Advanced Analytics Drives Reengineering of Field Operations for the 2020 U.S. Census

Tamara Adams (), Alessandro Ferrucci (), Pedro Carvalho (), Sothiara Em (), Benjamin Whitley (), Ryan Cecchi (), Teresa Hicks (), Alexander Wooten (), John Cuffe (), Stephanie Studds (), Irvin Lustig () and Steve Sashihara ()
Additional contact information
Tamara Adams: U.S. Census Bureau, Washington, DC 20233
Alessandro Ferrucci: U.S. Census Bureau, Washington, DC 20233
Pedro Carvalho: U.S. Census Bureau, Washington, DC 20233
Sothiara Em: U.S. Census Bureau, Washington, DC 20233
Benjamin Whitley: U.S. Census Bureau, Washington, DC 20233
Ryan Cecchi: U.S. Census Bureau, Washington, DC 20233
Teresa Hicks: U.S. Census Bureau, Washington, DC 20233
Alexander Wooten: U.S. Census Bureau, Washington, DC 20233
John Cuffe: U.S. Census Bureau, Washington, DC 20233
Stephanie Studds: U.S. Census Bureau, Washington, DC 20233
Irvin Lustig: Princeton Consultants, Princeton, New Jersey 08540
Steve Sashihara: Princeton Consultants, Princeton, New Jersey 08540

Interfaces, 2023, vol. 53, issue 1, 47-58

Abstract: The U.S. Census Bureau conducts a census of population and housing every 10 years as mandated in the U.S. Constitution. Following up in person with households that do not respond online, by phone, or by mail, which is known as nonresponse follow-up (NRFU), represents a major component of this effort. For the 2010 Census, the Census Bureau equipped enumerators with paper maps and notebooks filled with questionnaires and required enumerators to go door to door and collect decennial census data. The enumerators met daily with their supervisors to return completed questionnaires and update payroll information. For the 2020 Census, an advanced analytics solution, utilizing machine learning and optimization techniques, drove a reengineering of the entire field operations process, leading to substantially reduced costs and improved productivity. These reengineering efforts included business processes and technology centered around the development of this solution, the MOJO Optimizer, and resulted in an 80% increase in the number of cases completed per hour (from 1.05 to 1.92) and a 27% decrease in the number of miles reimbursed per case (from 5.05 to 3.68) compared with the 2010 Census NRFU. Capitalizing on the massive innovations realized during decennial census operations, the Census Bureau intends to use this technology to revolutionize its over 90 active surveys.

Keywords: optimization; vehicle routing problem; census; Edelman award (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/inte.2022.1146 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:53:y:2023:i:1:p:47-58

Access Statistics for this article

More articles in Interfaces from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().