Gee (JOB) Operating Expenses (2009 - 2026)
Gee's Operating Expenses came in at $7.75 million for fiscal Q1 2026 (quarter ended Dec 31, 2025), down 8.7% from $8.49 million a year earlier and down 13.6% from the prior quarter.
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Analysis
Gee (JOB) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Dec 31, 2025, Gee reported Operating Expenses of $35.09 million, down 8.4% year-over-year; for FY2025 (ended Sep 30, 2025), it was $35.83 million, down 10.6% from FY2024.
- Operating Expenses has declined in each of the last three fiscal years, with a five-year compound annual growth rate of -4.3% (FY2020 to FY2025).
- Going back by fiscal year, Operating Expenses was $40.07 million in FY2024 (-16.5%), $47.96 million in FY2023 (-8.3%), $52.28 million in FY2022 (+24.6%) and $41.96 million in FY2021 (-6.0%).
- The fiscal Q1 2026 figure represents the lowest quarterly Operating Expenses since fiscal Q2 2017.
- Year-over-year, Operating Expenses has declined for 12 consecutive quarters, with an average decline of 12.3% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q2 2022 (growth of 33.1%), and the weakest in fiscal Q2 2021 (a decline of 28.1%).
- Business Quant data shows JOB's Operating Expenses at $8.98 million (Q4 2025), $9 million (Q3 2025) and $9.36 million (Q2 2025) in the three fiscal quarters before Q1 2026.
Peer Set
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 | Gee | 658.12 Mn | 576.01 Mn | 8.28 Mn | 7.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.90 Mn |
| Mar 31, 2026 | 7.47 Mn |
| Dec 31, 2025 | 7.81 Mn |
| Sep 30, 2025 | 9.18 Mn |
| Jun 30, 2025 | 9.23 Mn |
| Mar 31, 2025 | 9.58 Mn |
| Dec 31, 2024 | 8.70 Mn |
| Sep 30, 2024 | 10.58 Mn |
| Jun 30, 2024 | 10.54 Mn |
| Mar 31, 2024 | 10.34 Mn |
| Dec 31, 2023 | 11.41 Mn |
| Sep 30, 2023 | 12.12 Mn |
| Jun 30, 2023 | 12.57 Mn |
| Mar 31, 2023 | 12.52 Mn |
| Dec 31, 2022 | 13.63 Mn |
| Sep 30, 2022 | 15.28 Mn |
| Jun 30, 2022 | 13.68 Mn |
| Mar 31, 2022 | 13.34 Mn |
| Dec 31, 2021 | 13.46 Mn |
| Sep 30, 2021 | 12.97 Mn |
API Access
Gee 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=JOB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JOB", "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=JOB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();