A few weeks ago, we published a research note on how to Use Data for Good to Impact Society.
For me, this note is from the heart and soul; I suspect the same is true for my co-authors. It’s been an evolution of a presentation and research for the past seven months, but these ideas that have been incubating for more than a decade. I remember being at a Hyperion conference more than a decade ago when the CEO described how Essbase was being used for microloans in third-world countries. I loved that story, and recall it as one of the first times I thought about how data might be used to better the world.
Over the next 15 years, I would occasionally hear of other inspiring stories. Cleveland Clinic shared with me how data was being used to save lives, at a time when many hospitals could barely use data to manage operations and supply chain costs. In 2007, I heard a presentation from Nationwide Insurance at the time, now Learning Circle on data’s use to improve high school graduation rates for teens in inner city schools. In my book, Successful Business Intelligence, I wrote about how data and BI could be used to make the world a better place. When I would mentioned this in conference talks, people kind of chuckled. Perhaps I was drinking too much industry Kool Aid. Wasn’t it all about operating efficiencies and improved revenue? These are valuable goals, of course, particularly in the private sector. But clearly, there are some great societal use cases, even if this is not yet mainstream thinking.
Skills, expertise, and money often lag in the public sector and in NGOs trying to use data to improve or serve society. Yes, money does matter. One organization I had been tracking since 2013 in its mission to use data in the public sector recently ceased operations. A university trying to run a data science for social good patterned after University of Chicago’s very successful program has since canceled their initiative due to lack of funding. Those are the disappointments.
Then there are the massive missteps and outright abuses of “data for bad” as well: Cambridge Analytica and Facebook. Some governments’ surveillance of citizens.
But when viewed as a whole, there are many more successes in data for good, with increased momentum. As we wrote in the note, social media mentions of #data4good, #dssg, #AIforgood and the like have grown 68% in the last year. Chloe Tseng’s #VizforSocialGood followers were at 600 when I first started tracking them earlier this year and has now topped over 1000 volunteers, with a world tour in the making. Data for Good Canada will have a week long program. Data Kind has grown to over 18000 volunteers.
These are all positive signs to me that data for good is a movement, more than a moment. I hope so.
If you are part of this movement, we want to hear about your work. Feel free to post upcoming conferences and calls for papers in the comments. And take a look at my Twitter data4good list of people and organizations, updating weekly.
Lastly, I was so happy that the powers-that-be at Gartner allowed us to make this research note publicly available, so that we can contribute in our own small way to this movement. Let’s keep it going!
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