Our solutions
bring expert approaches to life
Accenture
Californians on homelessness data and resources
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A strong overall majority of Californians recognize the power of data to help address issues of homelessness
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86% say its important to create a statewide homelessness database​
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Most Californians favor data to track the availability and use of resources available to the homeless population
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Most Californians support community facilities to provide overnight accommodations for veterans and others experiencing homelessness
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79% said yes to support community facilities being used as centers for homeless veterans
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74% said yes its important to provide a homeless person a place to sleep for the night
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United States Interagency Council on Homelessness
Priorities
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Housing
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Integrate Health Care
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Build Career Pathways
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Foster Education Connections
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Strengthen Crisis Response Systems
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Reduce Criminal Justice Involvement
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Build Partnerships
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Prevent Homelessness
Community Solutions
Priorities
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Data is the catalyst
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Collaboration makes radical change possible
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clear the path of structural and systemic barriers
Harvard University
Implementing a Data-Driven Approach to Tackling Homelessness: Understanding The Ecosystem of Solutions
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Are these siloed investments, initiatives, and programs working in concert with each other to solve the problem?
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How often is academic data and research translated into action in the field?
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How many government-funded institutions actually share data with each other or, for that matter, talk to each other?
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How many shelter providers work with churches, schools, and other community entities in order to provide advocacy to the homeless?
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Are low-income housing developments built at the pace and in the geography needed based on real-time data from shelter providers?
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A properly-defined ecosystem of solutions would answer these questions and many more.
Each individual solution is targeted towards a specific symptom of homelessness. This ecosystem of solutions there are some entities that work on their own and independent of the whole, some entities that work together but are woefully misaligned, and some entities that just don’t work at all.
In order to build a citywide data-driven strategy for tackling homelessness, the ecosystem should function in a cohesive manner towards completing tasks and initiatives that will help to bring down the homeless count in a city.
Journal of Technology in Human Services
Priorities
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This suggests that “long-term” shelter residents and those that re-enter shelters contribute significantly to the rise of the homeless population living in city shelters and indicate systemic challenges to finding adequate permanent housing.
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Understand the factors that predict readmission and length-of-stay of homeless families.
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Create a unified, comprehensive database of the homeless population in shelters, accounting for more than 6,000 homeless families.
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Applied logistic regression models and an unsupervised clustering algorithm to identify predictors of re-entry and long-term length-of-stay. Citizenship, age, medical conditions, employment, and history of foster care or shelter stays as a child are found to be significant predictors.
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Results of the K-means clustering identify three primary groups, consistent with previous typologies characterized by transitionally homeless, episodically homeless, and chronically homeless.
National Alliance to End Homeless
Priorities
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A Coordinated Approach
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Housing as the Solution
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Assistance for the Most Vulnerable
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Designing a Crisis Response
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Increasing Employment and Income
US Housing And Urban Development
Priorities
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Paradigm shift in the goals and approaches of the homeless assistance network
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Clear goal setting
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Community-wide approach
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Leadership and an effective organizational structure
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Mainstream agency involvement
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Catalyst trigger event
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Private sector involvement
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Local elected official commitment
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Progress tracking mechanisms
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New Approaches to services
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strategy to handle and minimize negative reactions to locating projects in neighborhoods (NIMBY response)