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 |
Jan15 |
Jan16 |
Jan17 |
Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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-3.19 |
-3.24 |
-2.96 |
-3.05 |
-2.57 |
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Workday Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
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Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-3.05 |
-2.74 |
-2.98 |
-2.94 |
-2.57 |
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 * 0.894 | + | 0.528 * 0.9578 | + | 0.404 * 1.0413 | + | 0.892 * 1.1678 | + | 0.115 * 1.2844 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9922 | + | 4.679 * -0.04583 | - | 0.327 * 0.8698 |
| = | -2.57 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was $1,639 Mil.
Revenue was 1922.247 + 1865.675 + 1786.766 + 1684.312 = $7,259 Mil.
Gross Profit was 1462.031 + 1420.435 + 1338.666 + 1266.868 = $5,488 Mil.
Total Current Assets was $9,939 Mil.
Total Assets was $16,452 Mil.
Property, Plant and Equipment(Net PPE) was $1,523 Mil.
Depreciation, Depletion and Amortization(DDA) was $282 Mil.
Selling, General, & Admin. Expense(SGA) was $2,841 Mil.
Total Current Liabilities was $5,055 Mil.
Long-Term Debt & Capital Lease Obligation was $3,207 Mil.
Net Income was 1188.495 + 113.709 + 78.66 + 0.136 = $1,381 Mil.
Non Operating Income was 0.999 + -10.081 + 2.522 + -7.44 = $-14 Mil.
Cash Flow from Operations was 995.645 + 450.775 + 425.264 + 277.316 = $2,149 Mil.
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Total Receivables was $1,570 Mil.
Revenue was 1646.442 + 1599.103 + 1535.798 + 1434.657 = $6,216 Mil.
Gross Profit was 1193.141 + 1163.31 + 1112.713 + 1031.836 = $4,501 Mil.
Total Current Assets was $8,108 Mil.
Total Assets was $13,486 Mil.
Property, Plant and Equipment(Net PPE) was $1,450 Mil.
Depreciation, Depletion and Amortization(DDA) was $364 Mil.
Selling, General, & Admin. Expense(SGA) was $2,452 Mil.
Total Current Liabilities was $4,628 Mil.
Long-Term Debt & Capital Lease Obligation was $3,158 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) |
| = | (1639 / 7259) | / | (1570 / 6216) |
| = | 0.225789 | / | 0.252574 |
| | = | 0.894 |
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) |
| = | (4501 / 6216) | / | (5488 / 7259) |
| = | 0.724099 | / | 0.756027 |
| | = | 0.9578 |
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 - (9939 + 1523) / 16452) | / | (1 - (8108 + 1450) / 13486) |
| = | 0.303307 | / | 0.291265 |
| | = | 1.0413 |
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 |
| = | 7259 | / | 6216 |
| | = | 1.1678 |
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)) |
| = | (364 / (364 + 1450)) | / | (282 / (282 + 1523)) |
| = | 0.200662 | / | 0.156233 |
| | = | 1.2844 |
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) |
| = | (2841 / 7259) | / | (2452 / 6216) |
| = | 0.391376 | / | 0.394466 |
| | = | 0.9922 |
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) |
| = | ((3207 + 5055) / 16452) | / | ((3158 + 4628) / 13486) |
| = | 0.502188 | / | 0.577339 |
| | = | 0.8698 |
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 |
| = | (1381 - -14 | - | 2149) | / | 16452 |
| | = | -0.04583 |
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 -2.57 suggests that the company is unlikely to be a manipulator.
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