This blog post covers some of the points discussed at a panel conversation on the integration of data and analysis in the nonprofit community, held at Civic Hall on 26 June 2018. For the complete panel, check it out on Facebook Live.
According to Pathfinder.vet’s lead analytic engineer, Michael Thorne (US Navy), “data is a nice buzzword, but without direction it really doesn’t solve any problems.” And according to the organizations and the foundations looking for data regarding the Veteran community and the success of organizational programs, he’s right. Without a well-formed purpose and intent, data never turns into its much more useful cousin: information.
“Good” data leads to information that helps nonprofits grow and advance. Derek Coy (US Marine Corps) of the New York State Health Foundation certainly believes that understanding the state of the community to include emotional health, perception, and attitude is a big piece of the puzzle when it comes to gauging the success of a nonprofit program his agency helps to fund. He relies on the reports from nonprofits to tell him this information, with a focus on measurable benchmarks that can also help improve the grant process.
But the question is how nonprofits - who often lack the overhead flexibility for analytics - collect and use data. These organizations need to optimize every dollar from donors, so they need to plan collection carefully. What are funders looking for when they request specific metrics, and where are the holes in information? Are there better, more honest and reliable means of getting this information? How do we balance protecting the privacy of individuals with some of that information being what we need to correct critical needs in the community?
Collecting this information is challenging and can be unreliable, and particularly difficult to make it “measurable” for funders; asking how someone “feels” is a subjective question. Do you “feel” positive today? Is it because of the program or just happens to be the day, or are you doing better in some respect than you were yesterday so comparatively you rate it higher?
Marie Roker-Jones (US Army Spouse) of Blue Star Families, a non-profit organization conducting annual surveys to help gauge the needs in military communities across the country, understands these challenges well. As a regional director, she would rather the reported success of a program (and therefore funding requests for similar programs) did not hinge on outside or subjective factors. Blue Star Families relies on the accurate reporting of different aspects of the community to plan military family programming and request grants, so filtering out different forms of bias is of particular interest. The organizations see a need for this data to become collectible, standardized, and measurable.
Michael sees the future - and the solution - in passive data collection, and the appropriate protection and analysis of this information. Home and wearable devices, social media, and miscellaneous question and feedback forums are always listening to the broad community, and constantly storing information people aren’t aware they are providing. It might be heart rate data sent to a wearable or how often someone uses a particular word in a paragraph pushed through a natural language processing algorithm, but this passive data can be combined to finally understand the real nuance of emotion and success with less of a tendency to be tainted with conscious bias. The technology can also then find the best ways to predict success and look into the future, a direction that makes Derek and his foundation eager to look at methods that will get them ahead of problems enough to create real change in the communities they fund.
Then, of course, is how to get all of the parties to understand each other. Data is important, and is critical to everything from gauging a successful program to getting that program funded. Organizations are collecting data, funders need data, but do those sets of data match? Is there enough literacy about data to make sure we are collecting the right things and translating it in the right way? Going back to Michael’s original point: without context, data is useless.
It’s a team effort to solve the data problem. The funders must be clear on their benchmarks and measures, even providing direction on how organizations might collect data. Then the organizations need to be careful to eliminate as much bias as possible, and to find specific questions to answer. And of course it is up to analysts - like those at Pathfinder.vet - to improve the way we translate the data into the information needed so both funders and nonprofits can work to make the community better.
According to Pathfinder.vet’s lead analytic engineer, Michael Thorne (US Navy), “data is a nice buzzword, but without direction it really doesn’t solve any problems.” And according to the organizations and the foundations looking for data regarding the Veteran community and the success of organizational programs, he’s right. Without a well-formed purpose and intent, data never turns into its much more useful cousin: information.
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| Thanks to Patrick Farrell for photos of the event! |
But the question is how nonprofits - who often lack the overhead flexibility for analytics - collect and use data. These organizations need to optimize every dollar from donors, so they need to plan collection carefully. What are funders looking for when they request specific metrics, and where are the holes in information? Are there better, more honest and reliable means of getting this information? How do we balance protecting the privacy of individuals with some of that information being what we need to correct critical needs in the community?
Collecting this information is challenging and can be unreliable, and particularly difficult to make it “measurable” for funders; asking how someone “feels” is a subjective question. Do you “feel” positive today? Is it because of the program or just happens to be the day, or are you doing better in some respect than you were yesterday so comparatively you rate it higher?
Marie Roker-Jones (US Army Spouse) of Blue Star Families, a non-profit organization conducting annual surveys to help gauge the needs in military communities across the country, understands these challenges well. As a regional director, she would rather the reported success of a program (and therefore funding requests for similar programs) did not hinge on outside or subjective factors. Blue Star Families relies on the accurate reporting of different aspects of the community to plan military family programming and request grants, so filtering out different forms of bias is of particular interest. The organizations see a need for this data to become collectible, standardized, and measurable.
Michael sees the future - and the solution - in passive data collection, and the appropriate protection and analysis of this information. Home and wearable devices, social media, and miscellaneous question and feedback forums are always listening to the broad community, and constantly storing information people aren’t aware they are providing. It might be heart rate data sent to a wearable or how often someone uses a particular word in a paragraph pushed through a natural language processing algorithm, but this passive data can be combined to finally understand the real nuance of emotion and success with less of a tendency to be tainted with conscious bias. The technology can also then find the best ways to predict success and look into the future, a direction that makes Derek and his foundation eager to look at methods that will get them ahead of problems enough to create real change in the communities they fund.
Then, of course, is how to get all of the parties to understand each other. Data is important, and is critical to everything from gauging a successful program to getting that program funded. Organizations are collecting data, funders need data, but do those sets of data match? Is there enough literacy about data to make sure we are collecting the right things and translating it in the right way? Going back to Michael’s original point: without context, data is useless.
It’s a team effort to solve the data problem. The funders must be clear on their benchmarks and measures, even providing direction on how organizations might collect data. Then the organizations need to be careful to eliminate as much bias as possible, and to find specific questions to answer. And of course it is up to analysts - like those at Pathfinder.vet - to improve the way we translate the data into the information needed so both funders and nonprofits can work to make the community better.