Workday Beneish M-Score Historical Data
The historical data trend for Workday'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.
Workday Beneish M-Score Chart
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Workday Annual Data
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Trend |
Jan16 |
Jan17 |
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Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
Jan25 |
| Beneish M-Score |
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-3.24 |
-2.96 |
-3.04 |
-2.57 |
-2.76 |
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Workday Quarterly Data
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Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
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Oct22 |
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Jan24 |
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Jul24 |
Oct24 |
Jan25 |
| Beneish M-Score |
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-2.57 |
-2.53 |
-2.57 |
-2.42 |
-2.76 |
Competitive Comparison of Workday's Beneish M-Score
For the Software - Application subindustry, Workday'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.
Workday's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Workday's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Workday's Beneish M-Score falls into.
Workday 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 Workday 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 * 1.1217 | + | 0.528 * 1.0015 | + | 0.404 * 1.0742 | + | 0.892 * 1.2739 | + | 0.115 * 0.9828 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9822 | + | 4.679 * -0.097003 | - | 0.327 * 0.976 |
| = | -2.54 |
* 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 (Jan25) TTM: | Last Year (Jan24) TTM: |
Total Receivables was MXN40,227 Mil.
Revenue was 45610.719 + 43267.824 + 38775.788 + 33957.758 = MXN161,612 Mil.
Gross Profit was 34491.688 + 32651.182 + 29272.465 + 25613.364 = MXN122,029 Mil.
Total Current Assets was MXN217,533 Mil.
Total Assets was MXN370,848 Mil.
Property, Plant and Equipment(Net PPE) was MXN32,491 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN6,249 Mil.
Selling, General, & Admin. Expense(SGA) was MXN62,159 Mil.
Total Current Liabilities was MXN114,450 Mil.
Long-Term Debt & Capital Lease Obligation was MXN67,312 Mil.
Net Income was 1939.126 + 3866.06 + 2454.87 + 1825.869 = MXN10,086 Mil.
Non Operating Income was -1939.126 + 100.157 + -55.793 + -85.321 = MXN-1,980 Mil.
Cash Flow from Operations was 22939.448 + 8132.748 + 10619.173 + 6347.882 = MXN48,039 Mil.
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Total Receivables was MXN28,152 Mil.
Revenue was 33012.656 + 33686.898 + 29875.602 + 30290.95 = MXN126,866 Mil.
Gross Profit was 25111.604 + 25653.313 + 22385.804 + 22790.163 = MXN95,941 Mil.
Total Current Assets was MXN170,714 Mil.
Total Assets was MXN282,583 Mil.
Property, Plant and Equipment(Net PPE) was MXN26,159 Mil.
Depreciation, Depletion and Amortization(DDA) was MXN4,928 Mil.
Selling, General, & Admin. Expense(SGA) was MXN49,681 Mil.
Total Current Liabilities was MXN86,826 Mil.
Long-Term Debt & Capital Lease Obligation was MXN55,084 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) |
| = | (40226.55 / 161612.089) | / | (28151.792 / 126866.106) |
| = | 0.248908 | / | 0.221902 |
| | = | 1.1217 |
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) |
| = | (95940.884 / 126866.106) | / | (122028.699 / 161612.089) |
| = | 0.756237 | / | 0.755072 |
| | = | 1.0015 |
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 - (217532.805 + 32490.675) / 370847.533) | / | (1 - (170714.252 + 26159.353) / 282582.843) |
| = | 0.325805 | / | 0.303307 |
| | = | 1.0742 |
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 |
| = | 161612.089 | / | 126866.106 |
| | = | 1.2739 |
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)) |
| = | (4928.467 / (4928.467 + 26159.353)) | / | (6248.8 / (6248.8 + 32490.675)) |
| = | 0.158534 | / | 0.161303 |
| | = | 0.9828 |
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) |
| = | (62158.921 / 161612.089) | / | (49680.835 / 126866.106) |
| = | 0.384618 | / | 0.391601 |
| | = | 0.9822 |
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) |
| = | ((67312.427 + 114449.692) / 370847.533) | / | ((55084.073 + 86825.691) / 282582.843) |
| = | 0.490126 | / | 0.502188 |
| | = | 0.976 |
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 |
| = | (10085.925 - -1980.083 | - | 48039.251) | / | 370847.533 |
| | = | -0.097003 |
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.
Workday has a M-score of -2.54 suggests that the company is unlikely to be a manipulator.
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