NTEN: Change | September 2014

Page 34


using it. We get requests all the time from organizations to send copies to their boards, and schools are posting the flyers on their walls.


What are some of the most interesting or unexpected findings you’ve observed from examining the data? Anna Wright (AW): The A conversation with LIMARIE CABRERA and ANNA WRIGHT differences in communities within Westchester County. For example, from the Westchester Children’s Association about how College Readiness Rates range they take a data-based approach to identifying children’s from 7% to 89% within the county. needs. I feel that residents don’t really know just how vast those The Westchester found that when people are faced differences are within their Children’s Association’s with many tables and charts, aka community. (WCA) Children by the “number vomit,” they frequently LC: Sometimes familiar Numbers project has come a shut down, so we started indicators, such as poverty rate, long way since it first published transforming our data into don’t do a great job of addressing its data in 2008. What was the infographics, which were at the some of the inequalities that exist impetus for this project? time an emerging communications across Westchester because of its Limarie Cabrera (LC): WCA has tool. Luckily, the software to create high cost of living. For example, always used data to understand them became affordable: When here it takes an income of about children’s needs and track their ESRI started releasing licenses for $57,960 (National Low Income well-being. We realized, however, ArcGIS, a powerful mapping tool, Housing Coalition, 2014) to afford Westchester County data as a through TechSoup, I did the happy the rent on a two bedroom whole wasn’t telling the full story dance in my office. apartment, and the federal poverty of how children were doing in The blog was established as our level for a family of four is at about each of our 43 municipalities. Data communication platform to $23,850 (2014 HHS Poverty disaggregated by community, by explain why we thought the data Guidelines). Other indicators, such age, or by race and ethnicity was was important, and as median family hard to find. Our goal was to to share it. We income, can better deliver current, accurate, and didn’t abandon our demonstrate areas disaggregated data to our offline efforts, but of need. That said, audience: social service we significantly while the Fast Facts organizations, school district reduced its cost. countywide • Project Start: 2006 administrators, local governments, We reduced our poverty rate is • Project Name: Children and other child advocates. We 300+ page book about 10%, we have by the Numbers produced a 300+ page book in down to a six-page neighborhoods • Funders: Westchester 2008, and a searchable online accordion flyer where the poverty Community Foundation, database with 300+ indicators in that was all rate approaches Curran Foundation 2009. infographics. The 45%. • Full-Time Staff Soon after we launched the feedback has been AW: One of the Members: 1.5 database, we realized that our great, and we’re greatest advantages • Number of Children efforts confused our stakeholders noticing that of the increasing Represented: 225k instead of informing them. We people are actually accessibility of data

Storytelling with Data: A Children’s Tale




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