Published by: Alexander Viter
Published Date: July 15, 2022

The best use cases of predictive technologies in government services

«You can predict the future with the same success as seeing a man in a fireman’s uniform and predicting that he will put out a fire»
Honore de Balzac

Indeed, based on the information or data we receive, we can draw conclusions and even predict what might happen. But today there are technologies that can predict on a larger scale. In this article, we would like to discuss Predictivetechnologies. What it is? How do they work? And give living examples of their application in the government.

What is predictive technology?

Predictive technologies are a set of tools that are able to predict patterns in data and to model future behavior and preferences among consumers. Predictive technologies include big data and machine learning to identify patterns that can be used to predict outcomes in various aspects of daily life. The tools used are data mining, neural networks and system modeling and simulation.

Initially, these tools were used to study the weather, the stock market, human behavior, and socio-economic activity. Of particular interest in the application of forecasting technologies was shown in the field of marketing and business to predict supply and demand patterns.

Today, almost all areas of activity are interested in these technologies. Some of our friends and partners share their examples of predictive technology applications and their effects in such areas as energy, retail, financial sector, mining and oil and gas sectors. Experts will talk about these cases in special training programs, which you can learn about on our website. And today we will tell you how forecasting technologies are used in public administration. Predictive technologies, in which organizations use data to identify trends and make judgements about the future, are growing in government.

How do predictive technology work??

Information and data are the fuel of this system. Governments are now developing new ways to harness the potential of data for the benefit of society. Information, both about the past and about present and future scenarios, complements the decision-making process and creates tremendous value by providing practical insight.

Thus, the government:

  • uses advanced analytics and machine learning capabilities to find and analyze past data and information about what worked and what didn’t.
  • analyzes data and results of what is actually happening in real time to make tactical decisions.
  • builds a forecast by applying predictive analytics and running simulation exercises to predict events before they happen.

Use cases #1. Estonia.

The government has created services that will take care of newborns throughout their lives. The principle itself is to build “zero bureaucracy and an invisible government,” said Estonian Prime Minister TaaviRõivas. All parents need to do is register their newborn via email. The service will then remind them via SMS when to register their children for school, bring them for vaccinations and other relevant reminders.

Use cases #2. USA.

Police departments across the country use software that aggregates crime data across agencies, correlates it with census data, terrain details – even the weather – and figures out the likelihood of crime types in patrol areas. The software uses AI-based analysis and helps strategically plan patrols that have consistent tactics designed to maximize crime deterrence with minimal impact on the community. By analyzing historical data, the system helps make decisions about deploying resources – for example, send more police to a particular area on Friday night, because the data shows that this is where violent crime is most often committed.

Another software that is also being tested in the US collects information about offenders such as employment status, family relationships and missed registrations. The data is then processed through an algorithm that advises officers when the offender is deemed to be at high risk of reoffending.

Use cases #3. Singapore.

Singapore is using analytics to better manage public sector workforce, including recruitment planning and training for civil servants. This will help understand what skills the public sector workforce will need in the future. Government agencies can now use data to predict what factors affect people leaving the public sector and how the government can better deal with them. The institution can analyze what motivates people to work in the public sector and which groups of people are most at risk of leaving it.

Based on these models, the government can make more strategic training and recruitment decisions in the public sector.

Use cases #4. Australia.

The Australian Institute of Health and Welfare ( AIHW) uses a model based on predictive technologies to forecast Australia’s health care spending. By collecting and analyzing data such as population growth, service volume per treatment, and excess health price inflation, the AIHW model was able to provide predictions for 20 disease groups. An assessment of changes in funding from national and state governments, as well as the private sector, was also presented.

Use cases #5. UK.

Hillingdon Council’s AXIS Project, which uses advanced technology to gather information from the local community to identify hard-to-reach children who may be exposed to exploitation. By collecting and analyzing data from various sources such as police, youth services and social media, the AXIS project enables early intervention groups to more effectively identify at-risk youth. This allows them to identify likely cases and inform relevant agencies that can provide targeted support and keep more children safe.

To summarize.

These are just some of the examples that show the role of predictive technologies in the public sector. As we can see , many government agencies,  with vast amounts of data at their disposal,  are using predictive technology-based tools to be more efficient and responsive to the needs of their citizens.

In this way, governments can:

  • Better understand the needs of your citizens;
  • Optimize the distribution of your resources;
  • Improve the decision-making process of civil servants;
  • Improvetheirriskmanagement; and
  • Ultimately, to provide quality services to its citizens.

Subscribe to our mailing list for more examples and cases of using digitaltechnologies in the public sector.

Predictive technologies are a set of tools that are able to predict patterns in data and to model future behavior and preferences among consumers. In this article, we will discuss how predictive technologies can be used by the Government. And we will learn how they work on real use cases from five countries.

Another principle contributing to the effective digitalization of the public sector lies in the user-centric Customer Experience. Practical recommendations and use cases are discussed in detail in the e-course “E-GOV: Digital transformation & Customer Experience”. Most importantly, 65% of the course content is dedicated to showcase the adoption of these principles in real government initiatives in Europe and Asia (Milan, Gent, Singapore, Seoul, Rotterdam, Belgium ++). For a detailed description of the course, see the link:

You can order an individual program specifically for your organization on our website or schedule an online meeting with our experts and discuss our options for your tasks

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