Spar (SGRP) Operating Expenses (2010 - 2026)
Spar (SGRP) recorded Operating Expenses of $7.2 million in Q2 2026, down 13.7% from $8.35 million a year earlier but up 11.7% from the prior quarter.
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Analysis
Spar (SGRP) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Spar's Operating Expenses came in at $36.83 million as of Jun 30, 2026, up 13.9% year-over-year; for FY2025, it came in at $37 million, up 9.2% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 2.1% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $33.88 million in FY2024 (-7.5%), $36.63 million in FY2023 (-11.0%), $41.14 million in FY2022 (+11.8%) and $36.78 million in FY2021 (+10.3%).
- Quarterly Operating Expenses has ranged from $4.28 million in Q4 2023 to $13.21 million in Q3 2025 over the past five years.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 18.6%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 123.3% in Q4 2024, against a decline of 61.7% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $6.44 million (Q1 2026), $9.99 million (Q4 2025) and $13.21 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn | 792.12 Mn |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn | 877.22 Mn |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn | 4.84 Bn |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn | 267.00 Mn |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - | - |
| 10 | Spar | 19.31 Mn | 586,021.00 | 8.41 Mn | 7.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.20 Mn |
| Mar 31, 2026 | 6.44 Mn |
| Dec 31, 2025 | 9.99 Mn |
| Sep 30, 2025 | 13.21 Mn |
| Jun 30, 2025 | 8.35 Mn |
| Mar 31, 2025 | 5.87 Mn |
| Dec 31, 2024 | 9.56 Mn |
| Sep 30, 2024 | 8.56 Mn |
| Jun 30, 2024 | 8.07 Mn |
| Mar 31, 2024 | 7.72 Mn |
| Dec 31, 2023 | 4.28 Mn |
| Sep 30, 2023 | 9.34 Mn |
| Jun 30, 2023 | 8.80 Mn |
| Mar 31, 2023 | 10.46 Mn |
| Dec 31, 2022 | 11.18 Mn |
| Sep 30, 2022 | 10.61 Mn |
| Jun 30, 2022 | 10.08 Mn |
| Mar 31, 2022 | 9.25 Mn |
| Dec 31, 2021 | 8.76 Mn |
| Sep 30, 2021 | 9.43 Mn |
API Access
Spar 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=SGRP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SGRP", "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=SGRP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();