Data on any one thing isn’t that interesting. You might know the ages of all the participants in a program or the average grant amounts for a group of foundations. But that doesn’t really tell you anything until you look at that data in relationship to something else. That “something else” usually falls into these categories: time, other data, space, rank, or networks.
Time. Is participation now greater or less than in the past? To see this, you need a line chart with some measure of time, such as each month of a year, along the horizontal (aka X) axis and number of participants along the vertical (aka Y) axis. Each point shows how many people participated in a given month. Connecting the dots gives you a slope, which instantly shows you whether participation is increasing, decreasing, or varying over time.
Other data. You might want to know how participation relates to other data you have on participants. For example, are the ages of participants related to their satisfaction with your program (as reported on a survey)? In this case, you could use a scatter plot with satisfaction scores along the vertical axis and age along the horizontal axes. Each dot shows the age and satisfaction of a single participant. If the dots suggest a rough increasing slope, then older participants are often more satisfied with your program than younger ones. You might then color dots representing females red and those representing males as blue to see if and how gender relates to the age and satisfaction of participants.
Space. To show where participants live in relation to each other and to your organization, participant dots can be placed on a map. If you size the dots to show another factor, such as income, then you have a bubble map.
Rank. These types of charts show your data in relationship to a scale that indicates importance, prevalence, or some other metric. Perhaps the most common type of chart in this category is the tree diagram, which is often used to show reporting relationships among staff in an organizational chart. You might use it to show the educational institutions of participants in your program, starting with school districts at the top, individual schools in the middle, and classrooms at the bottom.
Networks. In network visuals, the relationships among individuals, groups, things, concepts, etc., are shown using connecting lines. For example, you might visualize participants as dots and the connecting lines show what other participants they referred to your program. In this way, you can quickly distinguish frequent referrers from infrequent ones.
See other data tips in this series for more information on how to effectively visualize and make good use of your organization's data.