Presidion | Case Study – City of Almere

Case Study – City of Almere

Almere, Netherlands

www.almere.nl

Solution Components

  • IBM® SPSS® Statistics
  • IBM SPSS Modeler

City of Almere

 

Statistical analysis and predictive analytics allocate resources to citizens while planning for growth

 

Almere is the seventh-largest city in the Netherlands and part of the Amsterdam Metropolitan Area. Founded in 1975, Almere is the youngest city in the nation and one of the fastest growing cities in Europe. It has a population of approximately 200,000.

 

The Opportunity

The city of Almere provides an extensive list of services to its 200,000 residents, ranging from disability benefits for injuries to assistance for the immigrant population. The city used a tedious manual process for the allocation and administration of services to its citizens that was starting to strain. With the population expected to double in the next 18 years, the city saw that the existing method wouldn’t suffice for meeting the future needs of its residents. It began looking for a more robust business analytics solution that would help it allocate resources more quickly and adequately balance those resources to plan for rapid growth.

 

What Makes It Smarter

How can a city ensure that citizens are getting the services they need now while adequately planning for the services that those same citizens, and new ones, will need in the future? In the case of one city, statistical data and predictive analytics are the key. Almere analyzes city and citizen data from 21 different sources to quickly and accurately match appropriate benefits, services and subsidies to all of its citizens. Using the same data, the city can model future scenarios to help predict its growth trajectories, grouping people by age, socioeconomic background, occupation and
more. This enables city officials to appropriately plan for future growth while ensuring that resources are being allocated wisely now. The city is becoming a model for how rapid growth can be socially and economically sustainable.

What if you could allocate present and future benefits based on predictions for population growth?

Real Business Results

  • Reduces reporting time by 75 percent on trends in city growth, demographics and other population information used to allocate city services and benefits
  • Helps the city identify people who are receiving services for which they are not eligible as well as those who are eligible for services but not taking advantage of them
  • Enables city planners to forecast future scenarios as the population grows, helping them make smart, proactive decisions and better allocate present resources

The solution allows us to translate the insight into targeted actions, processing benefit applications much more quickly to provide the best service to our citizens. It helps us on the road to develop a smart society within a smarter city.

—Gerhard Dekker, head of research and statistics

© Copyright IBM Corporation 2014

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