Our Method | IZI Lab

Our
Method

We integrate methods and data from a variety of disciplines and technologies, merging cross-disciplinary expertise into a tailored approach.
In our method mix: the rigor of traditional research, the precision of data science, the visionary perspective of foresight, and the inclusivity of design thinking.

Through a flexible and customized process, we adapt tools and knowledge to specific contexts and objectives. This multidimensional approach allows us to navigate uncertainty with clarity, transforming complexity into opportunity and anticipating future scenarios with precision.

Forward-looking data

Data as a predictive resource, obtained through strategic foresight methodologies to anticipate megatrends, emerging phenomena, and unpredictable events.

Big Data

Real-time data generated from multiple sources through the use of AI and machine learning. Volume, velocity, and variety are the key characteristics.

Participatory data

Collected through participatory design workshops and design thinking processes applied to business, facilitating dialogue and ensuring the participation of all stakeholders in the decision-making process.

Thick Data

Detailed qualitative and quantitative data, collected through traditional research methods such as interviews, surveys, field observations, focus groups, research studies, and official statistics. These data provide a deep understanding of behaviors.

Forward-looking data

Data as a predictive resource, obtained through strategic foresight methodologies to anticipate megatrends, emerging phenomena, and unpredictable events.

Big Data

Real-time data generated from multiple sources through the use of AI and machine learning. Volume, velocity, and variety are the key characteristics.

Participatory data

Collected through participatory design workshops and design thinking processes applied to business, facilitating dialogue and ensuring the participation of all stakeholders in the decision-making process.

Thick Data

Detailed qualitative and quantitative data, collected through traditional research methods such as interviews, surveys, field observations, focus groups, research studies, and official statistics. These data provide a deep understanding of behaviors.

USE CASE

IZILab for the
Social Housing Agency

Analysis and monitoring of housing policies in Rome to address the emerging challenges of the housing crisis. Identification of trends and housing needs, assessment of the impact of socio-economic and global factors, and support for policy decisions to improve housing welfare.

Implementation of an interactive and dynamic dashboard to collect and visualize data on the urban housing context, facilitating the analysis of future scenarios and interaction among stakeholders. The system integrates socio-economic data, social media insights, telecom data, and essential services to provide a comprehensive policymaking tool.

Promote a digital ecosystem to facilitate the understanding of the housing situation and the engagement of stakeholders. Provide data journalism and visual analysis tools for students, citizens, and policymakers, fostering debates and creating spaces for discussion on housing in Rome.

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