To be ready for the 2020 Census, the U.S. Census Bureau needs to make several key information technology (IT) decisions immediately. That was the conclusion of the GAO's Carol Cha in testimony before the Subcommittees on Government Operations and Information Technology.
Following the 2010 Census, the most expensive census so far, the Census Bureau set out to reduce the projected cost of the 2020 Census by $5.2 billion by departing from the design used in the 2010 Census and using modern IT systems and infrastructure. Specifically, the Bureau has focused its research and testing to date on four redesign areas: identifying all the places where a person could live without the need for bodies on the ground to verify the existence of streets and addresses; increasing the number of households that self-respond by providing alternative modes for completing survey questions, like the Internet; using existing data from federal, state, and local entities to follow up on survey responses; and using technology to optimize field operations during the census.
Achieving these design goals for the 2020 Census depends on the success of the Bureau's enterprise-wide IT initiative, Census Enterprise Data Collection and Processing (CEDCAP), a program to modernize how the Census Bureau collects, stores, and processes data. But the Bureau has yet to make projections on the demand the IT infrastructure will need to meet for Census 2020 or decide whether the Bureau will build or buy the required IT systems. Ms. Cha testified that these key decisions have been deferred to 2016 through 2018, raising concerns that the Bureau will not have sufficient time to implement and test these systems before the census. In addition, she also raised concerns about the Bureau's lack of a permanent Chief Information Officer, lack of progress in addressing information security weaknesses, and its continuing lack of prioritization of IT decisions. Ms. Cha's testimony and the GAO's assessment of the Bureau's progress towards the 2020 Census can be found here: http://www.gao.gov/assets/680/673499.pdf.
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