In today’s technologically advanced world, data rules. But simply having highly relevant information will be of little use if your board of directors, management and staff don’t know what to do with it.

So how can your organization harness the power of data? You can use it in day-to-day decision making and strategic planning, of course. But you can also use data to provide your stakeholders, donors and volunteers with up-to-date information about your fundraising, programming and outreach.

What is it?

Data analytics is the science of collecting and analyzing sets of data to develop useful insights, connections and patterns that can lead to more informed decision making. It produces metrics — for example, outcomes vs. efforts, program efficacy and membership renewal — that can reflect past and current performance. And that information, in turn, can predict and guide future performance. The data analytics process incorporates statistics, computer programming and operations research.

Data can come from both internal and external sources. Internal sources include your organization’s databases of detailed information on donors, beneficiaries or members. External data may be obtained from government databases, social media and other organizations, both nonprofit and for-profit.

What are the advantages?

There are several potential advantages of data analytics for nonprofits. The process can help an organization:

  • Validate trends,
  • Uncover root causes of problems, and
  • Take a holistic view of performance.

Done right, data analytics allows management to zero in on your organization’s primary objectives and improve performance in a cost-efficient way.

For example, data analytics can serve a dual purpose when it comes to fundraising. First, it may provide a way to illustrate accomplishments for potential donors who demand evidence of program effectiveness. And second, analysis of certain data may make it easier to target those individuals most likely to contribute.

Initiatives to streamline operations or cut costs have the potential to stir up political or emotional waters, but data analytics facilitates fact-based discussions and planning. The ability to predict outcomes, for example, can support sensitive programming decisions by considering data from various perspectives, such as at-risk populations; funding restrictions; past financial and operational performance; offerings available from other organizations; and grant-maker priorities.

What should be considered before purchasing?

Excited about data analytics? If so, it’s important not to put the cart before the horse by purchasing costly data analytics software and then trying to decide how to use the information it produces.

While new technology may be a good idea, your organization’s informational needs should dictate what you buy. Thousands of potential performance metrics can be produced. That means you must take time to determine which financial and operational metrics you want to track, now and down the road. Which of your nonprofit’s programs are the most important? Which metrics matter most to stakeholders and can truly drive decisions? How can you actually use the information?

You also need to ensure that the technology solution you choose complies with any applicable privacy and security regulations, as well as your organization’s ethical standards. Security considerations are particularly important if you opt for a solution that resides in the cloud, rather than installed software.

Additionally, you should determine how well the technology solutions you’re considering can integrate with your other applications and data. If software can’t access or process vital data, it likely will be a poor investment.

Organization buy-in

It may be a good time to get started on a full program, or to revisit your current use of data and metrics. But remember, having a data analytics program is only as good as the people who use it. If your leadership and staff don’t understand how to use it, that’s money wasted. Take the time to educate everyone about the capabilities of data analytics and follow up to be sure it’s being used effectively.