Putting Data Analytics at the Forefront of Your Agency

Putting Data Analytics at the Forefront of Your Agency

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No matter what your job description says, data analytics is a crucial part of your role.

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Contents Persona one:

The Frontline Employee 6

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The Role of Data Analytics in Government

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Crafting a Data Persona

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Using the Digital Analytics Program in Federal Government

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Applying Entity Analytics at Your Agency

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A Progressive Approach to Data Analytics

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How to Build a Culture of Data Analytics

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Build Your Own Persona

Persona two:

The Data Scientist 12

Persona three:

The IT Manager 16

Persona four:

THe Agency Leader 22

Informing Better Construction and Maintenance Programs

Conclusion & Acknowledgments

Executive Summary Data is an increasingly crucial component of every aspect of government, from its use in critical decision-making to daily operations and management. In fact, a recent Government Accountability Office report found that data analytics – the process of generating insight from robust and complex data sets – should be a key theme for every agency facing shrinking budgets or other resource constraints.

But to ingrain data analytics into every agency decision, organizations cannot rely on data scientists alone. There is simply too much data and too few skilled professionals.

Instead, it will be up to every public servant to collect, manage, interpret and use data to further government’s missions.

Admittedly, that universal call to action might seem impossible to achieve given workforce shortages, legacy technologies and a growing amount of disparate data.

As this guide explains, however, data analytics doesn’t require complex systems or skills to start turning data into insights. Analytics simply requires an understanding of the data you have at your fingertips and the skills or tools you need to start investigating it.

This guide will help provide that understanding. We’ll explain how to create a “data persona” – a profile of your job, its relationship to data, the goals you might achieve and the tools you need to make it happen with data. We’ll also offer four high-level examples of how data analytics can directly enhance common agency positions. Additionally, we'll provide case studies and advice from real government workers. Finally, we’ll give you a worksheet to get started outlining the role of data in your job.

No matter what your job description says, data analytics is a crucial part of your role. This guide will help you get started making better, data-driven decisions with analytics.

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The Role of Data Analytics in Government Government maintains a wealth of data. Just think of the demographic, operational, intelligence, economic, digital services and environmental data created by agencies every day. And that’s not even considering the data from the private sector that government collects, or the data that citizens generate.

What’s government going to do with all that data? By itself, data isn’t very valuable. It might show you a number, image or other fact that proves or disproves a point, but that really just leads to more questions: Why is that point true? How did it happen? What can we do to replicate that result?

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To answer those questions and get more value from data, government has to use data analytics. Here’s a fancy definition from Techopedia of what that is: Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements.

Sound complicated? It doesn’t have to be. Put more simply, data analytics is the process of turning data into ideas.

The details of those ideas depend on a number of variables, including the type of data you’re using, which tools you have to support your analysis and what skills you have to process your analysis. But the biggest determinant of what ideas you’ll create via data analytics is the question you’re trying to answer. There are four broad possibilities, each supported by a different type of analytics:

1. What happened?

Answered by descriptive analytics

2. Why did it happen?

Answered by diagnostic analytics

3. What will happen?

Answered by predictive analytics

4. How can we make it happen?

Answered by prescriptive analytics

Nationwide, public servants are asking these types of questions and answering them with data analytics. Just take a look at the map below for a survey of public analytics projects.

Lancaster County, Pa. maps opioid drug overdose data to track the epidemic, identify triggers to addiction and increase community awareness.

Chicago’s Department of Streets and Sanitation runs a data analytics program using information from service requests to predict likely locations for rodent outbreaks.

The Intelligence Advanced Research Projects Activity’s Good Judgement Project tests methods for predicting foreign elections, treaty negotiations, disease outbreaks, political instability, weapons tests, cyberattacks and a range of other political events.

The U.S. Postal Service tracks daily package deliveries and truck routes to optimize operations and ensure mail is efficiently delivered on time.

South Carolina’s Department of Revenue is correlating IRS wage information and state tax data to predict fraud and stolen refunds.

New Mexico’s Department of Workforce Solutions matched and analyzed disconnected sets of behavioral and employment data to prevent unemployment insurance fraud and overpayments.

The General Services Administration maintains analytics.usa.gov to “provide a window into how people are interacting with the government online.”

As you can see, data analytics are being used at all levels of government, by different groups for different reasons. But what does data analytics look like in YOUR job? To ask the right questions and find the best answers for your agency, you’ll need a clear understanding of how data fits into your role – even when it’s not written in the job description.

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Crafting a Data Persona 1. BEGIN by thinking through the connection your role has (or could have) to data analytics.

What information do you rely on to do your job? How do you interact with data – whether it’s qualitative or quantitative, structured or unstructured, consolidated or scattered – as you perform daily tasks?

Describe the connection between your job and data in three to five sentences.

3. TOOLS YOU NEED While simple data analysis can be accomplished by searching spreadsheets for trends, there are many tools that can make analytics easier and generate more robust insights. These can be anything from free online platforms to more advanced software and hardware that automatically parse disparate and unformatted data.

4. SKILLS YOU NEED You don’t have to be a data scientist to generate insights from data. Certain skills, however – from soft capabilities like storytelling to more tactical ones like storage mechanics – can help you better manage, correlate and understand your data.

List three to four skills that you’ll need to make the most of your data-driven insights.

List three to four tools that will make your data analytics work easier and more effective.

2. YOUR GOALS Now, think about what you could achieve if you took your work with data to the next level. Instead of using data as raw information, consider analyzing multiple data sets to gain new insights. What could you improve in your job, department or even across the government with that new information?

List three goals you can achieve by using data analytics in your role.

5. GETTING STARTED With limited information, tools, time and budget, it’s impossible to build and apply your data strategy all at once. Plus, you’ll want to start small to minimize risks, learn from your mistakes and gradually improve the way you apply data to decisions.

List three to five small, low-risk steps you can take to make the most of data analytics in your role.

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The Frontline Employee

Whether you’re a program analyst, HR professional, citizen support officer or other frontline employee, data analytics can help you do your job better. While the connection between data and your role may not be obvious, the operational, programmatic and budgetary information you use to do your job actually provides a wealth of potential insights. It’s up to you to make the most of it, even without a robust analytics program in your department.

Your Goals Understand your impact.

If you do nothing else with data, use it to measure the outcomes of your work.

This not only allows you to define your contribution to your agency’s mission, but it also helps your department realize where it is and isn’t meeting the mark with current efforts. That data-informed understanding is the first step to making more of an impact, even as you face shrinking budgets and workforce shortages.

Be more productive.

It’s easy to fall into a routine at work.

Use the data you generate every day (think: timesheets, task lists, measured outcomes) to re-examine that routine.

Determine where you’re working effectively and where there’s room to make a greater impact, more efficiently.

That will not only help your agency meet its mission, but it will also help you propel your career forward.

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Communicate more effectively.

One of the greatest struggles for many frontline employees is showing the real story behind their work. How are you contributing to your agency’s mission and serving citizens? Data can help you show, rather than tell, others how your office or department is making a real-world impact. Bring your data to budget, planning and other meetings with leadership to garner support for your initiatives. Publish your findings to let citizens know what you’re up to and become more transparent.

Tools You Need Data Platform

Whether you use a simple Microsoft Excel spreadsheet or a more sophisticated suite of tools like STATA or IBM SPSS, a data management platform will be necessary to sort and correlate your data.

Visualization Software Rather than culling through spreadsheets of data, use visualization tools to quickly identify and highlight key insights.

Sharing Mechanisms Whether it’s a shared analytics platform, an internal web portal or simply an in-person meeting, you’ll need a way to share your data and the insights you generate to relevant stakeholders.

Skills You Need Organization and Management

Without data analytics tools or programs already in place, you’ll need to take charge of your own data. Especially for information that is scattered and unformatted, you’ll need a thoughtful strategy to collect, organize and analyze your data.

Storytelling You don’t need to talk numbers to show the power of data. You should be able to describe the results of your data-driven decisions in a relatable and impactful way.

Getting Started

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Find your data.

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You might not be supplied with your department’s data already, but there are multiple public data sets and tools specifically created for government employees to (freely) use.

For example, FedScope provides HR data for the entire federal government, as well as basic analytics tools. The Digital Analytics Program provides government website data, while DigitalGov.gov offers ideas for how to use it. For your work, there are probably more job-specific data sets to leverage.

Ask your manager, colleagues or agency data scientists where to find them.

Start local.

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It’s tempting to look at a wealth of data and think you can change your agency in one fell swoop. But to get a handle on data, start by looking in your own cubicle for straightforward data sets (e.g., your timesheet) and small problems to solve (e.g., your productivity on a personal project).

That will help you familiarize yourself with analytics techniques before taking on a more laborious or high-risk project.

Use descriptive analytics.

Similarly, you’ll want to start with the easiest type of analytics. Ultimately, you’ll want to use data to make better decisions and impact change. But to get to know your data and its potential value, start by simply figuring out what it’s telling you about your current state.

This will also help you determine the best questions to ask of your data as you try new types of analytics.

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Confidently plan and manage your future construction and maintenance programs

Make more precise, productive and profitable business decisions Leverage predictive analytics to inform and improve the accuracy of your capital planning and budgeting efforts Gain statistical analysis insights into prices paid and price drivers

To Learn More About Gordian’s RSMeans Enterprise Data Solutions: gordian.com/feddataguide

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Informing Better Construction and Maintenance Programs An interview with Lisa Cooley, Director of Federal Solutions, and Timothy Duggan, Director of Cost Analytics, at Gordian When you think about the role of analytics in government, you probably think about numbers flying through cyberspace to inform unseen or intangible decisions about operations. But in addition to influencing programmatic decisions, data analytics can actually have a dramatic impact on the way physical infrastructure is constructed and managed.

In a recent interview with GovLoop, Lisa Cooley, Director of Federal Solutions, and Timothy Duggan, Director of Cost Analytics, at Gordian explained how analytics can be used to inform and improve construction and maintenance programs in government. Gordian provides decisive RSMeans data and innovative technology to help facility and infrastructure managers use analytics for better decisions and outcomes.

The role of analytics in the future of government construction and maintenance cannot be overstated. Currently, federal facilities and infrastructure managers are confronted with significant challenges. In addition to resource constraints like the hiring freeze and shrinking budgets, they deal with long budgeting cycles in a volatile construction cost market.

“Managers are tasked with predicting construction costs many years out in a very unpredictable market. Projects end up requiring a lot of re-scoping effort to make sure they’re keeping to the budget and the program, even when costs change,” explained Cooley.

Construction market changes in government are swift, even as projects take years to complete. “Mega-projects,” like the Base Realignment and Closure (BRAC) initiative or the proposed new border wall, require so many resources to complete that the local market’s cost and demand balance is quickly and dramatically shifted. At the same time, federal contracting regulations are often disrupted and transformed by new administrations.

To confront these challenges and volatility, managers have to develop a baseline from which to assess changes and inform decisions. As Duggan explained, “history allows us to analyze the cause and effect of shifting markets, to help predict results in this new market. It’s just the size of these different elements and the scope of work that are being expanded or diminished. But all of these changes actually have happened in the past in some shape or form.”

By understanding how market shifts have impacted construction and maintenance project costs in the past, project managers can better manage future market shifts without disruption to their programs.

Federal agencies are sitting on a treasure trove of historic data that they collect under mandate. Managers should be leveraging that data to understand how much past projects cost in labor and time to construct, as well as maintain. Then, they can better understand cost drivers including supply costs, federal regulations, labor demands, agency budget and the condition of existing real property assets.

However, the reliability and quality of data held by disparate agencies and systems is sometimes uncertain. Moreover, agencies commonly lack the tools and external data assets to analyze that data and generate insights. As a result, managers often need to draw in external data sets, as well as consultative services from experts who understand that data.

“Gordian’s value proposition is to normalize and validate historic facilities and project information, and then intersect it with historic cost databases and new advanced analytics based on economic predictive inputs. This results in statistical analysis insights into prices paid and price drivers,” said Duggan.

At the Department of Energy (DOE), managers have already made significant strides towards better asset maintenance and construction with predictive tools to budget sustainment costs. The agency used Gordian’s RSMeans labor, material and equipment costs, as well as preventative and repair maintenance projections, to accurately calculate the replacement value and sustainment costs for their facilities.

That data informed a 10-year site plan that complies with OMB requirements. DOE can also export that data to its internal Facilities Information Management System where it is used to consistently update building models and cost forecasts.

However, many agencies will need more robust tools to support this type of in-depth analysis. Duggan and Cooley emphasized seeking commercial solutions that have the computing power and machine learning capabilities to consolidate and analyze these complex data sets for relevant trends.

“The right analytical tools can help federal managers do more with less,” Cooley said. Those tools, combined with historical and normalized data, are what set facilities and construction managers up to succeed in a volatile market. Ultimately, it will be robust data analytics that ensures that government infrastructure continues to be built and maintained in an effective manner.

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Using the Digital Analytics Program in Federal Government An interview with Timothy Lowden, Program Manager for the Digital Analytics Program at GSA

Government is creating and storing data at unimaginable rates. And within that data, there’s a wealth of information to glean.

What citizens want, where operational waste exists, what type of fraud is being executed and how services are being used are just a few of the insights hidden in this wealth of data. Yet many government departments aren’t finding these answers. Why?

provides a common web analytics tool that can be used across many different websites in government. That avoids duplication of agencies purchasing the same tool and going through separate procurements.

Timothy Lowden, Program Manager for the Digital Analytics Program at GSA, explained that it’s not for a lack of enthusiasm on the part of public servants. “We find a lot a people that get excited about having all this data at their fingertips, but they’re not sure what to do with it,” he said in a recent interview with GovLoop.

Second, DAP allows government leaders “to get a bird’s-eye view of public interaction with the federal web space at-large.”

That overview helps answer questions about what types of devices people use, as well as what content they seek from those access points. “The answers to those questions can prove to be very useful as we try to improve digital services for the entire government,” Lowden said.

That’s why GSA started the Digital Analytics Program (DAP), a hosted shared service provided by the Technology Transformation Service. It was created out of the belief that “every agency should have a metrics strategy to measure performance, customer satisfaction, and engagement, and use the data to make continuous improvements to serve its customers,” says the website.

To meet that objective, DAP provides comprehensive, easy-touse analytics for every section of federal government’s online presence.

The Program Established as part of President Obama’s Digital Government Strategy in 2012, the purpose of DAP is twofold. First, it

The program gives any participating agency access to a wealth of website data, including user traffic, clicks, completed actions and website performance, that is collected in real time. Historical data is also compiled for easy reference. That website-specific and cross-departmental comparative data foster decision-making related to user experience, design, resourcing and content at the site level.

Training and Support To help both frontline employees and agency leaders understand how to make the most of this data, DAP also offers a robust set of training opportunities, including a threehour DAP 101 course, a follow-up DAP 201 course and topical one-hour webinars on subjects like custom reports, campaign URLs and user behavior measurement. All of those trainings are also recorded on DigitalGov’s YouTube Analytics playlist, so remote users can take advantage.

Additionally, DAP provides support for users who have less technical challenges to getting data programs off the ground.

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The Digital Analytics Program creates and supports a number of resources and tools to help government users make the most of their data. Check them out: DAP Implementation Guide A guide to using DAP data and processes

analytics.usa.gov A public dashboard that offers high-level DAP data

DAP on GitHub A repository that provides a JavaScript file for federal agencies to link or embed in their websites to participate in the DAP

GSA’s Analytics Playlist A YouTube playlist of analytics training and instructional videos for DAP users

“The No. 1 thing that DAP users need to succeed is familiarity and buy-in from their leadership,” Lowden said. “When a leader sees the value in making an experience better for the user, and empowers her or his staff to use the data to make improvements, we see incredible results.”

In many cases, Lowden says he sees frontline employees sending valuable data to their managers only to never hear back on actionable next steps. That’s often because leaders don’t understand the value in the information they’re receiving. “So part of DAP is not just training people to use data, but also encouraging them to manage up,” Lowden said.

“You have to explain how data is important and how it can be used to make a better experience for users.”

DAP in Action DAP is already spurring change in the federal space. Lowden’s favorite example comes from the Federal Trade Commission, where one team is using site search data to improve their homepage. Using DAP data, the web team was able to determine that users were referencing the FTC webpage to fulfill mission-related tasks. However, those tasks weren’t highlighted on the main page, making it difficult for users to locate necessary resources.

The team redesigned the homepage to highlight what DAP information showed to be the most sought-after tasks. As a result, traffic from the homepage to the tasks in the Take Action area jumped dramatically — 47% for Complaint Assistant, 54% for Do Not Call, 9,691% for ID theft.

DAP Across Government FTC isn’t the only success story from DAP’s first few years in action. Teams at USAJOBS, the Health Resources and Services Administration and USA.gov have also used

analytics from the program to inform various operational and outreach strategies.

What’s more, other agencies are starting to learn from these early wins. While agencies shouldn’t use DAP data to publicize results of other departments, leaders should reference other agency data to provide perspective on their own results.

“Within government, we encourage all users to collaborate with other agencies to use the data for benchmarking, removal of repetitive content and sharing of best practices,” Lowden explained. “Many of the HHS sites across various operating divisions share common goals, for example. And the State Department works closely with Citizenship and Immigration Services (USCIS) with regard to visas and immigration, so there is opportunity there to correlate data.”

The Future Using the services and data available through DAP, Lowden’s team at GSA hopes to encourage users across all levels of government to start leveraging analytics for better decisionmaking. He also hopes that the momentum of DAP will encourage users to do even more.

“Web analytics data is just one piece of the overall puzzle when it comes to understanding your users and providing the best experiences,” Lowden said. “I also recommend using heat-mapping tools, feedback tools, A/B testing and usability testing, among others. Our hope is that web analytics data via DAP can be a gateway into using more data.”

Ultimately, DAP is just one tool to get public servants more engaged in data initiatives and decision-making processes.

To get involved, check out the resources box on this page or reach out to dap@support.digitalgov.gov for help.

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The Data Scientist As a data scientist, your responsibility to turn data into insights is obvious. It’s your job! But that’s just the beginning. You’re also in charge of organizing and disseminating agency data, translating complex ideas into understandable takeaways for decision-makers and setting data strategies that other public servants can advance with your help.

Your Goals

Wrangle data.

Your agency has a lot of data – much of which your frontline users and administrators don’t know about or don’t know what to do with. Your first objective is to collect relevant data from inside and outside your agency.

Then you’ll want to consolidate, tag and organize it so that it can be used to generate insights.

Generate relatable information.

Although you can find all the insights in the world, your real goal is to distill incomprehensible big data into insights that decision-makers can understand.

Because those leaders often lack the analytics and computer skills that you have, you’ll need to communicate complex ideas in a more relatable way.

That translation of data to real-world problems and solutions is the only way you’ll really make an impact with your analytics.

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Share data.

You’ll likely perform the majority of complex analytics, but you can’t tackle every data project at your agency.

Your last objective is to put more data, along with the tools to use it, in the hands of other agency stakeholders.

Publish organized data in open source platforms so that users across departments can perform their own analyses and become more familiar with the value of data.

Tools You Need

Skills You Need

TOOLS YOU NEED

SKILLS YOU NEED

Big data processing

Data science

Software such as Hadoop, High Performance Computing Cluster or Hydra enables you to query and process large data sets that would otherwise be indecipherable through manual analysis.

A degree in data science isn’t required for this role, but you’ll need to know how to parse large data sets using logic, the scientific method and statistical tools.

Statistical analysis tools

Programming

Tools like R, SAS, Matlab, SPSS and STATA allow you to perform analysis without manually comparing rows of data.

Scripting languages like Python, Java, C++, Perl and Ruby are used to develop and query custom data analysis solutions, which you will likely need for agency-specific analytics.

Publishing software

Product management

Content management and publication platforms like Drupal are used to distribute your data projects so that others can check your analysis and perform additional iterations on their own.

In essence, your data analysis is a product that you build, improve and share with agency stakeholders to impact decision-making. You need the organizational and management skills to stay on track and deliver understandable results in a relevant timeframe.

Getting Started

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Consolidate multiple datasets.

Whether you already have an analytics program or not, it’s likely that your agency’s data is spread across systems, platforms and locations. For your own projects and those of your non-data scientist peers, you’ll need as much data as possible in one accessible place. Start by consolidating information from multiple locations.

Organize your information.

You’ll also want to organize your collected data before diving into it. Create a standard system of tagging and storing formatted and unformatted data, so that you and your colleagues can quickly access relevant information for analysis.

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Create a governance strategy.

Once you have consolidated and organized your data, you’ll want to start analyzing it. But since more data will be created while you do that, you’ll need to have a governance strategy in place to dictate where and how that new information is managed, without your constant intervention.

Translate early results.

Forget emailing a spreadsheet of numeric outcomes to department leaders. If you’re going to get others on board with the value of data analytics, you’re going to have to explain that value in relatable terms. Start with a project that impacts multiple cohorts and explain the results in simple quantitative and qualitative terms.

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A DATA ANALYTICS PLATFORM FOR THREAT DETECTION ViON’s DataAdapt Platform accelerates cyber and criminal investigations through: • Accelerated data ingest • Identifying intersections in data • Connecting data points through entity analytics Learn more: www.vion.com/dataadapt

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Applying Entity Analytics at Your Agency

An interview with Roman Chanclor, Solution Sales Specialist, and Clint Green, Director of Advanced Analytic Strategies and Development, at ViON While many agencies are beginning to use analytics to understand events impacting their organization, those system-centric approaches often miss relevant connections between other objects, people, places or events. Without that context, agencies are forced to work with an incomplete view of their organization to inform decisions.

defined by a number of different identifiers, such as a social security number, a social media handle, a location, a name and even a nickname. To track that person across an enterprise, those disparate data points have to be reconciled and then analyzed. Then they have to be related to other entities, which might also have numerous different identifiers.

To gain a more holistic picture of what’s happening at your agency, Roman Chanclor, Solution Sales Specialist, and Clint Green, Director of Advanced Analytic Strategies and Development at ViON, suggested taking an entity-based approach to data analytics. ViON is a leading provider of solutions to help organizations make the most of their data.

Entity analytics is a complex process. IT staff commonly attempt to overcome these challenges through manual methods. However, that approach can’t match the explosive rate of data growth today.

Entity Analytics is an incremental context accumulator for detecting like and related entities across large, sparse, and disparate collections of data, including both new and old data, small and big data environments, to perform analytics on events, people, things, transactions, and relationships. In other words, entity analytics uses data from multiple sources and assembles a single story by making connections between those disparate points.

This approach is critical to many agency operations. Consider background investigations, for instance, which most agencies have to perform to hire employees or grant visas. Entity analytics can leverage big data analytics to examine an individual’s background from all perspectives. Social media profiles, aliases, public associations, and other personal traits can be correlated with demographic and government information like driver’s license and passport details. Together, those details can create a more complete picture to aid in the investigation.

“When you start to connect individual events to people, to locations, and to other entities, you start to understand them in a much broader concept,” said Green.

But for organizations without advanced analytics tools, achieving this broader view can be a challenge. Determining correlation and causality between entities requires an in-depth understanding of how those objects and events connect on operational and technical levels across the organization. However, organizational and technical siloes prevent IT personnel from easily combining and analyzing data from across the enterprise.

That data is also often a combination of structured and unstructured information, making it even more difficult to consolidate and compare. For instance, one person may be

Nevertheless, agencies shouldn’t be dissuaded from pursuing this approach to analytics. “It’s important to decompose all the effort that goes into entity analytics so people can understand that it’s approachable. There isn’t a huge barrier to entry if you use the technologies available,” Green said.

“There’s no reason to leave that context on the table, for fear that it might be too complicated a task,” agreed Chanclor.

The right tools can vastly simplify and empower an agency approach to entity analytics. Automated solutions can quickly sort and analyze data ¬– even unstructured and disparate information ¬– without taxing IT personnel. For instance, entity analytics can be applied to cybersecurity and fraud prevention operations with ViON’s DataAdapt Threat Detect. That solution ingests data from available sources and performs analytics to detect intersections in the data for cyberthreat and fraud detection, continuously learning with each new set of data.

The platform also accomplishes entity resolution. “Our approach uses a probabilistic engine that applies a statistical understanding of entities,” said Green. “Given what is known about an entity already, data can be disambiguated, deduplicated, or in other ways refined to provide a more accurate picture of the real world situation.”

Once IT personnel know who and what is happening on their network, they can begin to understand how different entities interact to form a more complete view of their organization.

They can then use that understanding to inform proactive cybersecurity, fraud detection, or other mission strategies.

In the face of constantly evolving technology, it’s imperative for government to move beyond manual, reactive processes of data identification. Entity analytics can help IT personnel move their agencies forward with automated tools that consolidate and make the most of disparate government data.

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The IT Manager Your entire agency runs on data that needs to be consolidated, arranged, stored and accessed. That requires a robust infrastructure of networking, computing and storage that you’ll manage. But in addition to supporting analytics, you’ll also use analytics to make sure you’re providing the right resources and security to your organization.

Your Goals Provision supporting infrastructure.

Allocate resources more effectively.

Secure your organization.

Sophisticated data analysis requires massive amounts of storage and computing power. Those requirements will only grow as data increases, even if your IT budgets decrease or your systems age. It’s your job to effectively provision what you have to support high-priority data projects. At the same time, you’ll need to consider how future technology acquisitions can help support data analytics.

In addition to supporting data, you’ll also use operational and network data to understand how IT resources are used, both in your department and across the agency. Especially with on-demand, cloud-based services becoming the norm, you need to use data to monitor the requirements of individual systems and users. Then, compare that demand to your current supply architecture to determine how you should shift your resource allocations – ultimately saving time and money for your agency.

Along with resource monitoring, your most critical application of analytics will be for cybersecurity. Analyze data generated from web traffic, in-house technology systems and employees to understand what’s happening on your network, identify vulnerabilities and catch cyberattacks as quickly as possible. With robust analytics, you can create automated alerts that correlate and act on disparate data points across your network.

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Tools You Need Sensors

While many IT systems generate significant data, some network endpoints can easily go unmonitored if you don’t create specific sensors to collect outputs and other data.

Network mapping You have to know what comprises your infrastructure, how each component is connected to and impacts others, and what data each produces in order to start making the most of your network.

Automation No matter how productive you are, you’ll need automated tools to identify, alert and react to basic data correlations without your interference.

Skills You Need Cybersecurity

Securing data and the systems that create it is an increasingly vital part of IT jobs. As you start analyzing data, you’ll need a baseline understanding of cyber-risk indicators to create and understand security alerts.

Computing Data storage, software applications, networking and other computing skills are all normal requirements of IT jobs in government. They’re also critical to ensuring you can support the analytics your agency performs.

Personnel management It’s a common misconception that IT roles deal only with technology. In fact, your greatest responsibility is to manage and work with the people who rely on technology to perform analytics and other duties.

Getting Started

1

Talk to data users.

Don’t rely on quantitative data alone to understand the needs of your agency. Instead, talk to everyone from agency leaders to frontline employees to understand how they access and understand organizational data. Specifically ask what technologies are supporting their efforts and what’s holding them back. That will help you set effective IT priorities to support analytics.

2

Learn your network.

3

Before you start using data, or even building the technology to support it, you need to understand what you already have. What systems are generating what kind of data, which users leverage which tools and what endpoints expose your network to more information or threats are all considerations to explore before you begin structuring your systems for new data processes.

Reduce alerts.

Don’t be fooled into thinking more alerts equal more insights. If you have too many automated alerts, you’ll end up creating a new type of big data that’s just as unhelpful as singular data points due to the scope and frequency of their use. Instead, target specific systems or types of risks that are high-priority while reducing the noise others make.

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Business Intelligence

Better Data.

Better Analytics.

Learn why Information Builders gets the highest percentage of recommendations and the widest adoption rates of any analytics platform at informationbuilders.com/products/intelligence.

Data Integrity

Data Integration

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I N D U S T R Y

S P O T L I G H T

A Progressive Approach to Data Analytics

An interview with Jake Freivald, Vice President of Product Marketing at Information Builders It’s no longer a question of whether data should be used to inform decisions in government. Agency leaders know that the massive amounts of information generated by business operations, employees and citizens can’t be ignored if organizations are going to truly meet their missions. The question now is how to make the most of the information, and turn it into insights in a timely fashion.

“Government organizations are working toward their core mission” said Jake Freivald, Vice President at Information Builders. “But right now, they’re having a hard time doing more than just basic reporting.”

In an interview with GovLoop, Freivald explained that many agencies lack the tools and processes to dive into their disparate data and form better insights. Information Builders addresses this issue, providing a suite of technologies to help organizations access, integrate and understand their data.

For many agencies, the main roadblock to data analytics is a technical one. Data often lies in many different systems, in various formats. Because most government organizations continue to rely on legacy systems, it’s difficult to marry that data to analyze it in a consistent manner. Agencies also usually lack the resources to completely overhaul their IT infrastructures to create a more coherent data environment.

For those agencies, a software solution that can consolidate disparate data from various sources without changing the underlying infrastructure is the best solution. Tools like Information Builder’s analytics and data management platform can leverage data from across an enterprise and make it accessible in one location.

Of course, many agency leaders will also point to a lack of data knowledge and skills within the workforce as a primary obstacle to robust analytics. However, Freivald explained that the right technology can help mitigate this challenge. The right data analytics platform will present consolidated data in visual formats that allow users to quickly digest information and generate insights.

“Being able to standardize and reconcile different data sources is important,” he said. “But you also want a tool that brings that data together in a form that is usable to a large number of people, or even the public, without having to train and license them to use these tools.”

However, finding the right tool is only one step towards better data analytics. The second step is to use those tools to gradually expand access to an agency’s data. Information Builders calls this a

progressive approach to analytics and data management. Selecting tools that can be incrementally invested in as you need more capability is extremely important as well.

“You really want to get started with the data that you have,” he said.

“If you can use one data source and create a dashboard that people actually use, then they will come back for more. Then you can start building in new parameters within the applications you’ve built to create additional value.”

Freivald explained that the ultimate goal for most data programs is predictive analytics – the most advanced and informative type of data analytics. However, newcomers to analytics should start with data applications that are easier to accomplish and grow from there.

The state of Louisiana’s Department of Children and Family Services’ program to curb fraud is a prime example of this progressive approach to data analytics. The department already had reporting mechanisms in place that were supposed to allow them to detect fraud in the Supplemental Nutrition Assistance Program (SNAP). However, the reports were difficult to consume.

Using Information Builder’s platform, the department was able to integrate multiple data sources to better understand where, how and why fraud was occurring without having to manually compare and correlate reports. Incorporating mapping technology into the solution made it much easier to consume insights into where fraud was likely occurring. That allowed the department to more effectively counter fraud and abuse of the program, while saving them time, money, and employee productivity.

But that was only the first step for Louisiana’s application. Using that initial data, the department realized they could also generate other insights about SNAP, including how people were using the program to save money and what further resources they could provide to legitimate users. Now, they’re using their model to help other departments provide similar insights into their areas of business.

“Louisiana is integrating large data sources across multiple parts of the organization to get a single view of the citizen so they can do more for their citizens to provide better service and prevent fraud more effectively,” Freivald said.

That’s the power of progressive analytics. By installing the right tools, starting small, and adding additional functionality over time, organizations can make a big impact on the way government serves citizens.

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S T A T E

&

L O C A L

S P O T L I G H T

How to Build a Culture of Data Analytics An interview with Dana Burmaster, Policy Initiatives Advisor, and Kelli Kaalele, Policy Director at the Department of Administration’s Division of Enterprise Technology for the state of Wisconsin In 2016, Wisconsin Governor Scott Walker signed an executive order to enhance the state’s efficiency and transparency. To meet that call to action, the administration began a statewide push to use more and better data to measure the state’s performance.

First, the state had to establish a platform that made reliable, standardized data available at an enterprise level. That was accomplished through an enterprise resource planning (ERP) implementation in 2016, which replaced 140 disparate administrative systems across dozens of agencies with one efficient system. The ERP has made it much easier to leverage available operational data. Currently the focus is on procurement activities, so that any department’s managers can access enterprise-wide information to inform purchasing decisions. But soon the analysis will expand to financial and human resources data.

While that ERP project serves as the springboard for the new data analytics emphasis in Wisconsin, it’s only the beginning.

The state’s executive branch is also working to collect and publish departmental data on a variety of topics outside procurement, in order to increase transparency and expand the use of data in decision-making.

In an interview with GovLoop, Dana Burmaster, Director of Planning and Performance & Department of Administration

and Kelli Kaalele, Policy Director at the Department of Administration’s Division of Enterprise Technology, said there is a noticeable uptick in the use of data to drive discussions and decisions in government.

While the emphasis on data analytics is still in its early stages in Wisconsin, they have noticed that some tactics seem to be helping government agencies embrace the change.

Specifically, they highlighted three strategies that have emerged from agencies’ experiences in encouraging the use of data analysis:

Strategy 1:

Recognize that analytics requires change.

Incorporating data analytics into government operations requires a significant cultural change. Therefore, recognizing and confronting the fact that some employees will be nervous to delve into data analysis is a necessary first step to changing organizational culture.

The Administration emphasized in its messaging that the data is best used to identify areas of improvement or to build on program successes.

This framing of the initiative helped promote a positive connotation of data analytics that focused on progress and understanding.

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Strategy 2:

Encourage sharing (in any form).

While messaging is important, the best way to make people comfortable with data is to get them started using it. In Wisconsin, users were acclimated to data analytics by first being allowed to publish datasets of their choosing.

Rather than requiring specific data sets or formats, the administration encouraged individual teams to start their data analytics journeys with any data they had available to share.

That allowed users to become comfortable with the process and understand how others would use data, before they released more high-impact information.

Strategy 3:

Ensure executive engagement.

Wisconsin is also tackling the challenge of cultural transformation from the top tiers of leadership. It’s a commonly held belief that executive support is necessary to launching new initiatives in government. You need budget and time to practice new projects, after all. However, early exercises in Wisconsin found that you need more than just support to really get data initiatives off the ground.

Teams need leaders engaged in data in order to engrain analytics into processes. Executive engagement emphasizes that analytics are a core part of agency goals and holds individual departments more accountable to their data collection and results.

Following Governor Walker’s lead in the Executive Order, in Wisconsin, state leaders from the executive branch review quarterly performance data and operational scorecards at monthly status meetings. By engaging with this data, executives show their dedication to leveraging data while simultaneously making data-driven discussions a norm at agencies.

The Next Stage Data analysis is becoming a central component of many discussions and decisions in Wisconsin, but there is still much more to do. While the administration has seen early success in their efforts, they want to fine-tune the process of collecting and sharing data.

To that end, the administration created a working group to examine current data. The group will work to develop guidance for agencies, giving them more direction regarding the type and format of data to collect in order to assist decision makers. Additionally, they’ll be working to add large datasets – specifically HR and finance data – to the state’s ERP analytics program.

These steps of examination, consolidation, and organization represent the logical next iteration of a statewide data analytics program. However, it can’t be the starting point for organizations unaccustomed to data sharing and analysis. Data analytics starts with a cultural shift, encouraged by leadership and practiced in small steps. That’s the secret to Wisconsin’s early success and the foundation for future analytics in government.

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P E R S O N A

F O U R

The Agency Leader As an agency leader, you might not perform analytics in your day-today role. But you will want your employees to use data consistently and thoughtfully, which requires your support and engagement. You’ll also want to use the insights they generate to measure the impact of your organization and make better decisions going forward. Ultimately, you’ll use data analytics to further the mission of your agency.

Your Goals Create a data-centric culture.

Provide resources for analytics.

Integrate data into decisions.

You may not be diving into data sets yourself, but you’ll want your employees to feel empowered to generate unique insights for your organization.

That will only happen if you build a culture that embraces data analytics, allowing employees to dedicate time and resources to projects and engaging with the results they produce.

As other personas in this guide suggest, sophisticated data analytics requires a number of resources to be successful.

Your goal is to make sure your employees have the understanding, technologies and opportunity to make the most of agency data. That will require you to push for budget allocations and employee time and training that might not otherwise be available to your agency.

This is important for every person in your organization, but you most of all. Not only will data analytics help you make better decisions regarding agency strategy, but using data in those decisions will help others understand what your agency is doing, why it’s doing it and where you’re headed in the future. Use data to back up your conclusions, and communicate that datadriven logic to your internal and external stakeholders.

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Tools You Need Champions

You can’t do everything; you need departmentlevel and frontline employees to help translate and disseminate your data ambitions to smaller groups within your agency.

Communication channels More than just email, you need multimedia avenues to promote your agency’s use of data analytics to the widest range of internal and external stakeholders to communicate your progress.

Partnerships Your data programs will be more resourceefficient and more informed if you partner with other agencies to share data and – more importantly – the insights they produce.

Skills You Need Market knowledge

You don’t need to know the latest technology in analytics, but you do need an understanding of what’s happening in the analytics field and how it could be applied to your agency to set the agenda for your own projects and goals.

Computing Analytics takes multiple labor and technology resources, which may be hard to acquire under constrained budgets. Based on the specific goals of your data projects, you must help employees prioritize which resources are must-haves vs. nice-to-haves.

Consensus-building No matter how low-risk or simple your first data strategy is, there will be employees who are reticent to divulge proprietary data sets and take on a new process of decision-making. As a leader, it’s up to you to build consensus over the future of analytics in government.

Getting Started

1

Lead by example.

The next time you draft a memo or approve a policy, take the time to find or request data that supports your thinking and ultimate recommendations. Then, make the insights from that data the driving force in the explanation of your decisions. That will show others that you’re following your own advice and incorporating analytics into your processes and choices.

2

Foster data-driven discussions.

Your first instinct might be to start making decisions with data, but your real motivation should be to infuse data analysis into even non-critical processes. Bring data to conversations with your employees, hold them accountable for their analysis and use numbers to frame discussions about future goals.

3

Encourage failure.

For many employees, data analytics will be a new endeavor. As a result, they may be reticent to dedicate time or other resources to a project when they aren’t sure what outcomes they can effectively produce. Your job is to reassure them that early failures, when taken on low-risk projects, are acceptable. In fact, you should frame them as ways for them to learn and move analytics forward.

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Y O U R

P E R S O N A

Use this template to build your own data analytics persona.

Your Goals

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Tools You Need

Skills You Need

Getting Started

1

2

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Conclusion While data analytics and all its variants have become buzzwords in government, it’s not always clear why. Especially if you don’t work in spreadsheets of numbers all day or your job description says nothing about using data, it might seem like analytics is really just another tech phrase that doesn’t relate to you.

But the reality is that data analytics will be necessary to the future of government. With constrained budgets, shrinking workforces and a greater reliance on technology, agencies will require the insights of analytics to make smarter decisions and secure their missions.

No matter what position you hold, it’s your responsibility to understand how analytics creates those insights and to generate insights of your own. Outline your goals, acquire tools and build your skillset to apply data analytics to your role. Then, get started making the public sector more efficient, productive and data-driven.

Thank You

About GovLoop

GovLoop’s mission is to “connect government to improve government.” We aim to inspire public-sector professionals by serving as the knowledge network for government. GovLoop connects more than 250,000 members, fostering cross-government collaboration, solving common problems and advancing government careers.

GovLoop is headquartered in Washington, D.C., with a team of dedicated professionals who share a commitment to connect and improve government.

For more information about this report, please reach out to info@govloop.com.

Thank you to Gordian, Information Builders and ViON for their support of this valuable resource for public-sector professionals.

Author

Hannah Moss, Senior Editor & Project Manager

Designer

govloop.com | @govloop

Kaitlyn Baker, Lead Graphic Designer

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