Seminar May 05, 2022

MRI Jigsaw Virtual Workshop – Tackling homelessness with data analytics & technology

  • Seminar
  • May 05, 2022
  • 9.45 am - 13.00 pm
  • FREE
  • Virtual Conference & Workshop

**THIS SEMINAR IS NOW FULL**

IF YOU WOULD LIKE TO REGISTER FOR OUR NEXT SESSION, PLEASE EMAIL: SOCIALHOUSING@MRISOFTWARE.COM

 

This half-day interactive seminar will bring together housing options, outreach and policy development colleagues to share their experiences about how they’re using data analytics and digital technologies to tackle all forms of homelessness.

The seminar will feature keynote sessions from sector leaders and MRI subject matter experts. Breakout sessions and collaborative workshops will discuss sector challenges and best practice tips, and explore how technology can play an integral role in addressing this pervasive issue.

Join peers using our Housing Jigsaw suite of solutions, and sector specialists to discuss and drive thinking about how data and technology can reduce barriers. By collating, analysing, and connecting systems, we can fuel resources for the communities and people with the greatest need.

Agenda
10.00 am Welcome & opening remarks
10.10 am Keynote speech – Francesca Albanese, Head of Research and Evaluation at Crisis, talks about why we need better data on all people experiencing homelessness
10.30 am Breakout workshop I – How can we remove the barriers to collaboration and use data analysis to address homelessness?
11.15 am Coffee break
11.30 am Breakout workshop II – Is current technology helping the sector evaluate the processes that best support people experiencing all forms of homelessness?
12.15 am Breakout review & summary – establish next steps for continued opportunities for collaboration
12.45 am Closing remarks & introducing ‘Basecamp’ – our online forum for Jigsaw solution users

 

With the right technology in place and a comprehensive understanding of the data they collect, local authorities and their partners can target resources for those experiencing homelessness more effectively and can use predictive analytics to better assist those at risk of becoming homeless.

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