SAVE THE DATE -and- CALL FOR SPEAKERS!
Predictive Analytics World for Government:
September 17-18, 2012 in Washington, DC
Speaker proposals are now being accepted for the 2nd Annual PAW-Gov conference: www.predictiveanalyticsworld.com/submit_gov.php
Speaker proposal deadline: April 30, 2012
Venue: The Ronald Reagan Building
Predictive Analytics World for Government, the leading vendor-neutral analytics conference for government, is holding its second annual conference this September 17-18 in Washington, DC. Predictive Analytics World for Government (PAWgov.com) is designed to help agency managers understand how they can apply predictive analytics to more effectively and efficiently accomplish their mission.
Last year, with over 250 attendees, PAW-Gov featured government-leading analytics speakers present real-world case studies from over 15 government agencies including the Department of Defense, Internal Revenue Service, U.S. Postal Service, Department of Agriculture, Department of Justice, National Security Agency, Social Security Administration, Department of Homeland Security, NASA, and the Richmond Police Department.
PAW-Gov 2011 Keynote Speakers:
 Congressman Darrell Issa Chairman House Committee on Oversight and Government Reform |
 Earl Devaney Chairman Recovery Accountability and Transparency Board |
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 David Williams Inspector General USPS OIG |
 John F. Elder CEO, Elder Research, Inc., and General Chair, PAW Gov |
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PAW-Gov In The News:
See the Federal Times article about last year's Predictive Analytics World for Government including interviews with several speakers from the inaugural conference: Software that predicts the future: Does it really help?
What is Predictive Analytics?
Predictive analytics is the process of discovering patterns in past behavior to predict the outcome of future cases. Drawing on a combination of computer science, statistics, and operations research, predictive analytics reduces fraud, waste, and abuse, automates manual processes, and drives smarter decisions by extracting actionable insights from the vast quantities of data within government agencies.
Case Studies
PAW-GOV showcases case studies from application areas of predictive analytics in the Public Sector including:
Accountability Analytics:
- Detecting Fraud, Waste, and Abuse – predicting high-risk cases for investigation or audit
- Preventing Improper Payments – predicting improper payments to be reviewed pre-payment
- Audit Analytics – focusing audits on high-risk program areas
- Complaint/Hotline Triage – categorizing and prioritizing important complaints and tips
Operational Analytics:
- Mission Analytics – improving agency service, performance, or operations
- Claims Processing – reducing backlog by semi-automating claims processing
- Workforce Analytics / Human Resources Analytics – predicting workforce attrition and future needs
- Portfolio Analytics – forecasting loans and grants
- Business Intelligence – monitoring and predicting agency key performance indicators and metrics
National Security / Law Enforcement Analytics:
- Cyber Security – detecting cyber threats and intrusions
- Crime Prediction – detecting criminal patterns or activities
- Intelligence Analytics – detecting terrorist activities
- Text Mining / Unstructured Data – uncovering actionable information in unstructured data
- Social Networking Analytics – investigating fraud and predicting events and public responses from Twitter and Facebook data
Who Should Attend?
Predictive Analytics World for Government is for Federal, State, and Local government leaders, analysts, and program managers including:
- CXO's, including CFOs, CIOs, CTOs, CHCOs,
- Directors
- Technology Leadership and IT Specialists
- Program and Project Managers
- Acquisition Leaders and Specialists
- Human Capital Leadership and Specialists
- Law Enforcement Agents and Managers
- Inspector General Staff and Leadership
- Auditor and Audit Managers
- Forensic Examiners
- Management Analysts
- Performance Analysts
- Appointed Officials
- Government contractors and consultants
- Private sector leaders interested in helping government use data to make better decisions
