Fully Leverage External Data Sources: A Census Bureau Change Principle Amy O’Hara, U.S. Census Bureau Washington Statistical Society Seminar on Administrative.

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Fully Leverage External Data Sources: A Census Bureau Change Principle Amy O’Hara, U.S. Census Bureau Washington Statistical Society Seminar on Administrative Records for Best Possible Estimates September 18, 2014

Vision and Planning to Effect a Paradigm Change  Pipedream about making changes in income estimates in surveys  Suggestions for moving forward  Need for vision and long-term planning  “Requires leadership buy-in at all levels of a statistical agency”

Change Principle: Fully Leverage External Data Sources We will fully leverage administrative records and other external data sources, including big data, to supplement and possibly supplant frame development and direct data collection, enhance self-response capabilities, support new data products or expand existing data products. Using external data will help the Census Bureau reduce data collection costs, redundancies, and respondent burden and improve data quality. The Census Bureau also has the opportunity to serve as a data integrator for the federal statistical system. -Future of Census Bureau Operations, April 25,

What are we doing to Fully Leverage External Data?  Research and testing with administrative records for use in 2020 Census  Demographic surveys using administrative records for frame, contact, modeling, and imputation  Big Data explorations in Economic Directorate

Strategic Plan: Research and Implement Records  Strategic Plan Tactic 1.2.4: Integrate data from existing sources, including administrative records, to produce new information products that provide deeper insights into our people and economy by combining data sets that had not previously been linked.  Strategic Plan Tactic 2.2.4: Explore and research uses of Big Data. - U.S. Census Bureau Strategic Plan, FY

More from the Strategic Plan  – Make the 2020 Census more cost effective while achieving quality targets.  Perform world-class research.  Use the most cost effective technologies available to update the MAF and assess its quality.  Promote the use of Census Bureau products.  Support reimbursable surveys and continue to improve the Interagency Agreement process.  Increase survey and census efficiency by using empirical data to facilitate intelligent business decisions prior to and during data collection.

What we are working on  Integrate new data sources – acquiring state data, negotiating to obtain new variables, school frames, housing data  Big Data – Big Data lab to test concurrent analysis and estimation, exploring options to acquire new data sources, Big Data class

Business Plan for Change: Identify and Acquire Data  Activity Introduce new business process for integrating data sets and producing new data products.  Activity Work with the Department of Commerce, the Office of Management and Budget, and key record suppliers to establish statistical policies, procedures, and timelines for maximizing the use of administrative records.  Activity Enter into Memoranda of Agreement with key suppliers. -U.S. Census Bureau Business Plan for Change

More from the Business Plan for Change  –Identify data gaps and evaluate internal and external data sets for relevant analyses, data products, and services.  2.4.3: Explore options to reduce burden.  Establish processes to engage individual and network partners in Census Bureau knowledge areas.

What we are working on  Business process to integrate data and create new products – documentation on data ingestion and processing, portfolio management  Policies, processes, and timelines to integrate data – policies in place, improving communication and knowledge management to standardize processes and introduce external data into operations and products  Enter MOA with suppliers – new federal, state, and third party negotiations underway

Summary  Seeking and testing more external data from federal, state, third party sources.  Need to:  Understand data quality  Design systems to accommodate "big" data  Collaborate with program and statistical agencies