Millerknoll (MLKN) Operating Expenses (2009 - 2026)
Millerknoll's Operating Expenses was $333.5 million in fiscal Q1 2027 (quarter ended Aug 29, 2026), up 6.0% from $314.6 million a year earlier but down 3.1% from the prior quarter.
Millerknoll (MLKN) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Millerknoll's Operating Expenses was $1.31 billion through Aug 29, 2026, down 4.1% year-over-year; for FY2026 (ended May 30, 2026), it was $1.29 billion, down 5.9% from FY2025.
- Operating Expenses shows a five-year compound annual growth rate of 12.4% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $1.37 billion in FY2025 (+9.6%), $1.25 billion in FY2024 (-4.2%), $1.31 billion in FY2023 (-0.4%) and $1.31 billion in FY2022 (+82.7%).
- Quarterly Operating Expenses has moved between $294.2 million (fiscal Q3 2024) and $414.6 million (fiscal Q3 2025) over five years.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 3.5%.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q2 2022 (growth of 100.2%); the worst was fiscal Q3 2026 (a decline of 25.7%).
- Per Business Quant data, MLKN's Operating Expenses in the three fiscal quarters before Q1 2027 was $344.2 million (Q4 2026), $308 million (Q3 2026) and $323.7 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | SharkNinja | 27.77 Bn | 25.44 Bn | 860.34 Mn | 680.96 Mn |
| 2 | Somnigroup International | 13.40 Bn | 12.94 Bn | 817.20 Mn | - |
| 3 | Hni | 3.31 Bn | 2.88 Bn | 647.20 Mn | 550.90 Mn |
| 4 | Newell Brands | 2.40 Bn | 1.56 Bn | 812.00 Mn | 529.00 Mn |
| 5 | Sonos | 2.08 Bn | 978.34 Mn | 189.31 Mn | 157.78 Mn |
| 6 | Whirlpool | 1.85 Bn | -1.62 Bn | 442.00 Mn | 412.00 Mn |
| 7 | Arhaus | 1.53 Bn | 611.57 Mn | 172.07 Mn | 117.81 Mn |
| 8 | Millerknoll | 1.46 Bn | 758.62 Mn | 385.30 Mn | 333.50 Mn |
| 9 | Corsair Gaming | 1.42 Bn | 951.49 Mn | 104.29 Mn | 96.68 Mn |
| 10 | Cricut | 1.36 Bn | 336.47 Mn | 116.41 Mn | 68.99 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 29, 2026 | 333.50 Mn |
| May 30, 2026 | 344.20 Mn |
| Feb 28, 2026 | 308.00 Mn |
| Nov 29, 2025 | 323.70 Mn |
| Aug 30, 2025 | 314.60 Mn |
| May 31, 2025 | 321.90 Mn |
| Mar 1, 2025 | 414.60 Mn |
| Nov 30, 2024 | 314.50 Mn |
| Aug 31, 2024 | 321.10 Mn |
| Jun 1, 2024 | 328.70 Mn |
| Mar 2, 2024 | 294.20 Mn |
| Dec 2, 2023 | 311.60 Mn |
| Sep 2, 2023 | 317.80 Mn |
| Jun 3, 2023 | 343.10 Mn |
| Mar 4, 2023 | 314.40 Mn |
| Dec 3, 2022 | 328.90 Mn |
| Sep 3, 2022 | 321.30 Mn |
| May 28, 2022 | 325.50 Mn |
| Feb 26, 2022 | 310.30 Mn |
| Nov 27, 2021 | 346.80 Mn |
Millerknoll 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=MLKN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MLKN", "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=MLKN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();