Big Data Is Here to Stay

Big data is here to stay.  The sooner your embrace it the sooner it can help you increase your nonprofit’s sustainability.

Even though it is awkward to be an early adopter, it is always better than being late.  Adopting early has a lower risk of failure than being a late adopter.  In the past, it was prudent to be conservative and wait for the best opportunity to change.  However, the increase in the speed of change means it is now prudent to change as soon as possible.

In its simplest form, big data is the data one needs to analyze trends, predict events, and find patterns.  Big data is especially valuable for assessing human behavior and interactions.

When there is a large quantity of data, the accuracy of the conclusions improves.  However, it is important to keep in mind that large is a relative term.  A small nonprofit with 50 years of history may only have data on a few thousand clients but that maybe more than enough data to draw very useful conclusions.  In addition, at some point very large becomes unnecessary.  All one more data point does is confirm what all of the other data points have already determined.

Imagine looking at your historical data and discovering that your nonprofit is rarely effective when serving children from the south side of town.  A strategic conclusion might be that your organization should stop serving those children.  However, further analysis might point out that only one of the several youth workers is effective serving those children.  Based upon that information you might decide to give the other workers additional training or have the effective worker be the sole server of the south side children.  In this case, the data becomes a valuable operational tool.  As you can see, the data needs to be analyzed in multiple ways before attempting to make a decision.

Examples of big questions that will justify the need for big data:

Is anyone (internally or externally) successfully serving south side youth?

Is there a demographic group of youth on the south side that can be successfully served?

What skills and resources are necessary to be successful on the south side?

Because of the amount of data from a variety of sources that must be processed to find the answers, big data usually requires significant computing resources and talent.  The cost and effort to analyze big data is worth it in the end but the upfront investment can be a challenge for a small organization.

Most nonprofits have more data about their clients, programming, donors, and fundraising than they realize.  In addition, there is an abundance of data available from free sources.  The two missing pieces are the big questions that justify analyzing the big data and the resources to process the data.

Next Step:

Ask your board to allocate funds specifically for big data in the next budget cycle

Create a cross-sectional team (representatives from finance, fundraising, and operations for instance) to determine what big questions to ask, what data is most appropriate, and how the answers to big questions will impact each area

Have the team determine which data sources will be most appropriate for each question

Remind your board that any commitment to big data is a multi-year commitment

It is hard to do anything with data without a budget to support the data gathering, filtering, and analysis.  In addition, someone must have time to formulate the critical questions to be asked of the data, convert the analysis into plans, and determine what data should be used to measure the changes the plan produces.  Therefore, the board must understand the value of analysis and support their understanding through the budgeting process.  Since tracking trends often spans years, the board needs to be prepared to commit to the big data budget for multiple years.  It is hard for a multi-year budget to be successful without a multi-year fundraising plan that includes creating a sustainable funding stream.

Big data can have a big influence on your nonprofit’s sustainability and client services.

Take It Further:

How can your board better use data to derive insights that will help with planning, policy setting, and budgeting?

What cultural changes need to occur to reduce the staff and the board’s dependence on intuition when making decisions?


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