Ecolab Beneish M-Score Historical Data
The historical data trend for Ecolab's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Ecolab Beneish M-Score Chart
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Ecolab Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.73 |
-3.33 |
-2.53 |
-2.52 |
-2.67 |
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Ecolab Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
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Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.52 |
-2.54 |
-2.60 |
-2.69 |
-2.67 |
Competitive Comparison of Ecolab's Beneish M-Score
For the Specialty Chemicals subindustry, Ecolab's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Ecolab's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Ecolab's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ecolab's Beneish M-Score falls into.
Ecolab Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Ecolab for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 0.9707 | + | 0.528 * 0.9382 | + | 0.404 * 0.9782 | + | 0.892 * 1.0798 | + | 0.115 * 1.0753 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0294 | + | 4.679 * -0.045224 | - | 0.327 * 0.9591 |
| = | -2.67 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $3,021 Mil.
Revenue was 3938.4 + 3958.1 + 3852.1 + 3571.6 = $15,320 Mil.
Gross Profit was 1654 + 1627.6 + 1517.3 + 1366.4 = $6,165 Mil.
Total Current Assets was $5,644 Mil.
Total Assets was $21,847 Mil.
Property, Plant and Equipment(Net PPE) was $4,028 Mil.
Depreciation, Depletion and Amortization(DDA) was $924 Mil.
Selling, General, & Admin. Expense(SGA) was $4,062 Mil.
Total Current Liabilities was $4,346 Mil.
Long-Term Debt & Capital Lease Obligation was $7,977 Mil.
Net Income was 405.2 + 404 + 329.7 + 233.4 = $1,372 Mil.
Non Operating Income was -11.3 + -22.2 + -6.6 + -11.4 = $-52 Mil.
Cash Flow from Operations was 852.5 + 787.7 + 573.4 + 198.2 = $2,412 Mil.
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Total Receivables was $2,882 Mil.
Revenue was 3671.2 + 3669.3 + 3580.6 + 3266.7 = $14,188 Mil.
Gross Profit was 1416.3 + 1377.7 + 1369.5 + 1193.3 = $5,357 Mil.
Total Current Assets was $5,494 Mil.
Total Assets was $21,464 Mil.
Property, Plant and Equipment(Net PPE) was $3,742 Mil.
Depreciation, Depletion and Amortization(DDA) was $939 Mil.
Selling, General, & Admin. Expense(SGA) was $3,654 Mil.
Total Current Liabilities was $4,210 Mil.
Long-Term Debt & Capital Lease Obligation was $8,413 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (3021.1 / 15320.2) | / | (2882.2 / 14187.8) |
| = | 0.197197 | / | 0.203146 |
| | = | 0.9707 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (5356.8 / 14187.8) | / | (6165.3 / 15320.2) |
| = | 0.377564 | / | 0.402429 |
| | = | 0.9382 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (5644.1 + 4028.1) / 21846.6) | / | (1 - (5494.2 + 3741.6) / 21464.3) |
| = | 0.557267 | / | 0.569713 |
| | = | 0.9782 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 15320.2 | / | 14187.8 |
| | = | 1.0798 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (938.7 / (938.7 + 3741.6)) | / | (923.6 / (923.6 + 4028.1)) |
| = | 0.200564 | / | 0.186522 |
| | = | 1.0753 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (4061.6 / 15320.2) | / | (3653.8 / 14187.8) |
| = | 0.265114 | / | 0.257531 |
| | = | 1.0294 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((7976.9 + 4345.8) / 21846.6) | / | ((8413.1 + 4210.4) / 21464.3) |
| = | 0.564056 | / | 0.588116 |
| | = | 0.9591 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (1372.3 - -51.5 | - | 2411.8) | / | 21846.6 |
| | = | -0.045224 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Ecolab has a M-score of -2.67 suggests that the company is unlikely to be a manipulator.
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