JULY 7, 2017
We know, gathering data can be expensive in terms of time and focus, and in all likelihood, you already have too much on your plate. So why invest in understanding the problem with such rigor?
First: because for your program to be effective, you must base your program design in reality. You cannot assume that you know the community you are serving without compiling real data from credible sources. Making the wrong assumptions can lead you to design an ineffective intervention; you don’t want to end up 2,000 away from your destination because you started down the wrong path.
Second, because being a credible spokesperson is essential to garnering support. A nuanced understanding of the problem gives you credibility when talking to potential funders, partners, and constituents – and that credibility only strengthens your cultivation efforts.
Once you’ve done the research necessary to develop a thorough understanding of the problem you’re working to solve, your next task to is to collect and present the right data to convey the need with urgency and clarity. There are two types of evidence you’ll need to leverage to explain the problem: qualitative and quantitative.
Quantitative information focuses on numerical data and analysis; it helps you define your problem in the language that decision makers typically understand and care about – from demographic statistics to changes in survey data to estimated costs. Qualitative evidence, on the other hand, focuses on the experience of individuals and their stories. They give life to your work.
Some supporters will be particularly moved by stories in a way they are not by numbers, while others assign more value to data and statistics; to cover your bases and present the strongest case possible, use a balance of both to provide the full picture of the importance of your work.
As you begin crafting your argument using the data you’ve gathered, be aware that using circular reasoning is an easy trap to fall into and one that will weaken your case substantially. Circular reasoning is a logical fallacy in which the writer or speaker begins their argument with the assumption that what they’re trying to prove is already true. Circular reasoning often takes the form: “A is true because of B; B is true because of A.”
For example, the argument “You should let me stay out until 10pm because I deserve to have a later curfew” is circular in nature.
While this type of flawed reasoning can sound convincing and even be difficult to detect, it is unlikely to persuade those who do not already believe in the validity of your argument. For this reason, your need statement cannot be that “the community lacks a park, and therefore it needs a park.” Instead, using a blend of quantitative and qualitative data to illustrate the benefits of community parks, the obstacles in accessing the nearest existing park, and/or the urgency of adding a park in the community you serve would make a much more effective argument,
Finally, we know that one of the biggest challenges in gather quality, credible data is knowing where to look. The following are reliable sources for gathering quantitative data to support your case and help you craft your argument:
Also, the Association for Research on Nonprofits and Voluntary Action connects individuals in the sector who are interested in research; and the International Society for Third-Sector Research promotes research and education for the nonprofit sector.
The content in this blog post is a great introduction to what we cover in our workshops, all of which are designed specifically for nonprofit professionals. We design our trainings to be hands-on, interactive, and efficient — all to make sure you get the most out of your time and walk away with practical skills you can put into use immediately.
See the full schedule of our upcoming trainings to learn more and register today. We hope to see you at a workshop soon!