Intended audience: Social Impact Professionals
“Data maturity” broadly describes an organization’s ability to collect and use data, and provides a framework to assess its data capabilities. Data maturity encompasses multiple dimensions in addition to an organization’s data infrastructure, such as leadership buy-in and the emphasis on and activities surrounding data skills, knowledge, ethics, and more. This introductory article summarizes the importance of assessing your organization’s data maturity when discovering potential data science and AI projects, and DataKind’s process for doing so.
Why is evaluating an organization’s data maturity during the Discover Stage so important for data and AI projects? First, scopers must consider the overall fit of the potential project with the organization’s capacity to support the creation of a data science solution. Second, it is essential to consider whether the organization has the capacity to manage the output of the project after it is complete. The organization must have a data savvy team who can understand and maintain the project output, make continuous improvements, or even build a data pipeline to incrementally update the data to sustain the solution. This capacity to support a solution and manage output speaks to the early stages of building sustainability and impact over time.
In the Discovery Stage at DataKind, scopers evaluate 12 categories of data maturity to assess whether the organization can (1) actually use whatever DataKind builds, and (2) leverage existing resources (e.g., technical, operational, financial, human, etc.) to support the continuation of the DataKind solution. This is done through a brief online data maturity assessment survey sent to the partner organization, followed by a complementary qualitative discussion with the organization during a Discovery Call . Note, however, that there is not a universal data maturity “level” required for an organization to work with DataKind. Organizations simply need to have sufficient familiarity with data, and the ability to use and sustain the project’s results to work with us.
Each data science solution is different, and requires a different set of elements to be maintained. Understanding an organization’s data maturity helps inform whether the necessary elements are there for a specific organization to sustain a specific proposed project.
Further information, DataKind’s full data maturity assessment process, and links to resources can be found in the Data Maturity Assessment Playbook article.
Please see other “scoping” articles for social impact organizations at the bottom of the Scoping page.
Contributer(s): Rachel Wells, Caroline Charrow, Fotis Zapantis
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If you would like to learn more about us, partner with us, or get in touch, email us at community@datakind.org
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