Help! 5 ways to overcome organizational roadblocks when bringing big data to your nonprofit

The Brief
When it comes to integrating big data into a nonprofit’s fundraising strategy, organizational leaders often point to money as the primary obstacle. Unfortunately, it’s not the only one. There are a number of speed bumps nonprofit data evangelists need to negotiate when trying to bring data to their orgs. Here are five to consider before you launch your campaign for data, and how to overcome them.
big data for nonprofits


1. Budget 

Yes, money is high on the list of hurdles to leap when dealing with data analysis. Not every organization can afford to shell out for software, data collection and data scientists. Luckily, there’s something in between big data and no data: medium data.

The solution: Try to match individual data sets to your organization’s objectives. By focusing your data initiatives on specific business strategies, you can smartly choose what data you need and what data you can ignore. Because this limits the data you’ll need to collect, clean and analyze, this can help to significantly lower your costs.

 2. Training 

Your staff won’t transform into data scientists overnight. You’ll need to set aside time and people to train employees in data analysis. On her blog, nonprofit business blogger Beth Kanter urges nonprofits to mine internal talent first. “There may be someone in another department who is a data nerd with expert Excel or data analysis skills,” she says.

The solution: Your organization’s staff may have hidden skills—ask around in-house before hiring an outside data science consultant.

3. Incomplete or inaccurate data

If your nonprofit is just getting started with data analysis, holding yourself to the same rigorous standards of academic and professional data scientists is more than a little daunting. But the truth is, not every nonprofit needs to operate at the level of a scientific institution.

The solution: Some tech strategists argue that “relaxed data”—imperfect data sets, for example, or research methods that aren’t ironclad—can be useful for storytelling, even if it isn’t scientifically valid. Not everyone agrees, but it may be a way to get your data strategy off the ground.

4. Unwillingness to adopt 

No matter how thoughtfully your leadership develops its data strategy, without a fully engaged, fully onboard staff, it won’t succeed.

The solution: There are a number of strategies for facilitating staff buy-in. Perhaps the most critical is make data an ongoing conversation among all members of staff.

5.Balancing data with storytelling

A good story can drive donations, galvanize volunteers and remind everyone involved in an organization why their work matters, which is why for many nonprofits, improving storytelling is a high priority. The pitfall here is failure to incorporate data into your stories, or, conversely, relying too heavily on numbers and leaving out the human element. 

The solution: Incorporate data into new storytelling platforms like infographics and video. Then collect data on those campaigns to track their effectiveness. 

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RelSci provides a relationship capital platform that helps create competitive advantage for organizations through a crucial yet vastly underutilized asset: relationship capital with influential decision makers. 

Download our white paper, “How to bridge the big data resource gap” to learn more about how to effectively implement data analytics at your organization.  

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