Editor’s note: David C. Dufendach is a CPA/ABV, ASA Valuations Services with Grant Thornton.Three generic factors drive the value of virtually all businesses — cash flow, growth of those cash flows and the riskiness of those cash flows.

Both the magnitude and direction of these value drivers are affected by various external and internal events. Technology companies must deal with a particularly complex set of potential events, and traditional valuation methods are often not flexible enough to capture this complexity.

Fortunately, advanced methods are available; such methods are designed to capture value-creating events explicitly. In doing so, they provide not only a measure of value at a point in time, but also a road map of future decision points, facilitating the management of value creation itself.

Traditional Valuation Concepts

As noted earlier, the value of any business enterprise can be determined through an analysis of cash flow, growth and risk considerations. The contribution each of these makes to an enterprise’s value tends to vary with the stage of the entity’s maturity, as well as other factors. Late-stage, mature companies, for example, may generate high levels of cash flow (due to low reinvestment needs), have low or negative growth prospects, and have low to moderate risk. At the other end of the spectrum, early-stage technology companies often have negative cash flow, but possess high growth opportunities and attendant risks. In between, of course, are various combinations.

Two basic valuation approaches are designed to measure value based on the generic value drivers discussed above. The first is commonly referred to as the income approach. Within this approach are two frequently encountered methodologies: the discounted future cash flow (DFCF) method and the single-period capitalization of earnings (Capitalized Earnings) method. Both of these methods are employed to estimate value based on expected future earnings or cash flows.

The major difference between them is that the DFCF method looks at multiple future periods, discounting all of these future cash flows back to the present using an appropriate discount rate. In this method, each value driver is explicitly modeled in each year of the forecast period.

The Capitalized Earnings method, on the other hand, utilizes only a single future period’s estimated earnings or cash flow. Implicit in this method is that growth (of annual cash flow) and risk in all future periods will be constant. The linkage with the value drivers is less direct than with the DFCF method — to estimate value under the Capitalized Earnings method, the next period’s earnings serve as a proxy for future cash flow, and the single capitalization rate must capture both the expected (constant) growth and expected (constant) risk. Higher growth expectations produce lower capitalization rates and higher value; higher risks produce higher capitalization rates and lower value.

The second traditional approach is commonly referred to as the market approach. Within the market approach are many of the multiples (“Market Multiples”) that are frequently mentioned in the business press: price/earnings (“P/E”), price/revenue (“P/R”), price/earnings before interest, taxes, depreciation and amortization (“P/EBITDA”), and others. Under this approach, multiples of publicly traded “guideline” companies are calculated. Once this range of multiples is obtained, an “appropriate” multiple is selected (for example, the P/E multiple) to estimate the price (P) of a share of stock based upon a multiple of its annual earnings per share (E). The linkage with the three value drivers using Market Multiples is virtually identical to the Capitalized Earnings method — earnings are considered to be a proxy for cash flow, and the Market Multiple simultaneously captures both expected (constant) growth and (constant) risk.

Higher growth prospects imply the selection of higher multiples and produce higher values; higher risks imply lower multiples and values.

Of course, proper application of this valuation approach requires the existence of suitable guideline companies. To be suitable, a guideline company should have similar expectations for cash flow, growth and risk. With respect to technology companies, therefore, a guideline company should have similar expectations about a complex set of future external and internal events that will have a material impact on these value drivers. In a practical sense, this means that guideline companies should be similar in many important ways, such as stage of maturity, breadth of potential products, depth of management, nature of end-markets, and quality of intellectual property. This makes the prospect of finding suitable guideline companies a challenging task.

To summarize, it is easy to see that a company that has a) reached a stable level of earnings or cash flow, with b) prospects for steady growth, and c) a risk profile that is not expected to change significantly during the foreseeable future, may be a good candidate for either the Capitalized Earnings method or the application of Market Multiples. Conversely, if any of these three value drivers are subject to material fluctuation, it is also apparent that a DFCF method of valuation may be superior, due to its ability to handle variable cash flows, unsteady growth, and/or fluctuating risks explicitly in each future period.

Unique aspects of early-stage technology companies

By their nature, early-stage technology companies are more difficult to value using traditional valuation approaches. Expected cash flows are often highly variable from period to period; growth rates may vary dramatically; and, most importantly, the risk profile itself generally changes over time, as companies move from research and development phases to the commercialization stage.

Given these characteristics, both of the single-period valuation methods (Capitalized Earnings, Market Multiples) can be problematic. Because these two methods only allow for two inputs (earnings/cash flow and capitalization rate/multiple), the potential variability in cash flow, growth and risk must be averaged in some fashion. As discussed, DFCF methods can be superior in this situation, due to the ability to model each future period’s value drivers explicitly. However, even DFCF methods fall short in the presence of complex risk profiles often present in early stage technology companies.

Biotechnology companies provide an excellent illustration of these issues. The outlook for these enterprises is subject to multiple risks, each of which can evolve differently. The external environment presents the company with market risks:

  • Will the ultimate product be accepted in the market?

  • Will demand be sufficiently high?

  • What unit price will prevail?

  • How much competition will the company face?
  • The external environment also presents the enterprise with legal and regulatory risks:

  • Will patent protection be obtained?

  • Will FDA approvals be obtained?
  • Internally, the company faces technology risks, in the form of milestones to be achieved:

  • Will the drug be safe?

  • Will it work?

  • Can it be produced in commercial quantities?
  • Internal risks also include non-technology related factors:

  • Will sufficient capital be available?

  • Can necessary strategic partnerships be obtained?
  • It is important to note that some of these risks are linear — e.g., will the product sell for $40, $50 or $60 per a dose? Other risks are actually contingencies, and can have extremely severe consequences — e.g., failure in Stage II trials may mean the company or project fails entirely. It is these contingent aspects of early-stage technology companies that produce major difficulties for traditional valuation methods, which are not flexible enough to handle contingent outcomes.

    Advanced models are available

    Fortunately, there are financial tools available to deal with tough valuation issues such as contingent outcomes. The two most common are decision analysis and option pricing methods. In decision analysis, contingencies can be dealt with probabilistically. If management believes there is a 25 percent chance of technological failure, for example, a decision tree can be constructed that shows a DFCF approach along the successful (75 percent) branch, and project or company abandonment along the unsuccessful (25 percent) branch. Note that, in this simplified example, the complex risk profile is now divided into two parts — a market risk that the DFCF method captures, and a technology risk that the decision tree captures.

    The other advanced methodology available is the option pricing method. Originally developed to estimate the value of stock options and other financial assets, this method can also be applied to estimate the value of operating, or “real” assets (and hence it is often referred to as the “real options” approach). Real options methods appear to be similar to decision trees (and are frequently used in conjunction with them), but are better in one key respect — the real options approach is more precise in adjusting business values for risks that produce “out-of-the-money” outcomes for the underlying business.

    Managing value drivers

    The final benefit provided by advanced valuation methods is that they can provide management with a road map of the future, as well as a series of decision rules to apply as risks unfold. For example, the use of a decision tree forces management to explicitly model contingent outcomes such as “hoped-for” FDA approvals or technology milestones. This modeling process includes not only the expected risks and benefits with regard to anticipated events/milestones, but also the specific costs and probabilities of success associated with each such event.

    Traditional valuation models do not provide this “granularity” and, therefore, even if they do produce a reasonable approximation of value, they are of little future benefit once a business or project is launched.

    In summary, there are two clear advantages associated with advanced valuation methods with respect to technology companies. First, with their explicit focus on each factor that is expected to impact value, these methods are much more likely to produce reasonable and more realistic values. Second, as the outcome of each major event becomes known, the key variables facing management in the next phase have already been identified, facilitating management’s future decision-making and value-creating process.

    Reprinted with permission from Grant Thornton. Grant Thornton International is the world’s leading accounting, tax and business advisory organization dedicated to middle market companies. Through its network of 585 offices in 110 countries, including 48 offices in the U.S., the firm has regional offices in Charlotte, Raleigh, and Greensboro, N.C., and Columbia, SC.