Topic Archives: Productivity

How We Collect Data When People Don’t Answer the Phone

I was asked recently how the U.S. Bureau of Labor Statistics can collect data these days when no one answers the telephone. A legitimate question and one we grapple with all the time. I had two answers – one related to data collection methods and one related to sources of data. I will elaborate here about both.

Beige wall phone with rotary dial

But first, do you remember the days before caller ID, when everyone answered the phone? If you were at home, the rotary phone, permanently attached to the kitchen wall, always rang during dinner.

If you were in the office, the phone probably had a row of clear plastic buttons at the bottom that would light up and flash. In either case, who was on the other end of the phone was a mystery until you answered. In those days, your friendly BLS caller could easily get through to you and ask for information.

Vintage office phone with rows of buttons

Fast forward to today’s world of smart phones and other mobile devices. Nobody talks on the phone anymore. Many phone calls are nuisances. A call from BLS might show up as Unknown Number, U.S. Government, or U.S. Department of Labor on your caller ID, or identified as potential spam. With the spread of “spoofing,” many people do not answer calls from numbers they don’t recognize. How do we get around these issues?

Data Collection

At BLS, we consider data collection as much an art as a science. Sure, our staff needs to be well-versed in the information they are collecting. But they also need to be salespersons, able to convince busy people to spend a few minutes answering key questions. Part of that art is making a connection. There are old-fashioned ways that still work, such as sending a letter or showing up at the door. And there are more modern techniques, such as email and text. We are nothing if not persistent.

Our data-collection techniques have been called “High Touch, High Tech.” We start by building a relationship—the High Touch step. BLS has a wide range of information that people and businesses can use to help make informed decisions. We can help you access that information, and we love to see survey respondents use BLS data they helped us produce. In return, we ask for some information from you. There’s where High Tech comes in. We continue to add flexibility to our data-collection toolkit. You can provide information in person, on paper, or on the phone. You also can email information or an encrypted file. Or you can access our online portal anytime and anywhere to provide information or upload a data file. We need your information, and we want to make providing that information as easy as possible.

For example, this chart shows the number of employer self-reports that we’ve received through our online portal over the past several years. Internet data collection has really taken off.

Editor’s note: Data for this chart are available in the table below.

Another data-collection strategy we use is asking businesses to allow us to get the information we need from their website. This might involve web scraping data or using an Application Programming Interface (API). We have had success showing businesses that we can get what we need from their website, often eliminating the need for them to compile data.

Alternative Data

Beyond these data-collection strategies, we are expanding efforts to get information from alternative sources, lessening our need to contact businesses and households. Some BLS programs, such as Local Area Unemployment Statistics, the Quarterly Census of Employment and Wages, and Productivity Studies, rely heavily on administrative data and information from other surveys. In these cases, there is little need to contact businesses or people directly.

Other BLS programs, such as the Consumer Price Index (CPI) and the Employment Cost Index (ECI), need to capture timely information. But there are alternatives that can complement direct data collection. The CPI, for example, has produced an experimental price index for new vehicles based on a file of vehicle purchase transactions provided by J.D. Power. Using information from sources like that may eventually lessen the need to have BLS employees contact vehicle dealerships. The ECI found that it was easier to capture employer premiums for unemployment insurance from state tax records than to ask employers.

Alternative data come in many forms, from government records, data aggregators, scanners, crowdsourcing, corporate data files, and many more. BLS is investing heavily in alternative data-collection techniques and alternative data sources. The High Touch and High Tech approach we use every day in our data-collection operations helps us to maximize data quality and minimize respondent burden and cost.

The telephone may go the way of the dinosaur, but that’s not stopping us from using every tool at our disposal to continue to produce gold standard data to inform your decisions.

Number of transactions with BLS internet data collection
YearNumber of transactions

2004

105,145

2005

148,754

2006

219,923

2007

534,555

2008

972,605

2009

1,544,795

2010

1,909,410

2011

2,322,540

2012

2,769,694

2013

3,236,376

2014

3,288,665

2015

3,554,639

2016

4,013,415

2017

4,513,297

2018

4,685,414

2019

4,868,939

Ensuring Security and Fairness in the Release of Economic Statistics

The U.S. Bureau of Labor Statistics is the gold standard of accurate, objective, relevant, timely, and accessible statistical data, and I am committed to keeping it that way. As Commissioner, it is my obligation to do everything possible to protect the integrity of our data and to make sure everyone has equitable access to these data.

One step toward equitable access and data security is coming soon; on March 1, 2020, the U.S. Department of Labor (DOL) will eliminate all electronics from the lock-up facility where we allow members of the media to review economic releases and prepare news stories before the official release of the data. We are changing the procedures to better protect our statistical information from premature disclosure and to ensure fairness in providing our information to the public.

For many years the news media have helped BLS and the Employment and Training Administration (ETA) inform the public about our data. Since the mid-1980s, BLS and ETA have provided prerelease data access to news organizations under strict embargoes, known as “lock-ups.” We have provided this early access consistent with federal Statistical Policy Directives of the Office of Management and Budget. BLS uses the lock-up for several major releases each month, including the Employment Situation and Consumer Price Index. ETA uses the lock-up for the Unemployment Insurance Weekly Claims data. These economic data have significant commercial value and may affect the movement of commodity and financial markets upon release.

Because of technological advancements, the current lock-up procedure creates an unfair competitive advantage for lock-up participants who provide BLS data to trading companies. Today, the internet permits anyone in the world to obtain economic releases for themselves directly from the BLS or DOL websites. However, unlike media organizations with computer access in the current lock-up, others who use the data do not have up to 30 minutes before the official release to process the data. Their postings about the data may lag behind those released directly from the lock-up at official publication time, 8:30 a.m. Eastern. High-speed algorithmic trading technology now gives a notable competitive advantage to market participants who have even a few microseconds head start. To eliminate this advantage and further protect our data from inadvertent or purposeful prerelease, no computers or any other electronic devices will be allowed in the lock-up.

In recent years, BLS and ETA have devoted significant resources to introducing improved technologies that strengthen our infrastructure and ensure data are posted to the BLS or DOL websites immediately following the official release time.

We at BLS and ETA are committed to the principle of a level playing field—our data must be made available to all users at the same time. We are equally committed to protecting our data. We are now positioned to continue helping the media produce accurate stories about the data, while also ensuring that all parties, including the media, businesses, and the general public, will have equitable and timely access to our most sensitive data.

You can find more details about these changes in our notice to lock-up participants. We also have a set of questions and answers about the changes to the lock-up procedures.

Why This Counts: Measuring Industry Productivity

At BLS, productivity is the economic statistic that describes the efficiency of production. The productivity statistics you hear about most often in the news are for the entire U.S. economy. But there’s more to the productivity story than just the overall numbers. The economy is made up of hundreds of industries, and each one works in a different way. Productivity data for each industry help us understand how specific types of production have changed over time. Let’s look at a few specific industries to see how labor productivity data can enhance our understanding of their unique production systems.

General Freight Trucking: Technological Innovations

Economic conditions in the general freight trucking industry closely mirror the health of the overall economy. During the 2007–09 recession, both output and hours worked fell dramatically in trucking. Because employment and spending were down nationwide, there was less demand for the transportation of all kinds of goods. After the recession ended, output and hours in trucking picked back up. Output reached prerecession levels by 2014, but in 2018 hours worked were still slightly below their 2007 level.

Dividing output by hours worked yields labor productivity. Because output in trucking has grown faster than hours during the recovery from the recession, labor productivity has increased. This helps us understand the nature of operations in general freight trucking. Innovative technologies such as communications systems, mapping software, and truck-based sensors and monitors known as “telematics” have improved transportation efficiency. These systems allow deliveries to be planned more efficiently with fewer delays, allowing more freight to be delivered without an equivalent increase in worker hours.

General freight trucking, average yearly percent change in output, hours worked, and productivity from 2007 to 2018

Editor’s note: Data for this chart are available in the table below.

Travel Agencies: Digital Transformation

Another industry that has changed the way it operates is travel agencies. Since 2000, output has increased substantially, while hours fell from 2000 to 2010 and have increased only slightly since then. The major transformation for travel agencies has been the Internet. Online tools have allowed clients to make travel reservations with far less help from workers. This increase in efficiency is reflected in the industry’s labor productivity, which has more than tripled from 2000 to 2017.

Travel agencies, average yearly percent change in output, hours worked, and productivity from 2000 to 2017

Editor’s note: Data for this chart are available in the table below.

Supermarkets: Incremental Change

Changes in other industries have been more subtle. Supermarkets are a particularly competitive industry, and firms employ a large number of workers to maintain high levels of customer service. Managing inventories, stocking shelves, checking out merchandise, and staffing specialty stations are all tasks that supermarkets continue to need. But even in supermarkets, productivity has been increasing since 2009, as output has grown faster than worker hours. To continue growing sales with lower costs, many firms in this industry have relied more on labor-saving technology, such as self-checkout machines. This technology increases efficiency by allowing supermarkets to process more transactions with less help from workers.

Supermarkets, average yearly percent change in output, hours worked, and productivity from 2009 to 2018

Editor’s note: Data for this chart are available in the table below.

Cut and Sew Apparel Manufacturing: Establishment Turnover

Productivity declines also can show the changing nature of work. Cut and sew apparel manufacturing has seen much of its production move outside the United States. In 2018, U.S. apparel manufacturers produced less than 15 percent of the output they produced in 1997. Although worker hours also have declined, they have not dropped as much as output, leading to a decline in labor productivity. This indicates a shift over time in the nature of the average apparel manufacturer. While many large establishments moved overseas in search of cheaper labor, the remaining domestic apparel manufacturing establishments are on average smaller and more specialized, requiring more labor-intensive work.

Cut and sew apparel manufacturing, average yearly percent change in output, hours worked, and productivity from 1997 to 2018

Editor’s note: Data for this chart are available in the table below.

To Learn More

BLS industry productivity data help us study the efficiencies of economic activities. Historical trends in productivity provide an important window into each industry’s working conditions, competitiveness, contribution to the economy, and potential for future growth. These data are used by investors, business leaders, jobseekers, researchers, and government decision makers. We have annual labor productivity measures for over 275 detailed industries.

To dive into the data for yourself, check out the BLS webpages on labor productivity. You also can see productivity data in a brand new way using our industry productivity viewer! Even more specialized industry data are on our webpages for hospitals, construction industries, elementary and secondary schools, and urban transit systems. We also have a recent article on productivity in grocery stores.

Average yearly percent change in output, hours worked, and productivity in selected industries
IndustryOutputHours workedProductivity

General freight trucking, 2007 to 2018

1.0%-0.1%1.2%

Travel agencies, 2000 to 2017

4.8-3.08.1

Supermarkets, 2009 to 2018

1.90.71.2

Cut and sew apparel manufacturing, 1997 to 2018

-9.4-7.5-2.1

Let’s Celebrate the Productive U.S. Workforce

Earlier this month our nation celebrated Labor Day. We celebrate Labor Day for many good reasons, but one of the best is to appreciate, even for just one day, how amazingly productive our nation’s workforce is. As we shop online or in stores, we rarely stop to think about the skills and effort it takes to produce our goods and services. Let’s take a moment to celebrate that productivity and the progress we have seen in the last few years.

Indeed, productivity of labor is at the heart of the American economy. How much workers produce for each hour they labor and how efficiently they use resources determines the pace of economic growth and the volume of goods that supply everyone (workers included) with the products and services that shape our daily lives. Growing productivity means that our standard of living very likely is improving.

Our workers are very productive. On average, each U.S. worker produced goods and services worth $129,755 last year. That’s compared with the next largest world economies: Germany at $99,377; the United Kingdom at $93,226; Japan at $78,615; China at $32,553; and India at $19,555.

Despite our great reliance on rising productivity to attain the good things of life, academics and researchers still marvel at the mysteries that surround the subject. What drives productivity change? What are the key factors behind these international differences in output per worker?

For example, does the quality of labor alone determine the rate of productivity growth? It is certainly a component of what drives labor productivity, although some countries have high educational and training levels but low productivity per worker. Labor quality has been steadily rising in the United States, but we don’t know the impact on productivity as the baby boomers retire and are replaced.

What is the right mix of labor and technology needed for changing the productivity growth rate? How can we measure the value of the dignity of work, or the personal and social value that work yields? And, what is the role of technical knowledge and product design in determining the productivity of labor?

Then there’s the mysterious role of innovation. Economists think they know that invention and scientific breakthroughs can make massive changes to productivity. However, which innovations transform productivity, and have all the low-lying fruits of productivity enhancement already been harvested?

Despite our strong international showing, analysts who watch these data may be a tad bit concerned with the sluggishness in U.S. productivity growth over the past 10 years. Since 2011, the rate of growth in labor productivity has slowed to one-third of the pace shown between 2000 and 2008, despite acceleration in the past 2 years. Even when we broaden the concept of productivity to include the output attributable to the combination of labor and other productive factors (also known as multifactor productivity), the rate of growth is still one-third of the pace it was in the first decade of this century.

Even with a subsidence in the growth rate, it is worth noting that both labor input and output are on the rise. Since the start of the current business cycle expansion in 2009, the rate of growth in labor input has been five times what it was prior to the Great Recession during the previous expansion.

Output has also grown steadily, but at a slower rate than hours. Because labor productivity is the quotient of output divided by hours, productivity can slow even when both components are rising. The relationship between the relative growth of output and hours is one of the many features that makes productivity both challenging and fascinating to study.

The Bureau of Labor Statistics engages with an extensive network of researchers in and out of the academic community whose mission is, like ours, to better understand and measure the productivity of the U.S. labor force. Labor productivity is an amazing subject because it incorporates so many facets of the nation’s economy into one statistic. By peeling back layers and looking at the details behind the summary number, we can gain valuable insight on the hours and output of our nation’s workforce. We will continue to produce and provide context for these valuable statistics that help tell the story of America’s workers.

That said, we should never lose sight of the big picture. America’s workers lead the world in their capacity to create the goods and services that define our economy and improve our lives. And that, certainly, is something great to celebrate!

Labor Day 2019 Fast Facts

I have been Commissioner of Labor Statistics for 5 months now, and I continue to be amazed by the range and quality of data we publish about the U.S. labor market and the well-being of American workers. As we like to say at BLS, we really do have a stat for that! We won’t rest on what we have done, however. We continue to strive for more data and better data to help workers, jobseekers, students, businesses, and policymakers make informed decisions. Labor Day is a good time to reflect on where we are. This year is the 125th anniversary of celebrating Labor Day as a national holiday. Before you set out to enjoy the long holiday weekend, take a moment to look at some fast facts we’ve compiled on the current picture of our labor market.

Working

Working or Looking for Work

  • The civilian labor force participation rate—the share of the population working or looking for work—was 63.0 percent in July 2019. The rate had trended down from the 2000s through the early 2010s, but it has remained fairly steady since 2014.

Not Working

  • The unemployment rate was 3.7 percent in July. In April and May, the rate hit its lowest point, 3.6 percent, since 1969.
  • In July, there were 1.2 million long-term unemployed (those jobless for 27 weeks or more). This represented 19.2 percent of the unemployed, down from a peak of 45.5 percent in April 2010 but still above the 16-percent share in late 2006.
  • Among the major worker groups, the unemployment rate for teenagers was 12.8 percent in July 2019, while the rates were 3.4 percent for both adult women and adult men. The unemployment rate was 6.0 percent for Blacks or African Americans, 4.5 percent for Hispanics or Latinos, 2.8 percent for Asians, and 3.3 percent for Whites.

Job Openings

Pay and Benefits

  • Average weekly earnings rose by 2.6 percent from July 2018 to July 2019. After adjusting for inflation in consumer prices, real average weekly earnings were up 0.8 percent during this period.
  • Civilian compensation (wage and benefit) costs increased 2.7 percent in June 2019 from a year earlier. After adjusting for inflation, real compensation costs rose 1.1 percent over the year.
  • Paid leave benefits are available to most private industry workers. The access rates in March 2018 were 71 percent for sick leave, 77 percent for vacation, and 78 percent for holidays.
  • About 91 percent of civilian workers with access to paid holidays receive Labor Day as a paid holiday.
  • In March 2018, civilian workers with employer-provided medical plans paid 20 percent of the cost of medical care premiums for single coverage and 32 percent for family coverage.

Productivity

  • Labor productivity—output per hour worked—in the U.S. nonfarm business sector grew 1.8 percent from the second quarter of 2018 to the second quarter of 2019.
  • Some industries had much faster growth in 2018, including electronic shopping and mail-order houses (10.6 percent) and wireless telecommunications carriers (10.1 percent).
  • Multifactor productivity in the private nonfarm business sector rose 1.0 percent in 2018. That growth is 0.2 percentage point higher than the average annual rate of 0.8 percent from 1987 to 2018.

Safety and Health

Unionization

  • The union membership rate—the percent of wage and salary workers who were members of unions—was 10.5 percent in 2018, down by 0.2 percentage point from 2017. In 1983, the first year for which comparable union data are available, the union membership rate was 20.1 percent.

Work Stoppages

  • In the first 7 months of 2019, there have been 307,500 workers involved in major work stoppages that began this year. (Major work stoppages are strikes or lockouts that involve 1,000 or more workers and last one full shift or longer.) For all of 2018, there were 485,200 workers involved in major work stoppages, the largest number since 1986, when about 533,100 workers were involved.
  • There have been 15 work stoppages beginning in 2019. For all of 2018, 20 work stoppages began during the year.

Education

  • Occupations that typically require a bachelor’s degree for entry made up 22 percent of employment in 2018. This educational category includes registered nurses, teachers at the kindergarten through secondary levels, and many management, business and financial operations, computer, and engineering occupations.
  • For 18 of the 30 occupations projected to grow the fastest between 2016 and 2026, some postsecondary education is typically required for entry. Be sure to check out our updated employment projections, covering 2018 to 2028, that we will publish September 4!

From an American worker’s first job to retirement and everything in between, BLS has a stat for that! Want to learn more? Follow us on Twitter @BLS_gov.