Si-Bone (SIBN) Change in Inventory (2017 - 2026)
Si-Bone (SIBN) recorded Change in Inventory of $2.81 million in Q2 2026, down 37.9% from $4.53 million a year earlier but up 37.8% from the prior quarter.
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Analysis
Si-Bone (SIBN) Change in Inventory (2017 - 2026) Analysis & Trends
On a TTM basis, Si-Bone's Change in Inventory came in at $5.24 million as of Jun 30, 2026, down 59.8% year-over-year; for FY2025, it was $8.68 million, up 7.9% from FY2024.
- Annual Change in Inventory has a five-year compound annual growth rate of 99.6% (FY2020 to FY2025).
- Across earlier years, Change in Inventory came in at $8.05 million in FY2024 (+70.5%), $4.72 million in FY2023 (-21.7%), $6.03 million in FY2022 (+4.2%) and $5.78 million in FY2021.
- Quarterly Change in Inventory has ranged from -$1.65 million in Q4 2025 to $4.53 million in Q2 2025 over the past five years.
- On a year-over-year basis, Change in Inventory rose in three of the last six quarters, with growth averaging 67.9%.
- Peak year-over-year performance for Change in Inventory in the last five years was growth of 500.3% in Q3 2023, against a decline of 85.7% in Q3 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $2.04 million (Q1 2026), -$1.65 million (Q4 2025) and $2.04 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | - |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 301.00 Mn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 46.00 Mn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 248.00 Mn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 240.00 Mn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 113.00 Mn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 133.00 Mn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 23.50 Mn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | - |
| 10 | Si-Bone | 840.31 Mn | 256.12 Mn | 44.55 Mn | 2.81 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.81 Mn |
| Mar 31, 2026 | 2.04 Mn |
| Dec 31, 2025 | -1.65 Mn |
| Sep 30, 2025 | 2.04 Mn |
| Jun 30, 2025 | 4.53 Mn |
| Mar 31, 2025 | 3.77 Mn |
| Dec 31, 2024 | 2.13 Mn |
| Sep 30, 2024 | 2.61 Mn |
| Jun 30, 2024 | 2.54 Mn |
| Mar 31, 2024 | 772,000.00 |
| Dec 31, 2023 | -510,000.00 |
| Sep 30, 2023 | 1.78 Mn |
| Jun 30, 2023 | 2.92 Mn |
| Mar 31, 2023 | 536,000.00 |
| Dec 31, 2022 | 850,000.00 |
| Sep 30, 2022 | 296,000.00 |
| Jun 30, 2022 | 1.70 Mn |
| Mar 31, 2022 | 3.18 Mn |
| Dec 31, 2021 | 1.24 Mn |
| Sep 30, 2021 | 2.06 Mn |
API Access
Si-Bone 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=SIBN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-inventory", "ticker": "SIBN", "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=SIBN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();