and identify the root of terms and their meaning. This allows you to create an organisational data model to clarify meanings and foster better conversations between teams. 

Once you really understand your organisation in this way, you can start building a common vocabulary, where terms such as “person” and “property” have the same meaning (or at least an agreed one!) to all.

The reason that data platforms fail is rarely due to the technology – it’s often because of the culture behind its use. Even something as simple as ownership can cause issues. It is usually clear to teams that they are responsible for the data in the databases that they look after. What is less clear to them is that the data still belongs to them once it has been copied into a data platform.

Helping the teams to feel connected to the platform, because they use it to solve a problem, will give them a reason to care about their data once it’s in there. This extends to governance and legal issues, too – the data doesn’t stop being the team’s responsibility just because it has been copied.

There is a cultural aspect of making sure you train all your people to be data literate too. 

Data literacy can take different shapes, but you are never going to become a data-mature organisation if you haven’t been through a cultural shift. 

Architect your technology to be replaced

Creating technology to be replaced is hard to do in the digital and data space. There are foundational pieces that you should put in place that won’t change. But, equally, try to use open technology as much as you can.  

There is a cost with open-source frameworks. They are free to use, but they can be expensive to maintain. But by using open technology, you can take your data and shift it from one system to another without having to rewrite everything.

The days of having a governance committee that reviews all things data feels opposite to what we have done within the digital sector. 

We, as a community, should be agreeing on what principles we want to apply to our data. Agreeing on the definition of “sufficient testing” and finding ways to share/contract data schemas is far more efficient than a distant panel taking control. Shifting the responsibility to the teams creating the products is a huge step towards true data maturity.

You would never build an API [application programming interface] for your customers and then change the interface without warning them. With APIs, we use techniques like version numbers or upgrade paths to ensure continuity or service. Sadly, this isn’t always the case with data.

Often, we find data is collected from points within a system that are not really intended for consumption, so the data’s schema can be ill-considered or, even worse, change with no notice. By building data as a product, where it is intended and designed for use by others, we can prevent this issue.

This comes back to making sure the team that generates the data owns the data. They need to maintain and care about it, otherwise people won’t use it and it will cost the organisation time, money and effort.

Focus on the ethics of personal data

Having access to a person’s name or address often feels vital to completing a piece of analysis. In the vast majority of cases, it is not. It is only human to want to see names and postcodes that seem familiar to use, rather than a column of random numbers, but from a mathematical point of view, it very rarely makes any difference. In fact, we usually convert them to numbers to use the values.

Wherever possible, we should question when we see personal details, and even more so protected characteristics. As a default, we should not have access to them and we should pseudonymise the values.

As data platforms become more mature and people start using machine learning, ethics becomes more important. One of the only exceptions to the pseudonymisation rule is to make sure that any selected training data is representative of the population and has no bias in it. Even in this case, we should not be able to identify a person, but only know enough to assess the data for bias.

Data continues to be a hot topic, across both the private and public sectors. And although all the foundations mentioned come from a technology point of view, they are particularly applicable to the pockets of legacy-facing portals within our public services. If we want to realise the benefits of data-driven government, we need to get our foundations in place – and there is no better time to do that than now.

Jim Stamp is head of data at Made Tech

Source link

Datadriven government practical steps
Share. Facebook Twitter Pinterest LinkedIn Tumblr Email

Related Posts

Senators Want ChatGPT-Level AI to Require a Government License

September 9, 2023

3 Steps To Building A Top-Performing Sales Team

September 1, 2023

Nine Steps To Take If You Want To Hire The Best COO For Your Company

August 22, 2023

A Data-Driven Approach To Improving Employee Performance And Morale

August 13, 2023
Add A Comment

Comments are closed.

Editors Picks

Samsung’s Z Fold 4 passes durability tests, but how will it hold up long term?

August 30, 2022

Amazon Investors Demand Answers About Its Cloud’s Human Rights Record

December 16, 2022

Rec Room hits 75M lifetime users and $1M in creator payouts for Q1

June 25, 2022

Green Parties Are Gaining Power—and Problems | Startup

June 23, 2023

Subscribe to Updates

Get the latest news and Updates from Behind The Scene about Tech, Startup and more.

Top Post

Elementor #32036

The Redmi Note 13 is a bigger downgrade compared to the 5G model than you might think

Xiaomi Redmi Watch 4 is a budget smartwatch with a premium look and feel

Behind The Screen
Facebook Twitter Instagram Pinterest Vimeo YouTube
  • Contact
  • Privacy Policy
  • Terms & Conditions
© 2025 behindthescreen.uk - All rights reserved.

Type above and press Enter to search. Press Esc to cancel.