A lack of institutional memory can hamper attempts to build new services, products or organisations.

Too often, valuable insight and research is lost over time and the danger is that teams are destined to repeat the same costly mistakes over and over again. Time is wasted replicating or duplicating what went before instead of trying to learn from it.

Embracing the past can help you understand what worked and more importantly what failed so you can learn from it and embed that knowledge in whatever you do next.  

The long view

In a very old Guardian interview, Depeche Mode lead singer Dave Gahan said, “if you stick around long enough you’re going to become fashionable eventually.”

I started working in digital government way back in 2001 at the Office of the e-Envoy. First, I worked on UK online, then Directgov and was a founder of the team that built GOV.UK. In that time, I’ve read hundreds of strategy documents, policy papers, usability reports and more recently blog posts about designing and building government services.

The song remains the same

What’s striking are the number of ideas, arguments and memes that continue to circulate and repeat. Take for example, this line:

“Making sure that public service users, not providers, are the focus, by matching services more closely to people’s lives.”

Sounds like it could have come from the Government Digital Service but in fact is from 1999’s ‘Modernising Government’ report. As one of the authors of the book ‘Digitising Government’, Jerry Fishenden points out the narrative and words to describe digital government in the last 20 years have remained “remarkably consistent”.

Digital myths

At a smaller scale, on long running projects, you can see the same lack of institutional memory and it can be costly. Sometimes a new team takes over a service with a mandate to make changes and ambition to make their service more ‘engaging’ or ‘compelling’ for the user. They design whizzy features to start conversations with users or give them a reason to return.

The need for these features has often been debunked at least once through user research or insight from seeing how people *actually* use a service. At best, teams will sink time into the same debates that went before, at worst they build expensive features that no-one uses and make the service harder to operate.

Talent drain

Often the single biggest factors is that people move on. In some Whitehall digital teams at the moment, you’ll see fast stream civil servants in key roles. While they will undoubtedly learn valuable digital skills, placements are generally only six months long so that built-up knowledge is then lost to the team when the fast-streamer moves to their next assignment.

The recent Institute of Government report on staff turnover in the Civil Service highlights this issue. According to the report, senior civil servants average just two years in a role, compared to five years for directors in the private sector.  

What to do

It sounds trite but working in the open really does make things better. Blogging in public about your work is the best way to maintain a public record. A friend of dxw, Giles Turnbull eloquently describes a blog as “your brain, on the internet, over time.” We try to do this for all our project work, for example rolling out new housing services with Metropolitan Thames Valley Housing, helping Croydon set up new digital teams or helping international governments do business.

Other ways to record conversations include techniques like architecture decision records which we use to document technical decisions on projects like Report Management Information for CCS. They give us a record of decisions that are made, but also the context around that decision to revisit it when things change, so we can constantly adapt to changing circumstances over time.

All dxw digital projects publish week notes every Friday which become a shared history of the work. We describe what we’re worried about, any blockers and list the things we did during the week and what’s planned for the following week. Weeknotes are an amazing tool that meet many different needs, for example, calling out risk to project stakeholders early so there are no nasty surprises. They keep people informed, those involved in the work or those in the wider organisation. If you’re trying to get momentum behind a project, weeknotes demonstrate visible progress to a wider organisation.

Let the past guide you

To be better keepers of institutional memory, teams must embrace and respect what’s gone before. Early on, in GDS, I wrote a blogpost to remind people that what we were doing was by no means unique in government, that we were not the first to tread this path.

Teams should be humble and remember that the work that went before always has value, even if it requires updating. The learnings along the way are of equal importance to the finished product.

The skills of the digital archivist or librarian need to be nurtured and appreciated. It speaks volumes that one of the fullest accounts of the last 20 years of government digital is on Jerry Fishenden’s website rather than GOV.UK.

We should cherish the tireless work of the National Archive in keeping the digital public record through the UK government web archive. However, with each departmental website redesign and with the mammoth transition to GOV.UK, some of the old links are broken. As an industry we forget that “cool URIs don’t change” and need to get better at preserving the digital public record. There are tools that can help, for example, the Transition Tool which gives departments the ability to manage all the URLs of content that moved to GOV.UK.

Build teams

If you want to maintain institutional memory, the best way is to fund teams rather than projects. One of the most frustrating things about short term projects are that just as the team is hitting its stride and working well together, it disbands. There is immense value in understanding different people’s ways of working, it makes it far easier to make rapid progress if you aren’t spending the first couple of weeks on a project getting to know each other.

Standards and shared principles can guide work over time, for example, the Government Service Standard or closer to home, dxw’s principles which we publish in our playbook.

One of the things that makes working at dxw so rewarding is that we’re in the business of building teams. Projects are transient, but teams endure.

 

The post The power of institutional memory appeared first on dxw digital.

Original source – dxw digital

Text saying "Service Assessment" with DHSC approved brand colours

From: NHSX

Assessment date: 6 June 2019

Stage: Alpha

Result: Met

Service provider: Public Health England

Service Description

The UK National Screening Committee advises ministers and the NHS in the 4 UK countries about all aspects of health screening and supports implementation of screening programmes.

The Committee has a list of 109 policy recommendations which are reviewed on a triennial basis. Their recommendations are based on evidence reviews which are commissioned and managed by the evidence team, and on the opinions of external stakeholders whose input is polled during public consultations. The service captures all this work by way of displaying the full list of policy recommendations and active consultations to the public.

Service users

The users of this service are:

  • Evidence review managers: commission and preside over evidence reviews
  • Policy stakeholders: access screening information, make statements on behalf of the perspective of their organisation
  • Interested members of the public: access screening information online

1. Understand user needs

Decision

The team met point 1 of the Standard.

What the team has done well

  • Usability testing in almost every sprint in alpha
  • In the alpha period after the first assessment the team used an agency to recruit users with accessibility and access needs
  • Tested admin interface with users at their place of work
  • Tested outside of England, in Wales and Scotland
  • Included staff users in almost every sprint
  • Tested with members of the public who weren’t familiar with the service

What the team needs to explore

  • It would be useful to understand the end to end journey for the user, what other services do they interact with to complete their wider goal? Is there anything the team learnt in their research that could be shared with these other services? Are there blockers to completing the user’s wider goal that the team could influence?
  • Explore how easy to understand and accessible the content written by policy team is likely to be. Perhaps test the content with users and have policy content writers observe? Also, are the plain English summaries produced by third parties accessible and easy to understand? If this hasn’t been tested it would be interesting to explore rather than assume.

2. Do ongoing user research

Decision

The team met point 2 of the Standard.

What the team has done well

  • The team have a thorough plan for ongoing user research and a dedicated user researcher in the team

What the team needs to explore

  • The team mentioned they plan to do unmoderated testing (by giving the prototype to users for feedback later). This is a great way to reach more people. However to get more useful results it would help to give users structure on what they are looking for so that you don’t end up with opinions or vague reviews. You also have to weigh this evidence against data you have collected through observation. For example, you may find that evidence collected in an unmoderated test is ambiguous or confusing. If this is the case you could hold shorter follow up interviews with users.
  • It appeared that the user researcher had carried out and analysed some sessions on their own. Sometimes this is unavoidable, but we would recommend at least one other person attend to take notes, that there is at least a remote viewing option and that as many as possible team members be involved with analysis

3. Have a multidisciplinary team

Decision

The team met point 3 of the Standard.

What the team has done well

  • The panel were pleased that content designers had been engaged several times throughout the extended alpha
  • The team explained that the content designers came from outside the team which helped ensure there was not a conflict of interest in the research and design process
  • The team are creating guidelines for the helpdesk for assisted digital users and have an alternate route of engagement in the shape of a postal form

What the team needs to explore

  • Based on recommendations from the last assessment where the content designer was doing some of the user research, the current user researcher chose to be less involved with content design reviews. We would recommend that the user research and content design roles are held by different people within the team and that they work closely together to set research goals, analyse research and agree on actions. The panel was pleased to hear that the team plan on bringing in a separate content designer as part of private Beta

7. Understand security and privacy issues

Decision

The team met point 7 of the Standard.

What the team has done well

  • The panel were pleased to hear that the team had plans to redirect the existing URL to reduce phishing potential
  • The team mentioned that they are working on a GDPR statement on how user data will be used
  • The team plan on using existing PHE login infrastructure

What the team needs to explore

  • The team needs to test the service with penetration testers and make sure all the content is sanitised

12. Make sure users succeed first time

Decision

The team met point 12 of the Standard.

What the team has done well

  • The panel were impressed that the team have timed task completion for admin users and have reduced this from about 60 minutes to about 5 minutes

What the team needs to explore

  • The team needs to test the service on mobile and tablet. Even though the current site isn’t accessed regularly on mobile, a lot of their users are repeat visitors and may have learned to avoid using their mobile. New users, the public in particular, will expect to be able to access content and complete tasks on their preferred device
  • Make changes based on the usability testing, for example the screen magnifying issue with the checkboxes. If this is a design system pattern the team could suggest a change to the design system by contacting the team

13. Make the user experience consistent with GOV.UK

Decision

The team met point 13 of the Standard.

What the team has done well

  • The team plan to run workshops with policy team who write the content so that they write in the GOV.UK style
  • They have engaged with other government teams who are delivering services for internal users. Keep doing this!

What the team needs to explore

  • Make a plan for ongoing engagement with policy team content writers to make sure they are still writing in the GOV.UK style
  • If there are health terms not covered by the GOV.UK style guide use the NHS content style guide to supplement it
  • PHE staff should be able to get access to cross-gov Slack and the Google groups. Contractors without a government or NHS email address could ask questions through PHE staff in their team. Or PHE should consider giving PHE email addresses to contract staff so that they can engage with the cross-gov community
  • It would improve the service to have a dedicated content designer in the team for beta, this doesn’t need to be full time if that isn’t necessary. This role could also lead on introducing content design methods to policy teams

14. Encourage everyone to use the digital service

Decision

The team met point 14 of the Standard.

What the team has done well

  • Users have the option of using email, letter or telephone to complete their task
  • Helpline is on every page and helpdesk can guide user the right content
  • The team had done analysis on number of email sign ups that came from outside of England and matched this to the number of registered charities outside of England
  • Product manager regularly reviews helpdesk reports

What the team needs to explore

  • It appeared that the team have engaged with the helpdesk, but not carried out any training with them. We’d recommend training them in the new website and have regular engagement going forward

16. Identify performance indicators

Decision

The team met point 16 of the Standard.

What the team has done well

  • The team have gathered some benchmark KPIs for comparison

What the team needs to explore

  • Add event tags to key behaviours and actions on the site so that you can interrogate this data in Google Analytics
  • Look at gathering data on task completion or click rate on old site and compare it to the same data on the new site. This would be useful when comparing changes in behaviour of mobile users or users from different traffic sources
  • It might be useful to gather qualitative data from internal users on the old site and compare it to the new site once it is in beta. This could be in the form of observing people use the site, or by asking for their feedback on specific tasks

17. Report performance data on the performance platform

Decision

The team met point 17 of the Standard.

What the team has done well

  • The service is registered with the performance platform team and product manager has been speaking with them

What the team needs to explore

  • Following a review of other PHE services on the platform we recommend that the team look to add the service to the site

Original source – Stephen Hale

All the Cloud

The MOJ are big users of public and private clouds to operate over 800 different technology systems ranging from internal IT tools/solutions (device management for laptops, WiFi etc) to case management solutions used for administering over £1 billion a year in legal aid, as well as brand new digital services.

We mainly use Amazon Web Services (AWS) and Microsoft Azure for commodity public cloud hosting.

Cloud is secure as you make it

Providers like AWS create powerful tooling and services that you can use to keep systems and data safe in the cloud (often safer than in a private datacentre where you have to do everything yourself, and likely do it worse) — but you have to actually use those tools and services to benefit from them.

Our baseline for our AWS accounts

We have  over 120 AWS accounts and counting, and for good operational reasons they can be configured differently. We wanted to ensure they all met a common baseline… so we wrote one.

We  believe ‘security’ can work in the open so in addition to publishing the MOJ’s IT policies, as part of a cyber security guidance microsite, we have published how our security baseline for MOJ Amazon Web Services accounts.

Why we did what we did

AWS have a lot of services and you can leverage their platforms in a great number of ways. We wanted to set the baseline at a good level, while catering for diverse architectures and applications, without creating unreasonable high-effort tasks for teams but ensuring we avoid common bad practice missteps like leaky S3 buckets.

We chose generally accepted good practices (for example, encryption); things that are a mixture of security and operational for good account/resource management (tagging); and leveraging powerful AWS platforms that offer a lot of security with minimal effort (AWS GuardDuty).

We included ‘monitoring’ and ‘resolution/escalation’ to catch any regressions and court correct. We preferred automated resolution over escalation to humans but worked to ensure that humans are involved where they should be, to make decisions that are not always black/white and thus easily programmable.

Journey over destination

The baseline is our current minimum security posture for our MOJ AWS accounts – not what we think is a gold standard. This helps set a bar but gives teams latitude for doing things differently when they need to.

Do the hard work to make it simple

The 4th government design principle is “do the hard work to make it simple” so we did exactly that: over 120 unique ways of implementing the new baseline didn’t make any sense, so we wrote and published a whole load of CloudFormation to help our colleagues implement the baseline quickly and easily.

Onwards

AWS SecurityHub

AWS SecurityHub is fairly new so we’re going to continue helping teams rollout our baseline and then take stock of where to see if we can make the baseline a little easier to implement, or whether we’re ready to raise the bar even higher because our MOJ colleagues already do a great job managing our systems safely in the Cloud.

All the Clouds

As mentioned above, the MOJ also uses other public cloud solutions including Microsoft Azure and Heroku. Like we have for AWS, we will write security baselines for those as well, publishing as part of our cyber security guidance microsite.

Don’t forget to sign up for updates

Psst, we are also hiring! If you’re interested in working in a fun, expert, diverse team keeping the very heart of the Justice system safe then have we got a URL for you to click!

Original source – MOJ Digital & Technology

I was watching the beginning of the latest series of Big Little Lies. In it a young teen explains to her Mum why she doesn’t want to go to college: she wants to join a start up that is a for-profit organisation providing accommodation for the homeless.

Obviously this was an effort to create a scenario that showcases the millennial snowflake generation set of ideals against the traditional. I found my 47 year old self on the side of the teenager, and so the cognitive dissonance begins.

In my lifetime I have done two important things: 1. I had two daughters and raised them with awareness and 2. I set up a not-for-profit organisation: Young Rewired State in 2007, aimed at bringing together the naturally talented young programmers and engineers who were brilliant but failing at school and failing exams, with few work or learning options and no community. The second failed in 2016, a victim of its own success and lack of sustainable business model/scale which is a total personal failure as I should have listened and learned (in some instances) to those who had slightly different values to myself, but who could have kept this important work alive.

When my darling nephew died in 2017 at age 19 and broke the world, my passing interest in mental health became far more than that, it became my lifeline. Although he did take his own life, there is scant evidence that there were mental health problems in advance of this act, it is all too sadly likely that this was a rash drunken decision — but we will never know.

However, the groups in which I sought and found comfort opened my eyes to a world of crisis especially with our young people and their mental health. Too many young people, google the stats it will shock you, and changes for the worst on a month by month basis. A story that broke my heart even more was from a mother in a group I had been a part of for a few months after my nephew died, who joined us when her 16 year old son got up from the family sofa, made a cup of tea for his parents and siblings, went back into the kitchen to get his own cup, walked into the garden and hung himself. No sign, rhyme or reason.

For several years, even before my nephew took his life, I had been working on an idea for a ‘spa for teens’ based on my interest in the 97ers generation. This rapidly became an idea for a cool members club for kids aged 16–24 where every person they came in touch with in the club including baristas and security had mental health training, but we also ran fun stuff and events that helped address all of the challenges facing them. With parental sessions early in the day to help scared grown ups.

I have the business plan and the breakdown of what it will take but my one thing was: it cannot fail like Young Rewired State. This is even more important IT HAS TO HAVE a sustainable business model. I cannot swoon into my liberal snowflake brain and make this a not-for-profit that relies wholly on donations and has no (slightly unethical in my mind) business model. This has to speak to the rich kids and their money in order to meet some of the needs of those who cannot pay.

And so I have been paralysed, for years now. I want to do this, I know what is needed. I know there is a business model here that will make it self sustaining and bring rewards for investors. But I can’t take the first step as my cognitive dissonance is so massive I can’t even begin to take the necessary next steps… but I KNOW we need this and I know this will save lives.

What would you do?

Original source – Emma Mulqueeny

Sticker sheet showing "Users First"

The User Research in Government blog has been running for over 5 years now. It kicked off with an article by former GDS luminary Leisa Reichart listing five ways to help user research work better in agile (definitely worth a read if you haven’t seen it before). And while, in the blog’s early days, many of the posts were very GDS-centric, it has since branched out to draw attention to the great user research going on across government. Here are a few examples:

We want to keep this momentum going, to ensure this blog serves the whole user researcher community, as well as all those who are simply curious about what user researchers in government do (it’s not all doodling on post-it notes, promise).

So, if you’re a user researcher in government (or work closely with user researchers) and have an idea for a blog post, whether it focuses on a particular method, a challenge you’ve faced in your research, a shining example of research that’s gone really well, or something else entirely (perhaps not your grandmother’s exquisite carrot cake recipe), we’d be delighted to hear from you.

If you’re not sure about an idea, no matter. Get in touch with us anyway and we’ll be more than happy to discuss whether there’s a potential blog post in the making, and if so we’ll help get your blog post spruced up for publication.

And while we’re here, I’ll end with some curated links to a selection of the blog’s most popular and enduring posts, from recent gems to older posts that remain as insightful today as they were when first published:

Have you got an idea for a user research-related blog post? Let us know in the comments.

Subscribe to this blog.

Original source – User research in government

Event attendees participating in an interview techniques session, photo shows 2 people about to shake hands

Taking part in the interview techniques session

It’s Carers Week, and this year’s theme is ‘getting carers connected’. So to recognise this significant date, I’ve written a blog-post about my work with the Business in the Community project, Apollo. It’s helping 100 care leavers into employment and education.

A day demonstrating possibilities

I introduced the project to Civil Service Local and together with a team of people from 5 departments we hosted a day for young care leavers in our Sheffield digital hub. The event introduced them to the work of the Civil Service and what we do in DWP Digital. One of the facts about carers is that they are 7 times lonelier than the general public, so our event helped them to meet other people in their situation and people in the world of work, build confidence and provide some employability skills along the way.

It was an action packed day that started with an interactive introduction, passing an inflatable palm tree around followed by a short game of ‘people’ bingo. This set the tone for the rest of the day – that learning can be fun!

Group of attendees with Carolynn and the inflatable palm tree from the interactive introductions session.

Interactive introductions

Activities included

A presentation showcasing how the Civil Service touches everyone’s lives; this was supported by the Civil Service volunteers own job stories.

A session on employability skills where we asked attendees to consider what they felt the top 10 skills employers want are. We had a fastest finger first quiz and a good natured interview role play session where we played out ‘good’ and ‘bad’ techniques.

The Department of Vehicles and Standards Agency, Highways Agency and the police ran sessions, demonstrating the breadth of roles available in the Civil Service and public sector.

Competing with the excitement of the police was a tough ask but DWP Digital stepped up with our Accessibility Solutions team, Clare, Rob and David – especially when we introduced Rob who has a guide dog. The team explained their role and demonstrated a range of accessibility tools.

At our ‘Tech Bar’ – a walk up service for colleagues having IT issues – the manager Fred shared his story. Despite not doing any higher education he has gained his skills and qualifications on the job and now manages the Tech Bar. He talked about the variation in the work and some of the more amusing incidents they have dealt with.

The day wouldn’t have been complete without a challenge – and so colleagues, Rashmi, Marc and Dave, used Lego to demonstrate agile ways of working. They set a task with user specification, digital design and development in mind. They ran the challenge in a series of sprints with the teams tasked to build something that the Product Owner wanted. It wasn’t always easy but everyone embraced the challenge with a little bit of healthy competition.

Rashmi and attendees working at a table on the Lego challenge

Embracing the agile Lego challenge

Going away inspired

The day ended with both attendees and volunteers full of enthusiasm. The feedback was brilliant with comments including:

“I feel more confident. And I feel I have more ability to achieve my goals.”

And, inspired by Fred’s session:

“Whatever your background you can have a successful career and make something of your life”.

One of the attendees also remarked that having a job helping people is awesome.

Overall it was a really rewarding experience. I want to encourage more women and young people to join us, and to do this we need to foster relationships with schools, colleges and disadvantaged groups. The event was very much ‘test and learn’ to develop a blueprint for future visits and cross department collaboration and I’m looking forward to developing the project further and hosting further visits planned for the Autumn.

Work with impact

If you want to do meaningful work that makes a difference, this is the place to be. Have a look at our careers site for our latest vacancies. Keep up to date by following us on Twitter @DWPDigital and @DWPDigital Jobs.

Original source – DWP Digital

[Summary: extended notes from an unConference session]

At the recent data literacy focussed Open Government Partnership unConference day (ably facilitated by my fellow Stroudie Dirk Slater)  I acted as host for a break-out discussion on ‘Artificial Intelligence and Data Literacy’, building on the ‘Algorithms and AI’ chapter I contributed to The State of Open Data book.

In that chapter, I offer the recommendation that machine learning should be addressed within wider open data literacy building.  However, it was only through the unConference discussions that we found a promising approach to take that recommendation forward: encouraging a critical look at how AI might be applied at each stage of the School of Data ‘Data Pipeline’.

The Data Pipeline, which features in the Data Literacy chapter of The State of Open Data, describes seven stages for woking with data, from defining the problem to be addressed, through to finding and getting hold of relevant data, verifying and cleaning it, and analysing data and presenting findings.

Figure 2: The School of Data’s data pipeline. Source: https://schoolofdata.org/methodology/
Figure: The School of Data’s data pipeline. Source: https://schoolofdata.org/methodology/

 

Often, AI is described as a tool for data analysis (any this was the mental framework many unConference session participants started with). Yet, in practice, AI tools might play a role at each stage of the data pipeline, and exploring these different applications of AI could support a more critical understanding of the affordances, and limitations, of AI.

The following rough worked example looks at how this could be applied in practice, using an imagined case study to illustrate the opportunities to build AI literacy along the data pipeline.

(Note: although I’ll use machine-learning and AI broadly interchangeably in this blog post, as I outline in the State of Open Data Chapter, AI is a  broader concept than machine-learning.)

Worked example

Imagine a human rights organisation, using a media-monitoring service to identify emerging trends that they should investigate. The monitoring service flags a spike in gender based violence, encouraging them to seek out more detailed data. Their research locates a mix of social media posts, crowdsourced data from a harassment mapping platform, and official statistics collected in different regions across the country. They bring this data together, and seek to check it’s accuracy, before producing an analysis and visually impactful report.

As we unpack this (fictional) example, we can consider how algorithms and machine-learning are, or could be, applied at each stage – and we can use that to consider the strengths and weaknesses of machine-learning approaches, building data and AI literacy.

  • Define – The patterns that first give rise to a hunch or topic to investigate may have been identified by an algorithmic model.  How does this fit with, or challenge, the perception of staff or community members? If there is a mis-match – is this because the model is able to spot a pattern than humans were not able to see (+1 for the AI)? Or could it be because the model is relying on input data that reflects certain bias (e.g. media may under-report certain stories, or certain stories may be over-reported because of certain cognitive biases amongst reporters)?
  • Find – Search engine algorithms may be applying machine-learning approaches to identify and rank results. Machine-translation tools, that could be used to search for data described in other languages, are also an example of really well established AI. Consider the accuracy of search engines and machine-translation: they are remarkable tools, but we also recognise that they are nowhere near 100% reliable. We still generally rely on a human to sift through the results they give.
  • Get – One of the most common, and powerful, applications of machine-learning, is in turning information into data: taking unstructured content, and adding structure through classification or data extraction. For example, image classification algorithms can be trained to convert complex imagery into a dataset of terms or descriptions; entity extraction and sentiment analysis tools can be used to pick out place names, event descriptions and a judgement on whether the event described is good or bad, from free text tweets, and data extraction algorithms can (in some cases) offer a much faster and cheaper way to transcribe thousands of documents than having humans do the work by hand. AI can, ultimately, change what counts as structured data or not.  However, that doesn’t mean that you can get all the data you need using AI tools. Sometimes, particularly where well-defined categorical data is needed, getting data may require creation of new reporting tools, definitions and data standards.
  • Verify – School of Data describe the verification step like this: “We got our hands in the data, but that doesn’t mean it’s the data we need. We have to check out if details are valid, such as the meta-data, the methodology of collection, if we know who organised the dataset and it’s a credible source.” In the context of AI-extracted data, this offers an opportunity to talk about training data and test data, and to think about the impact that tuning tolerances to false-positives or false-negatives might have on the analysis that will be carried out. It also offers an opportunity to think about the impact that different biases in the data might have on any models built to analyse it.
  • Clean – When bringing together data from multiple sources, there may be all sorts of errors and outliers to address. Machine-learning tools may prove particularly useful for de-duplication of data, or spotting possible outliers. Data cleaning to prepare data for a machine-learning based analysis may also involve simplifying a complex dataset into a smaller number of variables and categories. Working through this process can help build an understanding of the ways in which, before a model is applied, certain important decisions have already been made.
  • Analyse – Often, data analysis takes the form of simple descriptive charts, graphs and maps. But, when AI tools are added to the mix, analysis might involve building predictive models, able, for example, to suggest areas of a county that might see future hot-spots of violence, or that create interactive tools that can be used to perform ongoing monitoring of social media reports. However, it’s important in adding AI to the analysis toolbox, not to skip entirely over other statistical methods: and instead to think about the relative strengths and weaknesses of a machine-learning model as against some other form of statistical model. One of the key issues to consider in algorithmic analysis is the ’n’ required: that is, the sample size needed to train a model, or to get accurate results. It’s striking that many machine-learning techniques required a far larger dataset that can be easily supplied outside big corporate contexts. A second issue that can be considered in looking at analysis is how ‘explainable’ a model is: does the machine-learning method applied allow an exploration of the connections between input and output? Or is it only a black box.
  • Present – Where the output of conventional data analysis might be a graph or a chart describing a trend, the output of a machine-learning model may be a prediction. Where a summary of data might be static, a model could be used to create interactive content that responds to user input in some way. Thinking carefully about the presentation of the products of machine-learning based analysis could support a deeper understanding of the ways in which such outputs could or should be used to inform action.
  • The bullets above give just some (quickly drafted and incomplete) examples of how the data pipeline can be used to explore AI-literacy alongside data literacy. Hopefully, however, this acts as enough of a proof-of-concept to suggest this might warrant further development work.

    The benefit of teaching AI literacy through open data

    I also argue in The State of Open Data that:

    AI approaches often rely on centralising big datasets and seeking to personalise services through the application of black-box algorithms. Open data approaches can offer an important counter-narrative to this, focusing on both big and small data and enabling collective responses to social and developmental challenges.

    Operating well in a datified world requires citizens to have a critical appreciation of a wide variety of ways in which data is created, analysed and used – and the ability to judge which tool is appropriate to which context.  By introducing AI approaches as one part of the wider data toolbox, it’s possible to build this kind of literacy in ways that are not possible in training or capacity building efforts focussed on AI alone.

Original source – Tim Davies

people sitting around 5 desks, working on laptops

Developers running a coding workshop at GDS.

Over the past year, innovation has been a big area of focus for me, as it has been for the team here at GDS and for Minister for Implementation, Oliver Dowden.

Transformation cannot be achieved without innovation. As an organisation, we should look at how we can continue to transform government, by giving people the tools, structures and skills they need. We’ve done some great work so far: from the publication of the technology innovation in government survey to the delivery of the GovTech Catalyst programme.

The new Government Technology Innovation Strategy, developed by GDS, and the guide to using artificial intelligence (AI) in the public sector, developed by GDS and the Office for Artificial Intelligence (both published earlier this week) mark a significant step forward for us.

While developing the strategy, we worked hard to ensure that the views of academics and technologists in the private sector and from across the public sector were addressed, particularly what they believed blocked innovation and what enabled it in government.

The strategy rightly identifies people as an enabler of innovation. This is something I’ve believed for a long time. It’s all too easy to think that developments in technology make people less important. With every year and every job I’ve had in digital, I become more and more convinced that the reverse is true. It’s people that make the greatest contribution when it comes to emerging technology in government.

As head of the Digital, Data and Technology (DDaT) profession, I’d like to share what the Government Technology Innovation Strategy means for our people.

People progress so far

In the 2017 Government Transformation Strategy, we set our ambition as ‘creating one of the most digitally skilled populations of civil servants in the world’.

We’ve made great progress, and this will undoubtedly support the work we do in the future with emerging technologies in government.

To begin, we created the DDaT Profession Capability Framework, which helps to improve recruitment by ensuring that there’s consistency in job roles.

Before, there were many job roles across government – many of which were identical but with a different label. This meant that it wasn’t easy to move jobs between departments and it was confusing for those who wanted to join government.

As part of building the digital and technology profession, we created a clear structure of job roles. We reclassified and reorganised job roles across departments into a new taxonomy of nearly 40 job roles.

This has been used to create consistency and alignment across departments.

This means a more visible route for career progression and a better grasp of the huge scale of job opportunities for specialists across government.

The DDaT Fast Stream programme and our apprenticeship schemes give people the opportunity to join the Civil Service in specialist roles. Last year, the programmes received 3,000 applications.

And, of course, the GDS Academy continues to go from strength to strength. We’ve trained 10,000 students, which is a fantastic achievement. The GDS Academy  provides in-house training to any public servant who wants to update their digital skills. We run courses on agile methodology for practitioners and policy makers.

The GDS Academy’s recently launched Emerging Technology Development Programme offers in-depth training in subjects like artificial intelligence, virtual reality and biotechnology. We also launched GDS Academy masterclasses, which are a series of talks by world-leading academics and industry experts about the new technologies impacting public services.

To make sure these courses are available to anyone who needs them, we have created additional pop-up academies in Birmingham and Wales. We also helped Scotland set up its own digital academy.

We also work closely with colleagues in the Major Projects Leadership Academy to make digital a core part of their teaching as well.

Supporting people: next steps

The strategy sets the direction for how we will work to support our people.

The Data Science Partnership, lead by GDS and the Office for National Statistics (ONS) Data Science Campus is currently undertaking an audit to understand the current picture of data science capability across government. When the results of the audit are known, we will explore training opportunities for data specialists and those new to data.

We’ll also look to expand the courses available through the GDS Academy. We want to enable more secondments. We will develop a mechanism for seconding people from the tech sector into government and vice versa.

The strategy also outlines our continued commitment to working with academics through the Open Innovation Team (OIT).

We’ve identified that leaders need more support. We want leaders to fully understand what emerging technologies can do for their organisation and for citizens. We want them to feel empowered to take proportionate risk when it comes to experimenting with new technologies. We will focus our energies on understanding exactly how we can enable this.

The team at GDS (and those of you who attended the Sprint events we have held so far) know that my big ‘themes’ are: transformation, collaboration and innovation.

I’ve addressed transformation and innovation in this post. So in terms of collaboration: I hope that you’ll take the time to read the strategy, and to take a look at the AI guide published alongside it, which is designed to help public servants in government realise the potential of artificial intelligence. I hope (if you haven’t done already) that you’ll join one of the GDS Academy courses. And I hope that this strategy will help us all work together to build a government that is truly innovative.

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Original source – Government Digital Service

The FutureGov board: Peter Martin, Susan Murphy, Dominic Campbell & Matt Skinner

It seems like every new blog post begins with the phrase “a lot has happened since…”. And today is no different.

Last year we started our biggest work to date with Homes England, eight months ago we expanded the FutureGov family, seven months ago we moved to a bigger studio, six months ago we finished celebrating ten years, five months ago we began publicly sharing our impact, three months ago we began working with the NHS on our biggest health work to date, and today, we take another big step towards accelerated growth and delivering on our mission to design public services fit for the 21st Century with the highest quality, citizen-centred services that have a lasting impact for all.

Today, I’m proud to announce that FutureGov has joined The Panoply, a digitally native technology and design company. Growing into this new family of like-minded and purpose-driven organisations, who share our values, ways of working and mission, we will have the breadth of skills and scale to transform public services in the UK and abroad at speed. As a result, we will be the first scaled 21st Century organisation that can truly challenge the big four market.

https://medium.com/media/ce923da9dab87115213889a32e7ac8c1/href

Making an even bigger impact

You all know by now, I’m an ambitious person and we’re an ambitious change company. We’ve always been looking to grow for the sole purpose of having the scale and breadth of skills to support the total transformation of public services.

We’re proud of our track record of achievement and results, with over a decade of experience working in the public sector and health, which has led to the rapid growth of our team. With this growth came the ability for FutureGov to do more for our clients and our team. Not just bigger projects, but ones that were profoundly different in scope and scale to anything we’d done before.

We’re keen to keep this momentum going.

“The organizations that we build must be models of the world we want to create.” — Umair Haque

In The Panoply Group, we’ve found a conscious company with a deep-rooted purpose. With a deep respect for The Panoply’s ambition and a strong cultural fit, we believe that their leadership team is doing business in the same way that we do business – fast-moving, highly aligned companies with no overbearing top down command and control, addressing the challenges of today with integrity and focus on the long term.

We’re proud to be a trusted partner to the sector and want to keep it that way. Matched with The Panoply’s commercial strategy, capability and mission, together we will access new opportunities that would not otherwise be possible. Joining the likes of Manifesto, Notbinary​, GreenShootLabs, Questers​ and Bene Agere, we’ll help build the future, while retaining what makes us unique.

“FutureGov in every way reflects our own ethos, as a digitally native company built for the demands of the 21st century. It has built its reputation in the health and public sector thanks to countless projects with local authorities and other government bodies creating 21st-century citizen services in areas as diverse as housing, transport, children’s and adults social care and health. We’re excited by the opportunities that this opens up to all of our Group companies” — Neal Gandhi, Chief Executive Officer of The Panoply

What will change?

As with anything, some things will change, but we’re fortunate much will remain the same as we grow into our new family. We’ll continue working closely with our existing clients and nothing will change on a day-to-day delivery basis. We’ll continue to approach each new opportunity with the same militant optimism and commitment to working together, because we believe everyone has value to contribute.

I will continue my role as CEO of FutureGov and take on the additional role of Managing Director, Health and Public Services for The Panoply. I’m excited about my extended role in the Group, which will allow me to work closely with our partners to offer more and different skills, breadth and depth, particularly around tech.

FutureGov will remain largely autonomous within the Group, with Chairman Peter Martin, Managing Director Matt Skinner, Chief Operating Officer Susan Murphy and myself continuing the serve on the board, with the addition of Sarah Vickers, Chief of Staff from The Panoply, joining as a non-executive director.

As part of the move, as they move off our board we’re proud to have repaid the faith and investment that our key investors, Surrey County Council and Nesta, have shown in us over the past five years, delivering a significant return on their investment for further public service delivery and social impact.

And as many of you will know, I can’t thank Carrie enough for her support along the journey. While no longer on the FutureGov Board, I’m so pleased Carrie will be coming with us, now as a shareholder of The Panoply as a sign of her continued commitment to our mission.

What’s next?

How we do things is as important to us and our partners as what we do. Our aim continues to be making a real difference; designing public services for the 21st century and transforming organisations to make an even bigger impact. We’ll continue investing in becoming a model for what we believe 21st-century organisations should be by developing our FutureGov Experience offer.

We’ll continue to invest in our culture and our team, who will have new opportunities to collaborate with a wider group of organisations and disciplines. Broadening our scope will have a real benefit for our team who want to learn and do more, with long-term career development and succession opportunities.

An opportunity like this to accelerate our impact is very rare. Every day, I am astounded at how far this company has come, in the incredible people we have and the amazing work we’re doing. Accessing new skills, experience and knowledge from the wider group will immediately propel us into a stronger position. One where we can support our clients across health and government at a scale we’ve not yet been able to.

I’m excited to embark on this next chapter of FutureGov.


Expanding our offer (again) as FutureGov joins The Panoply was originally published in FutureGov on Medium, where people are continuing the conversation by highlighting and responding to this story.

Original source – FutureGov

imposter syndrome.jpg

When mental health and imposter syndrome collide it’s important to remind ourselves that we’re good at our jobs and are vital cogs in our organisations.

by Jill Spurr

I’ve really focussed on my mental health in the last couple of years, and in particular, I’ve been working on my response to situations.

My first epiphany was the realisation that in the work environment, when disaster hit, I slipped seamlessly into Crisis Response mode, ready to advise the most senior leaders. I have a formidable “kill or convert” record with negative media enquiries. Nothing fazes the professional me. But knock a cup over at home, and I could quite literally be crying over spilt milk. It’s like I am two people.

Was. Was two people. I’m steadily managing to align the two, and it’s reflected in my much improved resilience. Heck, I can almost throw that milk around with nary a care in the world now. Almost.

It’s happened through following some excellent mental health advice that you cannot control what happens in the world; you can’t control the wrongs people do to you, we can’t even control the political shenanigans that are defining this decade – but you can control how you react to them.

Finding my peace with the fact that people can be pretty darn horrible but that doesn’t have to disturb my equilibrium, has been transformational. You can debate those hotchpotch politics without coming to blows. You can ignore the passive aggressive Facebook posts from internet bullies that are designed to peck at your self-esteem. You can switch off breakfast TV when the ranting gets too much and enjoy American sitcoms instead. Most importantly, your body schools itself out of the physiological “fight or flight” response and your stress levels become increasingly manageable.

The only problem was, I hadn’t realised that I was still reacting to the meanest person: me.

Like many of my peers, I have chronic Imposter Syndrome. My negative voice is always the loudest, but you know what? She’s dishonest.

I’m pretty good at my job, as a Comms professional in social housing.

See, there she is. “Pretty good”. Mean girl.  

I’ve got 12 years experience in social housing, and many more in digital comms. I was working with digital when it was still New Media. I have experience and success to my name.

That’s more than “pretty good”. There, I’ve said it.

As much as we can evaluate a campaign by measuring our outputs, outcomes and outtakes against our aims, far too many talented Comms professionals feel like a fraud. Many don’t realise how talented, creative, inspiring, and uplifting they are. And as a result this can eat away at their own confidence by talking down their achievements. It doesn’t matter what the metrics say, that internal voice remains distinctly underwhelmed.

And the big problem about our internal voices is, they know our greatest weaknesses, so they can hit us the hardest. Honestly, would you talk to a colleague the way you talk to yourself?

For many, it’s a self defence mechanism. Get in yourself before someone else says something. This is a problem that will never go away, because there will always be someone who doesn’t understand Comms, and it’s likely that someone is pretty influential. But why do they need to understand? I don’t know a hill of beans about wiring and electricity, but I trust our operatives to do a good, safe job. If the senior management team doesn’t get Comms, so what? Tell them what success looks like and back it up with your evaluation. Their grasp of Comms is almost certainly similar to their grasp of the domestic electrical installations, but that doesn’t stop the operative doing the best job they can. So stop assuming your Comms house will burn down unless everyone gets what we do. There’s a reason why you spent years honing your craft: to be the expert you are.

But what really struck a chord with me recently, is that for every one of us trained, experienced Comms professionals doing an amazing job, there is someone else who will fake it till they make it. Especially when it comes to digital.

There are people who go on reality TV and cite their profession as “doing the Instagram”. There are people who haven’t been anywhere near a Comms qualification opening digital consultancies that offer social media campaigns at eye-watering rates but make schoolboy errors when it comes to effective content. There are people using social media as a selling or engagement tool, and blatantly getting it wrong.

In my other life, dog training, influencer marketing is booming. It makes perfect sense for a niche but competitive marketplace to utilise influence to create sales, but they are really, really bad at it. You can’t even see what their strategy might be, what their brand personality is, and influencers are not correctly briefed how to run advertising through their personal accounts. I’d honestly be surprised if their ROI was anything but in its boots.

When you look at it that way, even my negative voice says “Well at least you’re not that bad”. In fact, she gets slightly indignant and wonders why I’m pootling along in the not-for-profit sector.

Not everyone can do good Comms. That’s why we are here. The experts. The professionals.

But there’s a harsh truth, folks. Some people are so confident in their own ability; they are out there doing stuff you are better at, simply because they chose to. To be honest, if that doesn’t silence your negative voice, nothing will.

Jill Spurr is an external communications lead in the housing sector and you can say hello to her on Twitter at @DreamworkBC

Image via Florida Memory

Original source – comms2point0 free online resource for creative comms people – comms2point0