Standards
Common Impact Data Standard
Making better analysis possible.
The Common Impact Data Standard is a system—known as a data ontology—for organizing impact data. It represents a social purpose organization’s (SPO) impact model, whether that model is a theory of change, logic model, outcome chain, or other system.
By representing data in a standard and flexible way, the Data Standard allows the exchange of impact information across organizations and funders, regardless of the impact models being used. This makes it easier for everyone in the impact measurement ecosystem to share and aggregate data.
The benefits of a Common Impact Data Standard
Each organization makes some difference, but their most impactful stories are when the data can be connected and aggregated. The Common Impact Data Standard allows networks to see the impact, and use the data to improve impact.
The Common Impact Data Standard makes it possible for researchers to integrate their data, creating many new opportunities for analysis (e.g., longitudinal and transversal studies) using a variety of methods. This has the potential to lead to a better understanding of needs and a better understanding of what works.
Donors, investors, and government agencies are increasingly aware that old impact reporting techniques have been a burden to grantees and investors. The Common Impact Data Standard provides funders with the standard formats they need to understand portfolio-level impacts while leaving SPOs the autonomy to measure impact in ways that best fit their own data needs.
The Common Impact Data Standard allows impact data to be represented in ways that can accommodate the reporting needs of diverse funders. SPOs utilizing the Common Impact Data Standard will need to do less custom reporting.
The Common Impact Data Standard can enable the tagging of an organization’s content on the internet, making it easier for search engine users to find impact content on the web.
The Common Impact Data Standard makes it easier for organizations to connect their impact measurement with other measurement standards, such as the UN SDG Global Indicator Framework, IRIS+, the International Aid Transparency Initiative (IATI) Standard and others.
How do you use the Common Impact Data Standard?
The easiest way to use the Common Impact Data Standard is by using an aligned tool.
The Common Impact Data Standard is embedded into aligned software and data utilities. This allows social purpose organizations to access the standard without becoming data scientists.
Representing impact
A widely adopted Data Standard will create a uniform representation of impact while allowing each organization the flexibility to design an impact model that is most relevant to it and its stakeholders.
We understand “impact” as a change in outcomes for people and the planet. To show these changes, the Common Impact Data Standard represents the five dimensions of impact—what, who, how much, contribution, and risk—plus a sixth dimension of “how”.
What is a data ontology?
A data ontology is a computer science term for the conceptual scaffolding that maps how data is organized. Data ontologies like the Common Impact Data Standard improve impact measurement by facilitating interoperability among standards, meaning data can be shared across organizations and funders even when using different standards and metrics. They also generate efficiencies in impact measurement and management and elevate transparency.
More on the Common Impact Data Standard
Looking to explore further? Find other Common Impact Data Standard information and materials on the Resources page.
Acknowledgements
The Common Impact Data Standard has its roots in collaboration. The Data Standard was released in collaboration with Mark Fox at the Centre for Social Services Engineering at the University of Toronto.
To create this standard, the Common Approach consulted with experts and aligned with other leading standards, such as the Impact Management Project (now housed at Impact Frontiers), which itself consulted with over 2000 impact professionals.