This post was co-authored by Daniel Sternberg and Sarah Gustafson.
Gusto enables more than 100,000 small businesses across the United States to take care of their teams with full-service payroll, benefits, compliance, expert HR, and more. This report analyzes leading indicators and changes to employment at small businesses for the full month of May 2020.
May ‘20 marks a key point on the road to economic recovery from the impact of COVID-19 and the necessary shelter-in-place orders that started in March ‘20. Federal aid, in the form of Paycheck Protection Program (PPP) funding, continues to be disbursed as more and more pockets of the country are either reopening or planning to reopen. Our data shows an uptick in small business hiring and headcount—driven in part by rehiring—with some industries showing company headcount approaching pre-COVID levels.
But just because businesses are opening up again, doesn’t mean they’re opening for business as usual. Many small businesses have been forced to modify their operations according to new safety guidelines and social distancing procedures, which has made rebounding unequal and uneven across locations and industries. In some cases, headcount is up, but overall wages paid and hours worked are down. And, despite decreases in furlough and termination rates this month, many employees remain out of work—with hourly workers the hardest hit in terms of job and wage loss.
Several variables—including the possibility of additional outbreaks and the pace at which consumers feel ready to re-engage with their old buying habits—are still in flux as we continue to assess the return to a pre-COVID economy. And with new guidelines introduced that extend the duration for using PPP funds, time will tell whether the improvements made in May are truly a springboard for additional hiring and rehiring throughout the summer.
The findings reported below represent data points with meaningful sample sizes[1], but based on the distribution of Gusto’s customers, they may not be fully representative of the industry and geographic breakdown of small businesses across the United States.
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Key Findings
- Hiring is on the rebound: Overall hiring increased by 74% in May ‘20 (7.7%) compared to April ‘20 (4.2%). Rehiring (of previously terminated employees) continues to comprise an unprecedented proportion of overall hiring that took place in May (22%). Headcount in a number of industries is now approaching or in a few cases even above pre-COVID levels.
- Wages and hours are being cut: Reduction in hours had the biggest impact on wages in May, accounting for 32% of the total reduction in earnings for workers. Reduction in the hourly rate (both for hourly and salaried employees) explained 21% of overall wage loss.
- Hourly workers are being hit the hardest by COVID: Hourly workers were furloughed at more than five times the rate of salaried workers in May ‘20. Additionally, hourly employees averaged 23% less pay in May ‘20 compared to February ‘20 (pre-COVID).
- Furlough rate slowed in May compared to spike in April: Furloughs spiked substantially in April ‘20, and May ‘20 data showed a 26% decrease in the rate of furloughs from that peak.
May ’20 Small Business Trends
Similar to what our data showed in April, hiring and rehiring continued to increase nationwide in May. Hiring increases enabled some industries that had experienced significant losses by the end of April, such as Retail and Healthcare, to nearly reach their pre-COVID baselines, while others such as Food & Beverage and Salons & Spas remained down more than 10%. These rebounds also continue to vary widely based on location and many employees remain out of work—either terminated or furloughed—despite federal aid from PPP loans.
Below, Table 1 compares employer actions in spring ‘20 to the same period last year.
Table 1. Rates of employer actions affecting employee wages for 2019 and 2020 as compared to February of the same year[2].
| March ‘19 | April ‘19 | May ‘19 | March ‘20 | April ’20 | May ‘20 | YoY March | YoY April | YoY May | ||
| Furlough rate | 3.7% | 3.1% | 3.4% | 4.4% | 9.8% | 7.3% | 17.7% | 219.3% | 112.3% | |
| Reduction in hourly wages of at least 10% | 2.3% | 2.3% | 2.5% | 2.2% | 3.1% | 3.5% | -6.3% | 33.2% | 37.6% | |
| Reductions in hours of at least 10% | 9.4% | 10.5% | 7.5% | 13.3% | 11.7% | 9.7% | 41.1% | 11.5% | 30.0% | |
| Termination rate | 4.0% | 7.6% | 11.0% | 8.0% | 11.0% | 12.8% | 99.0% | 45.8% | 16.5% | |
| Layoff rate[3] | – | – | – | 3.0% | 1.8% | 0.7% | – | – | – |
Heightened furlough rates continue into May, but dropped 26% from April
The furloughing frenzy we saw last month has decreased by more than a quarter in May. However, furloughing is still up substantially year-over-year. In April ’20, we saw a 3.2x year-over-year overall increase in employees who were furloughed (9.8% versus 3.1%) and more than double the rate seen in March of this year (4.4%). We continued to see elevated furlough rates in May ‘20 compared to the same period last year (7.3% versus 3.4% in May ‘19), but this was a 26% reduction from the peak furlough rate that was measured in April ‘20.
Furloughing was the greatest contributor to overall reduction in employee earnings in April ‘20 (30% of all reduced wages were due to furloughs), but was overtaken by reduction in hours as the leading driver in May ’20. Reduction in hours accounted for 32% of the total reduction in earnings for workers in May, whereas furloughs dropped slightly to 28%. Reduction in the hourly rate (both for hourly and salaried employees) explained 21% of overall wage reduction. Terminations explained 17% of the reduction in earnings in April, but by May only accounted for 11%.
Furloughs are measured separately from more permanent headcount reduction like terminations and layoffs. Our data reveals the complexity of owning a small business during a dual pandemic—the need to cut costs to deal with the realities of the economic crisis at hand, while ensuring the well-being of their employees during this ongoing health crisis. Furloughed employees are still listed on employer payrolls but are not logging any hours and don’t earn any wages (although employees are eligible to file with their state for unemployment benefits, and employers may continue to provide benefits such as health insurance).
Hourly workers continue to be hit harder than salaried employees
As previously reported by Gusto, lower-income hourly workers appear to be bearing the brunt of the COVID-19 economic downturn. In May, the furlough rates for both hourly and salaried employees decreased compared to the peak month of April. The recovery in furlough rate from April to May, however, was higher for Salaried workers than for Hourly workers, who experienced a 126% year-over-year increase in furloughing from May ‘19.
Hourly workers were furloughed at a rate of 11.5% in May (as compared to 15.3% in April, a month-over-month decrease of -25%). Salaried employees were furloughed at a rate of 2.1% in May (as compared to 3.2% in April, a month-over-month decrease of -34%). In May, hourly workers were still furloughed at more than five times the rate of salaried workers. Additionally, hourly workers were more likely to be terminated and have reduced hours than their salaried counterparts, as shown in Table 3 below.
Table 2: Percent of workers that experienced the following changes in employment as compared to February of the same year, cut by FLSA Status (salaried vs. hourly).
| Salaried (exempt) | March ‘19 | April ‘19 | May ‘19 | March ‘20 | April ’20 | May ‘20 | YoY March | YoY April | YoY May | |
| Furlough rate | 2.5 | 1.3 | 1.5 | 2.3 | 3.2 | 2.1 | -9.6% | 137.3% | 41.7% | |
| Reduction in hourly wages of at least 10% | 2.9 | 2.9 | 3.1 | 3.0 | 5.1 | 5.7 | 5.6% | 77.5% | 86.4% | |
| Reductions in hours of at least 10% | 3.9 | 4.2 | 3.4 | 6.5 | 5.2 | 4.4 | 69.8% | 22.1% | 28.9% | |
| Termination rate | 2.5 | 4.7 | 7.0 | 4.0 | 6.3 | 7.5 | 60.2% | 32.3% | 6.9% |
| Hourly (nonexempt) | March ‘19 | April ‘19 | May ‘19 | March ‘20 | April ’20 | May ‘20 | YoY March | YoY April | YoY May | |
| Furlough rate | 4.9 | 4.5 | 5.1 | 6.0 | 15.3 | 11.5 | 23.2% | 237.6% | 125.9% | |
| Reduction in hourly wages of at least 10% | 1.7 | 1.6 | 1.8 | 1.4 | 1.2 | 1.5 | -21.5% | -24.9% | -14.8% | |
| Reductions in hours of at least 10% | 15.0 | 16.8 | 11.6 | 19.5 | 17.7 | 14.5 | 29.9% | 5.2% | 25.5% | |
| Termination rate | 5.6 | 10.6 | 15.3 | 11.7 | 15.7 | 18.2 | 108.7% | 48.0% | 18.8% |
Are previously furloughed workers returning to work?
Almost half (47.8%) of workers who were initially furloughed in April ‘20 are still furloughed as of May—and, of those workers, 7% are out of work permanently[4]. The remaining 45.2% worked some hours in May, albeit far less than the usual amount of hours they worked pre-COVID[5].
Of the employees furloughed in April (Table 2), employees in Technology and Consulting were the most likely to return to work in May, but also the most likely to return on a reduced hourly rate or lower salary. Workers furloughed in April from the Education, Non-Profits, Sports & Recreation, and Food & Beverage sectors were most likely to remain furloughed through May.
Table 3: Worker employment status in May ‘20 for workers that were on furlough in April.
| Industry | Still furloughed | Out of work | Returned to reduced hours | Returned to reduced hourly wage | Returned unaffected |
| Construction | 36.8% | 4.9% | 24.5% | 1.4% | 32.4% |
| Consulting | 34.2% | 3.8% | 15.9% | 5.1% | 40.9% |
| Education | 63.0% | 4.4% | 17.5% | 1.0% | 14.1% |
| Facilities | 43.5% | 7.0% | 19.0% | 1.8% | 28.7% |
| Food & Beverage | 55.3% | 8.2% | 20.8% | 1.3% | 14.4% |
| Healthcare & Social Assistance | 38.9% | 5.3% | 34.0% | 1.6% | 20.2% |
| Manufacturing | 46.6% | 7.1% | 20.8% | 2.4% | 23.1% |
| Non-Profits & Associations | 64.2% | 3.1% | 13.6% | 1.3% | 17.9% |
| Retail | 47.6% | 7.1% | 23.4% | 1.1% | 20.7% |
| Salon & Spa | 42.2% | 7.5% | 21.0% | 1.3% | 28.0% |
| Sports & Recreation | 59.4% | 7.0% | 17.9% | 1.5% | 14.2% |
| Technology | 37.5% | 5.5% | 13.6% | 6.2% | 37.1% |
Overall reduction in wages
Gusto’s payroll data provides a lens into the actions small businesses have taken to control their costs during this extraordinary period of time. In both April and May of this year, we saw a 10% gap in overall wages paid to small business employees compared to what we would expect based on year-over-year comparisons.
Again, the gap was most extreme for hourly workers. Hourly employees averaged 23% less pay in May ‘20 compared to February ‘20 and the same month last year, whereas salaried workers only experienced a 6% average reduction in wages.
Changes in staffing levels
Small business headcount increased by 3.2% in May, which left headcount down 1.6% since the crisis began at the beginning of March[6]. The headcount increase continued to be driven by recovered hiring—the hiring rate in May ‘20 was 7.3%, very similar to May ‘19 (7.7%), and a 74% increase over April (4.2%). Rehires continued to make up a much greater percentage of all hires than we have seen historically—22% of all May hires were rehires, as was the case in April. Voluntary terminations rose slightly, but continued to be below the pre-COVID baseline (2.5% for May, versus 2.2% for April, and 4.4% for February), while involuntary terminations in general and layoffs in particular remained just slightly above their pre-COVID baselines. Figure 1 shows the net change in headcount and hiring termination and layoff statistics by month since January 2019[7].
Figure 1. Monthly net change in headcount and hiring, termination, and layoff statistics.
The trends for May suggest that small businesses have invested significantly starting in late April and through May in rehiring former employees as well as increasing hiring of out-of-work individuals in the labor market. Some of this may be due to seasonal factors such as hiring for summer employment. According to Gusto’s own annual data, May tends to be a peak hiring month every year.
On a weekly basis, we saw consistent week over week growth in headcount, flat termination rates, and a rise in hiring rates through the first two weeks of April, followed by a leveling off. Figure 2 shows the cumulative net change in headcount and hiring, termination, and layoff statistics from the week of March 2 through the week of May 25. Rehiring followed a similar trend to overall hiring. Figure 3 shows weekly rehiring as a percentage of all hires from January ‘19 through the week of May 25, 2020.
Figure 2. Weekly net change in headcount and hiring, termination, and layoff statistics.
Figure 3. Rehires as a percentage of hires, on a weekly basis.
Industry Trends
Small business headcount grew across industries with at least 1,000 Gusto customers in May. The following industries experienced the highest growth levels:
- Facilities (+6.7%)
- Food & Beverage (+4.7%)
- Transportation (+4.4%)
- Construction (+4.4%)
- Retail (+4.1%)
Figure 4 shows net headcount changes for all industries with 1,000 Gusto customers over the past month, ranked by the cumulative change in headcount over the period.
Figure 4. Net change in headcount for March through May by industry.
Despite the headcount growth we’re seeing in May, the industries hardest hit by the economic fallout of COVID-19—particularly Accommodations and Tourism—still have a considerable way to go before they recover what’s been lost.
Figure 5 shows the cumulative net change in headcount for heavily affected industries over the course of the crisis compared to others.
Figure 5. Cumulative change in headcount since the week of March 2 across heavily affected industries and all others.
While other industries, like Retail, have mostly caught up to pre-COVID levels, many of the hardest-hit industries, such as Tourism and Accommodations, are still down 10% or more from their pre-COVID employment numbers.
Geographic Trends
Over the course of May, all US state governments reopened or began to execute phased or regional reopening plans. All US states with at least 1,000 employees on the Gusto platform also showed net increases in headcount in May. Many of the states with the largest increases were those that started reopening in early May or in some cases never passed full stay-at-home orders, including Montana, Maine, New Hampshire, Kansas, and Utah.
Figure 6. Net percentage change in headcount for March–May by state
Business Size
In May we saw increases in headcount across businesses of all sizes, driven by increase in hiring and declines in terminations.
Table 3. Layoff rates for employers of different sizes (# of employees) in April.
| Size | Terminations | Layoffs | Hires | % Change in terminations | % Change in layoffs | % Change in hires | Net change in headcount |
| 0–4 | 2.85 | 0.49 | 6.30 | -32% | -70% | 87% | 3.4% |
| 5–9 | 4.10 | 1.63 | 7.21 | -20% | -60% | 82% | 3.1% |
| 10–24 | 4.65 | 1.49 | 6.72 | -8% | -59% | 69% | 2.1% |
| 25–49 | 4.89 | 1.62 | 5.71 | -10% | -58% | 50% | 0.8% |
| 50+ | 4.85 | 3.24 | 5.43 | -33% | -78% | 44% | 0.6% |
About Gusto
Gusto is a modern, online people platform that helps small businesses take care of their teams. In addition to full-service payroll, Gusto offers health insurance, 401(k)s, compliance and expert HR, and more. The company serves over 100,000 businesses nationwide and has offices in Denver, New York City, and San Francisco.
Appendix
Table A1: Hires, terminations, and layoffs per 100 employees by industry, for the month of May ‘20, ranked in decreasing order by net change in headcount.
| Industry | Hires | Terms | Layoffs | % Change in hires vs. April | % Change in terms. | % Change in layoffs | Net headcount change |
| Facilities | 14.94 | 8.26 | 0.48 | 30% | -12% | -72% | 6.68 |
| Food & Beverage | 13.74 | 9 | 2.01 | 134% | -8% | -47% | 4.75 |
| Transportation | 10.74 | 6.31 | 0.77 | 43% | -19% | -71% | 4.43 |
| Construction | 8.58 | 4.19 | 0.48 | 51% | -24% | -67% | 4.38 |
| Retail | 9.27 | 5.14 | 0.71 | 47% | -18% | -64% | 4.13 |
| Manufacturing | 7.8 | 4.09 | 0.68 | 56% | -19% | -66% | 3.71 |
| Wholesale | 7.1 | 3.48 | 0.91 | 66% | -16% | -48% | 3.61 |
| Healthcare & Social Assistance | 7.72 | 4.1 | 0.3 | 92% | -15% | -80% | 3.61 |
| Insurance | 5.79 | 2.3 | 0.21 | 55% | -36% | -75% | 3.48 |
| Salon & Spa | 10.5 | 7.27 | 1.51 | 358% | 62% | -10% | 3.23 |
| Consulting | 6.3 | 3.1 | 0.64 | 43% | -23% | -56% | 3.21 |
| Other Personal Services | 7.67 | 4.64 | 0.7 | 109% | -31% | -78% | 3.04 |
| Education | 6.53 | 3.58 | 0.4 | 103% | -32% | -77% | 2.95 |
| Other Professional Services | 7.49 | 4.6 | 0.59 | 63% | -20% | -72% | 2.88 |
| Communications | 4.91 | 2.17 | 0.49 | 84% | -57% | -84% | 2.75 |
| Real Estate | 5.55 | 2.86 | 0.36 | 69% | -32% | -70% | 2.69 |
| Sports & Recreation | 8.28 | 5.65 | 1.3 | 154% | -28% | -52% | 2.63 |
| Technology | 4.74 | 2.19 | 0.35 | 40% | -34% | -72% | 2.55 |
| Finance | 4.49 | 1.99 | 0.37 | 29% | -38% | -67% | 2.5 |
| Legal | 4.75 | 2.26 | 0.3 | 84% | -27% | -61% | 2.49 |
| Non-Profits & Associations | 3.73 | 2.01 | 0.23 | 67% | -50% | -79% | 1.72 |
| Accounting | 4.53 | 3.06 | 0.47 | 83% | -41% | -79% | 1.47 |
| Arts & Entertainment | 4.93 | 4.2 | 1.13 | 88% | -39% | -49% | 0.72 |
Table A2: Hires, terminations, and layoffs per 100 employees across the most populous 50 Metropolitan Statistical Areas for the month of May ‘20, ranked in decreasing order by net change in headcount.
| MSA | Hires | Terms | Layoffs | % Change in hires | % Change in terms. | % Change in layoffs | Net headcount change |
| Louisville/Jefferson County, KY-IN | 8.72 | 2.81 | 0.36 | 61% | -21% | -88% | 5.91 |
| Columbus, OH | 10.21 | 4.49 | 0.22 | 97% | -27% | -81% | 5.71 |
| Detroit-Warren-Dearborn, MI | 9.33 | 3.86 | 0.65 | 125% | -34% | -81% | 5.47 |
| Houston-The Woodlands-Sugar Land, TX | 9.96 | 4.55 | 0.5 | 138% | -18% | -71% | 5.41 |
| Cleveland-Elyria, OH | 9.27 | 3.88 | 0.07 | 25% | 9% | -92% | 5.39 |
| Hartford-West Hartford-East Hartford, CT | 8.33 | 3.14 | 0.51 | 109% | -26% | 17% | 5.18 |
| Kansas City, MO-KS | 8.13 | 3.19 | 0.26 | 51% | -38% | -73% | 4.94 |
| Milwaukee-Waukesha-West Allis, WI | 9.25 | 4.52 | 0.22 | 152% | -14% | -82% | 4.74 |
| Tampa-St. Petersburg-Clearwater, FL | 9.62 | 5.16 | 0.47 | 68% | -10% | -64% | 4.47 |
| Salt Lake City, UT | 8.56 | 4.15 | 0.34 | 58% | -25% | -82% | 4.42 |
| Providence-Warwick, RI-MA | 8.25 | 3.93 | 0.19 | 122% | -19% | -90% | 4.32 |
| Jacksonville, FL | 8.75 | 4.51 | 0.16 | 91% | -26% | -92% | 4.24 |
| Austin-Round Rock, TX | 8.15 | 4 | 0.53 | 97% | -33% | -79% | 4.15 |
| Virginia Beach-Norfolk-Newport News, VA-NC | 6.47 | 2.36 | 0.09 | 21% | -38% | -87% | 4.11 |
| Dallas-Fort Worth-Arlington, TX | 9.48 | 5.43 | 0.45 | 79% | 3% | -69% | 4.05 |
| Atlanta-Sandy Springs-Roswell, GA | 8.34 | 4.35 | 0.56 | 121% | 4% | -48% | 3.99 |
| San Antonio-New Braunfels, TX | 8.91 | 4.97 | 0.44 | 79% | -6% | -66% | 3.95 |
| Charlotte-Concord-Gastonia, NC-SC | 7.59 | 3.68 | 0.18 | 91% | -42% | -95% | 3.91 |
| Miami-Fort Lauderdale-West Palm Beach, FL | 8.69 | 4.84 | 0.84 | 100% | -1% | -30% | 3.85 |
| Denver-Aurora-Lakewood, CO | 7.2 | 3.41 | 0.45 | 64% | -34% | -75% | 3.79 |
| Baltimore-Columbia-Towson, MD | 6.71 | 3 | 0.26 | 106% | -36% | -76% | 3.71 |
| Phoenix-Mesa-Scottsdale, AZ | 8.73 | 5.21 | 0.5 | 87% | -2% | -61% | 3.52 |
| Orlando-Kissimmee-Sanford, FL | 7.99 | 4.51 | 0.56 | 125% | -26% | -47% | 3.48 |
| Nashville-Davidson–Murfreesboro–Franklin, TN | 9.33 | 5.89 | 1.09 | 32% | -1% | -47% | 3.44 |
| Indianapolis-Carmel-Anderson, IN | 6.44 | 3.02 | 0.28 | 49% | -60% | -93% | 3.42 |
| Cincinnati, OH-KY-IN | 7.37 | 3.96 | 0.31 | 78% | 8% | -72% | 3.41 |
| New York-Newark-Jersey City, NY-NJ-PA | 7.31 | 3.99 | 0.85 | 112% | -38% | -71% | 3.32 |
| San Diego-Carlsbad, CA | 6.79 | 3.52 | 0.47 | 92% | -20% | -72% | 3.27 |
| Birmingham-Hoover, AL | 7.25 | 4.06 | 0.58 | 161% | 12% | 290% | 3.19 |
| Las Vegas-Henderson-Paradise, NV | 7.68 | 4.59 | 1.38 | 45% | -37% | -60% | 3.09 |
| Sacramento–Roseville–Arden-Arcade, CA | 6.8 | 3.83 | 0.44 | 90% | -23% | -64% | 2.97 |
| Portland-Vancouver-Hillsboro, OR-WA | 6.49 | 3.53 | 0.67 | 65% | -26% | -60% | 2.95 |
| New Orleans-Metairie, LA | 6.32 | 3.41 | 0.59 | 42% | -53% | -52% | 2.92 |
| Minneapolis-St. Paul-Bloomington, MN-WI | 6.52 | 3.66 | 0.67 | 64% | -38% | -44% | 2.86 |
| St. Louis, MO-IL | 8.24 | 5.42 | 1.54 | 16% | -30% | -28% | 2.82 |
| Washington-Arlington-Alexandria, DC-VA-MD-WV | 6.36 | 3.64 | 0.97 | 67% | -12% | -25% | 2.73 |
| Los Angeles-Long Beach-Anaheim, CA | 6.29 | 3.57 | 0.72 | 74% | -19% | -61% | 2.72 |
| Philadelphia-Camden-Wilmington, PA-NJ-DE-MD | 6.9 | 4.2 | 0.42 | 89% | -19% | -81% | 2.7 |
| Boston-Cambridge-Newton, MA-NH | 6.1 | 3.56 | 0.69 | 48% | 0% | -42% | 2.54 |
| Pittsburgh, PA | 6.07 | 3.6 | 0.3 | 30% | -53% | -93% | 2.46 |
| Chicago-Naperville-Elgin, IL-IN-WI | 5.72 | 3.26 | 0.7 | 43% | -38% | -64% | 2.45 |
| Memphis, TN-MS-AR | 8.84 | 6.78 | 0.14 | 31% | -3% | -93% | 2.07 |
| San Francisco-Oakland-Hayward, CA | 5.38 | 3.35 | 0.89 | 50% | -31% | -53% | 2.03 |
| Richmond, VA | 6.66 | 4.65 | 0.36 | 76% | -18% | -73% | 2.01 |
| Raleigh, NC | 7.17 | 5.27 | 0.51 | 108% | 4% | -72% | 1.9 |
| Seattle-Tacoma-Bellevue, WA | 6.01 | 4.15 | 0.78 | 66% | -38% | -70% | 1.86 |
| San Jose-Sunnyvale-Santa Clara, CA | 5.12 | 3.64 | 0.82 | 89% | -31% | -66% | 1.48 |
| Riverside-San Bernardino-Ontario, CA | 6.05 | 4.57 | 0.99 | 55% | -10% | -59% | 1.48 |
| Buffalo-Cheektowaga-Niagara Falls, NY | 3.56 | 2.85 | 0.43 | 21% | -71% | -94% | 0.71 |
| Oklahoma City, OK | 7.9 | 8.47 | 0.7 | 74% | 48% | -50% | -0.57 |
Methodology
The analyses described in this report were based on two separate datasets obtained from Gusto’s small business payroll, benefits, and HR applications. The first dataset used payroll data to capture employee hours, wages, and furloughing (Work Reduction & Furlough). The second dataset used data from employers hiring and terminating employees (Hiring & Termination).
Work Reduction & Furlough
Employees in our dataset were labeled as furloughed if they were employed for the entirety of February, March, and April (had no termination effective during that time), and either 1) had earned money in the final paycheck of the preceding month but had not earned money in the final paycheck of the following month (e.g. final paycheck of February was non-zero, and the final paycheck of March was $0), or 2) met the definition for part 1 and also continued to earn $0 on payrolls in the subsequent month, thereby on a continued furlough. Our furlough data in this April report only looks at furloughs that were active in April and were instigated in March or April, not furloughs that began earlier and have continued through this period.
Non-terminated, non-furloughed employees were labeled as work reduced for the April report if the total hours of their April paychecks were less than 90% of the hours on their February (used as a benchmark for pre-COVID) paychecks. This calculation was done for both 2019 and 2020, where 2019 was used to represent the counterfactual case (what would have happened).
Presumed COVID-related differences were calculated by subtracting the rates of termination, furlough, and work reduction in 2019 from the same numbers in 2020. This rate difference was used to calculate the number of additional employees affected by each cost-saving strategy. The average dollars saved per affected employee was calculated as the difference between total February and March payrolls, divided by the number of employees, for each type of affected employee, and this dollar amount was multiplied by the COVID-related count of impacted employees to calculate the total dollars saved by each strategy.
Hiring & Termination
A given employee on Gusto can have multiple “employments,” since an employer can potentially hire, terminate, and rehire the same employee multiple times. In our Hiring & Termination dataset, a hire corresponded to an employer creating a new employment with a hiring date, and a termination corresponded to the entry of a termination date for a given employment. Layoffs corresponded to terminations where the employer listed the reason for the termination as a “layoff” (one of the choices from a standardized list in Gusto’s termination flow). In order to capture a more time-sensitive view of employer activities, we recorded hires, terminations, and layoffs on the date that they were entered into the system, rather than their effective date. Terminations are also coded as voluntary or involuntary.
Monthly reporting of termination data may differ slightly from prior reporting, as employers often log a termination several days or weeks after the employee was actually released. For example, more than a third of terminations that were created (logged in the system) in May were actually effective before May. Data in this report may also differ slightly from prior reports due to methodology improvements. Further employment changes are incorporated into this month’s analysis, such as reduction to hourly wages. We also separately categorized employees that worked for companies who “paused” their payroll service with Gusto. Employees that fall into this new bucket may have previously not been labeled as impacted, or may have been attributed as “hours reduced” for a given month.
Employee hires, layoffs, and terminations were aggregated weekly and monthly for a given company and work location. Hiring, termination, and layoff rates reported in this document are based on the number of times each event occurred in a given week or month, divided by the number of employees who were employed at the beginning of the period.
Locations reported in this document are based on the most recent work location associated with the employee. Industries reported in this document are based on self-report from customers within Gusto’s product.
[1] Values provided in this report were only included for categories (e.g., state, industry, metropolitan area) where we had at least 1,000 employees.
[2] Historical data may differ from April and May Gusto reporting due to slight changes in methodology, as well as employers that log employee terminations after the actual termination date (e.g. more than a third of terminations that were logged in April by employers actually occurred in a prior month). Methodology improvements are described in the appendix.
[3] Layoff (a subset of overall terminations) data was not collected prior to January 2020.
[4] Either the employee was terminated or the company went out of business.
[5] Given the way furloughs are estimated by Gusto on a monthly basis, it’s possible that these employees continued to be furloughed through part of May before returning to work, and therefore their hours are showing up as “reduced” compared to pre-COVID months. They could have actually returned to full employment and are simply caught in the wrong bucket. Therefore, 22% is the ceiling of workers that returned on reduced hours.
[6] This number includes employees currently on the headcount roster for a business, even if they did not receive a paycheck (were furloughed) in the month.
[7] This report adds separate voluntary and involuntary termination rates throughout most figures. Termination reasons are only available consistently since February 2020.
