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Fostering modern and innovative data collection methods in several U.S. Bureau of Labor Statistics business surveys

Kenneth W. Robertson


The U.S. Bureau of Labor Statistics (BLS) manages many monthly, quarterly, and annual data
collections. Within BLS, the Office of Industry Employment Statistics (OIES) is responsible for data
acquisition efforts that result in over 40 million collections of business data each year.
The programs managed by OIES include the Current Employment Statistics (CES) survey, the
Quarterly Census of Employment and Wages (QCEW), and the Job Openings and Labor Turnover
Survey (JOLTS). The CES survey is a very large scale quick response establishment survey,
collecting data from a sample of about 651,000 business and government establishments each month.
The CES program produces estimates of employment, hours, and earnings by industry, for the nation,
states, and metropolitan areas. These data, published about three weeks after the reference period, are
among the first indicators of the health of the U.S. economy each month. The QCEW is a quarterly
submission of data by the nearly 10 million establishments in the U.S., including monthly
employment levels and quarterly wage totals. The JOLTS collects data from a sample of 16,000
establishments each month; data collected include job openings, hires, quits, layoffs and discharges,
and other separations.
These data collections utilize mixed modes that are managed centrally and collected across several
data collection centers. The methods utilized to collect these data have fundamentally changed over
the past two decades. At the beginning of that period survey and administrative data were collected
almost exclusively by mail, while data are now collected using multiple methods with most of the data
collected electronically. The transformation of the data collection methodology required a substantial
investment in managerial and human resource capabilities.
This paper describes the data collection management structure, the human resources utilized, and how
tasks are allocated across personnel dimensions. The paper also describes management efforts that
foster and lead to excellence and innovation in these programs. In addition, the paper describes recent
data collection innovations and current explorations into the realm of alternative data sources.