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Charities Who Wish to Save Money on Data Analytics are Looking in the Wrong Direction


A recent Computer Weekly article discussed charitable organizations and the way that they are exploring the use of big data analytics to try to solve pressing problems. However, like many organizations charities may be confused about exactly what is necessary to reap the benefits of these powerful problem-solving tools.

The article focused on data scientists and advanced responsive custom website programs such as the ones employed by Amazon and Netflix. It even talked about an organization called Data Kind which encourages data scientists to donate their time to charity, since charitable organizations do not usually have enough money to hire data scientists, nor do they have enough money for advanced software packages.

Without denigrating the contributions of any data scientist who chooses to so donate his time it’s worth noting that most charities simply do not need those kinds of capabilities and could approach this problem in another way.

There are many ways that data analytics could benefit any charity. It could help each charity marshal its resources in a more effective way. Charities are, after all, under enormous pressure to avoid wasting donor money, to do more with less, and to effectively solicit the donations that their organizations rely upon.

Charities could use predictive analytics to incrementally improve the performance of direct mail campaigns, increasing donor response and total revenue raised. Analytics can do the same for online donation campaigns. A good analytics project could also help charities identify which of their programs and activities ultimately do the most to forward the organization’s mission.

They can do all of this without expensive programs and without data scientists. Data scientists may even become a detriment to creating the projects that could offer these sorts of very real gains. That’s because data scientists tend to be focused on creating algorithms and processes. Most charities need people who are focused on solving problems instead.

That means that most charities will get massive gains by turning to an in-house staffer who truly understands the charity, its mission, the problems it faces, and the day-to-day operations of the organization. They can also make incredible gains by employing open source (free) software or commonly used, inexpensive programs like MS Excel.

That in-house staffer could be given seminar training which will teach him or her how to use the data to make better decisions about the organization and its resources.

What’s the difference between the expensive, often-unavailable data scientist and this specially trained in-house staffer?

A data scientist is someone who builds and tunes pianos. That’s useful if you desperately need to design or fix a piano.

But most organizations don’t need to build a better piano, nor do they even need to repair an existing piano. Most organizations need someone who can actually play that piano. Without a piano player it is tough to derive any benefit from having a piano. It may be a gleaming piece of beautiful workmanship, but it’s not producing any music.

There is a widespread failure to understand the difference between the two types of specialists, and that failure leads to data mining projects that just don’t accomplish anything. Charities may well find themselves wasting even more money as a result.

Interested in further exploring this and other common data mining problems? It’s not too late to sign up for the next installment of TMA’s free webinar: Data Mining, Failure to Launch, a webinar which will give you all of the tools that you need to make big data analytics a truly useful tool for your organization.

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