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Data Driven Philantropy

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Considers several ways in which data can help philanthropic organizations improve their missions, as well as pathways toward making philanthropy more data-driven.

Broadly speaking, when analyzed responsibly data and data science can provide philanthropies with an improved analysis or understanding of the situation or problem; help predict future trends or help evaluate the impact of investments made.

This in turn can perfect the way philanthropies function in three broad ways:
First, having access to data and data science can influence the overall operations of philanthropies, making them run more efficiently.
Second, data can transform how philanthropies are governed, making them more accountable — a topic of major importance in the current philanthropic landscape.
Third, data can increase the impact of an organization’s mission by allowing them to make evidence-based decisions and continuously adjust their activities to take account of realities on the ground.

Published in: Government & Nonprofit
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Data Driven Philantropy

  1. 1. 1 DATA DRIVEN PHILANTHROPY STEFAAN G. VERHULST The GovLab
  2. 2. 2 DATA DRIVEN PHILANTHROPY GOVERNANCE MISSION O PERATIONS PREDICTION SITUATION ANALYSIS KNOWLEDGECREATION IMPACT ASSESSMENT ACCOUNTABILITY IMPACT EFFICIENCY DATA
  3. 3. 3 SITUATION ANALYSIS
  4. 4. 4 KNOWLEDGE CREATION Foundation that used its data to generate insight in a problem
  5. 5. 5 PREDICTION AND FORECASTING Foundation that used its data to generate insight in a problem
  6. 6. 6 EVALUATION AND IMPACT ASSESSMENT Example of Foundations combining their data to assess collective impact
  7. 7. 7 UNLOCKING NEW DATA SOURCES OPEN GOVERNMENT DATA PRIVATELYHELD D ATA CROW DSOURCEDDATA
  8. 8. 8 OPEN GOVERNMENT DATA
  9. 9. 9 OPEN GOVERNMENT DATA
  10. 10. 10 CROWDSOURCED DATA
  11. 11. 11 PRIVATELY HELD DATA: DATA COLLABORATIVES
  12. 12. 12 PRIVATELY HELD DATA: DATA COLLABORATIVES Bill & Melinda Gates Foundation’s Data Access Principles Frequently Asked Questions This FAQ document is designed to provide guidelines for response to the anticipated frequently asked questions regarding the launch of the Bill & Melinda Gates Foundation‟s Data Access Program in 2011. This is considered a pilot year during which foundation staff and grantees should endeavor to apply the principles to grant making and management, seek guidance on the challenges that arise, and document these challenges for future program enhancements. As such, there are no “wrong answers” regarding the specific ways in which the principles will be applied in 2011, but good faith efforts should be made. The goal is to implement the principles broadly and to learn from experiences to refine the process. We appreciate your cooperation and patience. Principles and rationale  What are the Bill & Melinda Gates Foundation‟s Global Health Data Access Principles?  What is the difference between these principles and related elements of the Global Access Policy?  Why has the foundation developed these principles?  What are the benefits of providing access to data? Scope of the principles  To which activities and types of data do these principles apply?  What is meant by final data?  For which grants must a grantee prepare a Data Access Plan?  Do these principles apply to existing grants?  Do these principles apply to qualitative data? Data Access Plans  What should a Data Access Plan include?  What is the timing for completing a Data Access Plan?  I plan to publish a paper with the findings of this project. Do I need to provide access to the data?
  13. 13. 13 DATA COOPERATIVES OR POOLING PRIZES & CHALLENGES RESEARCH PARTNERSHIPS INTELLIGENCE PRODUCTS TRUSTED INTERMEDIARY APPLICATION PROGRAMMING INTERFACES (APIS) SIX TYPES OF DATA COLLABORATIVES
  14. 14. 14 MOTIVATIONS TO SHARE: THE SIX Rs BEHIND CORPORATE DATA SHARING RESPONSIBILITY REGULATORY COMPLIANCE REVENUE REPUTATION & RETAINMENT OF TALENT RECIPROCITY RESEARCH & INSIGHTS
  15. 15. 15
  16. 16. 16
  17. 17. 17
  18. 18. 18 PRIVACY & SECURITY COMP ETITIVECONCERNS GENERALIZABILITY & DATAQUALITYCULTURALCHALL ENGES CONCERNS
  19. 19. 19 RIS K AND VALUE ASSESSME NT METHO DSANDTECHNOLOGIES PRINCIPLESANDPROC ESSES TOWARD DATA RESPONSIBILITY
  20. 20. 20 METHODS MOVEMENTEVIDENCE STEWARDS MAKING DATA DRIVEN PHILANTHROPY SYSTEMIC
  21. 21. 21 DATA STEWARDS
  22. 22. 22 THANK YOU stefaan@thegovlab.org thegovlab.org

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