As noted in the Strong Roots story, over the span of my career I have found myself working in different fields – ranging from youth development to disability research to immigration – but throughout I have always kept a soft spot for cities, and more specifically, their neighbourhoods. Fortunately, I have been able to combine my passion for things urban with my career through work and volunteer opportunities, starting with my first job in the area of community development and community-based research. The summer after my first year in grad school, the community association for the neighbourhood I lived in received funds from the municipal government to hire summer students to support their work through preparing grants, investigating potential structures for their organization, and assisting with outreach and community research (hmm, sounds a lot like the services I provide today!).
Working with this group of committed volunteers was inspiring in many ways, but three lessons come to mind today:
Volunteers are an important piece of the puzzle for any non-profit organization. Whether they’re contributing to programs and special events, helping out with fundraising and outreach, or providing guidance and leadership as members of the board, good volunteers are indispensable. As these individuals are giving their time and effort without compensation (at least of the financial kind), organizations are increasingly recognizing that they can’t take these superstars for granted.
Along those lines, this week’s entry in the Seeds for Thought category is a case study from the Stanford Social Innovation Review on volunteer retention for Girls Scouts of Northern California (GSNorCal). Like many other nonprofits focused on youth development, GSNorCal relies heavily on volunteers and as a result already uses many best practices in orientation, training, and recognition: however, broader changes within and outside of the organization has made it difficult to keep volunteers returning. In response, the organization hired a consultant, TCC Group, to “mine its data and pinpoint ways to keep volunteers engaged”. Through a survey of 1,371 current and past volunteers and follow-up focus groups, TCC Group identified factors that predicted volunteer retention and suggested improvements to GSNorCal’s practices.
This example demonstrates the value in using multiple sources of information, in this case quantitative data from a large survey, qualitative insights from small groups of volunteers, and general principles from scholarly research on the topic. If you don’t have the resources that GSNorCal (or even if you do) and want to learn more about your volunteers, what can you do?
- Start by counting. How many volunteers do you currently have, how long have they been volunteering, how many new volunteers have come onboard recently and how many have left? How many hours are they contributing? Are there differences in these numbers based on demographic factors or what tasks they’re doing for your organization?
- Use some simple questionnaires with both current and former volunteers. I could spend a full post or three on what a volunteer questionnaire could look like, but at the very least it should include questions around overall satisfaction, support from the organization (or lack thereof) and what keeps them volunteering and what makes them leave. Just remember to use a mix of question types and watch out for potentially misleading numbers.
- Take a participatory approach. Include volunteers in the discussion, both long-time contributors and those who are new or in a temporary position, such as through a World Cafe: as a bonus, this approach can help improve retention by demonstrating to volunteers that their opinion is valued by the organization. Another idea – have a staff member step into the shoes of a volunteer for a shift to get a firsthand perspective!
- Partner with organizations that can provide a broader view. Many cities have a volunteer centre (either standalone or part of a larger organization like the United Way) or a professional association of volunteer administrators such as PAVRO liaisons in Ontario that can link you with resources on volunteering and keep you in the loop about new developments in the field. Volunteerism is also becoming increasingly recognized as a topic of scholarly research, so look into partnerships with universities: programs related to community development, organizational studies, public policy, and even business are good starting points.
- A bit of self-interest here: consultants can help! If resources are tight, use consulting expertise for specific tasks that may be impractical to do in-house, such as analyzing complex statistical data or acting as a neutral party to collect feedback (current and even former volunteers may be hesitant to provide criticism directly to staff). Volunteer management, especially as it relates to research and evaluation, is one of Strong Roots’ strengths, so drop us a line if you want to have a chat about how to learn more about your volunteers!
Question: What are some strategies that you have seen successfully used to engage volunteers and improve retention?
In response to my post last week on open-ended questionnaires, Sheila Robinson over at Evaluspheric Perceptions explored some of the risks in interpreting this type of data. Without a systematic approach to analyzing qualitative data, we can fall prey to confirmation bias, which as described in her post, “causes us to remember or focus on that with which we agree, or that which matches our internalized frameworks, understandings, or hypotheses”. Another risk is that we pay too much attention to extreme viewpoints, whether positive or negative, because they are more likely to be remembered. Check out Sheila’s post for more thoughts!
One question that I want to address quickly is what to do if you have collected some data from an open-ended survey and want to avoid these pitfalls, but don’t know where to begin? As with evaluation in general, one of the simplest starting points is counting. Read through all the responses and keep a running tally of how often certain ideas come up. You may already have some ideas in mind for how to categorize responses, which will help in sorting but could leave you open to confirmation bias: take care that you’re not trying to fit a square-shaped response into your round category! If you come across strong or extreme comments, make sure you view it in relation to general trends (having complementary numerical data helps here!) to determine how representative that position is: that’s not to say that you should ignore a point raised by a small number of people, but as in the example raised by Sheila in her post, you don’t need to rush and make sweeping changes to something that’s working for the vast majority of respondents.
If there’s interest, I can share an extended example from my first experience with qualitative analysis – food for a future post!
During the span of a week, I come across lots of interesting stories, resources, and sites online that may be of interest to those in the non-profit-sector. In line with my approach of connecting people with resources and sharing information, I’m thinking about starting a weekly feature to highlight some of those links – consider this the pilot edition!
This week, I’m highlighting a trio of posts from the Harvard Business Review’s Blog Network, a site I recently started following. Although the focus is primarily on for-profit organizations, I’ve already seen content on social enterprises, philanthropy, and international development, as well as resources and trends that would be equally applicable on the non-profit side.
All three articles below relate to managing and using data, particularly “Big Data”. The term recognizes that collectively we are producing and storing exponentially-greater amounts of data in recent years than at any other point in human history – the first article cites research that 90% of data currently in existence was created in the past two years! This explosion in information can help grow our understanding of practically every facet of life, but there are challenges in analyzing and interpretating these giant data sources as well as limits to how much we can learn from them.
- Jeff Bladt and Bob Filbin’s article title says it all – A Data Scientist’s Real Job: Storytelling. It’s similar to a truism I learned from a great professor during my undergraduate education, that all research projects have to tell a story: we start at some point of knowledge, we run an experiment or collect some information, and we learn something as a result. Tables of numbers and statistical tests are essential tools, but by themselves they do not advance our knowledge. As Bladt and Filbin put it, “Data gives you the what, but humans know the why“.
- Presenting data in an accurate, easily-comprehensible visual form has become a field in its own right. If you’re not sure where to start in sharing information, Nancy Durante gives a simple suggestion: When Presenting Your Data, Get to the Point Fast. Check her post for some good tips on how to help your audience focus on the key numbers (hint: tables of numbers and pie charts are not in the cards!).
- Finally, Kate Crawford explores The Hidden Biases in Big Data. Even databases with millions of records may not cover the full spectrum of a phenomenon: Crawford gives the example of the 20 million tweets generated during Hurricane Sandy, the majority of which came from tech-connected Manhattan compared to harder-hit neighbourhoods. Her prescription? “Take a page from social scientists”: pay attention to where the data comes from, examine your cognitive biases in interpreting the data, and utilize a diverse range of methods including qualitative approaches like interviews to complement the quanatitative data findings.
If you have any thoughts or additional links to share on this topic, I’d love to see them! You can use the comments field below or find me on Twitter. Also, any feedback or suggestions on this approach of weekly annotated links would be greatly appreciated.
While on Facebook earlier today (I was connecting with some colleagues on a work-related issue, honest!), I came across a survey for a local non-profit initiative. As someone who both identifies as a researcher and generally likes filling out surveys, I eagerly clicked the link … and found myself looking at ten open-ended, fill-in-the-blank questions.
Now, I don’t have anything against this style of question: indeed, as I noted in an earlier post, it’s good to provide space for respondents to share their own perspectives and stories without being boxed into a particular set of responses. In my opinion, though, inviting only written responses is a move too far in the other direction. Some respondents may not have the time to write down their thoughts, while others may feel pressured to provide insightful, well-crafted responses to each question and decide to take a pass on the survey as a result. I remember a conversation with a community group where one member personally disliked open-ended questions: this person’s view was perhaps a bit extreme, but it brings up the good point that individuals may simply have preferences for one question type over another. Accessibility is also a potential concern: will people who have low literacy skills or other challenges around writing feel comfortable participating? A final consideration is analyzing this type of data, which takes more time and effort compared to compiling statistics from multiple choice or rating questions.
Again, I have nothing against open-ended questions: depending on the intended audience and purpose of the survey, it may even be completely appropriate to only use that type of response. For most general surveys, though, a little bit of variety is probably a good thing.