Measurement & Evaluation
Harnessing the Power of Evidence
Better use of evidence and developments in evaluation practice can shift the power dynamic between funders, service-delivering organizations, and service users.
Tag: Big Data
Impact Investing
Data: The Next Frontier for Impact Investing
A call for investors to share their data to expand the field’s understanding of the breadth and depth of activity.
Video
Measurement & Evaluation
Data On Purpose | Do Good Data: Causal Inference Meets Big Data
Hal Varian, chief economist at Google, discusses methods of big data analysis that can indicate not just correlation but also causality.
Collaboration
Using Collaboration to Harness Big Data for Social Good
Not every nonprofit has a data science team. To truly harness big data for social good, we need collaborations between individuals, across organizations, and across sectors.
Impact Investing
Creating a Better Economy with Data Science
We need to channel capital in all its forms in a direction where it can have a lasting impact and generate competitive financial returns. Data science can help light the way.
Environment
Public-Planet Partnerships: Time to Ratify Our Free Trade Agreement with Nature
We protect nature. We learn from nature. But we are not collaborating with nature to solve the greatest challenges a human generation has ever faced.
Podcast
Collaboration
Unlocking Data and Unleashing Its Potential
Many valuable datasets remain locked away or siloed across different organizations and sectors. This panel from our February data conference looks how we can collaborate better on data projects.
Measurement & Evaluation
Telling Your Data Story Well
An important part of telling your organization’s data story well is picking the right storytelling technique for your audience.
Organizational Development
Winning the Internet
How nonprofits can use the same tactics that helped Trump win the US presidency for outsized social impact.
Podcast
Measurement & Evaluation
Prediction vs. Bias in Data: A Debate
Is it possible to use data to make predictions without enforcing existing biases?