Shifting from analogue to digital public services – citizens want joined up public services

I highlighted the positive view citizens have about digital public services in my last blog. And their appetite for more. I now want to address some of their concerns and why doubt the ability of government to continue to deliver.

The digital disruption brought about by new technologies is transforming the interaction between citizens, business and the public sector.

Citizens compare public services with innovative platform business models provided by digital trendsetters like Apple, Google and Amazon. I expect simplicity and even friendliness when I talk to Alexa or Siri.

What did we find? Government needs to join the dots

This year’s research shows that digital public services fall short of the best commercial services. While 64% of UK citizens said digital public services were advanced this falls to just 30% when they are asked to compare them to commercial services.

The UK Government can take some comfort from the comparison with France (18%), Norway (19%) and Germany (20%). And of course, we understand that governments face unique challenges, as ‘customers’ often have no choice when using public services that can be a last resort.  Governments need to address complex and long term needs like the reduction of re-offending or the treatment of chronic health conditions.

But citizens told us of their frustrations about the need to input information many times, including various passwords, the multiple steps needed to access services and an inability track progress. Some of these issues are being addressed by the UK Government, including through new platforms such as Verify and Notify. And they have flagged an intention to ‘improve citizen service across channels’ through a new Transformation (not digital) Strategy.

However, too often governments fail to meet citizen’s expectations when it reproduces its analogue bureaucratic procedures in a digitised way. Siloed service delivery approaches, with multiple websites and fragmented service delivery, organised around internal institutional structures are no longer acceptable. Which is why the number one priority for 44% of the UK citizens surveyed was the creation of a one-stop digital portal for undertaking interactions which need to be performed with multiple agencies (and this was a common priority across France, Norway and Germany).

Improving the experience of citizens in a revolutionary way

Citizens expect their public services to be designed with a user-driven perspective. And to adapt to different user profiles and needs. Through intelligent re-use of data and information previously generated or provided by citizens, governments can shift from reactive to proactive service delivery practices.

In a reactive service, the citizen is always responsible for starting the service demand, properly identifying herself and providing the required information. In a proactive service, the public sector knows its citizens, knows their life circumstances and current needs, and provides them the space to voice and signal their requests and preferences.

This enables the public sector to serve citizens in a personalised fashion about their rights, their duties and the services available. And to reach out to them to receive the authorisation to complete the service on their behalf.

This capacity to collect, combine and process data in a coherent way to better serve citizens must be a key feature of digital public services. And this needs a whole-of-government effort to exchange information across the public sector. With the key building blocks – common architecture, interoperability framework, digital identity system – in place to enable integrated service delivery.

Developing a user-driven approach also implies that the public sector’s capacities, workflows, business processes, operations need to be adapted to the rapidly evolving digital age. The challenge is not to introduce digital technologies but to integrate and embed them right from the start into efforts to modernise services.

I’d like to hear your views on how policies can be made digital by design, mobilising new technologies to rethink and re-engineer processes or open new channels of communication and engagement with citizens. And feel free to get in touch if you’d like more information on our research with Ipsos.

The Apple of my AI – GDPR for Good

Artwork by @aga_banach

Our common perception of machine learning and AI is that it needs an immense amount of data to work. That data is collected and annotated by humans or IoT type sensors to ensure the AI has access to all the vast information it needs to make the correct decisions. With new regulations to protect stored personal data like GDPR, does this mean AI will be at a disadvantage from the headache on restrictions for IoT and data collection? Maybe not!

What is GDPR and why does it matter?

For those who are outside of the European Union, GDPR (General Data Protection Regulation) is designed to “protect and empower all EU citizens data privacy”. Intending to return the control of personal data to individual citizens, it grants powers like requests for all data a business holds on them, a right to explanation for decisions made and even a right to be forgotten. Great for starting a new life in Mexico but will this impact on how much an AI can learn due to the limiting of information?

What’s the solution?

A new type of black box learning means we may not need human data at all. Falling into the category of ‘deep reinforcement learning’, we are now able to create systems which achieve super human performance in a fairly broad spread of domains. AIs are able to generate all training data themselves from simulated worlds. The poster-boy of this type of machine learning is AlphaZero and its derivatives from Google’s Deep Mind. In 2015 we saw the release AlphaGo which demonstrated the ability for a machine to become better than a human in a 5–0 victory against Go (former) champion Mr Fan Hui. AlphaGo reached this level by using human generated data of recorded professional and amateur games of Go. The evolution of this however was to remove the human data with AlphaGo Zero, beating its predecessor AlphaGo Lee 100:0 using 1/12th the processing power over a fraction of the time, and without any human training data. Instead AlphaGo Zero generated its own data by playing games against itself. While GDPR could force a drought of machine learning data in the EU, simulated data from this kind of deep reinforcement learning could re-open the flood gates.

Playing Go is a pretty limited area (though AlphaZero can play other board games!) and is defined by very clear rules. We want machine learning which can cover a broad spread of tasks, often in far more dynamic environments. Enter Google… again… Or rather Alphabet, the parent company of Google and their self-driving car spinoff Waymo. Level 4 and 5 autonomous driving presents a much more challenging goal for AI. In real time the AI needs to categorise huge numbers of objects, predict their paths in the future and translate that into the right control inputs. All to get the car and it’s passengers where they need to be on time and in one piece. This level of autonomy is being pursued by both Waymo and Tesla, but seemingly Tesla gets the majority of the press. This has a lot to do with Tesla’s physical presence.

Tesla has around 150,000 cars on the road equipped and boasted over 100 million miles driven by AutoPilot by 2016. This doesn’t even include data gathered while the feature is not active or more recent data (which I am struggling to find — if you know please comment below!). Meanwhile Waymo has covered a comparatively tiny 3.5 million real world miles, perhaps explaining the smaller public exposure. Google thinks it has the answer to this, again using deep reinforcement learning, meaning that their vehicles have driven billions of miles in their own simulated worlds, not using any human generated data. Only time will tell whether we can build a self-driving car, which is safe and confident on our roads alongside human drivers without human data and guidance in the training process. The early signs for deep reinforcement learning look promising. If we can do this for driving, what’s to say it can’t work in many other areas?

Beyond being a tick in the GDPR box there are other benefits to this type of learning. DeepMind describes human data as being ‘too expensive, unreliable or simply unavailable’, the second of these points (with a little artistic license) is critical. Human data will always have some level of bias, making it unreliable. On a very obvious level, Oakland Police Department’s ‘PredPol’, a system designed to predict areas of crime to dispatch police, trained on historical and biased crime data. It resulted in a system which dispatched police to those same historical hotspots. It’s entirely possible that just as much crime was going on in other areas, but by focusing its attention on the same old area and turning a blind eye to others the machine struggled to break human bias. Even when we think we’re not working on an unhealthy bias our lives are surrounded by unconscious bias and assumptions. I make an assumption each time I sit down on this chair that it will support my weight. I no doubt have a bias towards people similar to me, believing that we could work towards a common goal. Think you hold no bias? Try this implicit association test from Harvard. AlphaGo learned according to this bias, whereas AlphaGo Zero had no bias and performed better. Looking at the moves the machine made we tend to see creativity, a seemingly human attribute in its actions, when in reality their thought processes may have been entirely unlike human experience. By removing human data and therefore our bias machine learning could find solutions in possibly any domain which we might never have thought of, but in hindsight appear a stroke of creative brilliance.

Personally I still don’t think this type of deep reinforcement learning is perfect, or at least the environment it is implemented in. Though the learning itself may be free from bias, the rules and play board, be that a physical game board or rather road layout, factory, energy grid or anything else we are asking the AI to work on, is still designed by a human meaning it will include some human bias. With Waymo, the highway code and road layouts are still built by humans. We could possibly add another layer of abstraction, allowing the AI to develop new road rules or games for us, but then perhaps they will lose their relevance to us lowly humans who intend to make some use from the AI.

For AI, perhaps we’re beginning to see GDPR as an Apple in the market, throwing out the old CD drive, USB-A ports or even (and it still stings a little) headphone jacks, initially with consumer uproar. GDPR pushing us towards black box learning might feel like we’re losing the headphone jack a few generations before the market is ready, but perhaps it’s just this kind of thing that creates a market leader.

Citizens can feel the benefits of digital public services but are concerned about the ability of government to keep pace with their needs

As companies have transformed themselves with digital technologies, citizens are calling on governments to follow suit.

By digitising, the public sector can provide services that meet the evolving needs of citizens, even in a period of tight budgets and complex challenges.

This is the second year that Sopra Steria has asked the researchers at Ipsos to conduct a survey of 1000 citizens, from a broad range of social groups and across the United Kingdom, to understand their experience of and expectations for digital government. The same survey took place in France, Germany and Norway. So we have an opportunity to compare how citizens in the UK experience digital with others across Europe.

What did we find?

Citizens expect public services to be designed and delivered in a simple and intuitive way.

This year’s research shows that citizens recognise the efforts made by governments to use digital channels to streamline their interactions. 64% of the UK citizens surveyed described digital public services as advanced, compared to just 42% in Germany, 66% in France and 75% in Norway. The UK Government should seek to learn from experience of Norway, which has long used technology to streamline processes.

We asked citizens to describe the current degree of digital service development across Government

Citizens continue to support investment in digital public services. 75% of citizens surveyed in the UK said government should press ahead with plans to digitise public services. 25% described this as ‘an absolute priority’. Health is judged the most important public service to digitise in the future. 54% of citizens in the UK said health was the priority for investment, an increase of 5% in the 12 months since the last survey.

The research found that citizens also recognise the positive impact digital is having on the quality of public services. 58% of the UK citizens surveyed said that the introduction of online channels and services had improved the quality of public services, compared to 53% in France, 65% in Norway and 57% in Germany.

So far, so good – but what about the future of digital public service delivery?

Governments are working on simplifying access through the development of simple organisational hubs for digital government services. Fully developing this approach requires governments to achieve significant levels of interoperability of public sector information systems and, at times, cross-organisational service solutions.

Citizens are cautious when asked about the prospects of making further progress. 47% of the citizens surveyed said they did not believe the public sector had the necessary skills to make progress (which is similar to our own survey of civil servants last year). And France is the only country surveyed where citizens expressed confidence in their government’s will AND ability to continue to make progress.

We asked citizens for their views on the will and ability of governments to make progress with digital public services

The UK might learn from France and other countries that are seeking to introduce incentives across the public sector to help bring down cultural barriers in hierarchical and centralised administrative cultures. And develop a human resources strategy that helps develop, attract and retain vital data skills that facilitate collaboration.

In my next blog I will be looking in more detail at why citizens are so cautious about future prospects for digital public services. And how governments can address their concerns and shift away from the ‘vending machine’ model of service delivery.

In the meantime I’d like to hear your thoughts on the survey, including great examples of digital public services and how obstacles were overcome. And get in touch if you would like further details of the survey.

Make way for accessibility

I recently came across this fascinating report on the help extended by a computer scientist for a little girl with severe memory loss. It is an extraordinary example of the efforts of an individual in addressing an accessibility problem very effectively. Close on the heels of this story, there was the big announcement of a new Microsoft app being released for public use called “Seeing AI”. This app is perhaps one of the most intuitive tools out there for people with visual impairment and has been built with a lot of thought. I remember following this project a couple of years ago and wondering if only such large scale developments can bring about a change, or is it a good idea to keep working  on humble ideas, while not holding our breath for one big change to improve our lives. In reality, we need both just now – big technical corporations investing heavily in researching on ground breaking solutions, as well as small measures from individuals giving their best shot in ensuring someone feels comfortable in their everyday life.

Earlier this month, the United Nations Association-UK published a factsheet to mark the International Day for Persons with Disabilities, which indicates a grim situation for people with disabilities. Disabled people are four times more likely to be out of work than non-disabled people and the poverty rate is twice as high in comparison too. According to another factsheet published by the Papworth trust, disabled people experience much lower economic living standards than their peers, which is again attributed to increasing rate of unemployment. This deeply concerning trend needs to be immediately addressed on many levels. One of them is to improve the confidence of people with disability in approaching employment opportunities and to provide them with an environment in which they can operate comfortably. Here in Sopra Steria, our Company CEO Vincent Paris has reflected similar thoughts about being an employer with empathy. We have to think of being more proactive in engaging people with disabilities in our work places and also to engage better with those amongst us with disabilities, so they have the motivation to continue in employment. In the context of service industry that we are a part of, we often think about disabled people mainly as our customers/end-users but we have to think of colleagues with such conditions too, facing barriers constantly.

The topic of accessibility is a complex one which is dependent on perceptions of individuals as well as the bigger society, about the idea of disability. It will take a lot of determination to support this topic and we have a long way to go. But this journey can be easier if each one of us stand firmly to make sure accessibility is given its due consideration. Let us make way for accessibility in our lives, as individuals and as professionals, in the world around us.

What are your thoughts? Leave a reply below or contact me by email.

Data, consumers and trust: the quiet crisis

Building trust-based relationships with clients has always been important for successful business practice.  As the global data pool grows and consumer fears over personal privacy increase, it may become make-or-break.  Digilab’s Olivia Green investigates.

In the last two years, we have created 90% of the total data in the world today. In a day, we spit out an average of 2.5 quintillion bytes – and counting. From smart watches that monitor our heartrates to chat-bot therapists who manage our anxiety, nearly every aspect of our lives can be digitized. This undoubtedly provides us with immense benefits – increased speed, convenience and personalisation to name a few. Yet it also gives rise to a challenge: how do we protect our right to privacy?

Anxieties over internet privacy are nothing new. As the data pool continues to expand however, they have been picking up steam. Hacks and other tech-related scare stories are now a daily occurrence on our newsfeeds – and they are increasingly hitting closer to home. Back in May, the credit card details and passwords of nearly 700,000 UK citizens were compromised when Equifax fell victim to a hack. Even our private conversations don’t feel safe, as it emerged last month that Google’s new Home Mini had been accidentally recording its users without their knowledge.

Corporations themselves are also a target of consumer fear, and they are beginning to pay the price. According to recent research, US organisations alone lost $756 billion last year to lack of trust and poor personalisation, as consumers sought out alternatives. UK consumers share similar anxieties; nearly 80% of cite lack of confidence in the way that companies to handle their information as an extreme source of concern, while just under half now view data sharing as a “necessary evil”- something they will do reluctantly if they deem the reward high enough.

These findings aren’t an anomaly. Statistics gathered last year by the ICO show that only 22% of UK consumers trust internet brands with their personal data; more shockingly, they highlight that while over 50% of consumers trust High Street banks, only 36% have confidence in Governmental bodies to manage their data properly.

The price of complacency

So far, companies have largely managed to side-step the more serious consequences for consumer mistrust and data mismanagement. Not all have been lucky though. The notorious Ashley Madison hack in 2015 is a prime example of just how damaging loss of trust can be. The website, which provided an online platform enabling married people to conduct affairs, fell victim to hackers who published a digital “name and shame” list of its clients. For a business whose model was so dependent on trust and confidentiality, this proved disastrous. Despite the organisation’s insistent claims otherwise, analysis by SimilarWeb revealed that monthly site traffic had plunged since the attack, dropping by nearly 140 million a mere four months after the attack.

For some, the fallout is less dramatic – but still worrying. Take Uber’s recent breach for example, which dragged its already battered corporate reputation through the mud once again after it was revealed that the ride-sharing company had tried to cover up a 2016 data hack affecting 57 million customers. The immediate furore that followed this has raised some immediate problems for the firm, including the threat of prosecution and impending investigations by multiple countries worldwide. Even more problematic for Uber are the wider-ranging consequences of this cover up. In combination with their potential loss of the London market and recent workplace scandals, this disastrous year has materialised into real financial impact; at the close of this quarter, Uber logged record losses of $1.5 billion, a $400 million increase on previous quarter and a far cry from their triumphant predictions of growth at the beginning of 2017. In a particularly telling sign, Uber’s investors also appear to be hedging their bets. Fidelity, who already have a significant stake in Uber, announced last week that they had participated in a funding round for Uber’s closest competitor, Lyft, pushing the latter’s valuation up to $11.5 billion.

Unlike Ashley Madison, Uber’s problems arose not so much from the hack itself, but from their attempt to cover it up. But despite the evident lesson here, this is a scenario we could see again. Over 2/3 of UK boards currently have no training to deal with a cyber-incident and estimates suggest that only 20% of companies have appropriate response plans in place. For Uber, the ultimate consequences of its misconduct remain to be seen; for the moment, they are protected by their largely unique offering, which gives consumers limited alternatives. Should it happen to a business without Uber’s dominance, it could prove fatal.

Monetising trust

How can organisations move forward from here? In the current climate, it is unlikely that consumers will ever wholly withhold their data, as they place value on the services that giving away that data provide- as much has been shown by the fact that risky “data trade-offs” like Uber manage to survive.  However, as awareness of the risks and the stakes of losing data to a hacker increase, they are looking increasingly selective about who they choose to share their information with. As more and more information shifts from physical to digital, businesses must be prepared for change. We may be heading towards a future where access to data is no longer a handout but a privilege, hard won by effective risk management and transparent, secure systems that hand back sovereignty to the customer.

Yet it is this data that may ultimately decide who wins and who loses in our future digital economy. Consumer data is the life blood of capabilities like AI and predictive analytics, and is essential for providing the personalised services such as smart home devices that are becoming increasingly popular. Businesses that are cut off from this valuable information source will inevitably find themselves undercut by better-placed competitors.

To protect themselves against this eventuality, businesses in crowded markets should make effective data strategies an utmost priority. Companies like Uber may be shielded for the time being; nevertheless, even they can’t afford to breathe easy. As the surging interest in Lyft is demonstrating, rivals are never far behind.

Look out for my next blog about how GDPR can help your business build a future-proof data strategy.

What do you think? Leave a response below or contact me by email.

In pursuit of frictionless digital engagement with HR

by Claudia Quinton, Head of Workplace Transformation

What do I mean by frictionless engagement? And why is it relevant to today’s HR function? People like to book their holidays, make doctors’ appointments, shop and bank online. There’s no real need to talk with a travel agent, a GP’s receptionist, a shop assistant or a busy bank cashier – unless you want to, that is. This is the sort of ‘frictionless’ world that a large proportion of the modern workforce is used to – where everything is automated, clever and personalised.

And they expect a similar frictionless experience in the workplace. Only it seems they’re not getting it. A new survey report from Sopra Steria in partnership with Management Today reveals that employers have been slow to understand and implement the automation, analytics and other technologies that can facilitate a better workplace experience. And less than half (45%) of chief executives and directors were prepared to say their organisations had a clear, specific strategy for improving the employee experience.

Investing in robotics and artificial intelligence

I believe they’re missing out on a huge opportunity to transform the way in which employees engage with the business, especially with the HR services that help to define a good employee experience. In a new paper[1] discussing the survey findings, I take a look at how some companies are achieving frictionless engagement. Sopra Steria, for example, has developed a clever chatbot – we’ve named it Sam – that uses robotic process automation (RPA) and artificial intelligence to facilitate a range of HR services, such as booking holidays – all with no human intervention.

I question why more companies aren’t investing in greater automation and why the HR analytics that would drive a more personalised employee experience continues to be lacking in so many organisations. Failing to adopt the type of digital enablers employees are familiar with outside work is giving the wrong impression. It suggests a business unable or unwilling to invest in its people and to give them the tools and processes that will enhance their experience at work. That’s a dangerous impression to create, especially in today’s business climate where it can be difficult to attract talented people, and even harder to retain them.

Adding value at board level

I understand that changing entrenched processes and moving to new technology platforms, such as a cloud HR solution, can be met with resistance. Will automated process take away my job? I’ve done it this way for years, why should I change? How will I be able to monitor progress and quality when there’s no human intervention for key HR processes? There will always be fears and uncertainties like these. But what I am certain of is that only with investment in automation, analytics and AI, along with changes to IT infrastructure that equip employees to self-serve from anywhere, at any time, can today’s HR leaders remain a trusted and valued presence on the company board.

[1] For more on this, read my opinion paper ‘How can HR stay relevant in the 21st century?’

Ready Steady Cook

by Software Engineer Graduates, Alistair Steele and Gregg Wighton

Two from our February 2017 Graduates cohort discuss their recent Graduate Project using Chef Technology to solve the problem of setting up a machine (laptop) adhering to company standards. Their aim was to introduce a working example of DevOps and learn more about that sphere. This post talks about the problem they sought to address using Chef, what DevOps is and the experience they have gained from their Graduate Project.

The Problem

During a new starter’s induction day, a considerable amount of time and effort is spent on setting up a Development machine (laptop). Tasks involve downloading software and creating a folder structure which adheres to the guidelines set out by the company. This manual process is time consuming and tedious, plus it allows room for human error. The same issue occurs for a current employee who has to rebuild their machine. A third issue can be seen with employees who have forgotten the company guidelines.

Company time, in particular for new inductions, would be better spent in various other ways. Allowing the new employees to read company policy or familiarise themselves with the office building and appropriate contacts.

A key aspect of this project was to eliminate user interaction and cut down on the potential human error. To achieve this, three technologies were considered, Ansible, Puppet and Chef. We chose Chef as it is serverless, scalable and Windows compatible.

With the technology selected we looked at how best to use Chef and what it’s capabilities were. This required a lot of research – and trial and error. Understanding the problem enabled us to create three main goals: Silent Installs of required software, Folder Structure and Environment Variables, all of which were to be automated.

Our objective was for the user to simply download Chef Client, connect to the repository on InnerSource and then run a single command on the command line. The Automated process will then kick off and deliver the finished product. So what will it achieve?

  • Ensures standardisation throughout the company
  • Saves the company valuable time
  • Speeds up Induction process
  • Silent installs of software, folder structures and environment variables

Using DevOps to tackle the ‘Wall of Confusion’

In the traditional flow of software delivery, the interaction between development and support is often one of friction. Development teams are wired towards implementing change and the latest features. Support teams focus on stability of production environments through carefully constructed control measures. This divide in culture is now commonly referred to as the “wall of confusion”.

DevOps looks to break down this culture by improving the performance of the overall system, so that supporting the application is considered when it is designed. One method of doing this is to start treating your infrastructure as code so that it can be rebuilt and validated just like application code.

One area that would benefit from provisioning infrastructure would be the configuration of development environments. Setting these up can often be tedious as they rely on specific versions of software, installed in an exact order with particular environment variables and other project specific configurations – all of which can cause delays to working on a project and are prone to human error.

Automation, Automation, Automation

Chef is a powerful automation platform that uses custom Ruby DSL to provision infrastructure. A key feature of Chef is that it ensures Idempotency – only the changes that need to be applied are carried out, irrespective of the number of times it is ran. While it is intended to configure servers, the flexibility of the platform means that it can be used to set up local development environments.

Diagram described in the text belowOur diagram shows the architecture and workflow for the project. A developer writes Chef code on their workstation, then uploads their code to a Chef repository hosted on GitLab, and installers kept in an S3 bucket on AWS. This code can be pulled down to a developer’s machine to be configured and run in Chef Zero. This is a feature (usually used in testing code) where both a Chef Server and Chef Client are run at the same time. This approach ensures that development machines can be quickly and reliably configured for a project. This also introduces portability into development environments so that testing and support teams can recreate these environments should they need to.

Ready for the Cloud

Chef is tightly integrated with Amazon Web Services through AWS OpsWorks. This means that the Chef code used to automate physical servers or workstations can be used to configure AWS resources. This ability to standardize both physical and cloud environments means that it is possible to create a smooth workflow for both Development and Support teams.

Our Grad Project take-aways?

From experiencing work in a support team, we can see the benefits of embracing a DevOps culture and workflow. The ability to standardize environments means that Development teams are free to implement new technologies that can then be easily transferred and controlled by support teams. Having completed Phase I of ‘Ready Steady Cook’, we aim to embark on Phase II- developing an automated setup for a specific aspect in the support team.

We have both gained valuable experience in working through a project’s complete lifecycle, from inception to development to testing and production. Throughout the project we utilised Agile methodologies such as working towards fortnightly sprints and daily stand-up meetings. This project has also widened the scope of our graduate training in that we have gained certifications in Chef and are working towards certifications in other DevOps technologies.

Sopra Steria is currently recruiting for the Spring 2018 Consulting and Management Graduate Programme. If you, or someone you know, is interested in a career with us, take a look here.