Public sector data offers great opportunities, but demands a fine balancing act

Tension arises between two imperatives: using data to innovate; and protecting citizens’ data against misuse, such as rights infringements and cyberattacks, as well as criminal and other unethical activities. We argue that governments can do both by innovating within boundaries that protect privacy and sovereignty. Using people’s personal data will always be a delicate balancing act that involves a complex set of regulatory, organizational, technical, and cultural best practices. So how can the public sector create innovative data strategies to enable a free, responsible, and secure flow of data to provide better services, and experiences, to citizens and businesses?

Turn data into action – and added value

In a data-driven world, the challenge for all sectors is to turn data into action, adding value along the way. Anticipate, model, prioritize, standardize. This is an essential mantra for data. Organizations need to embrace innovation and optimize new technologies like artificial intelligence, computer vision and natural language processing.

More than any other sector, the public sector must apply outcomes in an ethical manner, ensuring data trust issues aren’t breached. In short, they must perfect the balancing act of embracing innovation, while safeguarding citizens’ interests.

Respecting data privacy

The public sector harvests a huge wealth of data from diverse social, economic, and geographical groups. Its medical, financial, and personal content makes the data extremely valuable, but also highly sensitive. To help nurture public trust, governments have put defenses in place to guard against abuse. For example, the EU’s General Data Protection Regulation (GDPR) provides a strong framework to protect and safeguard the privacy of all citizens.

Despite the opportunities, and the safeguards, public sector organizations are often reluctant to use the data in their care. They’re not always aware of the flexibility and opportunities to use data that they already have. In fact, a prudent use of personal data can positively impact our lives, but public sector organizations need to earn our trust.

Building the trust of citizens requires transparency, which encourages citizens to share data, and contribute to producing and gathering data, if they see that open, accessible information works in their interests.

See our recent blog, “Digital trust is the heartbeat of public sector transformation” to read more about digital trust.

A vast data pool of opportunities

There are significant opportunities for the public sector to use data to model hypothetical, future scenarios. This creates a unique foundation that helps policymakers to make informed decisions, and to anticipate and create new public services. Data can also be used to identify risk, or to flag a case for analysis. For example, modelling based on data and predictive analytics can identify anomalies in tax or welfare claims that can signal misuse or fraud. Or make predictive interventions in healthcare.

To illustrate the opportunities, we’ve identified a diverse range of stories, all featured in our report TechnoVision 2021 Public Sector Edition.

Improving citizen services and interaction

New technologies add value to public sector services, enhancing citizens’ experiences and increasing participation rates by promoting inclusion. Chatbots make everyday tasks faster and more efficient. Text-to-speech helps when people are unable to use a keyboard, or who are visually impaired. And speech-to-text helps those with hearing challenges.

In France, the smart City of Dijon provides a mobile app allowing citizens to communicate easily with the municipal government. Data is used to simplify and improve the coordination of service needs, maintenance works, and emergency responses. This led to a 40% cost reduction for services, while around 630 calls are processed daily.

In Scotland, Chatbot “Ave” provides COVID-19 support to NHS 24, a free-to-call single non-emergency number medical helpline. It provides information and real-time advice, redirecting more complex questions to a human webchat. In its first 30 days, the chatbot answered over 40,000 queries, using clinically approved information.

Text analytics are used by applications that classify and categorize information to identify privacy related information, or if some documents should be archived. They enable access to 80% of the valuable information that is hidden in emails, archives, or personal directories.

Intelligent automation rationalizes and streamlines the execution of repetitive tasks and administration processes. For example, the Norwegian Directorate for Immigration (UDI) and Capgemini worked with Celonis process mining software to establish a data model based on digital traces from UDI’s asylum case management system. Process mining delivers substantial improvements to asylum application processes, with the top three use cases alone demonstrating potential annual business value for UDI of more than NOK20-million.

One Western European Security Authority needed to streamline and speed up its end-to-end ID inspection at borders. Automatic control using computer vision, deep learning, and OCR technology are now used to achieve a high level of validation security, cross-checking all known falsification of IDs recently used. Using ID proofing knowledge in AI, Capgemini’s template-based document verification validates documents 10 seconds faster than existing solutions.

Prediction and modelling

Data is also instrumental in prediction and modelling scenarios. For example, as another winter approaches, data will help health authorities with the prediction and modelling of Covid-19 infections and the possible development of new mutations of the virus. Data is used to model potential future scenarios, creating a foundation from which policymakers can anticipate outcomes, prepare public services, and make life saving decisions.

In education, student dropout rates have increased worldwide. A strategic ambition for Europe 2020 was to have put at least 40% of all 30 to 34-year-olds through higher education. The Dutch Alfa-College uses a predictive model to identify students who may drop out. The prediction accuracy was 91%, allowing for early intervention.

Enhanced decision making

Data also offers significant opportunities in developing risk-based decision-making models, for example, in the justice system. In France, data driven algorithms are used to support judges in determining levels of compensation between opposing parties. The algorithm shows them levels of compensation awarded in previous, similar cases, helping achieve a fair verdict.

Similarly, post-pandemic, algorithms are helping prosecutors to manage their workloads in the face of huge backlogs due to court closures during lockdown. These algorithms help prosecutors to make their own decisions on prioritizing cases.

Also in France, The Health Data Hub provides a secure platform with easy access to health data, which enables researchers to innovate, while complying with legal regulations and citizens’ rights. Ultimately, it improves patient diagnoses, enhancing the way patients are treated through personalized recommendations.

Acting on the data opportunity

By responsibly orchestrating the data at its disposal, while respecting the intimacy of its relationship with citizens, the public sector can make people’s lives better, delivering increasingly impressive customer experiences. In a turbulent world, data will empower the public sector to prepare, not only to react, but also to understand, anticipate, and model, share insights, and recommend action.

Click here to read TechnoVision 2021 Public Sector Edition, our annual guide to what’s new and what’s coming next in the world of technology, focused on the public sector.

 Authors

Martijn van de RidderPublic Sector Leader – Insights & Data

Marit HellandPublic sector Lead – Insight & Data Norway

Pierre-Adrien Hanania Global Offer Leader – AI in Public Sector