Often, when people think of data, they think of dry facts and figures. What they may not consider is what could come from those facts and figures. Data does not just live in a vacuum, after all. It is collected in order to be applied to practical, real world situations.
Data is now used for just about any kind of industry or organization you can think of. Individual people are able to use it to find people and find out more information about them. It is even used to further the more altruistic efforts of charities and other non-profits. That latter application is what’s called “data for good.”
What is Data for Good?
Data for good describes the use of data to improve social conditions (usually with little to no financial profit expected). Over time, focused data collection can reveal patterns that, in turn, can predict future situations. Being able to predict negative outcomes can give people time to try and come up with solutions to problems and to change things.
Most organizations in the trenches don’t necessarily have the time or resources to analyze data. That’s when teams of data scientists dedicated to the data for good philosophy volunteer their time and expertise. They teach the organization how to collect data. Then, they interpret the data that’s been collected and present their findings to the organization, as well as recommendations for further action.
The efforts are lofty, noble and far-reaching. Some of the goals being pursued by organizations around the world include easing world hunger, stopping human rights violations, predicting the spread of diseases, mitigating crime and poverty, and improving education options. The list goes on and on.
How to Ensure Maximum Impact
In order to use data to their greatest advantage, organizations need to take care of at least two logistical aspects:
- Collect the right data. Data collection is a process that has gone on for decades. But is has not always been consistent or especially thorough. At times, organizations may collect data that is irrelevant to their mission. As such, data collectors need to understand what kinds of information are needed to meet a specific goal.
- Have the right tools and technology to analyze data properly. Data collected in one place needs to be able to be easily related to other data collected in another place. Say you have one list of data that shows all of the problems and another list that includes all the solutions. If it takes a whole lot of manual effort to bring these two separate lists together, the amount of time it would take could outweigh any perceived benefits.
Can Data for Good Really Succeed?
That depends on what you mean by success. For typical businesses, success can be easily measured through increased customers and profits. With non-profit organizations, measuring success is a bit more tricky.
Instead of financial gains, non-profits have to measure success through perceived quality of life, number of lives saved, and legislative measures enacted. Sometimes, positive change of any amount can be considered a success. Other times, only the complete and total reversal of a situation is acceptable as a success. Basically, it’s all relative.
Ask those in the business of data for good, though, and their take sounds decidedly optimistic. Finally, they have a tool that can categorically and dispassionately prove a case for change against those who would have things stay the same forever. That tool is data.
For more information about data and all the ways it can be used in real life, read the PeopleFinders blog. And for more ways where you can try and use data for your own good, find out more at PeopleFinders.com.
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