7. Gauging Performance and Impact /

7.5 Reaching realistic conclusions


We reach conclusions about the impact of our work that are based on reasonable assumptions.

To meet the standard in full, you give equal weight to positive and less positive findings (including negative outcomes) when making conclusions about your impact. You also consider any changes that are likely to have happened without your work. These include the contribution that other services might have made to the changes, as well as outside factors that are beyond your control.

So what does your performance and impact data tell you? What claims are you going to make to others?

This requires some careful consideration to ensure you avoid untested assumptions or generalisations based on inadequate data.

The first thing you can do is to ensure you are confident in your findings. You could take time to look into findings that appear unusual or unexpected. Sharing your initial findings with others can also help sense-check your results, enabling you to spot errors, obtain explanations or catch potential misunderstandings.

As you look at what your data is telling you, also be aware of the possibility of unwelcome or negative outcomes. While all organizations set out to bring about positive change, this does not always go as planned. For example, a vulnerable person might benefit in many of the expected ways from being rehoused to better accommodation (security, stability, etc.), but there may be an unforeseen increase in isolation and loneliness as they are removed from their social networks. Any unintended consequences should be carefully considered and reported.

Also be aware that the change (or lack of) that you find will usually involve a number of factors that contributed to results. You should be transparent about things that detracted from the results you wanted, or which enabled them to happen.

Keep in mind that some change will always occur naturally, independent of your work. So, be careful when making claims about your work and taking credit for results. This issue of attribution can be complicated and difficult to prove definitively. It is often more helpful and feasible for small social enterprises to describe their contribution to the outcomes observed. So, try not to worry too much about gathering definitive proof of a cause-and-effect relationship.

Course 7 in the Impact Practice series from the Social Enterprise Institute looks further into these issues and gives more guidance on various ways that you can strengthen the claims you make about your organization’s impact.