PagerDuty (PD) Other Operating Expenses (2018 - 2026)
PagerDuty (PD) recorded Other Operating Expenses of $38.33 million in fiscal Q2 2027 (quarter ended Jul 31, 2026), down 13.8% from $44.46 million a year earlier and down 3.2% from the prior quarter.
PagerDuty (PD) Other Operating Expenses (2018 - 2026) Analysis & Trends
On a TTM basis, PagerDuty's Other Operating Expenses came in at $167.47 million as of Jul 31, 2026, down 14.9% year-over-year; for FY2026 (ended Jan 31, 2026), it was $184.04 million, down 8.8% from FY2025.
- Annual Other Operating Expenses has a five-year compound annual growth rate of 8.5% (FY2021 to FY2026).
- Across earlier fiscal years, Other Operating Expenses came in at $201.82 million in FY2025 (+2.6%), $196.77 million in FY2024 (+0.6%), $195.62 million in FY2023 (+21.0%) and $161.62 million in FY2022 (+32.3%).
- The fiscal Q2 2027 figure is the lowest quarterly Other Operating Expenses since fiscal Q1 2022.
- On a year-over-year basis, Other Operating Expenses has declined for five consecutive quarters, with an average decline of 8.9% over the last eight quarters.
- Peak year-over-year performance for Other Operating Expenses in the last five years was growth of 28.1% in fiscal Q4 2022, against a decline of 20.9% in fiscal Q1 2027 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $39.61 million (Q1 2027), $45.22 million (Q4 2026) and $44.32 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | PagerDuty | 1.19 Bn | -729.06 Mn | 104.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 38.33 Mn |
| Apr 30, 2026 | 39.61 Mn |
| Jan 31, 2026 | 45.22 Mn |
| Oct 31, 2025 | 44.32 Mn |
| Jul 31, 2025 | 44.46 Mn |
| Apr 30, 2025 | 50.05 Mn |
| Jan 31, 2025 | 53.08 Mn |
| Oct 31, 2024 | 49.27 Mn |
| Jul 31, 2024 | 50.97 Mn |
| Apr 30, 2024 | 48.50 Mn |
| Jan 31, 2024 | 53.61 Mn |
| Oct 31, 2023 | 49.63 Mn |
| Jul 31, 2023 | 49.72 Mn |
| Apr 30, 2023 | 43.80 Mn |
| Jan 31, 2023 | 52.62 Mn |
| Oct 31, 2022 | 47.12 Mn |
| Jul 31, 2022 | 50.33 Mn |
| Apr 30, 2022 | 45.55 Mn |
| Jan 31, 2022 | 43.40 Mn |
| Oct 31, 2021 | 40.18 Mn |
PagerDuty Other 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=other-operating-expenses&ticker=PD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "PD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=PD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();