Why You Should Collect Data from Volunteers

Guest post by Roslyn Tate

Reasons to collect volunteer dataPerformance management, or the process of improving organizational efficiency through setting goals, measuring progress and acting on insights, is so fundamentally ingrained in our modern idea of business that it hardly seems worth calling out. For certainty’s sake, though, let’s use a simplified example to illustrate the concept:

In reviewing the hourly sales records for consecutive weeks, the new owner of a fast food restaurant discovers that Saturday afternoon sales followed a sharp rise before plateauing. Typically not at the restaurant during those hours, the owner consults the shift manager who explains that, as little league season has returned and a baseball field is just across the street from the restaurant, there have been more customers than normal coming in on Saturday afternoons.

At first this was a welcomed boon, but the employees were soon overwhelmed, wait times grew longer and eventually customers started turning elsewhere. In order to capitalize on this opportunity, the owner assigns another employee to the Saturday afternoon shift and sets a reward for the entire team: each percentage point increase in sales will earn the employees a percent bonus. The owner awaits the sales records of the upcoming weeks, eager to see if his plan will bear fruit.

Simple idea, right? Catch a pattern emerging, investigate its causes, leverage that knowledge into a strategy, track the results and repeat ad infinitum to improve incrementally but continuously.

What you may not realize is that performance management applies equally as well to volunteer organizations as it does to businesses. While increasing sales may not be a volunteer organization’s goal, performance management can still improve the organization’s efficiency. Take canvassing volunteers, the front lines of many non-profits: tracking simple data points, like the day of the week, the time of day and whether or not residents are home, can help a volunteer manager direct volunteers to where they will be most successful. It all starts with data – the right kinds of data, collected appropriately and leveraged effectively.

The Right Kinds of Data

Because of the diverse goals and methods of volunteer organizations, it’s impossible to suggest specific types of data that all of them should collect. That said, let’s try to generalize!

Volunteers enlist, serve with the organization, and eventually resign. These are three distinct phases, each accompanied by particular relevant data points. While all three phases are probably worth tracking to some extent, the limited hours in the day require us to prioritize, so focus should be honed as necessary. Need more volunteers? Track their entrances. Want to improve volunteers’ performance? Track their actions. Looking to reduce volunteer turnover? Track their exits.

As mentioned, the specifics of these details will be particular to each volunteer organization, but let’s consider a few examples:

  • One way that People for the Ethical Treatment of Animals (PETA) asks volunteers to invest their time is through letter-writing. If PETA were looking to shore up its corps of letter-writers, a good data point to start tracking would be how new volunteers are hearing about the opportunity in the first place.
  • The American Red Cross relies on volunteers to do everything from raising money to delivering emergency supplies, but the organization was widely criticized for its response to Hurricane Sandy. Did this discourage volunteers so thoroughly that they quit? The only way to tell is to track.

Collecting Your Data

After the relevant data points have been identified, the next step is actually collecting that information. As with the kinds of data that can be pertinent, the methods of gathering information are diverse. Solutions can be as technical as using cookies to track how volunteers are reaching your online sign-up page or as low-tech as a paper survey that volunteers complete as part of their exit interview. What’s central is matching your methods to your means. If all you need to know is why your team of 10 is losing half of its volunteers in two weeks, five printed surveys will probably be a better fit than an survey app you build from scratch.

Another consideration is the standardization of data, which is particularly important if you’re collecting large amounts of information. If you’re only interested in why a handful of volunteers left over the last month, it might be fine to have them complete a written survey with open-ended questions. But if you’re interested in why 10,000 volunteers left over the last 10 years, it will be a lot easier to aggregate that information with multiple-choice questions on a digital survey.

Leveraging Your Data

All right, you identified the data you needed, then you went out and collected it in a standardized form. Now what?

Aggregate it, analyze it, then strategize, that’s what! Aggregating could be as simple as tallying the results of a few dozen paper surveys to as complex as ciphering through millions of bits of digitized information. Analysis follows the same lines: parsing through information yourself looking for trends or using computing power to process large amounts of data. If the trends are simple and obvious enough, you should be able to come up with strategies to capitalize on them, like the aforementioned example of having volunteers canvas neighborhoods when you know residents will be home. Larger amounts of more complex data may be more difficult to tease insights out of, requiring greater manipulation before they reveal their secrets.

If this sounds like a lot, that’s because, admittedly, it can be. Identifying, collecting and analyzing data can get so complex that there’s an entire burgeoning field of academia related to it called Data Science. Thankfully this also means that there are professionals out there who can help you with your data needs. If you find yourself overwhelmed, considering enlisting the aid of a Data Scientist, perhaps as a pro bono volunteer! As an alternative, if you feel your volunteer organization could make greater use of data on a day to day basis, consider pursuing a Master’s in Data Science. It may just be what your organization and your career needs to get to the next level.

About the author: 
Roslyn Tate is an editor on the 2U Inc. website. A recent Goddard College MFA, she enjoys helping people achieve their goals through academics and art. 2U partners with leading colleges and universities to offer online master’s degree programs to students around the world.