No matter how well you plan and manage your company, you cannot guarantee that you won’t be one of the 40,000 companies filing bankruptcy in a given year. Not all factors resulting in business failure are under your control. Too often, though, companies fail because managers don’t have the tools to quickly check solvency. Here is one time-tested formula for predicting your chances of survival:

In 1966, Dr. Edward Altman, a financial economist in the Graduate School of Business at New York University, developed a model for predicting the likelihood of business failure. Applying a statistical technique called multiple discriminant analysis (MDA) to a sample of 66 corporations, half of which had filed bankruptcy during the previous three decades and half of which remained solvent, he developed the “Z Score” model still used by many credit analysts today.

The asset size of the original sample ranged from approximately \$5 million to \$130 million (in 2005 dollars), and the MDA analysis allowed Altman to extract the most accurate of 22 common financial ratios, weighting the formula for each to produce a single score. The model was modified and adapted for three categories of business—manufacturing (public and private) and a general use model. How does it work?

The original model was based on five ratios, using six balance sheet and two income statement figures. Figures based on balance sheet values include the following:

• Working capital (current assets minus current liabilities)
• Total assets
• Book value of total liabilities
• Retained earnings (the net historical total of profit and loss)
• Net worth (also called equity or shareholders’ equity)
• Market value of equity (common and preferred stock close to the statement date)

From the income statement come the other two figures: sales (all revenues) and EBIT (earnings before interest and taxes).

The system’s original formula, 1*A + 1.4*B + 3.3*C + 0.6*D + 1.0*E, can be used in conjunction with the results from the table below to determine the “Z Score.” A company with \$1 million in assets produces a healthy score of 3.94. Scores above 3.0 indicate solvency, 2.7 requires attention and 1.8 predicts bankruptcy within two years. The level of assets is critical in four of the five ratios.

Unfortunately, for privately held companies, there is no obvious market value of stock (ratio D), and the asset turnover (ratio E) values can vary widely between different industries. If this is a typical electrical contracting company, the 3.94 score may not be the level of security it seems to indicate.

To improve the accuracy of the model, Altman revised the model to include three different categories of business—private manufacturing, publicly traded manufacturing and general use, which are all non-manufacturing companies. In the general use category, ratios D and E are omitted. Instead, a ratio is substituted that compares net worth to total liabilities (new ratio D), and the weights are adjusted, producing the formula 6.56*A + 3.26*B + 6.72*C + 1.05*D with a resulting score of 3.74. There is still a strong likelihood of future survival for this electrical contractor using the same financial statement values.

So, what is the real value of the Z Score? It is not a cure for bad financial management or unanticipated problems. It is an easy way to check solvency in time to take action. Although the model is not perfect, it is one of the most widely used analytical tools available, is simple to plug into your accounting system and is quick to review.

A Google search produces more than 300,000 links, including built-in calculators such as the one on the Credit Guru site (www.creditguru.com), so you don’t have to alter your accounting system. You can test the effects of changes in asset level or other components of the formula. With such an accessible and easily interpreted tool, there is no longer any reason to let failure sneak up on your company because you will be wide awake when you catch your “Zs.”    EC

NORBERG-JOHNSON is a former subcontractor and past president of two national construction associations. She may be reached via e-mail at bigpeng@sbcglobal.net