Nonprofits avoid data for any number of understandable reasons, including:

Data animus. Many nonprofit staff members possess expertise in environmental issues, the arts, health, or education but not data analysis. Some suffer from data aversion. They admit — or sometimes proudly proclaim — that they are not “numbers people.”

Time. Nonprofit staffers do not have time for data analysis. They are struggling to stay afloat, to submit the next proposal, to sustain their programs, to address the huge and varied needs of their clientele, to cultivate donors. As a result, digging through data is almost always a back-burner item.

Fear. Some worry about what their data might reveal. They fear they won’t be able to control the narrative, that the data will be taken out of context, or that funders will withdraw their support based on the data.

“Dirty” data. Many nonprofits have entry-level staff or multiple staff entering data into management information systems or spreadsheets. The result can be “dirty” data — data with a troubling level of inaccuracy because it has not been entered correctly and/or consistently.

Wrong data. While many nonprofits have data on their financials and clients, they often lack data that demonstrates theimpact of their programs. A tutoring program may not track students’ school grades or test scores. An employment program may lack data on program graduates’ wages over time.

Disconnected data. Rather than maintaining a central management information system, small nonprofits often store their data in separate Excel spreadsheets.

See other data tips in this series for how to overcome barriers to data use.

Image Source: smejoinup.com

(This data tip originally appeared on Philanthropy News Digest’s PHILANTOPIC blog.)

Nonprofits are lousy with data. But, like secretive hoarders, we are reluctant to admit how little data we actually use. We may pay lip service to “evidence-based practices” or “data-driven strategies”. But, if pressed, many of us admit that we care about the people and the programs and glaze over at the site of a spreadsheet.

Indeed, we are not wired well for processing data in spreadsheets.

Our visual system has evolved, over millions of years, to process images essentially in parallel. We don’t read the Mona Lisa from top to bottom and from left to right. We take it all in together and understand, almost instantly, that this is a picture of a woman in front of a landscape, sporting a dark dress and an inscrutable smile. Words and numbers, which only appeared within the last few thousand years, require our visual system to scan individual characters one at a time and piece them together to create meaning.

Data is encoded in words and numbers making it difficult for us to extract the stories they can tell. However, if we use visual elements (like bars, pie slices, and sloping lines) to encode the data, the story can come into focus more quickly.

See other data tips in this series for more information on how to effectively visualize and make good use of your organization's data.

Image Sources: thinglink.com and perfect-cleaning.info

(This data tip originally appeared on Philanthropy News Digest’s PHILANTOPIC blog.)