Data Maturity Framework Survey
Please complete this survey to help us understand your project better.
About You
Name *
Email address *
What government or organization do you represent? *
Problem Definition
These questions will help us better understand the problem you are trying to solve with the data you have.
What is the problem you are trying to solve? *
What interventions do you have available to solve the problem? *
If this is successful, what impact will this project have? *
Target Population: For this problem, what % of entities are at risk or have resources to be intervened? *
Data Governance
These questions will help us better understand the data you have and who owns it.
What data sets do you have access to relevant to the problem? *
What fields are in each of the data sources? *
How many people/addresses/facilities/entities does the data contain? *
For each of these data sets, do you own the data? Do you have permission to use the data? If not, do you have relationships with the data owner? *
Is the data accessible outside of the department/agency? Is there VPN access? *
What security policies and considerations need to be in place for each of the data sources? (i.e. HIPAA, FERPA) *
Implementation and Maintenance
These questions will help us better understand the feasibility of implementing an intervention following the data science work.
Do you have people in-house who can implement/deploy the solution? *
Do you have the internal tech and data infrastructure to provide a continuous data feed from the relevant systems, as well as integrate the results/recommendations back into the agency systems? *
Can you update, maintain, and support the implemented solution? *
Data Readiness
These questions will assess how ready your data is for analysis. In order to self-assess your data in response to the questions below, see the Data and Tech Readiness Scorecard here: bit.ly/data-readiness
Data and Tech Readiness Scorecard *
Lagging
Basic
Advanced
Leading
Accessibility
Storage
Integration
Relevance and Sufficiency
Quality
Collection Frequency
Granularity
History
Privacy
Documentation
Give us some context to your answers about DATA STORAGE: How accessible is the data required to address this problem? How is that data stored? How integrated are the different data sources? *
Give us some context to your answers about DATA COLLECTION: Do you have data that is both relevant and sufficient to solve the problem? How is the data quality? How often is the data collected? What is the level of granularity for the data sources? How much history is stored and how are updates handled? *
Give us some context to your answers about DATA PRIVACY AND DOCUMENTATION: What data privacy policies do you have in place? How well documented are the data? *
Organizational Readiness
These questions will assess how ready your organization is to partner with outside data scientists. In order to self-assess your organization in response to the questions below, see the Organizational Readiness Scorecard here: http://bit.ly/org-readiness
Organizational Readiness Scorecard *
Lagging
Basic
Advanced
Leading
Staff Buy In
Data Collector Buy In
Leadership Buy In
People Resources
Data Use Policy
Intervenor Buy In
Funder Buy In
Staff Buy In Context: How bought in are staff throughout the organization? What percentage of staff are involved in data collection? Data analysis? *
Data Collector Buy In Context: How bought in are the people on the ground doing the data collection? Do they understand the importance and nuance of data collection? Do they get direct benefit from collection data? *
Leadership Buy In Context: How does leadership value data? Do they require data to be presented in order to make decisions? *
People Resources Context: Do you have people in house who can implement/deploy the solution? *
Data Use Policy Context: Are there policies in place around who can use data, how they can use data, which parts they can use, and for what purposes? *
Intervenor Buy In Context: Do the people who will act on the results buy in? *
Funder Buy In Context: How do your funders consider data? What kind of data do they require? What support for technology and personnel do they give you? *
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