Kohls (KSS) Operating Expenses (2009 - 2026)
Kohls (KSS) posted Operating Expenses of $1.19 billion for fiscal Q2 2027 (quarter ended Aug 1, 2026), down 1.8% from $1.21 billion a year earlier but up 3.8% from the prior quarter.
Kohls (KSS) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Aug 1, 2026, Operating Expenses at Kohls was $5.06 billion, down 2.7% year-over-year; for FY2026 (ended Jan 31, 2026), it was $5.1 billion, down 5.2% from FY2025.
- Annual Operating Expenses has declined for three consecutive fiscal years, though with a five-year compound annual growth rate of 0.3% (FY2021 to FY2026).
- In prior fiscal years, Kohls' Operating Expenses was $5.38 billion in FY2025 (-2.3%), $5.51 billion in FY2024 (-1.3%), $5.59 billion in FY2023 (+2.0%) and $5.48 billion in FY2022 (+9.1%).
- Quarterly Operating Expenses has run from a low of $1.15 billion in fiscal Q1 2027 to a high of $1.69 billion in fiscal Q4 2022 over five years.
- On a year-over-year basis, Operating Expenses has declined in each of the last 11 quarters, with an average decline of 3.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q1 2023, with growth of 10.5%; the weakest was fiscal Q1 2026, with a decline of 5.2%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $1.15 billion (Q1 2027), $1.46 billion (Q4 2026) and $1.27 billion (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Kohls | 2.08 Bn | 10.19 Mn | 1.62 Bn | 1.19 Bn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 1.19 Bn |
| May 2, 2026 | 1.15 Bn |
| Jan 31, 2026 | 1.46 Bn |
| Nov 1, 2025 | 1.27 Bn |
| Aug 2, 2025 | 1.21 Bn |
| May 3, 2025 | 1.16 Bn |
| Feb 1, 2025 | 1.54 Bn |
| Nov 2, 2024 | 1.29 Bn |
| Aug 3, 2024 | 1.25 Bn |
| May 4, 2024 | 1.23 Bn |
| Feb 3, 2024 | 1.61 Bn |
| Oct 28, 2023 | 1.36 Bn |
| Jul 29, 2023 | 1.30 Bn |
| Apr 29, 2023 | 1.24 Bn |
| Jan 28, 2023 | 1.68 Bn |
| Oct 29, 2022 | 1.33 Bn |
| Jul 30, 2022 | 1.28 Bn |
| Apr 30, 2022 | 1.29 Bn |
| Jan 29, 2022 | 1.69 Bn |
| Oct 30, 2021 | 1.38 Bn |
Kohls 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=KSS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KSS", "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=KSS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();