Know What Your Data Really Tells You in 1 Minute

If you ever wonder how to tell the story of your impact using data, this article is for you.


We typically collect data for two reasons. We either try to assess the situation or try to uncover the cause of it.


Some examples of data that describe a situation (hence the term "descriptive data) include:


The number of clients grew by 20% in the past quarter.

Black men make up a disproportionate percentage of the incarcerated population.

Minority employees consistently represent less than 3% of your workforce.


Descriptive data tells you what the situation is, but it does not tell you what has caused it. To find out the cause, you now need to choose between inductive and deductive research, corresponding to qualitative research and quantitative research, respectively.


In a nutshell, which one to choose depends on how much you know about the possible causes. If you have an "informed guess" of several possible causes and are interested in finding out the impact of each on the outcomes, you should choose quantitative research to test your hypothesis. If you don't know enough to form an informed guess, or if you want to find out whether you're missing anything important, go with qualitative research to find out what the possible causes are.


To read more about the differences between quantitative and qualitative research, click here to read my article A Decision Maker's Guide to Choose Between Qualitative Research and Quantitative Research.


Key Takeaway:


Descriptive data can help you assess the situation but does not tell you what is causing it. In order to find out the causes, you need to choose between qualitative and quantitative research, depending on how much information you have.