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BCT Partners Applies Precision Data Analysis to Increase Effectiveness of Social Programs


News provided by

BCT Partners

Apr 11, 2019, 08:43 ET

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NEWARK, N.J., April 11, 2019 /PRNewswire/ -- BCT Partners, a national consulting firm, is providing precision data insights about social programs that have never been available before. By combining machine learning with data analytics and social science expertise, BCT Partners is able to precisely pinpoint what programs are working, why they are working, and for whom they are working most effectively. This means that government agencies, nonprofits and philanthropies will now be able to shift from focusing on outputs to outcomes and can identify how to customize programs so that they will work more effectively for specific subsets of the target population. While industries such as healthcare, construction, retail and banking have been utilizing big data for years, this is one of the most innovative ways it is being utilized in the field of social services.

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BCT Partners Applies Precision Data Analysis to Increase Effectiveness of Social Programs
BCT Partners Applies Precision Data Analysis to Increase Effectiveness of Social Programs

BCT's insights could not be more crucial for social funding agencies as many are under intense pressure to do more with less. The proposed government spending cuts for 2020 (as much as 30% on non-defense discretionary spending) and are specifically aimed at many social programs. And some of our society's most vulnerable (such as the elderly and children) could face reductions in basic services that are already spread too thin. With BCT Partners' quantifiable data insights, funders will now be able to not only justify budget requests but can make necessary program adjustments to more effectively serve their constituencies.

Many government agencies have expressed interest in working with BCT Partners, and the National Science Foundation has actively engaged them to move forward with a project. BCT Partners is building a statistical model that can be used to analyze NSF's current data sets in order to determine which programs are making the most impact. The National Science Foundation accounts for about one-fourth of federal support to academic institutions for basic research and education in most fields of science and engineering. Their grants and cooperative agreements help to support more than 2,000 colleges, universities, K-12 school systems, businesses, informal science organizations and other research organizations within the United States.

As Pete York, Principal at BCT Partners and the head of the Precision Analytics team states, "With the increased focus on STEM education, we are incredibly proud to be working with NSF on this important project. According to the U.S. Department of Commerce, STEM occupations have been growing at 17%, and are a critical component to helping the U.S. to stay competitive in the global economy. It is incredibly rewarding to be able to help NSF determine which programs are most effective so they can continue to support this critical work".

Dr. Randal Pinkett CEO of BCT Partners continues, "For over twenty years, BCT has been committed to helping diverse populations achieve equity and we are now in a unique position to use data in a revolutionary way that can transform lives. We are extremely positive about the future and are excited about the ways that our work will strengthen social programs."

For more information about BCT's other projects such as the application of precision analytics in psychiatric residential treatment for Silver Springs-Martin Luther School, go to The Scattergood Foundation White Paper.

About BCT Partners:
BCT Partners is a national consulting firm that works with government agencies, Fortune 500 corporations, non-profits and foundations. Their mission is to provide insights about diverse people that lead to equity. 
www.BCTPartners.com

For Press Inquiries:
Please contact Patricia Neuray at [email protected] 
917-748-7127

SOURCE BCT Partners

Related Links

http://www.BCTPartners.com

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