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The Meaningless Volunteer Metrics We’re All Collecting and What to Do About Them

Updated: Feb 18, 2020

Photo by Franki Chamaki on Unsplash

Social Impact professionals (non-profit and Corporate Social Responsibility) must excel beyond collecting metrics that only communicate how many people did something and how long they spent doing it. Failing to do so is detrimental to the culture of volunteerism. It contributes to a disconnect that undermines the true value of those who volunteer and those who engage them in service.

I believe this to be true in both the non-profit sector and in Corporate Social Responsibility (CSR).

As you continue reading, you'll discover how I arrived at this conclusion and what we must do to fix it.

I was recently asked by a peer in CSR what my favorite metrics are when tracking volunteers. There’s just one catch. These metrics couldn’t include the number of volunteers or the number of hours served.

Truthfully, neither of those even come close to being my favorite to begin with. But, after careful thought, I replied. My favorite metrics are those that exist together or when paired together tell a full story of impact.

I’ll add that any meaningful metrics about volunteering won’t really be about the action of volunteering itself. Rather, it’ll be those related to the achieved outcomes resulting from the act of volunteering.

You see, volunteering is an action. It’s something you spend time and energy doing. It’s a driver of outcomes. In only a few occasions can it actually be considered an outcome itself. Just bear with me for one second, I’ll break this down for you.

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We’re wrapped around the axle about the wrong numbers.

You’ve seen this time after time, a non-profit organization or for-profit company’s CSR program stating in their annual report that they’ve engaged x-number of volunteers who served x-number hours.

In both instances these entities are collecting some variation or combination of the following;

  • Number of volunteers engaged

  • Number of hours served by volunteers

  • Percentage of increased engagement

  • Percentage of increased hours from year to year

  • Percentage or number of hours that may be specific to skills-based volunteerism

  • Percentage or number of hours spent supporting specific communities or causes

There’s just one problem. That data (alone) doesn’t tell you if there was a positive or negative change in society as a result of said actions.

Additionally, some of those metrics might be better for your internal tracking, versus those shared publicly. This may be the case if you collect demographics (i.e. Age, Gender, Race, Occupation, Education Level). Sure, you may wish to track demographics so you’re better informed about you who is or isn’t volunteering. Collecting demographics may allow you to better segment any communication to specific populations. But that’s as far as it’ll get you.

Then there are metrics that might be more appropriate for the public. This information may include the number of hours or percentage of hours served for a specific community or cause. But they all share a common theme.

They can’t stand alone. They only tell half the story.

At best, they tell you how long people spent doing stuff. That’s it. By itself it’s useless.

Yet, we collect them and expect they stand alone. When really, few people actually care about how much time people spent doing stuff without knowing the end result or outcome.

Photo by William Iven on Unsplash

We must make data related to volunteerism meaningful. Here’s how.

I’ll go back to the original question. What are my favorite metrics when tracking volunteerism? My answer, metrics that when paired together tell you a full story. Keep reading, I’ll explain what I mean.

Let’s say two people were tasked with planting one tree each. We’ll say it took each person three hours to plant their tree. This is how the story would be told If tracking only the number of volunteers and hours.

  • Story #1: 2 volunteers served a total of 6 hours.

After reading Story #1 you’re left asking, so what?

Now, let’s imagine the same two people were charged with the same task the following year. Planting one tree each. But because of learning curve it took those same two people half the time. The story would now look like this.

  • Story #2: 2 volunteers served a total of 3 hours.

Sadly though, this is where most non-profits and CSR programs stop when tracking volunteer metrics.

To me, this is enough information to give you one-third of the full picture. But it’s very misleading. Here’s why.

By itself and without knowing how many trees were planted, one might assume the act of volunteering is declining. If basing that on hours served alone, you’d be correct. You may even assume that the two volunteers are becoming less giving as people. But if you add the number of trees planted to the story it allows for a more accurate assessment to be formed. When you add the number of trees planted, the story evolves into the following.

  • Story #3: In the first year, 2 volunteers served a total of 6 hours and planted 2 trees. The following year, the same 2 volunteers served a total of 3 hours and planted 2 trees.

Suddenly this becomes what I call two-thirds of the full picture. Story #3 demonstrates the volunteers are becoming more efficient with the time they give. That’s a good thing. However, before the number of trees planted was known, the information can easily be misrepresented. Without knowing the number of trees, you may form a negative assessment that would lead others to believe the two volunteers are simply volunteering less.

And truthfully, in Story #3 I care less about them volunteering fewer hours, because they’re achieving the same result with less energy.

Still with me? Good, because there’s more.

That’s still only two-thirds of the full picture. You’ll want to capture that final one-third to make it complete. I’m talking about the outcome. More specifically what planting the two trees achieved.

Let’s say with each tree planted it reduced the overall greenhouse gases by x-amount each year. If you can calculate the pounds of carbon dioxide a mature tree consumes per year, then you can attribute that outcome (reducing your carbon footprint) to your volunteer action. It would then look like the below story.

  • Story #4: In the second year, 2 volunteers served a total of 3 hours and planted 2 trees which resulted in x-amount of carbon being consumed annually (by trees), thus reducing the carbon footprint by x-amount over the given period of time.

Suddenly, the number of volunteers and hours served are connected to outcomes that people care about. They’re now meaningful.

Here’s the point. The metrics specifically related to the act of volunteerism (i.e. number of volunteers and hours served) is only a part of the story. It’s often the least useful in my opinion. In order to get metrics that are meaningful they must tell a full story. So, we must be careful in how we use metrics that (by themselves) could be misleading.

We must graduate from collecting only those metrics that communicate how many people did something and how long they spent doing it (Story #1). An inability to do so contributes to a disconnect resulting in the undervaluing of volunteerism.

It sends the wrong signals about the real worth of volunteers and the networks that engage them.

For metrics to be meaningful, they must be paired with end results.

Photo by Bluehouse Skis on Unsplash

How we change this.

Three fundamental shifts must take place.

For one, there needs to be a change in thinking by those managing complex social impact programs (non-profit and CSR alike). We must rise to the challenge and strive to collect more outcome-based data. For non-profit volunteer engagement professionals this means working directly with your program managers to collect that data. For those of you in CSR this means holding your non-profit partners accountable while seeking that information at every reasonable opportunity. The outcomes you’re seeking to attribute to your corporate employee volunteer program rests with your non-profit partners in the community.

Secondly, be bold and courageous. Choose to set outcome-focused external goals that are available to the public. Beyond number of volunteers and hours served, we must aim to set goals that are based on measurable social and environmental changes. Sure, we can still tout x-number of volunteers being engaged, but we must also collect the associated outcome, so the action of volunteering is attributed to something meaningful. Also, notice I say external goals.

I say this because accountability is often followed by greater achievements.

Creating external goals will help motivate your organization or company to move more quickly, while also supporting the reputational health as progress is made.

Lastly, I recognize such changes aren’t realistic without the means. This requires resources. More specifically a data-collection plan and a capable platform that enables.

We must be equipped with data-collection platforms capable of collecting, tracking and reporting the type of metrics discussed. While many platforms can collect simple metrics (i.e. number of volunteers, hours served), connecting outcomes attributed to the action of volunteering has been elusive for many technology companies. Some have met this challenge, but many need to step it up. After all, there are many unique characteristics of each non-profit or CSR program that exist.

What it means is that we must be judicious when selecting a platform, as all platforms are not created equally.

As customers (or potential customers) seeking data platforms, we must also demand these changes of the companies that develop them. These modifications won’t be made unless the sector (non-profit and CSR alike) ask for them. It comes down to supply and demand. Period.

At the end of the day, all the changes suggested are realistic and rest with those in the Social Impact space. Have a differing opinion on the matter? Let me know, we should have that discussion.

If you agree but don’t know where to start, reach out, I’m happy to be of service. Alternatively, if you have a suggestion that has worked for you, leave a comment or send me a note, I’d love to hear from you.

Until next time, keep it Responsible AF.

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