About the Assessment
data.org launched the Data Maturity Assessment (DMA) to enable better benchmarking of the social impact sector, help organizations prioritize which areas of data maturity need investment, and enable self-service connections to tools and resources that help with the transformation needed to become a “Data Led” organization. The tool was built from extensive research and in consultation with social impact organizations tackling these topics. The assessment takes about 12 minutes to complete and delivers a clear results summary to inspire discussion and inform action.
In addition to providing a snapshot of data maturity, we matched your assessment results to materials in our Resource Library. These customized recommendations provide informative and actionable next steps for your organization to consider. While we include resources from a range of social and private sector organizations, we remain agnostic on software and methodologies.
Categories
The data.org DMA provides a framework for assessing organizational data maturity within three categories.
Strategy:Â
How data-driven is your organization’s strategy?Â
Strategy is about how your organization uses data to define goals, make decisions, measure success, and identify areas for change.
Application:Â
How much does your organization apply data to better understand different areas of work, across programs and internal operations?Â
Application is about whether your organization uses data to better understand different areas of work, including program evaluation, market research, organizational efficiency, and more.Â
Analysis:
What types of data analysis techniques does your organization take advantage of?Â
Analysis is about your organization’s ability to use data to understand the past, predict the future, compile information across data sources, make decisions, and automate processes.
Quality:
What is the quality level of the data that your organization maintains?Â
Quality is about how trustworthy and therefore useful the organization’s data is currently, and how this trustworthiness of the data is maintained and improved.
Security:
How secure is the personal, private, or confidential data that your organization maintains?Â
Security is about ensuring that data is stored in accordance with regulations and in a manner that protects individuals.
Responsible Use:Â
Does your organization employ responsible data science practices in its data use?Â
Responsible use is about evaluating the appropriateness of decisions and practices regarding data and models, including data collection, storage, training, and use.
Infrastructure:
Is your organization able to select, purchase (as needed), maintain, and use technology tools and external data sources to maximize the use of data?Â
Infrastructure is about the funding, technology systems, and data that the organization has access to in order to build and sustain their data use.
Leadership:
Is your organization’s leadership prepared to lead the organization towards maximizing the use of data?Â
Leadership is about the buy-in, expertise, and support of those at the top of the organization to strategically use data for decision making and invest in expanding the use of data.
Talent:
Does your organization have access to people with the skills needed to effectively use, store, and interpret data?Â
Talent is about ensuring the data skills of staff and consultants are sufficient to maximize the use of data.
Culture:
How much is data embedding into the culture of your organization?
Culture is about the ability of staff across the organization to communicate about data, interact with data, share data across teams, ask difficult questions with data, and collaborate in data use.