Is Statistics a Foreign Language?

Last week’s blog post was a reminder about the Fundraising Effectiveness Project’s annual survey. Titled ‘Giving Metrics and Benchmarks: Something Quick and Easy,’ it was intended to encourage you to take a few simple steps to allow everyone to benefit from the value of our collective fundraising statistics.

But if you’re one of those people who thinks that ‘Metrics’ is that fad from the eighties, and ‘Benchmarks’ are those indentations on the back of your legs after sitting too long at the park, then don’t feel alone. It’s more likely that people in the development field were hired for their compassion and people skills rather than their mathematical abilities.

Yes, I mean math. Because, according to Merriam-Webster, statistics is “a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data.” And judging by the number of inquiries we get, probably not many of us were Stats majors in college. For us, statistics is a foreign language.

It’s pretty common to talk with customers who are just not sure how to actually use all this donor data being gathered, entered and stored in ResultsPlus. And while the collection part of the process may be intuitive, it’s the analysis and interpretation that may be difficult to logic your way through.

To that end, here are some suggestions to get you moving in the right direction. First, take a look at some resources recently made available by the Nonprofit Technology Network (NTEN):

Getting Started With Data-Driven Decision Making: A Workbook – a practical guide to help you start thinking about how to use your data to make strategic decisions.

2012 State of Nonprofit Data Report – a survey focused on how nonprofits use the data they collect.

And the simplest suggestion is to take the advice of my colleague from last week’s blog posting and participate in the FEP process. Even if you decide not to submit it for inclusion in the larger effort, print the report for your own information and use it as a jump start on your data analysis journey. See what it tells you about your data and what it might suggest for your future plans.

It would be great to hear from current FEP participants – how do you use this information to make decisions?