State Data Maturity Assessment

Helping data leaders track and evaluate the progress of data strategies in states.

Why It Matters

There has been a noticeable lack of a comprehensive self-assessment tool for government agencies, specifically one that incorporates a deep understanding of the complexities involved in data-sharing agreements, siloed grant funding, and legislative barriers to data sharing, including a century-old law governing public records.

A data maturity assessment tool tailored for governments can equip Chief Data Officers (CDOs) and other data leaders with essential information to evaluate their state or organization’s strengths and weaknesses. Additionally, it identifies key areas requiring investment and enhancement. This tool is an extension of the Beeck Center for Social Impact + Innovation’s ongoing efforts within the State Chief Data Officers Network, including defining the CDO role. It has been rigorously reviewed by current CDOs, representing three-quarters of U.S. states.

We invite state data leaders to engage with this assessment to refine their strategic and tactical plans. This is not a state ranking tool; it is the pathway up a mountain. And as you climb the first summit, you will see there are more mountains to climb.

What You Need to Know

A data-maturity assessment is a tool that empowers states to identify strengths and weak- nesses in harnessing data insights for informed policymaking and service delivery. By conducting this assessment, your state can:

Gain valuable insights into its data culture and practices;
Pinpoint areas for improvement; and
Prioritize investments in data-related initiatives.

This model examines five areas that all U.S. states commonly encounter—commitment, data talent pipeline, data action planning, sharing, and analysis —and benchmarked measures of state governments as they grow their data maturity.

This assessment does not produce a single score and is not intended to disparage states; rather, the purpose is for each state to gain a nuanced and comprehensive overview of their maturity level and determine what areas can grow further.

This model is intended to be used primarily by state level CDOs, or other data leaders seeking to:

Advance the use of data in their state;
Guide conversations with less technical leaders such as governors, policy directors, budget directors, legislators, or others in decision-making roles; or
Track year-over-year improvements in statewide data strategy.

The first iteration of the assessment model is designed to capture statewide data maturity, not that of individual departments or agencies, although departments or agencies are welcome to use the tool. This assessment also focuses on qualitative assessments of data maturity, unlike other technical data-management maturity assessments.

How to Take This Assessment

Review the whole document, including the self-assessment questions and options for answers. There are five categories and a total of 17 questions. We encourage states to select a team knowledgeable about the data policies and pro- cesses in your state to review the questions, discuss answer options for each question, and start collecting relevant documentation supporting your state’s answers.

(Optional) Share your state’s responses with the Beeck Center. The Beeck Center may use you reponses for research puprose in the future. You can also email additional notes about your state’s assessment to digitalservicenetwork@georgetown.edu.

Scale: Levels of Maturity

Below is an overall framework for the maturity measures and benchmarks for each level. States usually start their data journeys from initial awareness and emerging practices. The highest maturity level is an ambitious benchmark, challenging states to stretch their goals and become nationally recognized data leaders.

Self Assessment

Below is the state data-maturity assessment framework listing the main categories, questions, and the specific benchmarks to meet one of five maturity levels for each question. The five components of the framework are:
A. Commitment
B. Data Talent Pipeline
C. Data Action Plan
D. Sharing
E. Analysis

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A. Commitment: State has an ongoing commitment to establishing and empowering data leaders.

Advanced states have appropriated budgets allocated to support and sustain the CDO office. Three quarters of states have a formally established CDO role and a third of them have established a deputy CDO role. Six states allocate more than $6 million annually for their CDO offices.

A1. Does your state have a formally established CDO or equivalent role?

CDO is a defined role that leads a comprehensive statewide data strategy and has a cross-cutting influence in state data-management and initiatives.

INITIAL AWARENESS

No statewide data leadership role or responsibilities.

EMERGING PRACTICE

CDO role exists, but is not established by a formal action.

Geographic Information Systems (GIS) team(s) exists.

LEARNING

CDO role is established by administrative action.

Roles and responsibilities are defined.

CDO roles are established at an agency level.

GIO (geographic information officer) for the state is established.

MANAGING

CDO role is established by legislation.

CDO roles and responsibilities are communicated and calibrated with other state-level positions such as chief information officer (CIO), chief information security officer (CISO), geographic information officer (GIO), etc.

MASTERING

Statewide CDO role is defined in legislation and empowered to inform data strategy across all departments.

CDO has a strategic role, is well integrated with the GIO role, collaborates with CIO, CISO, human resources, and budget directors.

A2. What funding does your state provide for the CDO office and data initiatives?

INITIAL AWARENESS

No budget exists or the state uses ad-hoc funding approaches.

Senior leaders do not see data as important or valuable.

EMERGING PRACTICE

Individual efforts are funded through federal grants or other one-time funding mechanisms.

Leaders show some recognition of the importance of data to the state, but they do not see the value of engaging with it.

LEARNING

CDO office is staffed with core roles sufficient to implement a basic data strategy.

State leaders know data is important and are curious to learn about its potential uses and benefits.

MANAGING

CDO office is staffed with core roles sufficient to implement a growing data strategy, including dedicated legal support.

Collaborative relationship with enterprise IT.

Senior leadership teams model good data culture and agencies have funding for data roles corresponding to statewide standards.

MASTERING

CDO has a budget authority, established funding, and financial planning process in place.

Funding is appropriated through the state budget and costs are built into federal grants.

State proactively provides annual funds to agencies to improve data infrastructure in alignment with data strategy, in addition to providing enterprise tools.

Senior leadership teams continuously support a well-embedded, strong data culture throughout the agencies and champion statewide data governance.

A3. How actively is your state involved in data initiatives, collaborations, and partnerships?

INITIAL AWARENESS

No data leadership at state level or at large agencies (health and human services, education, workforce, transportation, justice).

State leaders do not communicate data policies and principles or seek to embed them due to a lack of interest or dedicated resources.

State leaders do not see external data users as stakeholders useful in influencing data strategy.

EMERGING PRACTICE

Some agencies have data leadership positions, with ad-hoc and varying resources.

Data principles and policies exist but are not widely supported or understood.

Data leaders are piloting central data functions, but not yet scaling.

State engages in ad-hoc, one way external communication regarding data efforts.

LEARNING

All medium and large agencies in the state have data leaders with financial and staff resources.

CDO can provide guidance on data standards and policies statewide.

State has a widely supported data strategy, principles. and policies that are publicly available.

State establishes and shares data transparency, access, equity goals and initiatives publicly.

MANAGING

State data leaders have defined collaborative processes with agency data leaders, local data leaders, GIOs, open data managers across the state, etc.

CDO has authority to establish data standards and policies statewide and is able to centralize important data functions.

State is actively working to embed data strategy, principles, and transparency, access, equity and other data policies across the agencies.

MASTERING

State’s CDO leads collaboration and data collection or reporting relationships with the federal government and other states.

State leaders use data alongside community input to provide robust, credible evidence to influence policy and decision makers.

Data principles and policies embedded and governed with clear visibility across agencies and to the public.

B. Data Talent Pipeline: State is increasing capacity of public-service workforce to use data for decision making and operational excellence.

Advanced states are making changes to civil service classifications and job descriptions to include skills such as data engineering and data science, and have ongoing, statewide data-literacy programs.

B1. Is your state prepared to fund dedicated staff to implement a statewide data strategy?

INITIAL AWARENESS

No formal or stand-alone data-related job classifications exist.

Staff are not given sufficient support, time, or funding to incorporate data into their work.

Senior leaders have a very basic understanding of data and require specialized support to make use of data. This may be limited to working with data visualizations.

EMERGING PRACTICE

Specialization in data- related jobs is recognized via distinct job titles like “data scientist,” “data engineer,” and “data analyst.”

Most staff recognize data is part of the agency’s operation but are not aware of how their data connects to a statewide data strategy.

Leaders of some agencies are capable of using data analysis to make strategic decisions with some specialist support.

LEARNING

Specialized data-related job classifications are established statewide. Many types of job classifications include data stewardship responsibilities.

People across agencies are able to collaborate to implement data strategy goals.

Many agency leaders are capable of using data analysis to make decisions with minimal specialized support.

MANAGING

Data-related job classifications are regularly updated based on changes in the industry.

Blueprints and guidance exist for agencies to implement data teams and best practices internally.

All senior leaders are confident in using data analysis without much support, and some are capable of using data in cutting edge ways.

Formal data roles and responsibilities exist including GIS, data scientists, data management, etc., in larger agencies.

MASTERING

All classifications are updated to include data stewardship roles and responsibilities.

State has many people with a range of data and analysis expertise in leadership positions. including at the most senior levels.

Senior leaders have regular data-analysis practices and are able to assess risk and opportunity of emerging data trends.

Formal data roles and responsibilities, with ongoing support, exist and are in use across many departments and agencies.

B2. Does your state have an ongoing, statewide data-skills training program and learning opportunities for staff?

INITIAL AWARENESS

Training is ad-hoc and based on agency-level determination and funding.

State limits training or expertise in data skills to small groups, junior staff, or IT and administrative roles.

EMERGING PRACTICE

In addition to agency- specific, ad-hoc training, state offers training on specific state data tools regularly.

Some staff have data skills, but are not using them regularly or confidently.

LEARNING

State has a strategic approach to data training and literacy, offering tailored trainings appropriate for different data-related and non- related staff at little to no cost (e.g. management, analysts, and non-analysts).

Staff have the skills to adequately understand and make use of data systems and a variety of data tools.

MANAGING

Training programs exist, are regularly offered, and are part of the state’s core requirements for all staff and leadership roles (cyber security, ethics, etc).

Job classifications with dedicated responsibilities for data management and data architecture have access to specialized support.

State aligns data training opportunities with wider data strategy (e.g.. upskilling for new data systems or emerging trends).

MASTERING

Training programs include certification or other forms of employee recognition.

Agency staff are regularly trained and capable of implementing data strategy goals and responding to emerging trends.

C. Data Action Plan: State actively manages its data, knows what data is available, and has a data strategy and a transparent data-governance process.

Advanced states have a written data strategy, are involved in creating and updating statewide data inventories, catalogs, and individual agency data strategies, fund data quality programs, and implement data-architecture standards.

C1. Does your state have a statewide data strategy?

INITIAL AWARENESS

No statewide data strategy.

EMERGING PRACTICE

Data strategy exists and is publicly available.

LEARNING

Data strategy is publicly available and is updated on a regular, defined schedule.

MANAGING

Data strategy is publicly available and is updated on a regular, defined schedule, and mechanisms exist to ensure state actions are consistent with the strategy.

MASTERING

Data strategy is publicly available and regularly updated with opportunities for public comment and community input.

State’s data strategy influences other strategies and annual action plans.

C2. How much is your state improving data-management programs and data-integration initiatives?

INITIAL AWARENESS

EMERGING PRACTICE

An inventory of data collection systems exists. The process for how to record data in the inventory is not described, supported, or monitored.

All metadata definitions allocated to IT. IT continuously follows up with the business for metadata business definitions.

No standardized data quality processes in place. Issues are addressed as they are identified by users.

The agency is project driven and data-architecture teams disband after each project. Ad-hoc use of internal or third party standards.

State has a defined and documented process to link administrative data records, and data-sharing agreements provide a predictable process for such data integration.

All metadata definitions allocated to IT. IT continuously follows up with the business for metadata business definitions.

No standardized data quality processes in place. Issues are addressed as they are identified by users.

The agency is project driven and data-architecture teams disband after each project. Ad-hoc use of internal or third party standards.

State has a defined and documented process to link administrative data records, and data-sharing agreements provide a predictable process for such data integration.

LEARNING

Individual agencies have data inventories, but no statewide inventory exists

Business metadata management is allocated to the businesses and technical metadata to IT. There is a recognized need for metadata management across projects and programs.

There is a recognized need for standardized data- quality processes. A data-quality strategy is formulated and data- quality targets are defined.

A data-architecture team has been defined and has taken responsibility for ownership of the conceptual, logical, and physical data architecture, data-architecture standards, and the oversight of the delivery of data systems.

Data standards and interoperability from statewide projects such as health information exchanges, longitudinal education data systems, and public health meaningful use registries are used by others.

Business metadata management is allocated to the businesses and technical metadata to IT. There is a recognized need for metadata management across projects and programs.

There is a recognized need for standardized data- quality processes. A data-quality strategy is formulated and data- quality targets are defined.

Data standards and interoperability from statewide projects such as health information exchanges, longitudinal education data systems, and public health meaningful use registries are used by others.

MANAGING

MASTERING

C3. How comprehensive are your state’s defined and adopted data-governance processes?

INITIAL AWARENESS

State relies on agency-level leaders to set ad-hoc rules on data governance in their purview.

State centrally collects and uses data for specific administrative purposes only when required.

Data is not governed in a consistent way across the state.

EMERGING PRACTICE

Formalized data governance exists within individual agencies or programs.

High-level data-governance policies and standards are in place statewide but not widely understood or implemented.

Multiple data owners have been identified who manage, but aren’t responsible for, critical data across agency systems.

LEARNING

Data governance is defined by an administrative policy, and defined roles, responsibilities, and areas of accountability are being developed.

Agencies sometimes collaborate to share data using formal data-sharing processes, interacting with agency-level governance.

High-value datasets have assigned stewards and conform to agreed data standards.

Senior leaders meet regularly to discuss data governance as a shared initiative across their areas.

MANAGING

Data governance is defined by policy and authorized in statewide legislation or executive order.

A clear, hierarchical data-governance model exists, responsibilities are communicated and endorsed by leadership, and processes are in place to request data from both enterprise and functional levels.

Responsibilities and roles for data-governance processes and data stewardship are clearly defined across the state.

Performance of the senior leadership team includes consideration of progress toward data- interoperability objectives.

MASTERING

Governance structures and processes exist in state agencies and are coordinated statewide via a state CDO office.

Data governance is treated as a core competency across strategy, people, process, technology, and control.

Statewide data-governance framework is subject to continual review, monitoring, and refinement.

Delivery of the objectives in the data strategy is reviewed and reported on as part of routine data governance, and goals are adjusted over time to continually drive improvement.

D. Sharing: State has an established, clear, and predictable process for data sharing.

Advanced states have umbrella data-sharing agreements or data trusts to simplify and expedite data sharing across the agencies and with external stakeholders

D1. Does your state have either a standard data-sharing agreement or an “umbrella” agreement?

INITIAL AWARENESS

Data-sharing agreements exist between agencies for discrete projects.

State engages in data sharing only if it is mandated to do so.

EMERGING PRACTICE

Data-sharing agreements have a common template that is used statewide and exist between multiple agencies.

State leaders perceive data sharing more as an administrative task, not a strategy.

LEARNING

Data-sharing agreements are statewide and exist between multiple agencies, and are cataloged and accessible to agencies so it is transparent what data is shared among state agencies.

Data sharing is a codified strategic goal for some state agencies, and leaders implement specific administrative policies to simplify data sharing.

MANAGING

Data-sharing goals are included in the statewide data strategy.

Master data-sharing agreement is in place or in development on a statewide level.

State agencies and leaders advocate for legislative or executive policies that facilitate statewide data sharing.

MASTERING

Data sharing both inside and outside of government are core goals of the data strategy.

Data-sharing authority established at a statewide level and within agencies is institutionalized and executed.

Data-sharing agreements are cataloged and actively reviewed to ensure strategic goals are met.

D2. How comprehensive is your state’s open-data program?

INITIAL AWARENESS

Open data is available but distributed across websites of different agencies.

EMERGING PRACTICE

Some open data is available in a machine-readable format through a single state website.

Central data team follows an open-data policy or program strategy, whether or not it is being implemented.

Individual agencies have strategic plans that help prioritize data for publication.

LEARNING

Open data is regularly updated. The most frequently requested data are easy to find via a single state website.

Agencies coordinate with a central data team to plan data for publication.

State provides agencies with guidance for publishing data.

MANAGING

Application Programming Interfaces (APIs) exist, and are developed in consultation with stakeholders for high-value datasets.

State has a position(s) dedicated to supporting the open-data program across agencies.

Open data is part of the statewide data strategy.

MASTERING

State has a process to actively measure the use or impact of open data.

State has an open-data program with a statewide open-data manager and agency-level open-data stewards.

State’s open data is interoperable with local and federal open-data standards.

D3. At what level does your state make data available and understandable for different users (for example, community members interested in a map vs. university data scientists asking for an API)?

INITIAL AWARENESS

Data staff manually prepare data when requested.

Much of collected state data is not available for analysis by agencies outside the collecting agency and is not shared.

State occasionally engages data users to better understand issues like data needs or privacy issues.

EMERGING PRACTICE

Data staff manually rework data for presentation in written reports for different internal and external audiences.

Not all state agencies have the same capacity to share data.

External users are engaged only in high-profile areas.

LEARNING

State enables some internal users to interactively explore and report on the data available, however, the users may need substantial technical expertise or support from data specialists to do so.

State is beginning to build relationships with a wide range of high-impact external users to learn about their needs.

MANAGING

State enables most internal users and some external users to interactively explore, analyze, and report on the data collected by the state.

State establishes and maintains relationships with external users and works to understand their needs.

MASTERING

State carefully analyzes different audiences from the beginning when planning data form and medium of final presentations.

State shares and presents data so that it is easily and quickly interpreted without specialized support.

State consistently responds to external user needs as appropriate.

State demonstrates leadership on data standards, interoperability, and real time data exchanges to improve usability of data.

E. Analysis: State provides skills, knowledge, and tools to enable data analysis.

Advanced states invest in data tools and data-integration efforts to encourage use of data in solving problems and making decisions..

E1. How much does your state invest in providing data analytical tools to state staff at various agencies?

INITIAL AWARENESS

Agencies or individuals procure data tools as necessary on an ad-hoc basis.

Data tools are used to meet agency-level operational requirements.

Analysts frequently spend time creating custom datasets to meet user needs due to inadequate analytical capability of tools.

State reviews data tools when there are digital service failures with a substantial negative impact on services (e.g., app or website is not working).

EMERGING PRACTICE

There are documented pathways to procure data tools and platforms that can be completed within a reasonably short period of time.

Most often data has to be exported from state data systems in order for analysis to be conducted in other tools.

Some agencies use analytical data tools (e.g., R, SAS) for basic data processing or descriptive statistical analysis.

LEARNING

Statewide user groups or communities of practice are organized around specific tools (i.e GIS, business intelligence, cloud data warehouses, etc.)

Some business intelligence tools may be disproportionately complex for the needs of the small, lower-maturity agencies.

MANAGING

Standard data-sharing, analysis, and visualization tools are made more readily available and supported to agencies to enable cross-training and skill development.

Agency-level analysts are able to produce effective, efficient outputs with tools aligned to their agency’s needs.

MASTERING

Agencies can use analytical and data governance platforms (collections of tools, technologies, and processes) across the enterprise to enable the secure sharing, integration, and analysis of data.

Agencies use tools for delivering batch analytics and real-time streamed data.

State data leaders collect use cases for emerging tools to understand business cases.

State leaders invest funds into new data tools and technologies to meet data strategy goals.

E2. How much does your state invest in research, evaluation and data-driven decision making practices?

INITIAL AWARENESS

No documented use of data-driven practices or performance management.

Leaders in the agency have limited belief or experience in using data for research, analysis and evaluation.

State leaders do not understand the link between poor data management and risks to public services.

EMERGING PRACTICE

State publicly measures and reports data on performance goals.

Research and evaluation initiatives are selected and executed by agencies and sometimes there are statewide initiatives.

Agencies have taken ad-hoc steps to understand how data-management practices support public-service outcomes.

Data initiatives are carried out without explicitly linking to public-services outcomes that the data supports.

LEARNING

State provides centralized guidance for agency leaders to use data for performance management and decision making.

Leaders understand and communicate publicly about how good data management, evaluations of programs and research activities support public- service outcomes.

State resources are allocated for research, analysis, evaluation activities.

MANAGING

State agencies invest funds toward solving problems within programs that consistently do not achieve desired outcomes.

Leaders include updates to data-management practices and research and evaluation outputs in policy decisions to ensure that data directly supports positive outcomes.

Agencies use shared data from other agencies to inform internal performance goals and policy decisions.

MASTERING

Leaders have a clear understanding of the link between data management and public-service delivery outcomes. They proactively work to ensure that data initiatives are connected to the policy implementation.

Agency leaders use analytics and evidence to support decision making for all high priority activities.

State proactively works with cross-government networks and communities of practice to ensure data sharing does not compromise ethical use of data.

You can add additional details or evidence about your state or agency such as links to relevant legislation, executive orders, or reports to share with the Beeck Center.

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State Data Maturity Assessment

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​​Why It Matters

What You Need to Know

This assessment does not produce a single score and is not intended to disparage states; rather, the purpose is for each state to gain a nuanced and comprehensive overview of their maturity level and determine what areas can grow further.

Scale: Levels of Maturity

Self Assessment

A. Commitment: State has an ongoing commitment to establishing and empowering data leaders.

A1. Does your state have a formally established CDO or equivalent role?

A2. What funding does your state provide for the CDO office and data initiatives?

A3. How actively is your state involved in data initiatives, collaborations, and partnerships?

B. Data Talent Pipeline: State is increasing capacity of public-service workforce to use data for decision making and operational excellence.

B1. Is your state prepared to fund dedicated staff to implement a statewide data strategy?

B2. Does your state have an ongoing, statewide data-skills training program and learning opportunities for staff?

C. Data Action Plan: State actively manages its data, knows what data is available, and has a data strategy and a transparent data-governance process.

C1. Does your state have a statewide data strategy?

C2. How much is your state improving data-management programs and data-integration initiatives?

C3. How comprehensive are your state’s defined and adopted data-governance processes?

D. Sharing: State has an established, clear, and predictable process for data sharing.

D1. Does your state have either a standard data-sharing agreement or an “umbrella” agreement?

D2. How comprehensive is your state’s open-data program?

D3. At what level does your state make data available and understandable for different users (for example, community members interested in a map vs. university data scientists asking for an API)?

E. Analysis: State provides skills, knowledge, and tools to enable data analysis.

E1. How much does your state invest in providing data analytical tools to state staff at various agencies?

E2. How much does your state invest in research, evaluation and data-driven decision making practices?

You can add additional details or evidence about your state or agency such as links to relevant legislation, executive orders, or reports to share with the Beeck Center.

Why It Matters