Sangoma Technologies (SANG) Restructuring Costs (2020 - 2026)
Sangoma Technologies (SANG) posted Restructuring Costs of $1.45 million for the quarter ended Jun 30, 2026, up 224.2% from $447,000 a year earlier and up 308.2% from the prior quarter.
Sangoma Technologies (SANG) Restructuring Costs (2020 - 2026) Analysis & Trends
For the year ended Jun 30, 2026, Sangoma Technologies' Restructuring Costs came in at $2.51 million, up 160.8% from the prior year.
- Annual Restructuring Costs shows a five-year compound annual growth rate of -8.4% (years ended Jun 2021 to Jun 2026).
- In prior years, Sangoma Technologies' Restructuring Costs was $961,000 in the year ended Jun 30, 2025 (-39.8%), $1.6 million in the year ended Jun 30, 2024 (-41.1%), $2.71 million in the year ended Jun 30, 2023 (-7.8%) and $2.94 million in the year ended Jun 30, 2022 (-24.4%).
- The figure for the quarter ended Jun 30, 2026 stands as the highest quarterly Restructuring Costs since the quarter ended Jun 30, 2023.
- On a year-over-year basis, Restructuring Costs increased in three of the last five quarters, with growth averaging 91.2%.
- The strongest year-over-year quarter for Restructuring Costs in the past five years was the quarter ended Jun 30, 2025, with growth of 325.7%; the weakest was the quarter ended Jun 30, 2024, with a decline of 99.9%.
- According to Business Quant data, Restructuring Costs for the three prior quarters was $355,000 (quarter ended Mar 31, 2026), $139,000 (quarter ended Dec 31, 2025) and $563,000 (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Adobe | 90.32 Bn | 65.57 Bn | 6.00 Bn |
| 2 | Atlassian | 46.45 Bn | 39.73 Bn | 1.53 Bn |
| 3 | Twilio | 44.08 Bn | 34.07 Bn | 725.87 Mn |
| 4 | Autodesk | 43.30 Bn | 31.34 Bn | 1.87 Bn |
| 5 | Zoom Communications | 25.52 Bn | -5.27 Bn | 985.50 Mn |
| 6 | Figma | 10.74 Bn | 4.24 Bn | 309.61 Mn |
| 7 | Dropbox | 7.01 Bn | 2.65 Bn | 506.50 Mn |
| 8 | Nice | 6.59 Bn | 5.06 Bn | 995.81 Mn |
| 9 | RingCentral | 6.37 Bn | 5.87 Bn | 472.31 Mn |
| 10 | Sangoma Technologies | 119.69 Mn | 119.69 Mn | 32.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.45 Mn |
| Mar 31, 2026 | 355,000.00 |
| Dec 31, 2025 | 139,000.00 |
| Sep 30, 2025 | 563,000.00 |
| Jun 30, 2025 | 447,000.00 |
| Mar 31, 2025 | 272,000.00 |
| Dec 31, 2024 | 242,000.00 |
| Jun 30, 2024 | 105,000.00 |
| Dec 31, 2023 | 1.34 Mn |
| Sep 30, 2023 | 156,000.00 |
| Jun 30, 2023 | 76.86 Mn |
| Mar 31, 2023 | 2.19 Mn |
| Dec 31, 2022 | 355,000.00 |
| Sep 30, 2022 | 52,000.00 |
| Jun 30, 2022 | -182,000.00 |
| Mar 31, 2022 | 3.12 Mn |
| Jun 30, 2021 | 124,544.00 |
| Mar 31, 2021 | 3.76 Mn |
| Dec 31, 2020 | 750,000.00 |
Sangoma Technologies Restructuring Costs 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=restructuring-costs&ticker=SANG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "restructuring-costs", "ticker": "SANG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=restructuring-costs&ticker=SANG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();