Beyond the Altman Z-Score: Predicting Vendor Financial Viability in a SaaS World

As CFO of Coupa, a high-growth, pre-IPO Software as a Service (SaaS) company, I frequently have conversations with finance groups at customer and prospect organizations who want to make sure that our company will be around for the long term. It’s a reasonable conversation to have since they’re investing in our solution to support critical business processes. One only need look at the pre-IPO financials of any SaaS company to understand how for those uninitiated into the SaaS business model, this conversation can sometimes be challenging.

The most challenging conversations are with organizations that have decided to rely on the Altman Z-Score as their test of vendor viability. The Altman Z-Score is a measure that was developed in 1967 by Edward Altman, then an assistant finance professor at NYU’s Stern School of Business, to predict the likelihood of a company going bankrupt.

The original Z-Score was used to evaluate U.S. public manufacturing companies. New versions retaining the same basic construct followed. Z’-Score is used for evaluating U.S. private manufacturing companies.  Z”-Score was designed to be applied to U.S. non-manufacturing firms and foreign firms. The calculation for Z”-Score, which finance groups typically use to evaluate SaaS companies, is as follows:

Z”-Score = 6.56A + 3.26B + 6.72C + 1.05D + 3.25

Where:

A = Working Capital/Total Assets

B = Retained Earnings/Total Assets

C = Earnings Before Interest & Tax/Total Assets

D = Book Value of Equity/Total Liabilities

Professor Altman posited that a score below 1.8 means the company is probably headed for bankruptcy, while companies with scores above 3.0 are not likely to go bankrupt. The lower the score, the higher the likelihood of bankruptcy, and vice versa. While historically this has been a very accurate predictive metric, I believe its usefulness is questionable when it is used to evaluate emerging SaaS companies. There are a number of reasons for this.

First off, a big chunk of SaaS company assets take the elevator each day and don’t show up on the balance sheet. Liabilities consist principally of deferred subscription fees that must be carried on the balance sheet until revenue recognition, rather than debts payable in cash. At my company and many others, there are no retained earnings as a result of a continually growing investment in product, support, and operations.

This is all standard operating procedure for a SaaS business, and applying the Altman Z”-Score doesn’t yield an attractive number. To illustrate, here are the Z”-scores for some of the most successful SaaS companies, as calculated for the year prior to each of their IPOs based on their public filings on sec.gov:

salesforce.com = .22 + (6.26) + (1.66) + 0.15 + 3.25 = (4.30)

NetSuite = (4.39) + (12.84) + (3.12) + (0.53) + 3.25 = (17.63)

Marketo = 2.35 + (3.39) + (2.90) + 1.29 + 3.25 = 0.60

Workday = (0.27) + (6.37) + (3.74) + (0.19) + 3.25 = (7.32)

According to their Altman Z”-scores, all of these companies were on the brink of disaster, yet less than 12 months prior to going public, none of them were in any actual danger of going bankrupt. So if the Z”-Score wasn’t indicative of sustainability for these companies, what should finance professionals look at to evaluate private SaaS vendor viability?

I think the important factors to consider are:

•        Ability to raise funds: How is the company funded and does it appear that this funding mechanism is sustainable? If a company has a history of raising money from a diverse group of investors, it is a good indicator of investor interest and there is a stronger likelihood that this will continue. For startups in general, investors and management are not interested in raising too much money in advance of requirements, so the ability to raise money predictably can be more important than cash on the balance sheet.
•        Participation of existing investors: Have early investors continued to participate in subsequent funding rounds? High participation confirms their support of the company. Non-participation may indicate disillusionment and should be investigated.
•        Cash net of debt: The ability to raise funds is great. Money in the bank is even better. Paying the bills clearly demonstrates sustainability. If the company has readily available liquidity, most other metrics pale in comparison.
•        Product Investment: A focus on investing in research and development, rather than on maximizing short-term cash flows, shows that investors and management see a long-term opportunity for the business. A meaningful investment in developing and expanding the product demonstrates commitment to that opportunity.
•        Growth: Growth is the lynchpin of venture investments, and ironically investing for growth also has the biggest negative impact on Z”-Score.  If you need capital and you’re growing, that capital is readily available. However, if you need capital and you’re not growing you may not have a sustainable business model.

As you can see, none of this is neatly captured by Altman’s formulas. With SaaS and other cloud models becoming more and more prevalent, we need a new scoring method that addresses factors such as, rounds of capital raised, months of runway held in cash, percent of new and existing investors participating in each round, and amount of investment in R&D relative to total capital raised.

Altman’s Z-Scores provide a proven formula that has stood the test of time, but they are not universally applicable in today’s climate of rapid innovation and cloud business models.  It takes more judgment and a different kind of understanding to assess a company’s prospects by looking at its fundraising history, near-term runway and the investment the company is making in the future of its product, but you have a better chance of being right than if you apply a formula that doesn’t fit. Imagine having passed on salesforce, NetSuite, Marketo or Workday on the basis of their Z”-Scores. When it comes to private SaaS companies, it could be more dangerous to rely on a formula than not.

This article previously appeared on cfo.com.