Millerknoll (MLKN) EBITDA (2009 - 2026)
Millerknoll (MLKN) posted EBITDA of $86.9 million for fiscal Q1 2027 (quarter ended Aug 29, 2026), down 3.1% from $89.7 million a year earlier and down 45.3% from the prior quarter.
Millerknoll (MLKN) EBITDA (2009 - 2026) Analysis & Trends
For the trailing twelve months through Aug 29, 2026, EBITDA at Millerknoll was $415.3 million, up 114.8% year-over-year; for FY2026 (ended May 30, 2026), it was $349.3 million, up 78.6% from FY2025.
- Annual EBITDA shows a five-year compound annual growth rate of 1.8% (FY2021 to FY2026).
- In prior fiscal years, Millerknoll's EBITDA was $195.6 million in FY2025 (-40.2%), $326.9 million in FY2024 (+15.9%), $282 million in FY2023 (+20.2%) and $234.6 million in FY2022 (-26.7%).
- Quarterly EBITDA has run from a low of -$46.7 million in fiscal Q3 2025 to a high of $159 million in fiscal Q4 2026 over five years.
- On a year-over-year basis, EBITDA increased in two of the last four quarters, with growth averaging 14.9%.
- The strongest year-over-year quarter for EBITDA in the past five years was fiscal Q1 2026, with growth of 75.9%; the weakest was fiscal Q2 2022, with a decline of 38.3%.
- According to Business Quant data, EBITDA for the three prior fiscal quarters was $159 million (Q4 2026), $83.7 million (Q3 2026) and $85.7 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | SharkNinja | 32.02 Bn | 29.46 Bn | 1.17 Bn | 483.80 Mn |
| 2 | Somnigroup International | 13.95 Bn | 13.49 Bn | 817.20 Mn | 265.70 Mn |
| 3 | Hni | 3.57 Bn | 3.06 Bn | 678.50 Mn | 207.10 Mn |
| 4 | Newell Brands | 2.47 Bn | 1.61 Bn | 649.00 Mn | 104.00 Mn |
| 5 | Arhaus | 2.13 Bn | 1.21 Bn | 172.07 Mn | 76.17 Mn |
| 6 | Whirlpool | 2.04 Bn | -1.59 Bn | 473.00 Mn | 109.00 Mn |
| 7 | Sonos | 1.98 Bn | 879.61 Mn | 189.31 Mn | 42.60 Mn |
| 8 | Cricut | 1.84 Bn | 749.66 Mn | 108.88 Mn | 40.33 Mn |
| 9 | Millerknoll | 1.55 Bn | 843.84 Mn | 385.30 Mn | 86.90 Mn |
| 10 | Corsair Gaming | 1.33 Bn | 791.65 Mn | 97.83 Mn | 11.06 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 29, 2026 | 86.90 Mn |
| May 30, 2026 | 159.00 Mn |
| Feb 28, 2026 | 83.70 Mn |
| Nov 29, 2025 | 85.70 Mn |
| Aug 30, 2025 | 89.70 Mn |
| Mar 1, 2025 | -46.70 Mn |
| Nov 30, 2024 | 99.30 Mn |
| Aug 31, 2024 | 51.00 Mn |
| Mar 2, 2024 | 81.00 Mn |
| Dec 2, 2023 | 98.90 Mn |
| Sep 2, 2023 | 78.70 Mn |
| Mar 4, 2023 | 60.60 Mn |
| Dec 3, 2022 | 77.90 Mn |
| Sep 3, 2022 | 91.60 Mn |
| Feb 26, 2022 | 70.80 Mn |
| Nov 27, 2021 | 57.40 Mn |
| Aug 28, 2021 | 7.50 Mn |
| Feb 27, 2021 | 76.60 Mn |
| Nov 28, 2020 | 93.10 Mn |
| Aug 29, 2020 | 116.60 Mn |
Millerknoll EBITDA 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=ebitda&ticker=MLKN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=MLKN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();