Data culture: Why don’t we know how many people work in the nonprofit sector?

Data culture: Why don’t we know how many people work in the nonprofit sector?

really-300x161.gifWhen I shared that “25 Situations Only Nonprofit People Can Understand” post on Facebook, it seemed like all of my “friends” responded with, “this is my life!”

Sometimes I forget that the working world is composed of more than the nonprofit sector. I mean, obviously all the cool kids work in nonprofits. But that’s not EVERYONE. You might be wondering how many people in the United States actually work in nonprofits. Turns out, that’s a question we may just be learning how to answer.

Unlike other industries, the nonprofit sector doesn’t have continuously updated national data that describes its employees, impacts and services rendered. This matches the paucity and variability of data on equity, diversity, and inclusion (EDI) describing nonprofit employment, leadership and funding.

Comic by Toothpaste for Dinner

surveycartoon-300x235.jpgIt can sometimes feel like we are constantly filling out surveys, getting asked employment related questions, and generally selling our souls to forms and questionnaires. This begs the question: how on earth, in 2015, can we not adequately discuss the nonprofit sector in the United States? Simple: because we haven’t cohesively asked the right, or even the same questions, and we haven’t done so in an ongoing and timely manner. Even if we did, nationwide real-time data collection and analysis takes an enormous infrastructure and investment that isn’t an achievable priority for most.

That means we need to find data sets that already exist and manipulate them to serve our reporting needs. The question, do you work in the nonprofit sector, may not even be included in the original survey. An analyst will have to take a question that is somewhat similar in nature to the answer they want to investigate, and find a way to use that in their research.

For example, I used a data set for my dissertation that was initially designed to assess academic achievement during school transitions. I was able to use this data to study childhood obesity and the school food environment only because the original investigators measured height and weight at each data wave (which is used to calculate BMI). I got lucky. Researchers can spend a lot of time on a wild goose chase looking for just the right question in a data set. The alternative –  designing and collecting your own data – is an even more untenable option.

Luckily, YNPN realized how important it is to make data a priority. We are looking beyond the (sometimes) dry data and emphasizing the creation of a culture within the network that embraces and appreciates data. With a cohesive data system in place, we will be better able to understand and describe our work across the YNPN network. We want to have the ability to say things like, “YNPN increases diversity in the social sector by having a diverse membership base, elegant and sophisticated programming, and promoting discussions on equity and diversity,” and actually have the data to back it up. Right now, we have to preface that statement with, “Anecdotally, …”

Basically, we want to be able to accurately tell the story of an experience as a YNPN member and chapter.  Without good data, we can’t do that. And we can’t represent our YNPN National voice as speaking for all of our chapters and members. Further, we can’t actively contribute to shaping research within the sector that shows how nonprofit leaders become more effective. Or help to make the sector stronger and more diverse.

nb-logo-white-rect-300x188.jpgYou’ve probably been hearing a lot about the Chapter Operating System. A big part of that project is bringing all of the chapters onto our selected database, NationBuilder, and creating metrics which will align with the field on EDI, and allow us to collate the YNPN network-wide data in one place. We are excited to work in partnership with our chapters and members to delineate and refine our data metrics, build enthusiasm for quantitative and qualitative data collection and analysis, and have the ability to effectively describe YNPN. You are integral in helping to build a data positive culture that will allow us to fully tell the story of YNPN.

You may be asking why this rambling post about data matters for you. Our goal was to emphasize how and why data is important to YNPN. In the coming months, we will be putting out requests for assistance in refining metrics, contributing to other data driven projects, and to work with me to train chapters on our new database. Keep your eye out for those requests, get involved and remember – data is awesome!