Kelly Services (KELYA) Operating Expenses (2009 - 2026)
Kelly Services (KELYA) posted Operating Expenses of $195.9 million for Q2 2026, down 5.5% from $207.3 million a year earlier and down 1.7% from the prior quarter.
Kelly Services (KELYA) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 28, 2026, Operating Expenses at Kelly Services was $788.1 million, down 9.4% year-over-year; for FY2025, it came in at $825.9 million, up 0.9% from FY2024.
- Annual Operating Expenses shows a four-year compound annual growth rate of 0.6% (FY2021 to FY2025).
- In prior years, Kelly Services' Operating Expenses was $818.4 million in FY2024 (-12.4%), $934.7 million in FY2023 (-0.9%), $943.5 million in FY2022 and $805.6 million in FY2021.
- Quarterly Operating Expenses has run from a low of $190.5 million in Q1 2024 to a high of $303.6 million in Q4 2022 over five years.
- On a year-over-year basis, Operating Expenses has declined in each of the last four quarters, with an average decline of 2.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2025, with growth of 18.5%; the weakest was Q4 2023, with a decline of 23.9%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $199.3 million (Q1 2026), $198.5 million (Q4 2025) and $194.4 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 172.92 Bn | 132.01 Bn | 5.98 Bn | 15.82 Bn |
| 2 | Cintas | 90.00 Bn | 89.09 Bn | 1.55 Bn | 841.66 Mn |
| 3 | Iron Mountain | 32.99 Bn | 32.50 Bn | 1.06 Bn | 1.58 Bn |
| 4 | Rollins | 18.37 Bn | 17.91 Bn | 582.90 Mn | 866.81 Mn |
| 5 | APi | 18.18 Bn | 15.39 Bn | 770.00 Mn | 568.00 Mn |
| 6 | UL Solutions | 16.47 Bn | 14.51 Bn | 423.00 Mn | 261.00 Mn |
| 7 | Aramark | 14.29 Bn | 12.30 Bn | 430.34 Mn | 4.84 Bn |
| 8 | Rentokil Initial | 11.99 Bn | 5.51 Bn | - | - |
| 9 | Gartner | 11.92 Bn | 5.41 Bn | 1.07 Bn | 1.22 Bn |
| 10 | Kelly Services | 487.19 Mn | 382.19 Mn | 194.40 Mn | 193.80 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 193.80 Mn |
| Jun 28, 2026 | 195.90 Mn |
| Mar 29, 2026 | 201.50 Mn |
| Dec 28, 2025 | 198.50 Mn |
| Sep 28, 2025 | 194.40 Mn |
| Jun 29, 2025 | 207.30 Mn |
| Mar 30, 2025 | 225.70 Mn |
| Dec 29, 2024 | 217.40 Mn |
| Sep 29, 2024 | 219.00 Mn |
| Jun 30, 2024 | 197.00 Mn |
| Mar 31, 2024 | 190.50 Mn |
| Dec 31, 2023 | 230.90 Mn |
| Oct 1, 2023 | 228.40 Mn |
| Jul 2, 2023 | 234.40 Mn |
| Apr 2, 2023 | 243.40 Mn |
| Dec 31, 2022 | 943.50 Mn |
| Oct 2, 2022 | 231.10 Mn |
| Jul 3, 2022 | 258.60 Mn |
| Apr 3, 2022 | 236.10 Mn |
| Dec 31, 2021 | 870.60 Mn |
Kelly Services Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=KELYA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KELYA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=KELYA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();