In the U.S. today, we invest over $6T/year in solutions to social problems. We fund thousands of social programs and charities, but we don't know which interventions work the best. We're spending billions on evaluation, but we're not systematically learning why some programs work and others don't.
In the nonprofit and public sector we invest first, and then measure to see what we got. That may be a key reason why we aren't making as much progress as we could be. Predicting the success of social programs before we fund them holds great promise for the future of social impact
Making use of machine learning technology as a business sounds cutting edge, but as a business it's not easy to navigate and know what to look for in a nascent industry.
Hey, all you millennial marketers, take note--it wasn't always this easy. Literally, one recent high-school graduate ago (17-ish years), Google Adwords reps were knocking down doors at marketing firms across the United States, giving CEOs a sales pitch about keyword-rich content, closing face-to-face transactions, and returning a month later with graphs and charts galore to highlight new search results.
Savvy difference-makers know how to research and network. They will find current and former employees on LinkedIn and chat with industry insiders to get the scoop on what it's really like to work there.