2019 Agenda

Stay tuned for the 2020 Agenda!

For all the technological progress made in the last century, it seems we have an overabundance of data and very little in the way of actual information. The 116th Congress is making steady strides to implement an information-driven government, including modernization of the federal grant reporting process. Our grant reporting process should work for, not against, those advancing the public good. Rep. Foxx spearheads this effort with her bipartisan Grant Reporting Efficiency and Agreements Transparency (GREAT)Act, which would leverage data provided in grant reports to increase efficiency and transparency for the over $600 billion spent annually on federal grants. Making grant report information available in an open government data structure would alleviate grantee compliance burdens, provide insights for Congress and grant-making agencies, and facilitate program evaluation. The possibilities for government modernization are endless; now is a unique moment for recognizing tangible ways to bring grant reporting into the 21st Century.For all the technological progress made in the last century, it seems we have an overabundance of data and very little in the way of actual information. The 116th Congress is making steady strides to implement an information-driven government, including modernization of the federal grant reporting process. Our grant reporting process should work for, not against, those advancing the public good. Rep. Foxx spearheads this effort with her bipartisan Grant Reporting Efficiency and Agreements Transparency (GREAT)Act, which would leverage data provided in grant reports to increase efficiency and transparency for the over $600 billion spent annually on federal grants. Making grant report information available in an open government data structure would alleviate grantee compliance burdens, provide insights for Congress and grant-making agencies, and facilitate program evaluation. The possibilities for government modernization are endless; now is a unique moment for recognizing tangible ways to bring grant reporting into the 21st Century

This session will cover:

·         Overview of Treasury’s work to expand financial transparency and increase the use of data.

·         Provide a demo of Treasury’s new tools on resources on the Data Lab.

·         Discuss the potential to use data to better inform decision-making in government.

Big data, advanced analytics, and data-driven decision making have been both disrupting and enhancing the government’s ability to detect and mitigate fraud, waste, abuse, and risk. From developing data-driven enterprise risk and fraud frameworks to improving racking-and-stacking to enhancing big data pattern discovery to deploying predictive risk models, hear from key fraud and risk analytics champions across the government on how they’ve (A) designed and deployed innovative analytic solutions, (B) catalyzed change and adoption across their agencies, and (C) tackled common pain points and challenges.

BUYSMARTER is a transformative, data-driven initiative leveraging the collective purchasing power of the U.S. Department of Health and Human Services (HHS) to secure lower prices, achieve operational efficiencies, and generate cost savings on goods and services. BUYSMARTER uses artificial intelligence (A.I.) and blockchain technology to analyze departmental requirements based on current HHS-wide spend data. This helps identify opportunities to consolidate contract vehicles across agencies within HHS to leverage overlapping requirements at a significant cost savings for the federal government.

 This session will explore the new paradigm of acquisition that BUYSMARTER leverages. This new standard of excellence will not be a simple change or tweak over existing acquisition processes; it will create a new, transformational structure of how agencies acquire their goods and services together. Attendees will learn how BUYSMARTER has uses A.I. and and new and emerging technologies to assess, evaluate, coordinate, and develop a full-spectrum HHS acquisition strategy that streamlines the entire buying lifecycle by considering and validating each activity, function, condition, requirement, and output in support of HHS and divisional operating requirements. Discover how the BUYSMARTER initiative is redefining data-driven acquisitions processes.

·         Session will outline a brief history of the Initiative, outline what has been done so far in the development and early implementation as well as talk about the long term vision for BUYSMARTER

The Canada Revenue Agency (CRA) has experienced a substantial increase in interest for data and analytics. The presentation shares the Non-Filer Program’s journey towards a comprehensive and integrated approach to applied analytics. It provides insight into complementary fields and approaches used to introduce and fully leverage world-class applied analytics in decision-making. The progressive use of analytics is demonstrated through the following stages: research, the development of predictive models (including those using neural nets), and efficiency testing through randomized controlled trials, as well as the enhancement and deployment of predictive models; all with a view of improving business results/outcomes.

This session will outline the SEC’s Structured Disclosure rule makings and the resulting enhancements in the accessibility and reusability of registrant disclosures for use and analysis by investors, analysts, and Commission staff as well as by other agencies and a broad range of market participants.  Policy planning considerations include the type and nature of disclosures, the relevance of industry driven open market standards, the supplemental dissemination of disclosures, and the relevance of proactive data quality and risk assessments.  Participants will also learn where to access the structured disclosures and how the structured data exposes disclosures not previously available from traditional commercial sources thereby improving transparency as well as new green field research areas enabled by the standardized meta-data.   Finally, participants will observe the analytical, data quality and review features available within the open source Inline XBRL viewer along with the process and analytical benefits enabled.  

The Army Talent Management Task Force (ATMTF) is charged with examining data and analytical tools that enable a better understanding of officers’ knowledge, skills, behaviors, and preferences (KSB-Ps) to optimally employ them and increase readiness. This concept requires the Army to leverage existing data collection and analytical efforts and integrate those with new collection and analytical programs to provide a more holistic look at an officer’s KSB-Ps relative to their potential for assignment, development, recruitment, and retention. To this end, the ATMTF must identify gaps in data collection and analytic capability, and recommend capabilities to advance the state of human capital analytics. This session will review the Task Force’s current analytical initiatives and a vision for effective partnering of industry, academia, other Services, and associated stakeholders to advance data augmented human capital decision making.

This talk is about how we can utilize design thinking to help better define data science problems upfront and help reduce requirements churn. It makes a business case for UX feedback in many stages of the Data Science life cycle and aims to bring an awareness of UX as a discipline in the context of Data Science and AI.It intends to bring a point of view that is a bit outside (but still complementary) of a data scientist’s typical ways of thinking about DS work.It also explores ways in which AI can help UX.

Join Paul Horan for a discussion on cross-agency collaboration at scale with Snowflake, the first data warehouse built for the cloud. We’ll examine how agencies can leverage secure data sharing and enable a multi-cloud strategy to instantly and cost-effectively scale your analytics. 

Deloitte’s Ashwin Admala and Tom Sawyer Software’s Kevin Madden will demystify graph analytics and network visualizations and discuss how agencies use them to solve complex problems. Mr. Admala will examine how data-driven graph visualization of a federal healthcare reporting database reveals hidden connections, like those between popular drugs and their side effects, to assist investigators. Mr. Madden will conduct live demonstrations and cover topics of importance to agencies such as:

• Crime and terror social network analysis
• Fraud detection
• Unified views of logical, geospatial, and times series data with sentiment analysis
• Graph database visualization, query and analysis
• Network routing and logistics
• Model-based Systems Engineering diagram navigation

Attendees will learn how they can improve results with sophisticated graph visualization and analytics. They will see how more precise automated diagram layout and customization enhances communication with stakeholders to enable more informed decisions.

In February 2019, the White House released the “President’s Executive Order for American AI Leadership.” The Executive Order outlines strategic focus areas for continued AI investments across the federal government. This panel will consist of experienced Chief Data Officers across the federal government. Come hear them discuss key takeaways, how they are applying the Executive Order in their agencies, key challenges and how they have been tackling them, and recommendations for audience members (federal leaders, federal analytics practitioners, and industry partners) on how to support the practical implementation of the Executive Order.

The Department of Veterans Affairs (VA) Office of Inspector General (OIG) conducts oversight of VA programs and services, which is a monumental undertaking in the context of VA’s 2019 budget of $201.1 billion; VA’s status as the second-largest federal employer, with more than 380,000 employees serving an estimated 19.6 million veterans; and the complexity of VA programs and services, which includes operating the country’s largest integrated healthcare system. Since 2018, the VA OIG has partnered with Booz Allen Hamilton to establish and sustain a Predictive Data Analytics and Modeling Program to more proactively detect and mitigate the risk of fraud, waste, and abuse across VA programs and services. This presentation will draw on a case study involving VA’s $12.4 billion educational benefits programs for veterans to showcase the OIG’s successes and lessons learned for leveraging subject matter expertise and data-derived insights to generate leads and self-service tools that meaningfully enhance oversight activities. To that end, we will share VA OIG’s insights regarding how to: (a) stand-up productive, cross-discipline teams; (b) select the most effective analytic methods and techniques for common use cases; and (c) drive adoption from leadership to the front line.

HUD’s mission is to create strong, sustainable, and inclusive communities; and utilize housing as a platform for improving the quality of life.  To achieve this end, HUD has numerous critical business processes which rely on disparate systems across multiple program areas. These legacy systems often create barriers for HUD to make informed decisions and execute its mission efficiently and effectively.

To enable ongoing business transformation & IT modernization initiatives being executed across the agency, HUD leveraged its institutional knowledge & experience with Microsoft technologies to develop an Enterprise Data Management (EDM) solution to enable downstream business process improvements, including transparency, data analytics, reporting and compliance. 

This session will provide the audience with HUD’s use of EDM and associated applications/services.

The Canada Revenue Agency (CRA) is investigating practical applications of behavioral insights to support evidence-based decision making. Behavioral insights yield innovative new tools in the form of nudges designed to improve tax compliance, and help taxpayers connect to benefits and credits available to them. To measure the impact of nudges, several randomized controlled trials have been conducted in the Collections and Verification Branch’s, Non-Filer and Collections programs. The presentation aims to share experiences including best practices and lessons learned, in the design, implementation, analysis, as well as the measurable benefits of selected nudge experiments.

 I will give an introduction to OPA, its stakeholders, mission and research capabilities and discuss some current and future research efforts of OPA’s Data Science Directorate.

From the perspective of an Office of the Chief Data Officer, this session will cover how to develop prioritized projects for data management and analytics, and build and organization to manage and communicate these projects effectively.

As the healthcare system’s goals expands beyond treatment, and into prevention the need to learn about the community is imperative. Predictive analytics can benefit from social and environmental determinants of health. This presentation discusses using predictive analytics to learn about a population health within a community.  

This session focuses on how an AWS customer created a data lake and used machine learning services to analyze and search massive amounts of historical unstructured data. The Municipal Securities Rulemaking Board modernized their analytics platform by using a combination of machine learning natural language services, free-text search capabilities, and optimized storage services to extract information from stores of data without labor-, cost-, and time-intensive processes. The result astonished Board of Directors, who saw the potential of leveraging the cloud to generate tremendous and transformative value for the municipal securities market.