Measured Steps To Social Impact

The 18th December, 2014 tweet chat by Doers’ Labs focused on identifying the main steps to measuring social impact, and the finer points of each step.  But the first question that organizations often ask themselves is, “why is measurement important?”  One participant in the tweet chat posed this  question provocatively, asking whether measurement is really important for for-profit social enterprises or only to donors and impact investors.  There are many reasons that measurement is important, for both for-profit social enterprises and non-profit organizations.  The reasons offered during the chat were concentrated on the importance of measurement to testing an organization’s assumptions of what it needs to do to reach its goals (create impact), and consequently providing the basis for short and long-term decision-making.

The main steps to measuring social impact are formulating: 1) a logic model, 2) assumptions, 3) indicators and 4) tools.  A logic model defines the end goal (impact) that an organization wants to create, its intermediate goals (outcomes) and links them to what it does through a chain of results.  While an organization’s end goal should be less flexible than its activities, often unfortunately it’s the other way around.

The assumptions in your logic model are what an organization’s measurement system should test.  These assumptions will often lead an organization to the questions it wants its measurement system to answer.  It is good practice to also identify the decisions that will follow from answering each question, for an organization to ensure that its measurement system is providing data that will be used.

All too many times discussions of measurement begin with indicators.  However, organizations that hesitate to state impacts that are difficult to measure forget that what you can measure evolves over time.  An organization may choose to start by measuring outcomes, and as its knowledge and resources increase include impacts at a later stage.  Nevertheless, it is important that the logic model articulates a complete chain of results, to keep the organization headed in the right direction.

In addition, indicators are only one part of a measurement system, and are only useful in so far as they help an organization answer the questions that it identified in the previous step.  The tweet chat included a conversation on how rubrics can be used to turn qualitative data into quantitative indicators, to measure phenomena like social autonomy and empowerment.  However, the greatest power of qualitative data is probably in its ability to help an organization understand why change has or has not happened.  The usefulness of indicators is limited to understanding whether change has happened or not.  Therefore, identifying questions that go beyond indicators is critical.

There was widespread agreement during the tweet chat that unless an organization goes through the steps above, it is unlikely to be able to design effective tools to collect data.  However, once an organization goes through the above steps, there are technologies available to help it design and administer tools to collect data.  Uniphore, Social Cops and Vera Solutions were some of the companies mentioned during the tweet chat who enable organizations to collect, visualize and disseminate data.  Finally, it was suggested that the “next practice” for organizations that have robust measurement systems would be to use this data to create social impact models much as is done in the field of economics.

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