BLS has partnered with the U.S. Department of Labor’s Office of the Chief Information Officer to update the CareerInfo app with more content. The updated app is now available from the App Store and Google Play. CareerInfo presents information from the Occupational Outlook Handbook, the most popular BLS resource for career information.
The CareerInfo app helps you find information about employment, pay, job outlook, education and training requirements, and more for hundreds of detailed occupations. You can browse occupational groups and titles or search by occupation or keywords. Within occupational groups, the app allows you to sort by occupation title, projected growth, and typical education or median pay. You also now can browse top lists such as top paying, fastest growing, and most new jobs! Each occupational profile now includes more detailed information on what they do, work environment, how to become one, pay, and job outlook.
Future updates will add features that will let you personalize the app by filtering searches and by “liking,” saving, viewing, and comparing favorites.
Check out the new CareerInfo app and explore the occupational information from BLS. You’ll be glad you did!
Our work at the Bureau of Labor Statistics is driven by the idea that good measurement leads to better decisions. Good measures of economic and social conditions help public policymakers and private businesses and households assess opportunities and areas for improvement. Measuring these conditions consistently over time helps people who use our data evaluate the impact of public and private decisions.
We also believe we must be completely transparent about the design of our surveys and programs and the methods we use to conduct them. It isn’t enough to publish statistics and expect people simply to trust their quality. We gain this trust by documenting the design and procedures for all our programs in our Handbook of Methods. Our website also explains our policies for ensuring data quality and protecting the confidentiality and privacy of the people and businesses who participate in our surveys and programs. Further, BLS works with the wider U.S. statistical community to ensure and enhance the quality of statistical information.
Good measures are essential in “normal” times, but the global COVID-19 pandemic has made these last few months anything but normal. I am so proud of the work of the career professionals at BLS and our fellow statistical agencies for continuing to produce vital economic statistics. Our entire BLS staff moved to full-time telework in mid-March and didn’t miss a beat. We continue to publish measures of labor market activity, working conditions, price changes, and productivity like BLS has done since its founding in 1884. See our dashboard of key economic indicators in the time of COVID-19.
Publishing these measures hasn’t been easy. The pandemic has raised new questions about how businesses, households, and consumers have changed their behavior. BLS also has had to innovate to find new ways of doing things during the pandemic.
Today I want to tell you about the new data we have been collecting to learn more about the effects of the pandemic. I also want to tell you about some of the ways the BLS staff has innovated to keep producing data that are accurate, objective, relevant, timely, and accessible.
How businesses have responded to the pandemic
We have collected new data on how U.S. businesses changed their operations and employment from the onset of the pandemic through September 2020. This information, combined with data collected in other BLS surveys, will aid in understanding how businesses responded during the pandemic. Other statistics we have collected and published during the pandemic show changes in employment, job openings and terminations, wages, employer-provided benefits, prices, and more. These new data provide more insights by asking employers directly what they experienced as a result of the pandemic and how they reacted. Data for the Business Response Survey to the Coronavirus Pandemic will be released in early December 2020.
Changes in telework, loss of jobs, and job search
The Current Population Survey is the large monthly survey of U.S. households from which we measure the unemployment rate and other important labor market indicators. We added questions to the survey to help gauge the effects of the pandemic on the labor market. These questions were added in May 2020 and will remain in the survey until further notice. One question asks whether people teleworked or worked from home because of the pandemic.
Editor’s note: Data for this chart are available in the table below.
Other questions ask whether people were unable to work because their employers closed or lost business because of the pandemic; whether they were paid for that missed work; and whether the pandemic prevented them from searching for jobs.
Editor’s note: Data for this chart are available in the table below.
Receiving and using stimulus payments during the pandemic
BLS is one of several federal agencies that developed questions for the rapid response Household Pulse Survey. The survey is a collaboration among the U.S. Census Bureau, BLS, the U.S. Department of Housing and Urban Development, the National Center for Education Statistics, the National Center for Health Statistics, and the U.S. Department of Agriculture’s Economic Research Service. BLS contributed questions on the receipt and use of Economic Impact Payments and on sources of income used to meet spending needs during the pandemic.
Our staff will continue to publish research on how the pandemic has affected the labor market and markets for goods and services. Check back regularly as we add to this library of research.
Innovations in Data Collection and Training
The COVID-19 pandemic has caused profound changes in the daily lives of Americans. BLS is no exception. As I mentioned earlier, all BLS staff moved to full-time telework in March. The pandemic hasn’t prevented us from continuing to publish high-quality data, but we have had to change some of our data-collection methods and estimation procedures. We will continue to explain those changes so you can understand how they affect the quality of our measures.
Our survey respondents are the heart of everything we do at BLS. Without their generous and voluntary cooperation, we would not be able to publish high-quality data for public and private decision making. Respondents have businesses and households to run, and a pandemic is a challenging time to ask for their help. The data-collection staffs at BLS, the U.S. Census Bureau, and our state partners form great relationships with survey respondents. We must continue to protect the health of data collectors while also training them in a rapidly changing environment. Let me highlight a few of the innovative changes we have made during the pandemic that focus on our relationships with respondents and how we train data collectors.
Using videoconferencing technology for data collection
Several of our surveys have started using videoconferencing tools to speak with respondents and collect data from them. Some of the surveys that now use this technology include the National Compensation Survey, the Occupational Requirements Survey, and the Producer Price Index. Many of our surveys previously relied on interviewers visiting businesses or households to collect data. We suspended all in-person data collection in March to protect the health of data collectors and respondents, so we had to find other ways to collect data. Many of our surveys also use telephone and internet to collect data, but those modes aren’t always ideal for every kind of data. We often need to develop personal relationships with respondents to gain their trust and cooperation and ensure high-quality data. Videoconferencing helps us accomplish what we often can’t do with phones or web survey forms.
The Occupational Requirements Survey is one that has begun using videoconferencing in data collection. The survey provides information about the physical demands; environmental conditions; education, training, and experience; and cognitive and mental requirements for jobs in the U.S. economy. Collecting data for this survey often requires visual aids, hand gestures, and other nonverbal information to understand job characteristics. It often helps to watch jobs as they are performed at a worksite, but that’s not an option during the pandemic. Videoconferencing is the next best alternative.
Many of our data collectors and respondents have mentioned how helpful videoconferencing is for developing a rapport and for sharing screens and other visual information. Videoconferencing also helps us reduce travel and lodging costs, so we likely will continue to rely on videoconferencing at least partly even after the pandemic.
Using videoconferencing technology for training and mentoring
Many of our surveys are complex and require considerable ongoing training for data collectors. For example, before the pandemic, our Consumer Price Index Commodities and Services (C&S) survey involved in-person training at our Washington, DC, headquarters. There were two classroom training courses: a 2-week introductory course and a 1-week advanced course. Each course was followed by on-the-job training held in our regional offices. Even before the pandemic, we were developing videoconference training. The pandemic caused us to accelerate these plans. We now provide C&S survey training through video collaboration tools. We also integrate on-the-job training throughout the classes.
Several other surveys have adopted a similar training approach as the Consumer Price Index. Our data-collection staffs also increasingly use videoconferencing for mentoring and to share ideas about how to make the data-collection experience better for data collectors and respondents.
A final note
Before I conclude, I want to share some sad news about one of the people who played an indispensable leadership role in developing the new survey questions and innovative data-collection and training methods. Jennifer Edgar, our Associate Commissioner for Survey Methods Research, died November 8 in a tragic fall in her home. She leaves behind her husband and two young children, her parents, and her sister. Moreover, she leaves hundreds of BLS colleagues and many more throughout the statistical community and beyond, who will grieve the loss of an exceptionally gifted friend and professional whose great promise was cut suddenly and tragically short. Jennifer was using her considerable energies to move BLS forward. Her passing is a huge blow to her family, loved ones, and the entire statistical community. We are working on ways to ensure Jennifer’s memory and passion is forever present at BLS.
Percent of employed people who teleworked at some point in the previous 4 weeks because of the COVID-19 pandemic
Number of people not in the labor force who did not look for work because of the COVID-19 pandemic
In the few months that I’ve had the pleasure of occupying the Commissioner’s seat at the Bureau of Labor Statistics, it’s been clear that I’m surrounded by a smart, dedicated, and innovative staff who collect and publish high-quality information while working to improve our products and services to meet the needs of customers today and tomorrow. And soon after I arrived, we added to that high-quality staff by welcoming a cadre of Civic Digital Fellows to join us for the summer.
In its third year, the Civic Digital Fellowship program was designed by college students for college students who wanted to put their data science skills to use helping federal agencies solve problems, introduce innovations, and modernize functions. This year, the program brought 55 fellows to DC and placed them in 6 agencies – Census Bureau, Citizenship and Immigration Service, General Services Administration, Health and Human Services, National Institutes of Health, and BLS. From their website:
BLS hosted 9 Civic Digital Fellows for summer 2019. Here are some of their activities.
Classification of data is a big job at BLS. Almost all of our statistics are grouped by some classification system, such as industry, occupation, product code, or type of workplace injury. Often the source data for this information is unstructured text, which must then be translated into codes. This can be a tedious, manual task, but not for Civic Digital Fellows. Andres worked on a machine learning project that took employer files and classified detailed product names (such as cereal, meat, and milk from a grocery store) into categories used in the Producer Price Index. Vinesh took employer payroll listings with very specific job titles and identified occupational classifications used in the Occupational Employment Statistics program. And Michell used machine learning to translate purchases recorded by households in the Consumer Expenditure Diary Survey into codes for specific goods and services.
We are always looking to improve the experience of customers who use BLS information, and the Civic Digital Fellows provided a leg up on some of those activities. Daniel used R and Python to create a dashboard that pulled together customer experience information, including phone calls and emails, internet page views, social media comments, and responses to satisfaction surveys. Olivia used natural language processing to develop a text generation application to automatically write text for BLS news releases. Her system expands on previous efforts by identifying and describing trends in data over time.
BLS staff spend a lot of time reviewing data before the information ends up being published. While such review is more automated than in the past, the Civic Digital Fellows showed us some techniques that can revolutionize the process. Avena used Random Forest techniques to help determine which individual prices collected for the Consumer Price Index may need additional review.
Finally, BLS is always on the lookout for additional sources of data, to provide new products and services, improve quality, or reduce burden on respondents (employers and households). Christina experimented with unit value data to determine the effect on export price movements in the International Price Program. Somya and Rebecca worked on separate projects that both used external data sources to improve and expand autocoding within the Occupational Requirements Survey. Somya looked at data from a private vendor to help classify jobs, while Rebecca looked at data from a government source to help classify work tasks.
Our cadre of fellows has completed their work at BLS, with some entering grad school and the working world. But they left a lasting legacy. They’ve gotten some publicity for their efforts. Following their well-attended “demo day” in the lobby at BLS headquarters, some of their presentations and computer programs are available to the world on GitHub.
I think what most impressed me about this impressive bunch of fellows was the way they grasped the issues facing BLS and focused their work on making improvements. I will paraphrase one fellow who said “I don’t want to just do machine learning. I want to apply my skills to solve a problem.” Another heaped praise on BLS supervisors for “letting her run” with a project with few constraints. We are following up on all of the summer projects and have plans for further research and implementation.
We ended the summer by providing the fellows with some information about federal job opportunities. I have no doubt that these bright young minds will have many opportunities, but I also saw an interest in putting their skills to work on real issues facing government agencies like BLS. I look forward to seeing them shine, whether at BLS or wherever they end up. I know they will be successful.
And, we are already making plans to host another group of Civic Digital Fellows next summer.
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.
Our monthly payroll survey shows that employment continues to expand—now 13.0 million jobs above the January 2008 peak reached as the 2007–09 recession began.
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.
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.
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.
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.
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.
You probably know that BLS publishes data and analysis about employment, unemployment, job openings, earnings, productivity, occupational safety and health, and more. But did you know we also publish information about how often workers have to lift objects; the maximum weight they lift or carry; whether they work in extreme heat or cold; and how much training and experience they need for a job? We call these characteristics “occupational requirements.”
Physical demands of work, such as keyboarding, reaching overhead, lifting or carrying
Environmental conditions, such as extreme heat, exposure to outdoors, proximity to moving parts
Education, training, and experience requirements, such as prior work experience, on-the-job training, and license requirements
Cognitive and mental requirements, such as interaction with other people, independence of work, and the amount of review
How did BLS get into doing this survey?
This survey is one of our newest statistical programs; we first published data on December 1, 2016.
The Social Security Administration asked us to help them obtain accurate and current data to use in their disability programs. They are developing an Occupational Information System, which will use data from the Occupational Requirements Survey. That means the survey is crucial for Social Security to manage their disability programs fairly and efficiently.
How can I use occupational requirements information?
Users of Occupational Requirements Survey data include:
Researchers exploring occupational change
Jobseekers and students
Government agencies evaluating skill gaps
People with disabilities and their advocates
Let’s discuss a couple of examples to show you what I mean.
You may want to know the minimum formal education requirements for jobs. The survey has a stat for that! In 2018, a high school diploma was required for jobs covering 40.7 percent of workers, while 17.9 percent had a bachelor’s degree requirement. The chart below shows the percent of jobs by minimum education requirement.
Editor’s note: Data for this chart are available in the table below.
We have more information on education, training, and experience. The 2018 news release showed that on-the-job training was required for about 77 percent of workers, and the average duration was 34 days.
We also have information on preparation time, which includes minimum formal education, training, and work experience a typical worker needs to perform a job. Preparation time between 4 hours and 1 month was required for 31.5 percent of workers.
Is the noise level at your workplace closer to a library (quiet) or a rock concert (very loud)? For some jobseekers, understanding the noise level and other environmental conditions might be extremely important as they evaluate job options. The chart below provides examples of the noise intensity in different occupations.
Editor’s note: Data for this chart are available in the table below.
Examples of work environments with different noise intensity levels include:
Quiet: private office, a golf course, or art museum
Moderate: department stores, business office, or fast food restaurant
Loud: manufacturing plant, atop large earth moving equipment, or jobs next to the highway
Very loud: rock concert venues, working with jack hammers, or rocket testing areas
How do we collect job requirement data?
To collect job requirement data, our field economists ask business owners, human resource professionals, worker safety officers, and supervisors to collect requirements of work. Field economists do not use paper or online questionnaires to collect these data; instead, they rely on a conversational interviews and descriptive documents, such as task lists, to collect information on occupational requirements.
How are we improving the survey?
Survey scope: Since it began, we have continued to refine the survey to improve its accuracy. In the third year of collection, we redefined the survey scope to focus on critical job functions—that is, the reason the job exists.
Survey content: Beginning with the current sample in collection, we added questions about cognitive and mental requirements. The Social Security Administration asked for this change so we can provide information on the requirements for workers to adapt to changes in the pace of work, solve problems, and interact with others.
Sample: The survey sample is collected over a 5-year period. That will provide the large amount of data necessary to publish information about detailed occupations. We have revised the sampling process to ensure we collect information about less common occupations.
Website: We recently improved the web layout to make it easier for users to find the data they want.