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From Big Data to Big Information In Federal Performance

From Big Data to Big Information In Federal Performance . Lynn McQueen, SAMHSA PIC Performance Ambassador Program December 2013. Does “Big Data” Align With GPRAMA & A-11?. Conceptual Frameworks, Models Relationships: Networks, Collaboration Strategic Plan, Objectives, SOARS

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From Big Data to Big Information In Federal Performance

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  1. From Big Data to Big InformationIn Federal Performance Lynn McQueen, SAMHSA PIC Performance Ambassador Program December 2013

  2. Does “Big Data” Align With GPRAMA & A-11? • Conceptual Frameworks, Models • Relationships: Networks, Collaboration • Strategic Plan, Objectives, SOARS • Reviews & Monitoring • Evidence-Based Everything • Accountability & Transparency

  3. “Big Data”: No Universal Definition • Information demanding processing for enhanced insight and decision making (Gartner, 2001) • Lots of Structured & Unstructured Data • High V • Volume • Velocity • Variety • Exceed(s) current capacity/capability to use • (National Institute of Standards & Technology )

  4. “Big Data” In Context • “Big Data” is becoming more understandable • Data reported in Zettabytes • 1 Trillion connected devices  2.5 quintrillion bytes/day • US Federal Government seen as one of largest repositories of data in the world—called a “buried national asset” • Access & Transparency • 1 Billion health apps downloaded (US) in next 2-3 years • Use: More easily combined & analyze • Beyond trends  outliers, patterns, integration Visual Aids to Cognition Transformative

  5. The Pictures We Know

  6. Visual Aids to Cognition + Intuition/Experience Listen to the Data  Decisions Proceedings of the IEEE VisWeek Workshop on Visual Analytics in Healthcare: Understanding the Physicians Perspective, October 23rd, 2011, Providence, RI, http://visual.nlm.nih.gov/~cabanj/VAHC2011-Proceedings-LowRes.pdf

  7. Business Intelligence, Visual Analytics, Predictive Analysis, High Performance Analytics, Operational Analytics

  8. From Data Hairballs to Useful Pictures Visualizing Facebook’s Locality of Friendship (Paul Butler) …an integrated approach that helps the mind take in, explore, and understand large/complex data more easily Not just more data but…

  9. GPRAMA’s Intent (2010) GPRAMA “aimed at increasing the use of Performance information to improve performance and results…Agencies are collecting a significant amount of information, but are not consistently using that information to improve their management and results” (U.S. Senate Committee on Homeland Security and Governmental Affairs, 2010, 11-12)

  10. Performance Moving Forward • “Big Data” + Visual Analytics + Intuition + Experience: • Sharing, networking, crossing boundaries • Faster, dynamic, interactions • Insights • Innovation • Communication • Hypothesis generating • Beyond • Outcomes • Accountability • Combinations • Tables, Graphs • Reporting

  11. HHS Launches BI During FY12-FY13 • Reporting & Analysis • Ad hoc reports • “My reports” • Pre-defined reports • Comparisons across agencies/Opdivs • Filters, preferences • Online tutorials • Manual • Workgroup • May 2012 Retreat

  12. HHS Performance: Wide Variationin Data Storage, Reporting, Analysis • 4/15 using regularly • Time to learn, use • Overall workload • Questions about output accuracy • Time to process • Printing options • Desire for more regular use, training • Positive • BI “has a lot of potential” • Tutorials • Pre-defined & Ad hoc reporting • Comparisons • Graphs, Visual Aids • Trends, Comparisons • Eager to share data

  13. HHS & SAS Findings Are Consistent…Time Is Needed to Manage & Use Data • SAS White Paper “How Governments are Using the Power of High-Performance Analytics”, September 2012 • NY Times, “The Age of Big Data”, 2/11/12 • “From Data to Decisions II”, IBM, October 2012 • SAS 2012 Survey of Federal managers & staff (many GS levels) • 64% (managers) & 55% (analysts) “agree or strongly agree” it is hard to turn data into useful information • Over 2/3 use simple reporting & analysis • Less than half use advanced or complex analysis methods • 69% say that more data/processes would help performance

  14. Facilitators & Challenges2012 SAS Survey • What Would Help Agencies Use Data to Achieve Their Mission? • Faster access to data • Quicker automation • Expanded visual aids • Faster responses to requests/processes • Expanded reporting & capacity • Challenges • Time, skills, training, staffing • Difficulty using data to interpret & predict • Complicated restrictions • Resources • Leadership priorities

  15. From “Big Data” to Big Information • Vision: Long & short term planning, networking • Brainstorm about leadership issues • Dedicated time to learn well & use systematically • Focus on system-wide approaches • Incentives for learning and using analytics • “Wish List” for contractor and HHS • Ongoing Tutorials • Showcase BI Best Practices • Journal Club • Site Visits, Guest Presenters • Retreat and Monthly PO Calls

  16. Progress On The Right Path

  17. Questions

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