Through this challenge, students had the opportunity to further develop their skill sets while working to address a real-world problem. Students reported development of their skills in business analytics, business communications, learning a complex social problem, leadership, networking, teamwork, and applied consulting strategies.

Team Five received fellowships funded by Accenture to work with the Allegheny County Department of Human Services to implement their solution.

A portable handwashing station was installed at the Hot Metal Bridge Faith Community in Pittsburgh’s South Side, addressing the lack of hygiene facilities for the homeless during the pandemic and promoting public health, and reducing COVID-19 transmission risks.

To learn more about the results of the 2021 Super Analytics Challenge, download the 2021 Impact Report. 

Executive support and guidance were provided by executive leaders from:

Support from local non-profits and organizations included:

Impact Highlights

Media Mentions

One Mic Stand: Pitt Launches Community-Based Analytics Challenge to Address Homelessness, Pittsburgh Technology Council Podcast

Listen here >

Student Teams

Solution Summary

Team 5 suggested that by delivering services in high-need areas, and tracking access to meeting basic needs for the homeless popuulations, DHS can support, predict, and improve rates of transition to stable housing. By utilizing data at each step of their process, and showcasing how the process will become more accurate over time with more data, this team provided practical ideas on how to support people as they regain stable housing. 

Solution Summary

To solve homelessness, demand for services must be reduced. Proposed models provided insights for the County to reduce the demand for homeless services by decreasing homeless rates. This solution wisely considered the need to utilize important adjacent data and identify “near misses” to develop a more complete picture of those at risk for experiencing homelessness.

Solution Summary

Using a two-part plan that relies on practical improvements and a technologically creative and sustainable idea, the solution proposed providing K-12 students experiencing housing insecurity with academic resources at learning centers. It also proposed affordable, sustainable 3D-printing to construct permanent housing to break the cycle of homelessness.

Solution Summary

 Implementing a holistic approach which considers multiple interconnected aspects of the problem, such as cost, eligibility thresholds and recurrence, and long-term support services, this solution aimed to increase the efficiency of the three phases of rapid rehousing to help individuals permanently exit homelessness in a cost effective manner. 

Solution Summary

This team developed an Optimize Existing Resources Better (OERB) model. The model creatively utilized relevant data and machine learning, particularly surrounding the notably high intersection of individuals experiencing homelessness and jailing. The OERB model uses a predictive algorithm to anticipate what support resources are most optimal for an individual.

Advisory Committee

Pamela Peele, Chief Analytics Officer, UPMC Health Plan, UPMC Entreprises

Richard Clarke, Chief Analytics Office, Highmark Health

Albrecht Powell, Managing Director, Digital Data & Analytics, Accenture

Manpreet Saini, Practice Head, Analytics & Insight, North America, SAP

Jack Peterson, Director, Strategic Relations, National Association of Counties

Audrey Russo, CEO, Pittsburgh Technology Council

Andy Halfhill, Manager, Homeless, Housing Analytics, Allegheny Count (PA), Department of Human Services

Sara Moeller, Associate Dean, University of Pittsburgh Joseph M. Katz Graduate School of Business

Andy Hannah, Adjunct Professor, University of Pittsburgh

Christopher Barlow, Director, Corporate Engagement & Career Services, University of Pittsburgh Joseph M. Katz Graduate School of Business