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  • Ryan Brooks

Measuring Nonprofit Success is Hard. Part 1

Updated: Jan 29

Exploring the Metrics of Nonprofit Success: An Introduction


In a previous article, we discussed the what and how much approach to measuring your nonprofit's services and achievements. By tracking your nonprofit's key outputs and outcomes, along with participant demographics, you can begin to demonstrate that your work matters.


The number of outputs or outcomes that your program delivers is a key indicator of the scale of your program and its success. But, raw numbers only give you one perspective on whether your organization is doing well or improving over time, and you need additional information to get a more complete picture. Success rates and cost per outcome are two simple yet critical measures to improve your understanding of your nonprofit's effectiveness.

Counting Outcomes is a Good Starting Place


Counting outcomes is a great way to understand the impact of your work. Outcomes represent meaningful successes that your organization achieves, and many nonprofits continually strive to do more.


We will use a simple scenario of two job training programs and try to determine which one is better.


Program 1: 100 adults obtained full time employment last year.

Program 2: 50 adults obtained full time employment last year.


Table 1: Comparing the Number of Adults Obtaining Full-Time Employment by Job By Job Training Program.

Program 1

Program 2

Adults Obtaining FT Employment (n)

100

50

Conclusion: The raw numbers say that Program 1 has twice as many successes as Program 2, so Program 1 is clearly better. Our work here is done. Time for lunch.


Wait! We don’t know nearly enough to make that claim. Hold off on the chips and guacamole.


Success Rates Can Tell A Different Story - Program Efficiency.


Success rates can show us how efficient a program is. In other words, it can tell us how likely the program is to produce a successful outcome. For example, if Program A helps 90% of their participants obtain full-time employment and Program B helps 50% of their participants obtain full-time employment, then Program A is clearly more efficient.


Continuing our Example

Program 1: 100 adults obtained full time employment last year out of 300 adults who participated the program


Program 2: 50 adults obtained full time employment last year out of 75 adults who participated in the program.


Table 2: Comparing Participants, Employment Obtained, and Success Rates by Job Training Program.

Program 1

Program 2

Adults Participating in Job Program (n)

300

​75

Adults Obtaining FT Employment (n)

100

50

Adults Obtaining FT Employment Success Rate

33.3%

66.7%

Success Rate Calculated by : Number of Adults Obtaining Full Time Employment / Number of Adults Completing Job Training Program X 100. Ex: 100 Obtained Employment / 300 Completing Program X 100 = 33.3%


Conclusion: Program 2 has a better success rate. Program 2 wins! There's a great taco truck right around the corner. Let's go!


Sorry, friend. We aren’t done just yet.


Cost Per Successful Outcome


So, we know the relative success rates (i.e. efficiency) of these programs, but we have no idea how much the programs cost. If Program 2 costs $100 per participant and Program 1 costs $5 per participant, then that might explain why their success rates are so different. And, that could certainly change our perception of the programs.


We should use great care when calculating the cost per successful outcome & using the value for program design decisions. Many programs have multiple outcomes. For example, a job training program might have outcomes data on achieving a full time job The easiest way to navigate this is to identify the most important outcome your program achieves (i.e. a north star) and use that outcome in your cost-per-outcome calculation. There are more complex alternatives, such as developing weighted averages for outcomes to make a single outcome value, but these are significantly more work and might not provide better information for decision making.


Back To Our Example

Program 1: $500 per participant.


Program 2: $1,250 per participant.


Table 3: Comparing the Cost Per Participant and Cost Per Outcome

Program 1

Program 2

Adults Participating in Job Program (n)

300

75

Adults Obtaining FT Employment (n)

100

50

Cost Per Participant ($)

$500

$1,250

Cost Per Outcome ($)

$1,500

$1,875

Cost Per outcome Calculated by Number of Participants X Cost Per Participant / Number of Successes. Ex Program 1: (300 participants X $500) / 100 outcomes = $1,500


Conclusion: So, program 1 is looking better again. Please let me eat one chip. I just really like salt.


Let’s step back to look at everything at once, then I'll buy us the extra large guacamole.


Table 4: Comparing Total Outcome Successes, Success Rate, and Cost Per Adult

​Program 1

Program 2

Adults Obtaining FT Employment (n)

100

50

Adults Obtaining FT Employment Success Rate

33.3%

66.7%

Cost Per Outcome ($)

$1,500

$1,875

Conclusion: Overall, Program 1 is looking pretty good. It’s winning more of these head-to-head comparisons, so it must be better. Right?


Maybe so, but that’s not really the point.


Well what is the point then?!?!


Measuring Nonprofit Success is Hard, And It’s Worth Doing


The point is that we should use multiple metrics to evaluate how well our own programs are doing compared to how well we expect them to do. Using additional metrics provides us a more complete picture of the effectiveness and efficiency of our programs. We want to know if we are helping more (or fewer) people every year, and we also want to know if we are doing a better job helping each person we encounter.


Success rates and cost per outcome are a great starting place to move beyond raw counts of outputs and outcomes. Of course, your organization can create additional metrics that indicate success toward your purpose.


Some Words of Caution


Even with these richer metrics we need to draw conclusions with care. Numerous factors determine the efficiency of a program including the quality of the program, the characteristics of participants, the environment they in which they work, and more.


For example, let's pretend that Program 1 focuses on people with at least a HS education while Program 2 is open to anyone. Program 1 could have better metrics than Program 2 because they are serving different populations- even if they offer identical services delivered by the same staff members.


In addition, nonprofits can't make decisions based on metrics alone. Most organizations will want to push success rates closer to 100 percent. However, it's important to make changes that are consistent with your mission and values. For example, if Program 1 decides to prioritize people who have excellent work histories, then they might be moving away from their mission and values just to boost their success rates.



Reporting your impact is hard when you’re juggling spreadsheets. countbubble makes it easy so you can focus on your mission.



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