Proper Data Collection for Nonprofits: Why Does it Matter?
In the realm of nonprofit data collection, NPOs have a wealth of tools, strategies, and talent to rely on to achieve their goals, despite the inherent challenges they may face. The hard work of nonprofit professionals can often go unnoticed, but your organization still needs to be managed much as a for-profit business would.
One of the most critical aspects that businesses and nonprofits need to be cognizant of is their data because it can be an invaluable asset — or relatively worthless. Data can be immensely useful in helping the organization move forward or maintain the status quo to keep the lights on. But far too often do nonprofit organizations have access to the right data or proper visibility into data they already can see.
Data can be like pieces of a puzzle, but only form an incomplete picture if there isn’t enough to put together. Nonprofit data collection is important for many reasons, but here’s a look at what data can do for your nonprofit and why reliability is key.
Nonprofit Data Collection Needs By Size
Data seems like something that should only be used by mammoth corporations and organizations, but this just is not the case. Size doesn’t matter, but rather the amount of data varies depending on the size of an organization — data will always have value.
Whether you have the bandwidth to hire individuals whose sole purpose is to analyze data or your nonprofit can only support a smaller team, data still has its purpose. Of course, it would be ideal if there was one person or a dedicated team responsible for nonprofit data collection and analysis, but data management is still achievable with the right tools and strategy.
Even some of the largest nonprofits the world over are embracing their data, so data should never be seen as intimidating. The most important first step is to understand how data is being collected, what types of data are being collected, and what are the issues with poor nonprofit data collection.
Data Nonprofits Collect
Before diving into the finer points of data collection, it’s important to realize what types of data are being collected by nonprofits.
What often first comes to mind for nonprofits is related to internal and financial data such as metrics associated with accounting (expenses, taxes, revenue, etc). These data types alone are crucial for budgeting and making larger organizational decisions.
Outreach efforts are another area with data points about marketing and communications costs, and more importantly, fundraising data. This often includes data stored from various marketing, CRM, and fundraising software and tools. These tools are not only important for fundraising efforts, but they’re also needed to demonstrate the effectiveness of a given outreach campaign or efficiency of the organization as a whole.
In combination with data from third-party sources, such as those from the government or shared data from other nonprofits, there is a whole wealth of knowledge which must be protected but also analyzed. But there are inherent problems with data collection, and that can cause an issue with the quality of your data.
Problems With Collecting Data for Nonprofits
In a recent study by Nonprofit Hub, 90% of nonprofits reported that they are collecting data, but a surprising 49% stated that they don’t know how data is being collected. Not knowing where or how data is being collected can lead to issues with proper analysis and the quality of data being stored.
One issue that comes with a lack of visibility is that the reliability of your data is brought into question. Reliability is the key concept by which data can be used to inform decisions. When data is unreliable, you run the risk of making poor decisions which will only harm the organization in the long-run.
Another glaring problem with data collection is that nonprofits likely work with multiple software solutions, many of which don’t necessarily “play well” with one another. Compatibility can be a major pain point for nonprofit professionals when it comes to managing data. For example, multiple tools and systems may have specific data collected against a specific donor, but if those systems aren’t designed to communicate with each other, the data needs to be pieced together like one gargantuan jigsaw puzzle.
Protecting Sensitive Data
There is a giant elephant in the room when it comes to nonprofits and their data — is that data being protected from malicious third parties?
Some data is just sensitive in nature, and it is the nonprofit’s duty to protect that data if it could be exploited by someone who aims to steal it. Whether it’s personally identifiable information (PII), such as full names and SSNs, or sensitive payment/financial information, this will always be the target of fraudsters and hackers. More specifically for nonprofits, sensitive data also pertains to ensuring consent of data collection.
Protecting user data is becoming more important, particularly after European Parliament passed the EU GDPR, a set of rules which states organizations must provide a reasonable level of protection in regards to user data. While enforcement of these rules pertains mostly to organizations located within the EU, the EU GDPR has essentially become a standard for data protection across the world.
Data collection also impacts how sensitive data is stored, identified, and ultimately protected. Having a data collection strategy and protocol can do a lot to mitigate these potential risks.
For Nonprofit Data Collection, Reliability is Key
To sum up, data can be the ultimate game changer when leveraged correctly. If data is collected and stored the right way, it can help review campaign performance, provide a full view of your donor lifecycle, improve communication, and more importantly, inform critical decision making for the entire organization.
Many nonprofits are collecting data, but most are not doing enough with that data. From the outset, the reliability of your data cannot be stressed enough. If there are limitations or outside factors which are only giving you small bits of the bigger picture, cleaning up your data and collection methods is the first place to start.