Mesa Laboratories (MLAB) Operating Expenses (2010 - 2026)
Mesa Laboratories (MLAB) posted Operating Expenses of $31.98 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), down 5.6% from $33.88 million a year earlier and down 18.9% from the prior quarter.
Mesa Laboratories (MLAB) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Mesa Laboratories was $137.87 million, up 0.8% year-over-year; for FY2026 (ended Mar 31, 2026), it came in at $139.76 million, up 3.9% from FY2025.
- Annual Operating Expenses shows a five-year compound annual growth rate of 13.4% (FY2021 to FY2026).
- In prior fiscal years, Mesa Laboratories' Operating Expenses was $134.53 million in FY2025 (-66.8%), $405.33 million in FY2024 (+210.9%), $130.37 million in FY2023 (+24.9%) and $104.39 million in FY2022 (+39.8%).
- The fiscal Q1 2027 figure stands as the lowest quarterly Operating Expenses since fiscal Q2 2025.
- On a year-over-year basis, Operating Expenses increased in four of the last eight quarters, with an average decline of 15.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q4 2024, with growth of 841.9%; the weakest was fiscal Q4 2025, with a decline of 88.0%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $39.46 million (Q4 2026), $33.82 million (Q3 2026) and $32.61 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Mesa Laboratories | 727.12 Mn | 620.10 Mn | 39.01 Mn | 31.98 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 31.98 Mn |
| Mar 31, 2026 | 39.46 Mn |
| Dec 31, 2025 | 33.82 Mn |
| Sep 30, 2025 | 32.61 Mn |
| Jun 30, 2025 | 33.88 Mn |
| Mar 31, 2025 | 36.94 Mn |
| Dec 31, 2024 | 33.98 Mn |
| Sep 30, 2024 | 31.95 Mn |
| Jun 30, 2024 | 31.67 Mn |
| Mar 31, 2024 | 307.84 Mn |
| Dec 31, 2023 | 33.47 Mn |
| Sep 30, 2023 | 32.17 Mn |
| Jun 30, 2023 | 31.85 Mn |
| Mar 31, 2023 | 32.68 Mn |
| Dec 31, 2022 | 29.36 Mn |
| Sep 30, 2022 | 32.39 Mn |
| Jun 30, 2022 | 35.94 Mn |
| Mar 31, 2022 | 35.22 Mn |
| Dec 31, 2021 | 31.14 Mn |
| Sep 30, 2021 | 18.94 Mn |
Mesa Laboratories 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=MLAB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MLAB", "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=MLAB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();