How to measure the impact of open data: the importance of SROI

Traditionally, companies have measured their results based on a simple operation: how much they have earned compared to the expenses they have incurred. However, this question is not so simple. There are many aspects to take into account that are not easily quantifiable, especially when we speak about an organization that pursues a social goal. Here is when the SROI appear on the scene.

The Social Return of Investments (SROI) was defined by Roberts Enterprise Development Fund (REDF) at the end of the 1990s, in order to measure the social value of its philanthropic investments. The idea was simple: while the Return on Investment (ROI) approach only measures profits, SROI includes the economic, socio-economic and social value of an enterprise. After the REDF, various experts and organizations have been adapting this approach and developing multiple frameworks that help calculate the impact of an operation.

This approach is used by a multitude of non-profit organizations, associations or foundations with a strong social focus, but it is also very useful for open data. In the current context, measuring the impact of open data initiatives can be a big challenge, since its effects may occur several year after.

The SROI method describe 4 values: the use of resources (input), direct results (output), indirect activities (outcome) and the consequences of value creation (impact). Each of these aspects is explained below, based on the report Measuring the promise of open data: Development of the Impact Monitoring Framework. This report, carried out by CEDEM, explains how this methodology can be applied to an open data ecosystem:

• Input: includes all the resources that an organization uses to execute a certain action, such as money, people, equipment and facilities. In the case of open data, it is necessary to take into account the "raw" data obtained by the organization and the technical and economic efforts involved in transforming those data into open and reusable formats.
• Output: refers to the results that are directly controlled by the organization, that is, the direct and tangible deliverables produced by the organization. For example, the open data portal where the information is published.
• Outcome: covers all direct or indirect consequences derived from the actions carried out by the organization. In the open data context, all the activities carried out by users would be included in this section. For example, an application.
• Impact: the short, medium or long term effects that would have happened thanks to the intervention by the organization. In the case of open data, this covers only the results actually caused by releasing the data.

Let's see an example. Imagine that a city council makes available to citizens data on public transport routes and their schedules (input) through a platform in real time (output). These data, which should be found in an open format to facilitate their reuse and interoperability, are used by a citizen to create an app (outcome) that facilitates and encourages the use of public transport. The final result (impact) would be a reduction of the CO2 emitted into the atmosphere. A final result that can be quantified. The challenge is to determine if this CO2 reduction has been a consequence of this application - and consequently, of the data release - or if there have been more actions aimed at the same end. In the second case, it would be necessary to determine which part corresponds to each action based on different parameters: use, impact, etc. There are companies specialized in making this type of models.

Using this framework, we can measure the impact of an action in retrospect. Mapping the applications or use cases based on open data, we can know what the impact of a certain data set is. Also, if decision-makers are aware of the potential impact of reusing a given data set, it will be easier to increase their investment resources in their opening.

Thanks to SROI, it is easier to monitor the activity of an open data initiative, to know what data is being reused and what their impact is. This can encourage more activities aimed at improving our environment. But, above all, the SROI allows us to know how we contribute to society, what challenges we are solving, and that is fundamental to continue evolving in a sustainable manner.