Good governance: how administrations can use data to enhance service experience, boost resiliency and improve public trust

By on 13/09/2023 | Updated on 13/09/2023
Image by Tara Winstead via Pexels

Now more than ever, governments need to be resilient in the face of uncertainty – whilst also working to win back public trust and satisfy demand for ever higher quality public services. As experts from AI and analytics partner SAS explain, the answers to these conundrums can be found in data

Governments around the world are facing great challenges. Post-COVID recovery, Russia’s invasion of Ukraine, uncertain inflation and the cost-of-living crisis, climate change, rising populism and more divided societies combined are putting administrations under strain to deliver effective policy and improved public services – and at a time when budgets are constrained.

Times are tough, but with it comes the opportunity to challenge the status quo, innovate and make changes that – if done well – could benefit individuals and governments themselves for decades to come.

To do this, governments will need to be resilient in the face of uncertainty and successive crises, to build public trust in them and other institutions, and engage with people and businesses and improve their experiences of interactions with the state. So, how can this be achieved?

Digital technology and effective use of data will play a large part. Here, we set out how governments can overcome some of the challenges they’re up against in 2023 and beyond, with comment from experts at AI and analytics partner, SAS.

Building trust in public institutions

Trust in public institutions has been waning for years, driven by governments’ demands of citizens during the COVID-19 crisis, frustration over stagnant economies, privacy concerns and other stressors. The response to the pandemic – however necessary – may have been part of the problem but it also demonstrated just how important it is that citizens believe their government works in their interest.

One of the ways that governments can start to win back people’s trust – in turn, enabling policy and services to be delivered more effectively – is to prove social value through the collection, analysis and reporting of data. But, crucially, this must be done securely, ethically and transparently – or trust could be damaged further still.

Vrushali Sawant, a data scientist in SAS’ data ethics practice and an expert on responsible innovation, gives the example of artificial intelligence. The emerging technology has already been adopted by many governments for certain tasks, freeing up civil and public servants to do more complex work that requires human thought, creativity and ingenuity. With great potential to streamline services, the use of AI will only increase as the technology matures. However, citizens are nervous about the risks and must be confident that it is being used for good.

According to Sawant, building trust requires a balance between AI ‘explainability’ and privacy and security. In order to gain trust, institutions need to be transparent. And being transparent when using an AI system, she explains, means requiring organisations to make clear to stakeholders – citizens, policymakers, budget holders and legislators – exactly how an AI system makes decisions and why a certain decision was made. 

However, privacy and security are equally as important as explainability if public trust is to be maintained or improved, and as Sawant explains: “When we make systems more explainable, there is a chance that you make it more vulnerable to attacks, or data is exposed and you hurt the privacy of the person whose data has been collected. So there needs to be balance.”

Authentication and authorisation mechanisms, which govern the level of access someone implementing or maintaining a system is given, is key to protecting privacy and security. Differential privacy – whereby trends and patterns drawn from a dataset are shared publicly whilst ensuring that nothing can be inferred about any single individual – is another technique. As is data suppression.

Training is important too, so that officials who work with data understand how to ensure that models are transparent and explainable and, at the same time, not susceptible to adversarial attacks. “That’s how trust will be built,” Sawant says. “As a citizen, I need to know how decisions were made, and that my data is secure.”

Stamping out bias is also critical. AI is trained on data and, if that data has been collected in a way that accentuates bias, then the decisions made by that AI system will too. “Appropriate checks should be in place so that any bias does not perpetuate along the data chain of custody. We have to make sure that we are making decisions that are not only accurate but are underpinned by the principles of equity and fairness,” Sawant says. “Because if I see a person who looks different to me, but they have the same characteristics and yet that person is being treated differently, then I lose trust in the institution.” In addition to helping to engender trust, promoting fairness and reducing disparities in service delivery will improve outcomes for users, as this SAS whitepaper on health equity demonstrates.

As more and more government systems become AI-driven and more and more decisions are made by algorithms, the importance of in-house data teams’ adherence to ‘human centricity by design’ principles grows, Sawant highlights.

And there’s another consideration too – being selective about the collection and analysis of data. “You might have all this data, petabytes of it, and the temptation is to think ‘let’s use this to create a system and we can increase the efficiency of all these things’. But at the back of the mind, we should be asking the question: it’s not about can we do it, it’s about should we do it?

“You might have the technical progress, the algorithms, the cloud storage ability – these are at your disposal. You can do it. But should you?”

“Ultimately, anything you do should be a win-win for both the government and citizens.”

Boosting experience and engagement

Expectations of interactions with government are higher than ever before. People are accustomed to the ease and convenience of digital services offered by businesses such as banks and expect a high level of customer experience and engagement from the public sector too – but governments are behind the private sector when it comes to digital transformation.

Harnessing digital technology will enable governments to better understand the users of their services – whether individuals or businesses – anticipate their needs and act accordingly. More specifically, integrating data, automating and integrating processes, and enabling people to securely access digital services, allows governments to build a 360-degree view of citizens and stakeholders, delivering more intuitive and personalised online services that reduce the friction that can leave them frustrated.

Governments that deliver successful customer experiences tend to organise themselves around customer-oriented outcomes, power their decisions and actions with data, and establish systems that allow them to monitor experience, identify weak spots and make improvements. 

And there’s a link with trust too. Research by global management consulting firm McKinsey has found that when a customer’s experience of using state services meets or exceeds expectations, it can boost trust in government and diminish negative media coverage, as well as improve morale among civil servants, and lower costs for government agencies.  

Caroline Payne, head of customer advisory – public sector, at SAS UKI explains how to boost citizen experience and engagement through orchestrating more personalised services.

“In order to communicate and engage with the citizen in the appropriate way, to contact them at the right time with the right message, you have to understand their wishes and their behaviours. The only way you can do that – aside from conducting surveys – is to capture data about how they’re interacting with your services and then use analytics to predict their behaviour.”

She gives an example: “If I’m completing my tax return online and I’m spending more time than the average person on a particular field, the likelihood is that I’m struggling with it. If you recognise that, you can provide a prompt or whatever it may be to help guide me through the process. It’s about being able to respond to the citizen’s needs at the time of interaction.”

What that requires is a system that recognises where a person is in a process and what they’ve done historically when interacting with similar services, runs analysis, and then makes a decision based on that analysis in real time. The resulting prompt or support needs to be integrated into the platform or interface that person is using, whether it be in-person at a government office or filling out a benefits form online.

“The essence is treating citizens like they’re individuals, humans, like the organisation understands something about them as a person and therefore the situation that they might be in. Organisations who get customer experience right are absolutely more successful than those that don’t,” Payne says. 

She also emphasises how important it is to enable the citizen to opt out. They may not want you to gather information about the way they’re using services or to receive any communication unless they’ve instigated it so an opt out option is “absolutely critical”.  

However, it’s also important to communicate effectively to citizens the benefits of government engaging with them in a personalised manner and how their privacy is protected, so they can make an informed decision about whether or not they want in. 

“If they know it’s being done for a purpose and how it’s going to benefit them, they may well not be resistant to it. Essentially, you have to listen to your citizen or your customer and treat them in the way that they want to be treated.”

When citizen engagement is underpinned by good data, interactions with the state can be quick and seamless, and there are additional benefits for governments too – not least saving money, improving compliance and reducing error. 

Resiliency in the face of uncertainty

The pandemic, inflation, political risk, and climate related disasters have made it difficult for governments to ensure safety, stability and continued services, but in the age of ‘permacrisis’, governments are going to need to be resilient and well prepared for shocks big and small.

As shown in the pandemic, integrated data enables governments to flex and respond quickly as circumstances change. Yet the sharing of data between government departments, national and local government, and between the public and private sector remains difficult.

A significant amount of government data is fragmented, siloed and unsuitable for analysis, but this will need to change if governments are to harness its insights for improved decision-making – especially when decisions need to be made at speed.

Meg Schaeffer, a national public health advisor, epidemiologist, and senior manager at SAS, shares her thoughts on resilience from a public health perspective. 

She describes the crises the world has faced in recent years as a “mixed blessing”, giving COVID as an example.

On the negative side, the authority and expertise government had in healthcare prior to the pandemic has been challenged, she says. She has worked as an epidemiologist in the US for over 20 years, at various levels of government, and she and her colleagues had often deferred to the Centers for Disease Control and Prevention (CDC) – the country’s national public health agency – for guidance during outbreaks of mumps, swine flu, SARS and other health emergencies. But when it came to COVID, the political landscape in the US meant the science wasn’t always taken seriously. “It’s very difficult to have the knowledge that you’ve worked so hard to earn questioned. It burns people out. And people have left government in droves,” she says. “I work with states every day and they say they cannot retain or recruit epidemiologists – they don’t feel they can do the work they need to do to truly protect the health of their communities.”

However, “there’s a remarkable opportunity for public health”, post-pandemic, she says, as governments increase the focus and funding going into predicting the next crisis. As a result, public health “finally has the space to work” and is going through a “dramatic transformation”.

In the US context, Schaeffer believes the government is working towards better alignment, improved social programmes, public health expansion, and in the direction of preparedness for future shocks. This will, she believes, “get us to the point of having the tools and resources we need to be able to respond”, and not just in public health but across government. “I definitely see that in my engagements with all different kinds of agencies every day,” she says.

Of course, preparedness and resilience are closely intertwined. And in order to be able to predict and prepare for what’s coming down the line, the ability to share data is key.

“We need to take the knowledge that advanced so far during COVID and continue to apply and expand it. And we need to intersect as many different data sources as possible.”

She gives the example of avian flu. The outbreak was first detected in Europe in 2020, it spread to North America and so far 60 million birds in the US alone have either died of the virus or been culled. “The virus can jump from commercial poultry and wild birds to mammals and if it infects pigs, it can jump to people. If that happens, we could have a pandemic much more severe than COVID, despite the fact that we now have the capability to rapidly ramp up a vaccine. So, we have to get countries to share data with each other.”  

Gathering the data needed to be resilient in the face of a possible pandemic, identifying the risks early and working to head them off would require surveying migrating animals’ – and humans’ – movements across borders, monitoring symptoms of illness to identify new diseases, and keeping tabs on weather and temperature change – humidity is a big contributor to the spread of certain infections.

“We can do it because agencies around the world already have the information but it’s complex because it’s all held in siloes,” Schaeffer says. “Grassroots advocacy is already happening. What’s needed now is for the leaders of major countries to be speaking about working together, sharing information and making progress.”

‘Enterprise analytics’ – the act of performing analytical processes on data stored across an organisation, rather than on smaller segments of it – will also play an important role, enabling senior officials to understand the needs of an administration or department as a whole, identify the appropriate strategic direction, make sound operational decisions and drive more effective policy. This approach allows governments to respond quickly to changeable situations and to measure outcomes, whether in the midst of a pandemic or emergency or during times of ‘business as usual’.

As a recent whitepaper by SAS explains: “An enterprise analytics programme creates a dynamic, evolving capability where questions are asked, data is analysed, decisions are made – and the impact and outcomes of those decisions become new data to feed back into analytic models.

“As circumstances change due to policy decisions, economic cycles, health pandemics, natural disasters and more, your models learn and adapt to the changing world and the data it provides. This ever-changing, always-learning approach will keep you prepared to serve and protect your citizens.”

Protecting citizens from another pandemic is front of Schaeffer’s mind. “When we have the next pandemic – which will happen and will happen probably much sooner than people think – we will have to deploy the same mechanisms that worked during COVID. And maybe after several learned experiences, we will start to recognise the actions we have to take to save lives,” she says.  

Governments are dealing with multiple crises, but it isn’t all doom and gloom. As Sawant, Payne and Schaeffer demonstrate, with challenge comes opportunity. Effective data collection, analysis and sharing can improve government service culture, agility and resilience, help to build trust – and answer some of the world’s big problems.

You can read blogs and articles written by the SAS experts quoted in this article here:

Vrushali Sawant on embedding responsible innovation and the ethics of responsible innovation.

Caroline Payne on accelerating digital transformation in the UK government, data and insights accessibility, AI and ethics, and more.  

Meg Schaeffer on preparing for the next pandemic. You can also view an interactive demo on emerging disease surveillance and forecasting.

This is a piece of partner content, produced by Global Government Forum on behalf of SAS.

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