SMASSA Big Data Strategy Definition
Development of a Big Data strategy to improve parking problems, providing quality service to users.
Thanks to the Consulting services, a Big Data strategy has been developed for SMASSA; including Digitization, Operational Efficiency, Sustainability and External Monetization.
The Municipal Parking Society SMASSA, had a mission to solve the parking problems that existed in the city of Malaga. It started its activity in 1986 with the development of urban space planning, regulation and construction of surface car parks and traffic standardization. SMASSA manages 41 parking buildings for residents, with a capacity of 14,010 spaces. It also has 6,763 parking spaces, distributed among 12 rotating car parks. SMASSA also provides a Traffic Support Service together with the Málaga Local Police and controls the legality of the city's traffic routes, removing vehicles that are parked improperly and transferring them to the different municipal holding stations.
Recently, LUCA, the data unit of the Telefónica group, has collaborated with SMASSA, Sociedad Municipal de Aparcamientos y Servicios de Málaga (Municipal Parking and Services Society of Malaga), in a consultancy project to define the organization's Big Data strategy. This project has identified 4 levers on which to build the Big Data strategy: Digitization, Operational Efficiency, Sustainability and External Monetization.
To activate these 4 levers, an implementation of specific initiatives in the short, medium and long term has been proposed. Gradually, SMASSA hopes to be able to respond to its needs of surveying, processing and analysis of the multiple sources of information available, in order to improve the parking problems that exist in Malaga, providing a quality service to users.
Making the parking system in Malaga more efficient
The challenge was to design a Big Data and analytics strategy for the next few years that allows SMASSA to evolve towards a data-driven organization from which a parking and service model can be built. Also to take advantage of the current capabilities of an intelligent city to strengthen business pillars such as sustainability and data monetization.
4-year vision of SMASSA's Big Data and AI strategy
Short term: Advanced display to report KPIS. Transactional correlation analysis, providing mobility insights in the city. New development of parking reservation platform through mobile application.
Medium term: Consolidated Multiplatform Data Model. Recommended distribution of recharging points. Advanced segmentation to offer new services to users.
Long term: Model for converting users to the digital channel. Cluster advertising advice. Circular management of vehicle waste. Automated sale of data and insights to third parties.
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