White Paper

Center of Analytics: What It Is and Why It Matters

ContentsCenter of Analytics: A New Way to Govern ................1

How to Get Started ...........................................................2

Leadership and Vision ......................................................3

Start Small, Then Grow .....................................................3

Data Sharing and Governance ......................................4

Common Technology Platform ......................................5

How to Structure the COA ..............................................5

Centralized .............................................................................5

Hybrid .......................................................................................6

Distributed ..............................................................................6

The Keys to Success .........................................................7

Learn More .........................................................................7

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As stewards of the public’s resources, state government leaders want to be able to prove they’ve used tax dollars for the services and programs that provide the greatest benefits to citizens. At the same time, citizens want to see solid evidence that govern-ment programs have overcome the traditional plagues of bureaucracy and inefficiency.

There are longstanding challenges to achieving these goals. Consider age-old political boundaries, outdated technologies and processes. And a culture that inhibits efforts to access, share, integrate and analyze big data from across the govern-ment enterprise.

Despite these roadblocks, it’s more important than ever to help government change the way it works. Clues tucked away in agency, institution, department and technological silos can uncover deep, previously hidden insights. By sharing and analyzing data, policy and operational leaders can:

• Strengthen transparency and accountability. Given tighter budgets and limited tax revenue, citizens want to know that funds are going to programs that achieve the expected outcomes. Government leaders can address these expecta-tions by giving citizens timely access to relevant information that has not typically been available in the public view.

• Uncover fraud and waste, and ensure compliance. Governments that can quickly evaluate data from across the enterprise can identify suspect or unusual behavior and prevent losses – such as those arising from tax evasion and fraudulent medical, social service and unemployment benefit claims. At the same time, they can prevent wasteful or improper payments and ensure compliance with regulations.

• Monitor performance and outcomes. It’s no easy task to develop budgets based on the relationship between funding levels for programs and services and the expected results. Governments can serve the right people with the right programs – and achieve the right outcomes – by using data as a way to monitor, evaluate and make fact-based decisions about which programs to continue, expand, discontinue or replace.

• Improve citizen experiences. When they interact with government, citizens expect up-to-date technologies, self-service capabilities and one-stop shopping. Taking the right approach to data and technology can free govern-ments from privacy concerns and allow citizens to interact with government in a more comprehensive, secure and convenient way.

• Make better-informed policy decisions. Balancing constrained budgets and limited resources, lawmakers and policy analysts can use data as evidence for decision making. In turn, they can appropriate funds in the most effective way possible to serve and protect the public.

With all these advantages, what’s stopping governments from moving ahead?

Traditional government approaches have set up tightly guarded data silos that have to be broken down. While legacy systems serve operational functions, many agencies and programs have inefficient processes and lack neces-sary control over data quality and consistency. Sharing data requires adopting an entirely different paradigm from the norm. In short, working together to share data across the boundaries of politics, people and technology requires a transformative – and sometimes difficult – shift. Doing it with limited government resources sometimes seems impossible.

Center of Analytics: A New Way to GovernAt SAS, we believe that implementing a center of analytics (COA) is an optimal way for governments to overcome tradi-tional roadblocks and make analytics an integral, comprehen-sive component of operations. But a COA is not a solution or a product – it’s a strategy that turns data into a utility that can be shared across agencies, departments and political boundaries.

A COA pools analytical talent to prevent individual departments from needing to independently develop their own analytics solutions. It also establishes data governance, security and management approaches and enables a common technology platform. As a result, governments can share and reuse data, and build from a solid base of best practices.

A center of analytics may span an entire state, or just a county or city government. It could involve a group of organizations with a common focus, such as criminal justice, public utilities or financial services. Or it could entail a single agency that repre-sents multiple divisions and responsibilities, such as health and human services.

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Regardless of how it’s set up, the goal of a COA is to provide a more thorough, cross-agency understanding of changes, trends and issues associated with citizens, services, operational and program costs, and more. For example, you might need information from criminal justice systems, education systems, child protective services, foster care, social services and other agencies to treat children in the juvenile justice system. This cross-agency view of children would be the only way to get a full understanding of each child’s background, needs and supervision options.

How to Get StartedEstablishing a COA is not a one-time project. It’s a long-term vision that moves an organization from basic reporting capabili-ties to a point where it uses advanced analytics to gain broad insights. The effort pays off – because a COA can help policy and operational leaders make optimal program investment decisions, manage resources better, and improve financial programs, budgets and results.

If you treat analytics as a government enterprise solution established through a center of analytics, you can:

• Use all key sources of information to help you make better decisions, be proactive and improve efficiencies.

• Align technology with business strategy so analytics will become a solution to drive day-to-day operations. You’ll start to understand not just what happened in the past, but why it happened and how you can influence outcomes and predict the future.

• Put the right information into the hands of those who need it – operational analytics for front-line people, managerial summary analysis to those who make tactical decisions, and executive analysis for those who drive strategy.

• Build repeatable processes and capabilities to bolster future success.

• Get answers to the hard questions that cross government agencies, such as the underground economy or social services oversight.

Why Governments Need Enterprise Analytics

To be successful, a center of analytics must have strong leaders who can articulate strategic vision and mission. This will equip the center to evangelize the values of participation, to develop and share best practices, and to provide support and training. You can start by building a common solution that works for one agency – then expand it to work with others.

}}A center of analytics aims to create the right mix of processes, people, tools, skills and data to enable governments to follow repeatable processes of analyzing information quickly and effectively as they make fact-based decisions.

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Leadership and VisionOne of the best ways to set up a COA program for success is by establishing appropriate advocacy and leadership up front. Ideally, you need executive and legislative leaders who support the vision of a COA and can provide clear direction about outcomes and expectations. These leaders will have the authority to authorize data sharing and to get commitment from everyone involved in different branches of government. They can help build a common vision among these branches, getting buy-in from key individuals along the way.

Many different people need to be involved in a center of analytics. They include:

• Champions/executives, such as the chief data officer, chief analytics officer and program director. These leaders set the vision, manage resources, prioritize and oversee analytic solutions and ensure that value and ROI are reported to key stakeholders. They approve the road map for the initiative, justify and secure program funding and prioritize projects, and make sure the program has visibility and support and can act to meet its objectives.

• Policymakers. Legislative and executive branch decision makers gain funding to establish the program. They provide high-level support and ensure long-term viability by providing authority and potentially legislation to enable enterprise data sharing and analytics development.

• Key stakeholders. These agency/organization executives are the people who will use the analytic solutions being devel-oped. If they know the program vision and understand the benefits of taking an enterprise approach to data sharing and using an enterprise platform, they can provide direction, public support and continuity for the program.

• Center of analytics staff. These people develop the program road map and evangelize mission and objectives to key stakeholders and project teams. They also develop and implement policy and procedures, define and share best practices, oversee and provide consultative services to program projects, enforce governance and security, and document the return on investment of the program and solutions.

• Project teams, including business analysts, domain experts, data scientists and others. Program and agency teams engage in analytic solution design, development, implemen-tation and support. This team can include program, agency and vendor personnel. Technical resources handle data management, integration and analytics development work, while business resources determine requirements, test analytic output, and provide training and solution support.

Start Small, Then GrowYou can instill success if you begin with a business area that has a high impact or a broad reach. For example, you can focus on a key legislative issue, citizen safety or a compliance issue. By starting with one small area, it will be simpler to determine what data is needed and what can to be done to achieve your goals. By choosing a high-impact area, you’ll garner heightened interest and support. After a small start, you can build the COA program incrementally, expanding as you go. There’s no need to wait to put analytics in the hands of your users until a perfect solution is complete. Start with data that’s available now, and build the core functions – then let your users push expansion.

One way you can build coalitions is by identifying organiza-tions that share common interests, then proving the worth of doing sophisticated analytics with combined data from multiple departments and agencies. For example, you might be able to show that you can reduce the number of automobile accidents on a highway by analyzing combined data from the Department of Motor Vehicles, the Department of Transportation and the Highway Patrol.

Making a Mental Health Service System More EfficientThe County of San Bernardino Department of Behavioral Health (DBH) needed to treat behavioral health issues in an effective, cost-efficient manner. Using SAS® for integrated citizen outcome management, DBH gained a holistic, integrated view of consumers that allows the county to analyze needs, design effective programs, and predict and plan for future needs.1

1 sas.com/en_us/customers/san-bernardino-county-health.html.

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}}Citizens expect their government to keep them safe, stop fraud and abuse, and care for those in need. But they often don’t feel the govern-ment should track them or use their personal data. For example, citizens want improved traffic, safer bridges and expanded public transit – but to do that, governments must track information about commuters, usage and travel patterns.

Data Sharing and GovernanceFor analytics to be a seamless part of government business, you must establish governance across the enterprise. That includes developing agreements for how to share and protect data, and how to address privacy concerns and regulations.

To give everyone confidence in analytic results, your data – the foundation of analytics – has to be of the highest quality. Your data should be standardized and reliable, and should enable entity resolution – matching records for a person, business, location, etc. The governance program should encompass an understanding of state and federal data sharing regulations so you’ll know what data can be shared, how it can be used, who can see the data, how long it can be retained and how public requests for information are to be handled. Having standard security protocols is also critical to keeping confidential data protected and controlled.

Information Delivery Portal

Government Analytics Center of Excellence

DataFinancials

Revenue

HR Payroll

Health Plan

Court Records

Sex O�ender

Jail Data

Correction Data

DOT/DMV

Medicaid

Social Service

Workers Comp

Corporation Registrations

Unemployment Insurance

Third Party

Retirement

Education

Governance

• Third Party Data

• Death Master File

• DOT/DMV

• Criminal Justice

• HR/Payroll

• Financials

• Education

• Healthcare

• Unemployment Insurance

• Wage and Labor

• Medicaid

• Social Services

• Revenue

Fraud and Compliance Analysis and Alerts

• Unemployment Insurance Fraud

• Workers Comp Compliance• Social Services Eligibility• Medicaid Program Integrity• Revenue Collections

Reporting and Analysis

• Health Plan Metrics• Healthcare Outcomes• Budget/Accounting

Reports• Revenue Analysis• Medicaid/Social Service

Analysis• Retirement Plans Analysis

Criminal Justice

• Criminal O�ender Search /Watch

• Criminal Incident Mapping

• Criminal Incident Analysis

• Recidivism/Prison Population Analysis

Education

• SAS® EVAAS®

• Longitudinal Data Analysis

• • •

• Future Solution• Future Solution• Future Solution

Security and AuditingData Governance

• Identity Management and Authorization

• Data/System Monitoring

• Business Intelligence• Policy and Procedure• Data Standards• Data Management

and Administration• Security

Figure 1: With a center of analytics, governments can significantly improve the way they manage big data across the enterprise.

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Strong legal counsel is also vital for successful data sharing and governance efforts. Legal counsel provides an objective assess-ment of regulations related to data sharing and can debunk ingrained (and often perceived) limitations. This approach ensures that data can be used appropriately and lawfully.

Common Technology PlatformTo build knowledge and experience with analytics, it’s invalu-able to have a common enterprise technology platform that nurtures experience and expertise. A common platform allows everyone to use the same tools, and to share their knowledge of what analytics is and how it works.

You should choose an implementation approach that’s based on your internal technical and analytic resources, funding, and overall strategies for outsourcing. You can keep the tech-nology and data in your internal environment and use existing resources to manage it for you. You may opt for a hosted/cloud approach where you outsource hosting for the data and solution as well as services. Or, you could take a remote managed approach where you use external resources to manage your on-site data and systems.

How to Structure the COAAs you get started, it’s important to select the best way to structure your COA program. Ideally, the program will have strong collaboration between the business and IT organizations. A COA may be structured in a centralized, hybrid or distributed manner.

Centralized Centralized analytics centers generally operate under a single organization. In many government organizations, the program resides under the purview of the centralized IT division and provides services to other government agencies. Policy, proce-dure, governance and best practices are established by a centralized program. Development is also managed centrally. The COA staff works closely with teams in different business organizations as each solution is developed and deployed. Challenges to this approach tend to be limited resources and funding, and lack of buy-in from agencies. But the benefits are efficiency and effectiveness – because staff can identify models that can be reused, and they can avoid known pitfalls. This model can also be scalable and flexible to accommodate rapid expansion.

Figure 2: Centralized analytics centers tend to be efficient and effective, while offering flexibility to easily accommodate expansion.

IT Unit

• Analysts

• Data Modelers

• Testers

State Chief Information

O�cer

IT UnitCenter of

Analytics Chief Data O�cer

• Security

• Technical

• Business Services

COA Resources

Health and Human Services

Public Safety

Transportation

Finance/Taxation

Other Agencies

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DistributedIn distributed analytics centers, the COA acts similarly to a think tank while agencies implement their own individual solutions. This model makes it difficult to efficiently reuse integrated data and analytic models. Policy, governance and best practices are provided, but there is limited day-to-day involvement in analytic solution development. Organizations that take this approach must proactively work with business organizations to ensure that analytic solutions do not recreate the silos often seen in operational systems. The biggest benefits of a distrib-uted model are that it requires limited resources and funding at the enterprise level, and has more influence and autonomy at the business level. But good results require strong oversight and governance.

HybridHybrid analytics centers are centrally staffed to establish policy, procedure, governance and best practices. But as solutions are developed, COA resources are identified and embedded with the agency’s team of resources. The central staff provides consultation and implementation guidance while the embedded team provides business context, influences change and drives adoption. The challenges of this approach tend to be difficulty communicating to ensure that best prac-tices, design and development approach, governance and oversight, and implementation support meet the expectations of the enterprise program. Like a centralized approach, the hybrid approach is efficient and effective. It can also make it easier for agencies to engage, because they feel more in control of analytic development. Embedded teams may also facilitate easier adoption and institutionalization of analytic solutions.

Figure 3: Hybrid analytics centers make it easy to adopt and institutionalize analytic solutions.

IT Unit

• Policy• Governance• Best Practice

State Chief Information

O�cer

IT UnitCenter of

Analytics Chief Data O�cer

Health and Human Services Public Safety Transportation Finance/Taxation Other Agencies

COA Resource COA Resource COA Resource COA Resource COA Resource

Figure 4: Distributed analytics centers require limited resources and funding at the enterprise level.

Agency IT Agency IT Agency IT Agency ITIT Unit

• Policy• Governance• Best Practice

State Chief Information

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IT UnitCenter of

Analytics Chief Data O�cer

Health and Human Services Public Safety Transportation Finance/Taxation Other Agencies

Agency IT

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Learn MoreFind out how SAS can help you successfully implement a center of analytics: sas.com/center.

The Keys to SuccessWhen you make analytics an integral part of government opera-tions, there are tremendous payoffs. Both citizens and govern-ments benefit when you engage stakeholders and consistently turn your data into an asset that policy and operational leaders use to guide important decisions. Results from those who have already started down this new path of governing prove that sharing and analyzing data across traditional boundary lines can reduce costs, enhance services and avoid fraud.

By starting with an appropriate COA foundation, you can shorten development time, create a common user experi-ence and ensure that all of your state’s analytic solutions follow standard governance and management guidelines. These front-line efforts will be invaluable to your success.

• Ensure that you have strong executive and/or legislative support to provide vision, authority and advocacy for the program. Then, build strong teams.

• Have a strong knowledge of data privacy, compliance and security regulations.

• Define clear outcomes and expectations.

• Manage the “people” factor first – data sharing is rarely just a technical issue.

• Think globally, but act locally – start small and grow incrementally.

• Develop a data repository based on business need, and make sure it allows you to reuse information.

• Operationalize results to ensure everyone in the organization learns how to use new analytic solutions.

• Base policies and decisions on evidence (facts).

What Does It Take to Implement a Successful COA?

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