Starbucks (SBUX) Change in Inventory (2009 - 2026)
Starbucks (SBUX) recorded Change in Inventory of $54.4 million in fiscal Q3 2026 (quarter ended Jun 28, 2026), down 72.3% from $196.6 million a year earlier and down 7.2% from the prior quarter.
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Analysis
Starbucks (SBUX) Change in Inventory (2009 - 2026) Analysis & Trends
On a TTM basis, Starbucks' Change in Inventory came in at $75.6 million as of Jun 28, 2026, down 80.2% year-over-year; for FY2025 (ended Sep 28, 2025), it was $408.4 million.
- Annual Change in Inventory has a five-year compound annual growth rate of 106.4% (FY2020 to FY2025).
- Across earlier fiscal years, Change in Inventory came in at -$42.8 million in FY2024, -$366.4 million in FY2023, $641 million in FY2022 and $49.8 million in FY2021 (+356.9%).
- Quarterly Change in Inventory has ranged from -$174.3 million in fiscal Q1 2024 to $306.1 million in fiscal Q2 2025 over the past five years.
- On a year-over-year basis, Change in Inventory rose in two of the last four quarters, with growth averaging 23.1%.
- Peak year-over-year performance for Change in Inventory in the last five years was growth of 644.6% in fiscal Q2 2022, against a decline of 100.0% in fiscal Q3 2023 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $58.6 million (Q2 2026), $31.8 million (Q1 2026) and -$69.2 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.89 Bn | 166.71 Bn | 6.42 Bn | - |
| 2 | Starbucks | 109.83 Bn | 97.45 Bn | - | 54.40 Mn |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | - |
| 4 | Chipotle Mexican Grill | 39.16 Bn | 35.14 Bn | - | 1.97 Mn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.36 Bn | 1.38 Bn | - |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | -5.30 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | - |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 38.00 Mn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 3.64 Mn |
| 10 | Luckin Coffee | 10.72 Bn | 9.80 Bn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 54.40 Mn |
| Mar 29, 2026 | 58.60 Mn |
| Dec 28, 2025 | 31.80 Mn |
| Sep 28, 2025 | -69.20 Mn |
| Jun 29, 2025 | 196.60 Mn |
| Mar 30, 2025 | 306.10 Mn |
| Dec 29, 2024 | -25.10 Mn |
| Sep 29, 2024 | -96.20 Mn |
| Jun 30, 2024 | 117.90 Mn |
| Mar 31, 2024 | 109.80 Mn |
| Dec 31, 2023 | -174.30 Mn |
| Oct 1, 2023 | -171.90 Mn |
| Jul 2, 2023 | 100,000.00 |
| Apr 2, 2023 | -86.10 Mn |
| Jan 1, 2023 | -108.50 Mn |
| Oct 2, 2022 | 83.70 Mn |
| Jul 3, 2022 | 232.40 Mn |
| Apr 3, 2022 | 288.90 Mn |
| Jan 2, 2022 | 36.00 Mn |
| Oct 3, 2021 | 58.20 Mn |
API Access
Starbucks Change in Inventory 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=change-in-inventory&ticker=SBUX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-inventory", "ticker": "SBUX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-inventory&ticker=SBUX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();