The Intelligent Welfare State

SAS helps leaders in government increase employment by turning data into knowledge

Not everyone is employed. Most people, however, want to contribute actively to society.

There are fewer and fewer workers in the job market, presenting the public sector with challenges to sustaining their social safety nets. This can only be reversed by bringing more people into the job market, which promises two benefits: 1) A reduction in public spending and 2) An increase in tax revenues.

The unemployed have diverse needs. The strongest among the unemployed do not have as much need for re-schooling or job search assistance; they can often help themselves. The weakest, on the other hand, face a myriad of challenges ranging from interpersonal and work skills to demographics, which often restrict opportunities for returning to work quickly, if at all.

Since resources at unemployment agencies and unemployment benefits from unions and local communities are scarce, it is necessary to prioritize constituents in accordance to needs. Such an approach addresses issues of social fairness as well as fiscal benefits to local governments.

Although much data is available that highlights what has worked best in the past, we have yet to use data effectively enough to achieve job-creating growth.

SAS help turn healthcare data into decision support for healthcare systems

Healthcare systems face enormous challenges. With fewer resources, more treatments must be handled while quality must be improved simultaneously. Patient-centered care, patient dialog and inventive thinking are topics currently on the agenda. Better and more agile transitions, increased ambulatory-patient throughput and prevention are some of the areas where the public sector can utilize analytics to effect savings  .

Data-driven management can be a tool to achieve the political ambitions of realizing a patient-centered, value-based healthcare system. New connections across regions and municipalities, physicians, hospitals and community care, can be created by using anonymous patient data and sharing information and expertise.

Data is needed to transform and provide a balance between production, prevention and allowing more and better healthcare for the available resources. For instance, patient risk scoring data can be used to analyze patient risk profiles and determine if resources could be better spent on ambulatory or preventative care for chronically ill, high-risk patients.

There are enormous quantities of data in the Nordic countries—more than what is currently being used —and on which intelligent decision can be based. Typically, data is available, perhaps with some delay, but it is primarily used in a research or political context, rather than locally for decision-making or in a clinical setting.

Healthcare providers can benefit from using data far more proactively and to enable this, SAS collaborates with healthcare leaders to transform their organizations with the help of data insights. The systematic and proactive use of healthcare data is critical for the empowerment of healthcare providers to become value-based organizations.

SAS helps leading public officials improve social services by turning data into knowledge.

There are good reasons to increase social mobility. Children benefit, as does society as a whole.

While the general standard of living and the quality of our safety net is high, too many vulnerable children lack opportunities for social mobility. Helping these children will not only reward them with a brighter future, it will have a long-term economic impact, as fewer children grow up unable to support themselves.

The worst cases involve abused children in families that fall through the social safety net. As soon as the problem is identified by schools or social workers, many families move on to another municipality. Here they may get a bit of breathing space, until someone becomes aware of the problem and the scenario repeats itself. Once the problem comes to the public’s attention, we learn that it is not new, but rather a pattern of behavior that has happened elsewhere before. The common explanation is that “it wasn't handled in time."

Today it is possible to ensure that once a problem like this becomes known, it will not repeat itself. It is also possible to take preventative measures and prioritize multidisciplinary interventions through coordinated action from different professionals and agencies. This will naturally require oversight and insight, which data analytics can help provide.

However, there is not enough hard data about what measures works for vulnerable children. In addition, no one knows how to prevent children from growing into adulthood dependent on welfare, or how children being raised by parents with substance abuse problems can avoid repeating the family tradition. Advanced data analysis would yield deeper and actionable insights that could help multiple agencies in their efforts.

There is plenty to be done, and when trying to comprehend an immense area such as social services, there are many issues to address.

The National Board of Social Services in Denmark has created a unified, comprehensive platform that gives a holistic view of multiple agencies. For instance, the Danish Prison & Probation Service used the shared platform and predictive analytics to forecast the economic consequences of different types of prison sentences.

Many areas remain unexplored. These include the administration of the overall economy, and not the least ways to reduce welfare fraud. Read more about Risk-based control here.

SAS helps school administrators improve schools and education by turning data into knowledge.

Data is knowledge. Knowledge can make us smarter about which measures improve learning. 

In Denmark, a major education system reform has been implemented, including initiatives such as inclusion programs, homework cafés and increased exercise as part of the curriculum, to make pupils smarter. However, is the new reform producing the desired results and which of the initiatives has the biggest impact? SAS Institute wish to take part in answering these questions, and we can do just that, thanks to intelligent data-based tools.

In the same way, through student retention analytics, we can find the answers to out why 95% of our youth have difficulties completing a high school education, and why 60% face adversity continuing to university. Perhaps they lack the competences needed to choose and complete their education. Or maybe they are met with initiatives and intentions that do not match their needs for digitalization, changeability, openness and individual acknowledgement.

At SAS Institute, we are experts in turning resources into impact, and we accommodate visions and objectives by evaluating and acquire new knowledge based on data. For instance, SAS Institute has helped the University of Alabama minimize student dropout rates and use data to recruit and retain the best students. As a outcome, the university is now more successful in recruiting and retaining students, resulting in freed resources and higher student satisfaction.

Analytical Solutions

The public sector needs to deliver more for less. This includes detecting more people who are abusing the system.

The expectations from the citizens to the social services are increasing, even though budgets can’t keep up. Unfortunately, a minority of the public is taking advantage of the system at the expense of others – either consciously or unconsciously. When that happens, not only does it undermine trust in public administration, but the structure of our society as a whole. 

Trust is good. Control is better. However, the problem with control is that it inconveniences the many to find the few fraudsters. The good news is that it is now possible to focus on the abusers and criminals when we let data speak for itself. 

As humans, we can use our intuition, experience and work even harder. However, that is not necessarily the most efficient approach. But when we systemize our human insights and combine them with risk management control systems and data analytics, we can achieve results quickly. That is the approach of SAS Institute.

Over decades, we have refined our analytical models to catch fraudsters from any angle. The starting point is the insights and intuition of experienced specialists. From there, the system automatically searches for numbers that deviates from the norm and combines these with predictive analysis to make solid data based forecasts. Then focus shifts back to the people again. However, this time, analytics and AI is used to detect suspicious networks, patterns and combinations that would otherwise take untold manpower hours to do manually.

The result is effective risk based control that not only support supervision but also detects fraud and abuse of public funds. This way, repeat offences is limited, and focus can stay on those that ruin things for others, without burdening administrators with an extra workload.

In the end, the majority of the citizens experience better service, and the trust in public administration grows.