When implemented thoughtfully, data analytics can streamline operations, strengthen impact, and save valuable time and resources over the long run. Unfortunately, many not-for-profit organizations assume this kind of technology-driven approach is out of reach. If that mindset describes your organization, there’s good news: The use of data analytics (and the benefits it brings) is more attainable than it may seem.
Benefits of a data-driven approach
At its core, data analytics involves gathering and examining data to uncover trends, connections and patterns that support smarter decision-making. For not-for-profits of all shapes and sizes, the potential from these data-driven insights is almost endless. They can produce such metrics as program efficacy, outcomes vs. efforts and membership renewal that can reflect past and current performance and, in turn, predict and guide future performance. Data analytics can also help your organization validate trends, uncover root causes and improve transparency. For example, analysis of certain fundraising data makes it easier to target those individuals most likely to contribute to your not-for-profit.
Data analytics typically facilitates fact-based discussions and planning, which is helpful when considering new initiatives or cost-cutting measures that stir political or emotional waters. The ability to predict outcomes can support sensitive programming decisions by considering data on a wide range of factors. These might include at-risk populations, funding restrictions and grantmaker priorities.
Identifying the right tools
Data usually comes from two sources, internal and external. Internal data includes your organization’s databases of detailed information on donors, beneficiaries and members. External data can be obtained from government databases, social media and other organizations. Some basic analytics tools are free or available through non- and for-profit partnerships. But for more sophisticated and powerful functions, your organization may need to spend a little money.
Increasingly, artificial intelligence (AI) is embedded within data analytics tools. AI can help you automate data preparation, surface insights more quickly and make advanced analysis more accessible, even if you have limited staff or technical resources. AI-powered features can reduce the need for manual analysis while enabling your organization to work with larger, more complex datasets.
Your informational needs should dictate your data analytics package. Thousands of potential performance metrics can be produced, but not all of them will be useful. So identify those metrics that matter most to stakeholders and that truly drive decisions. Also, ensure that the technology solution you choose complies with any applicable privacy and security regulations, as well as your organization’s ethical standards.
Seeking appropriate guidance
Whether you’re considering the use of data analytics for the first time or want to enhance your current efforts, the best place to start is within your organization. If any employees or board members have experience in data analytics, begin by drawing on their knowledge. If there’s little or no such experience internally, consider consulting with data professionals who can help you determine the best approach. Contact us for recommendations.
