Your impact story: from outputs to outcomes

Dive into the 'why' behind the data

You can use outputs in powerful infographics and data visualizations, for example, in annual reports. Sometimes, this is all a funder needs to know. Outputs can tell a memorable story about the scale of activities, the audience reached, when, and how. The data is often collected via Google Analytics, websites, social media, or streaming platforms, without actual interaction with participants or the audience.

In this example, we look at the data from a digital theater production:

• 100 people watched the (digital) production on the first night;
  
• 15 viewers watched the performance a second time;
• 28 viewers shared the link with someone else.

This data is easy to measure, visualize, and share with stakeholders. However, you can do more with this data. Do you know what the data you have means? A quick win! What else can you measure? What other data or information can help you tell the story of your project or organization’s activities? It’s important to have this part of your impact story well-organized.

Then you can ask yourself the important question: 'So what?'

Based on the above example, you can ask yourself:

• What did the audience think of the show in the short term?
• Did this digital art experience contribute to a change in perspective or mindset? If so, how?
• Why did 28 people share the link with someone else? Why only 28 and not 100?
• And what about the 15 people who watched the show a second time? Why did they do this? Did they enjoy it or find it boring?
• What other information can help us better understand the collected quantitative data?

When we ask these kinds of questions, we enter the domain of 'outcomes.' Outcomes usually refer to a change in behavior, actions, experiences, emotions, etc.

How to get started with outcomes

Outcomes are harder to measure than outputs. They are often demonstrated with qualitative data. You need to formulate research questions and use various methods to collect and analyze this data. There is more room for interpretation and bias, but if done well, you can give meaning to the change you aim to achieve and want to showcase in your impact story.

However, be careful! Some reports consist of numbers and a few carefully chosen, inspiring 'quotes' from a limited number of participants. This is not effective qualitative data collection or analysis. Qualitative data analysis is a rigorous process. As with any part of your impact assessment or evaluation, you can seek help within or outside your organization if you’re unsure. It’s worth it because it helps you dive deeper into the participant experience.

Let’s continue with the above example:

• Overall, participants were satisfied with the quality of the experience, the digital production. They gave an average score of 4.5 out of 5.
  
• Of the 20 people who completed the survey after the event, the majority indicated it made them think differently about the topic.
  
• One respondent stated that "the play was an inspiring way to delve deeper into the emotional impact of the topic."
• More than a quarter of respondents searched online for further information.

Qualitative data can help us understand the 'twist' in the impact story: data that is less positive than we thought or other unexpected results:

• Another participant told us that the intensity of the topic made it difficult to watch the performance in one sitting.
  
• Others shared that they were easily distracted because they were at home. That was the reason they, and perhaps others, had to stream the performance twice. Online accessibility works for some but not for others.

This is a short, fictional example, but it clearly shows that a more meaningful story about the experience of a digital production can be extracted, rather than just ‘flat’ numbers.

Think about what impact story you want to tell when formulating your research questions. This helps you create a plan that captures both outputs and outcomes. That’s how you start your impact journey!

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