Harte Hanks (HHS) Total Non-Current Liabilities (2010 - 2026)
Harte Hanks' Total Non-Current Liabilities came in at $71.82 million for Q2 2026, up 0.5% from $71.5 million a year earlier and up 3.7% from the prior quarter.
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Analysis
Harte Hanks (HHS) Total Non-Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Harte Hanks' Total Non-Current Liabilities was $70.13 million, down 10.7% from FY2024.
- Total Non-Current Liabilities carries a five-year compound annual growth rate of -16.0% (FY2020 to FY2025).
- Going back by year, Total Non-Current Liabilities was $78.55 million in FY2024 (-22.2%), $100.97 million in FY2023 (+3.1%), $97.91 million in FY2022 (-24.0%) and $128.88 million in FY2021 (-23.2%).
- The Q2 2026 figure represents the highest quarterly Total Non-Current Liabilities since Q1 2025.
- Year-over-year, Total Non-Current Liabilities increased in 1 of the last eight quarters, with an average decline of 11.9%.
- The fastest year-over-year change in Total Non-Current Liabilities over five years came in Q4 2023 (growth of 3.1%), and the weakest in Q1 2023 (a decline of 29.0%).
- Business Quant data shows HHS's Total Non-Current Liabilities at $69.26 million (Q1 2026), $70.13 million (Q4 2025) and $71.64 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 118.39 Bn | 78.80 Bn | 6.13 Bn | 13.69 Bn |
| 2 | Cintas | 79.13 Bn | 78.31 Bn | 1.48 Bn | 2.70 Bn |
| 3 | Iron Mountain | 33.17 Bn | 32.69 Bn | 1.07 Bn | 22.86 Bn |
| 4 | APi | 16.75 Bn | 13.79 Bn | 703.00 Mn | 6.29 Bn |
| 5 | Rollins | 14.67 Bn | 14.22 Bn | 569.95 Mn | 1.79 Bn |
| 6 | Aramark | 14.35 Bn | 12.37 Bn | 430.34 Mn | 9.92 Bn |
| 7 | UL Solutions | 13.11 Bn | 11.89 Bn | 417.00 Mn | 1.41 Bn |
| 8 | Gartner | 11.73 Bn | 5.42 Bn | 1.19 Bn | 6.90 Bn |
| 9 | Rentokil Initial | 10.12 Bn | 3.46 Bn | - | -6.00 Mn |
| 10 | Harte Hanks | 34.36 Mn | 12.54 Mn | - | 71.82 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 71.82 Mn |
| Mar 31, 2026 | 69.26 Mn |
| Dec 31, 2025 | 70.13 Mn |
| Sep 30, 2025 | 71.64 Mn |
| Jun 30, 2025 | 71.50 Mn |
| Mar 31, 2025 | 77.89 Mn |
| Dec 31, 2024 | 78.55 Mn |
| Sep 30, 2024 | 85.31 Mn |
| Jun 30, 2024 | 86.65 Mn |
| Mar 31, 2024 | 91.56 Mn |
| Dec 31, 2023 | 100.97 Mn |
| Sep 30, 2023 | 88.17 Mn |
| Jun 30, 2023 | 91.73 Mn |
| Mar 31, 2023 | 91.20 Mn |
| Dec 31, 2022 | 97.91 Mn |
| Sep 30, 2022 | 121.01 Mn |
| Jun 30, 2022 | 128.67 Mn |
| Mar 31, 2022 | 128.40 Mn |
| Dec 31, 2021 | 128.88 Mn |
| Sep 30, 2021 | 147.10 Mn |
API Access
Harte Hanks Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=HHS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "HHS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=HHS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();