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ELI LILLY AND COMPANY: operating cash flow

Operating cash flow for ELI LILLY AND COMPANY. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All ELI LILLY AND COMPANY financial histories

What this measure means

Cash generated or used by operating activities. Working-capital timing can make this differ substantially from reported income.

Exact concept: us-gaap:NetCashProvidedByUsedInOperatingActivities. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Operating cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3116,813,000,000USD2026-02-1210-K · 0000059478-26-000013
2024-01-012024-12-318,818,000,000USD2026-02-1210-K · 0000059478-26-000013
2023-01-012023-12-314,240,000,000USD2026-02-1210-K · 0000059478-26-000013
2022-01-012022-12-317,585,700,000USD2025-02-1910-K · 0000059478-25-000067
2021-01-012021-12-317,365,900,000USD2024-02-2110-K · 0000059478-24-000065
2020-01-012020-12-316,499,600,000USD2023-02-2210-K · 0000059478-23-000082
2019-01-012019-12-314,836,600,000USD2022-02-2310-K · 0000059478-22-000068
2018-01-012018-12-315,524,500,000USD2021-02-1710-K · 0000059478-21-000083
2017-01-012017-12-315,615,600,000USD2020-02-1910-K · 0000059478-20-000057
2016-01-012016-12-314,851,000,000USD2019-02-1910-K · 0000059478-19-000082
2015-01-012015-12-312,964,600,000USD2018-02-2010-K · 0000059478-18-000089
2014-01-012014-12-314,458,400,000USD2017-02-2110-K · 0000059478-17-000098
2013-01-012013-12-315,735,000,000USD2016-02-1910-K · 0000059478-16-000321
2012-01-012012-12-315,304,800,000USD2015-02-1910-K · 0000059478-15-000100
2011-01-012011-12-317,234,500,000USD2014-02-1910-K · 0000059478-14-000078
2010-01-012010-12-316,856,800,000USD2013-02-2110-K · 0000059478-13-000007
2009-01-012009-12-314,335,500,000USD2012-02-2410-K · 0001193125-12-078393
2008-01-012008-12-317,295,600,000USD2011-02-2210-K · 0001193125-11-041620
2007-01-012007-12-315,154,500,000USD2010-02-2210-K · 0000950123-10-014958

Related financial histories

Inspect the source

Entity
ELI LILLY AND COMPANY / CIK 0000059478
Captured
2026-09-19T14:48:51.337Z
SEC response SHA-256
3fe29099e6efaef9acac95711c271de1a644602939ea18487e29708310985942

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000059478.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))