Factset Research Systems (FDS) Property, Plant & Equipment (Net) (2010 - 2026)
Factset Research Systems' Property, Plant & Equipment (Net) was $79.25 million in fiscal Q4 2026 (quarter ended Aug 31, 2026), down 7.0% from $85.2 million a year earlier and down 3.7% from the prior quarter.
Factset Research Systems (FDS) Property, Plant & Equipment (Net) (2010 - 2026) Analysis & Trends
From fiscal Q4 2010 onward, Factset Research Systems has reported Property, Plant & Equipment (Net) for 65 quarters.
- Property, Plant & Equipment (Net) shows a five-year compound annual growth rate of -9.6% (FY2021 to FY2026).
- In earlier fiscal years, Property, Plant & Equipment (Net) was $85.2 million in FY2025 (+3.3%), $82.51 million in FY2024 (-4.2%), $86.11 million in FY2023 (+6.5%) and $80.84 million in FY2022 (-38.5%).
- The fiscal Q4 2026 figure marks the lowest quarterly Property, Plant & Equipment (Net) since fiscal Q3 2016.
- Compared with a year earlier, Property, Plant & Equipment (Net) was higher in four of the last eight quarters, with growth averaging 0.6%.
- The best year-over-year quarter for Property, Plant & Equipment (Net) over five years was fiscal Q4 2023 (growth of 6.5%); the worst was fiscal Q4 2022 (a decline of 38.5%).
- Per Business Quant data, FDS's Property, Plant & Equipment (Net) in the three fiscal quarters before Q4 2026 was $82.32 million (Q3 2026), $84.43 million (Q2 2026) and $84.96 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | PP&E (Net) (Qtr) |
|---|---|---|---|---|---|
| 1 | S&P Global | 132.72 Bn | 128.33 Bn | 2.98 Bn | 254.00 Mn |
| 2 | Moodys | 83.35 Bn | 76.42 Bn | 1.50 Bn | 782.00 Mn |
| 3 | Msci | 44.14 Bn | 42.62 Bn | 739.80 Mn | 99.10 Mn |
| 4 | Verisk Analytics | 25.49 Bn | 20.13 Bn | 572.90 Mn | 580.60 Mn |
| 5 | Equifax | 21.35 Bn | 20.74 Bn | 940.10 Mn | 1.92 Bn |
| 6 | TransUnion | 15.61 Bn | 12.59 Bn | - | 270.90 Mn |
| 7 | Factset Research Systems | 11.68 Bn | 10.53 Bn | 308.40 Mn | 79.25 Mn |
| 8 | Morningstar | 8.44 Bn | 6.34 Bn | 423.90 Mn | 239.60 Mn |
| 9 | Mastercard | 542.86 Bn | 502.77 Bn | - | 2.54 Bn |
| 10 | Cme | 109.27 Bn | 97.61 Bn | - | 338.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 79.25 Mn |
| May 31, 2026 | 82.32 Mn |
| Feb 28, 2026 | 84.43 Mn |
| Nov 30, 2025 | 84.96 Mn |
| Aug 31, 2025 | 85.20 Mn |
| May 31, 2025 | 79.63 Mn |
| Feb 28, 2025 | 79.74 Mn |
| Nov 30, 2024 | 81.52 Mn |
| Aug 31, 2024 | 82.51 Mn |
| May 31, 2024 | 80.84 Mn |
| Feb 29, 2024 | 80.97 Mn |
| Nov 30, 2023 | 83.17 Mn |
| Aug 31, 2023 | 86.11 Mn |
| May 31, 2023 | 81.91 Mn |
| Feb 28, 2023 | 81.79 Mn |
| Nov 30, 2022 | 79.30 Mn |
| Aug 31, 2022 | 80.84 Mn |
| May 31, 2022 | 85.63 Mn |
| Feb 28, 2022 | 114.79 Mn |
| Nov 30, 2021 | 122.41 Mn |
Factset Research Systems Property, Plant & Equipment (Net) 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=property-plant-and-equipment-net&ticker=FDS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "property-plant-and-equipment-net", "ticker": "FDS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=property-plant-and-equipment-net&ticker=FDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();