Data Maturity Framework

	A	B	C	D	E	F
1		Data Maturity Framework Questionnaire
2	Scorecard Category	Question
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4	Problem Definition
5	Problem Definition	What is the problem you are trying to solve? What does success look like/how much does the needle need to move?
6	Interventions	What interventions do you have available to solve the problem?
7	Impact	If this is successful, what impact will this project have? Will it encourage future projects/goodwill?
8	Available Data	What data sets do you have access to relevant to the problem?
9	Data Fields	What fields are in each of the data sources? (See Data Sources Worksheet)
10	Size	How many people/addresses/facilities/entities does the data contain?
11	Target Population	For this problem, what % of entities are at risk or have resources to be intervened?
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13	Data Governance
14	Ownership	For the data sets that you have access to - do you own the data? Do you have permission to use the data? If you do not own the data, do you have the relationships with the data owner?
15	Physical Accessibility	Is the data accessible outside the department/agency? Is there a VPN?
16	Security Policy	What security policies and considerations need to be in place for each of the data sources? (HIPPA, FERPA)
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18	Implementation and Maintenance
19	Technical Implementation	Do you have people in house who can implement/deploy the solution?
20	Data Infrastructure	Do you have the internal tech and data infrstructure to provide a continuous data feed from all the systems, and integrate the results/recommendations back in to the agency systems?
21	Maintenance	Can you update, maintain, and support the implemented solution?
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23	Data Readiness
24			Lagging	Basic	Advanced	Leading
25	Accessibility	How accessible is the data that's required?
26	Storage	How is the data stored?
27	Integration	How intergrated are the different data sources?
28	Relevance and Sufficiency	Do you have data that is both relevant and sufficient to solve the problem?
29	Quality	How is the data quality?
30	Collection Frequency	How often is the data collected?
31	Granularity	What is the level of granularity for the data sources?
32	History	How much history is stored and how are updates handled?
33	Privacy	What data privacy policies do you have in place?
34	Documentation	How well documented are the data?
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36	ORGANIZATIONAL READINESS
37			Lagging	Basic	Advanced	Leading
38	Staff Buy In	How bought in are staff throughout the organization? What percentage of the staff are involved in data collection? Data analysis?
39	Data Collector Buy In	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?
40	Leadership Buy In	How does leadership value data? Do they require data to be presented in order to make decisions?
41	People Resources	Do the people who will act on the results buy in?
42	Data Use Policy	Are there policies in place around who can use data, how they can use data, which parts can they use, and for what purposes?
43	Intervenor Buy In	Do the people who will act on the results buy in?
44	Funder Buy In	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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