CHAPTER 8
APPROACHES TO INVESTMENT VALUATION
Enterprises typically have to address many opportunities for investments. Often they create these opportunities via R&D or market research. Sometimes these opportunities represent the convergence of the enterprise’s aspirations and an unexpected way to fulfill these aspirations—in other words, serendipity. Regardless of the source, a central question concerns the worth or value of the opportunity relative to the cost of pursuing it. In part due to uncertainty, enterprises usually want the assessed value to substantially exceed the projected costs.
This chapter does not address the noneconomic attributes of investments, which are often very important. For example, when a firm invests in upgrading its business processes, or in R&D to create new, proprietary technologies, it usually has other concerns that extend beyond only the economic value of the monetary investment. Typical additional concerns include strategic fit, leveraging of core competencies, and the extent to which the investment is likely to create a sustainable competitive advantage (Rouse, 2001). An investment not compatible with the firm’s business strategy, or one that requires new competencies or that creates only temporary advantage, is less likely to garner investment despite its potential investment value greatly exceeding its costs.
This chapter addresses several alternative methods for valuation of investments including discounted cash flow (DCF), the capital asset pricing model (CAPM), Holt’s cash flow ROI (CFROI) valuation (discussed in Madden, 1999), Stern–Stewart economic value added (EVA) (Stern, Shiely, Ross, 2001), and various competing methodologies. Two case studies are employed. One addresses investing in the efficiency of the processes for delivering current market offerings. The other one concerns investing in R&D to create and deploy new market offerings.
This chapter also addresses the limitations of these valuation methods. They all were developed with a particular perspective, depend on several critical assumptions, and often require parameter estimates that can be difficult to make. Several of the assumptions underlying the methods in this chapter are relaxed in Chapter 9. However, the methods in Chapter 9 involve a variety of new assumptions relative to the phenomena associated with relaxing the assumptions in this chapter.
It is important to place these valuation methods in the context of earlier expositions in this book, particularly in Chapters 2 to 4. Thus, this chapter begins by revisiting the theory of the firm and the theory of the consumer. The formulations from earlier chapters are used to pursue a notional example focused on a firm’s pricing decisions. These decisions are then linked to alternative investment decisions. This leads to a discussion of fundamental investment issues.
8.1.1 Theory of the Firm
Recall from Chapter 2 that an enterprise’s production function, f, is a specific mapping from or between the M input variables x to the production process and the output quantity produced, denoted by q:
If the firm prices these products or services at p per unit, then revenue is given by pq. If each input xi has “wage” wi, then profit ∏ is given by
8.1.2 Theory of the Consumer
In Chapter 3, it was noted that consumers consider multiple attributes, which we can denote by y1, y2,. . ., yM. Multi-attribute utility theory considers the relationship between the set of attributes of an alternative y and the consumer’s relative preferences for this alternative:
There may be K stakeholders whose preferences are of interest. This leads to the multi-attribute, multistakeholder model:
8.1.3 Example: Optimal Pricing
Consider how these simple models can provide insights into investment issues. First, assume that the consumer’s desires QD can be characterized by
Note that this assumes that the consumer values only one attribute—price. It further assumes that the consumer’s utility function is a linear function of price. In reality, one would expect a nonlinear utility function, but over small price ranges this is a reasonable approximation.
The profitability of the enterprise that provides these offerings, in quantities denoted by QP, can be characterized by
where the variable and fixed costs can be modeled by
The linear models for price sensitivity and economy of scales are shown in Fig. 8.1. These linear approximations assume that variations in prices and quantities do not take on extreme values where nonlinearities would certainly emerge.
Figure 8.1. Price Sensitivity and Economy of Scale Models.
To find the optimal pricing, one takes the first partial derivative of profit with respect to price (∂π/∂P), sets this result equal to zero, and solves for the price. To determine whether this price is a maximum or minimum, one takes the second partial derivative with respect to price (∂2π/∂P2), substitutes in the optimal price, and examines the sign of the result. If the second derivative is negative, the price is a maximum; if it is positive, the price is a minimum.
Performing these operations, along with quite a bit of algebra, yields the price that optimizes profit (Rouse, 2010):
This represents the maximum profit when αβV0Q0 ≤ GM, and the minimum loss when αβV0Q0 > GM. The latter condition holds when the parameters of the model are such that it is not possible to make a profit.
Figure 8.2 shows the sensitivity of the optimal price to market price sensitivities and economies of scale. Market price sensitivity, reflected in α, has a very strong effect, while economy of scale, captured by β, has a much more modest effect. Figure 8.3 shows the sensitivity of profit, where the disparate effects of α and β are again evident. Thus, one can see that price and profits are highly affected by the price sensitivity of the market. In contrast, investments in improvements of economies of scale do not yield the same magnitudes of returns. Thus, a firm’s discretionary monies may be better spent on convincing consumers, for example, via advertising that they want the firm’s product or service rather than invest these monies in efficiency.
Figure 8.2. Optimal Price as a Function of α and β.
Figure 8.3. Maximum Profit as a Function of α and β.
Consider the firm’s investment choices in terms of the model parameters. The firm could increase prices and profits by investing in decreasing α. They might do this by increasing advertising and/or addressing broader markets. This would tend to increase general and administrative (G&A) expenses and, hence, decrease GM that would, in turn, decrease profits. Thus, this may or may not be a good idea.
Another way to decrease α would be to invest in creating new proprietary products and services. The required R&D investments would have to be balanced against potential profits to determine whether these investments made sense. Such investments are the focus of a case study later in this chapter.
The firm could invest in improving process efficiency and, consequently, increase β. As noted above, such investments do not tend to yield the magnitude of returns possible from decreasing α. However, in some markets, for example, military aircraft, advertising does not provide much leverage, the range of customers is constrained, and new proprietary offerings are rarely initiated without customer investments.
Another approach to increasing prices and improving profits is to increase GM. This can be accomplished by shrinking G&A, disinvesting in R&D, and minimizing other costs not directly related to current offerings. This can have an immediate and significant impact. However, it also tends to mortgage the future in the sense that the investments that are curtailed may be central to success in the future.
The application of this model to price controls in healthcare provided a variety of insights (Rouse, 2010). Identifying the criteria for increased advertising, minimizing discretionary costs, or even market exit—as opposed to investing in increased efficiency—enabled predictions of these behaviors that were subsequently validated via compilations of studies where healthcare providers exhibited these exact behaviors.
Thus, both in this model and in reality, it is clear that there are important trade-offs among the possible ways to improve the firm’s profitability. The ability to address and resolve these trade-offs is central to a firm’s competitiveness and success.
8.1.4 Fundamental Investment Issues
Achieving an enterprise’s objectives requires increasing the efficiency of existing processes and/or launching new solutions that require new processes and/or technologies. In a broad sense, success depends on running the current enterprise well while also investing in and creating the future enterprise. Many senior executives find this a difficult balancing act.
It is reasonable to argue that the economic value of potential future cash flow streams should inform decisions regarding the appropriate levels of investments in these processes and technologies. The series of initiatives needed to yield these future cash flow streams can determine the processes and technologies needed and the costs of providing them. The remainder of this chapter addresses the economic valuation of such initiatives.
As noted earlier, it is important to keep in mind that noneconomic attributes can also be very important. Strategic fit, leveraging of core competencies, and sustainable advantage are all great examples of such attributes. It is very important that economic analyses and assessments be appropriate and accurate. However, this is only a necessary condition for good decision making, not a sufficient condition.
One can think about an enterprise’s investment problems in terms of three time series, with typical time increments of one year. There is the investment time series including those in R&D and capacity creation. Once capacity is created, there is the time series of operating costs for creating and delivering products and services. The third time series is of profits, which can be characterized as free cash flow. For simplicity, we will not consider issues like taxes and depreciation.
There are many uncertainties associated with these time series. There are technical uncertainties related to the success of the R&D and the creation of capacity. There are market uncertainties related to demands for products and services, both related to the nature of these offerings and the competition, as well as the economic climate. Investment valuation needs to be concerned with these types of uncertainties.
One way to mitigate these uncertainties is to stage investments (Rouse et al., 2000). For example, the enterprise might delay committing to capacity creation until the R&D has proven to be successful. It might also delay this commitment until there are clearer market signals that the demand for the offerings will be sufficient to justify investments. In Chapter 9, the economic value of being able to appropriately stage investments is discussed.
The general investment valuation problem can be stated as follows. Given the three time series described above, are the required investments worth the projected returns? Alternatively, what are the required investments worth? Clearly, one would like the worth of investments to far exceed the costs of investments.
Why do people tend to seek investments whose worth far exceeds the costs? This is due, in part, to substantial uncertainties being associated with projected returns. A significant difference between worth and cost provides a margin for error. Another reason is the typical constraints on the investment budget. If only a few investments can be made, then those alternatives whose worth most exceeds costs are a good place to start. Of course, the noneconomic attributes have to also be considered in the decision-making process.
8.2.1 Two Case Studies
Two case studies will be employed to illustrate the investment valuation methods discussed in this chapter as well as in Chapter 9. In this section, these case studies are outlined in terms of returns sought, the costs incurred, and associated uncertainties and risks.
8.2.1.1 Efficiency Case Study
The first case study focuses on investing in the efficiency of the processes for delivery of current market offerings. The returns sought include decreased variable costs as well as decreased fixed costs. There may be a trade-off between these two types of costs in that decreasing variable costs may require increasing fixed costs. The costs incurred in pursuit of these efficiencies include increased engineering costs and possibly increased capital costs for new or upgraded capacity.
Typical examples of such investments include process automation, supply chain management, sales automation, customer support, and information technology efforts more broadly. These investments often include equipment, facilities, and engineering services for installation, tailoring, and testing. There may also be training costs for the personnel whose workflow is affected by these investments.
The uncertainties and risks associated with this case study include abilities to sustain prices for current offerings, including the risk of commoditization whereby all competitors are providing effectively identical offerings, resulting in steadily decreasing prices and profit margins. There is also uncertainty associated with sustained demand for current offerings. At some point, new types of offerings will displace current offerings. Finally, there are uncertainties and risks associated with the strategies of competitors.
8.2.1.2 R&D Case Study
The second case study concerns investing in R&D to create and deploy new market offerings. The returns sought include new offerings over time, hopefully yielding price and profit premiums. The costs incurred include increased R&D costs and, assuming the R&D is successful, increased engineering costs and increased capital costs to create the needed capacity to deliver the new offerings. The estimation of such costs was addressed in Chapter 7.
Examples of R&D investments include discovery, development, and translation of new technologies into new market offerings in terms of products and services. If these investments result in proprietary capabilities (e.g., a new chip design or a new approach to process automation), the capabilities may enable price and profit premiums. In some situations, patents can prevent other firms from developing similar product, service, or process innovations.
The uncertainties and risks associated with this case study include R&D costs and the probability of technical success. There is usually considerable uncertainty in the likely demand for new offerings. Finally, there are often substantial uncertainties associated with competitors’ strategies with regard to the types of offerings envisioned and technologies pursued.
Table 8.1 shows a “pro forma” financial summary for these two case studies. The shaded areas indicate where the nonzero entries typically appear. The notes at the bottom of the table refer to whether or not costs are scalable. This refers to whether or not the demand for offerings affects these costs. Operating costs usually scale with quantity produced. Capacity costs may or may not be scalable depending on whether capacity is “fungible” relative to other uses. R&D costs are rarely scalable in that these costs are usually incurred whether or not any of the subsequent offerings are successful in the marketplace.
TABLE 8.1. Pro Forma Financials
This section describes and compares the following four different, but related, methods for valuation of investments:
- discounted cash flow (DCF);
- capital asset pricing model (CAPM);
- cash flow ROI valuation (CFROI); and
- economic value added (EVA).
Following a discussion of these methods, the methods are compared by applying them to one of the two case studies. The limitations of these approaches are also discussed, thereby setting the stage for Chapter 9.
The basic nomenclature that is employed is as follows. The time series of costs is denoted by ci, i = 0, 1, . . . N. The time series of returns is denoted by ri, i = 0, 1, . . . N. N denotes the number of time periods of interest. Often point estimates of ci and ri are employed. Of course, the use of probability distributions for these variables would usually be more appropriate, especially for returns. This possibility is pursued in more depth in Chapter 9.
8.3.1 Discounted Cash Flow
DCF is concerned with the time value of money, which was discussed in detail in Chapter 6. A given amount of money in the future is worth less than the same amount of money now. Why is this the case? The basic idea is that a given amount of money now should be worth more in the future. For example, $100 now should equal $105 dollars one year from now, assuming a 5% annual interest rate. Thus, $100 one year from now will be worth $95.24 now (i.e., $100/1.05), again assuming a 5% annual simple interest rate.
Thus, future profits or cash flows should be discounted by an interest rate that reflects the earnings forgone by delaying receipt of these cash flows. In general, the current value of money is the sum of the discounted values of future cash flows assuming a given interest rate over the period during which these cash flows will occur. This interest rate is termed the discount rate (DR) because it is the rate at which future cash flows are discounted.
The choice of DR involves significant subtleties, as elaborated in Chapter 6. One needs to decide what returns the money would have earned had the money been received now rather than in the future. Would this money have been invested in government bonds? Then the DR might be 5% or, in light of recent events, much lower. However, would the firm really have invested in government bonds?
More likely, enterprises would also have invested in other lines of business. Thus, the DR might be set as the rate of return experienced with the firm’s mature lines of business. Of course, this assumes that these funds could have been productively invested in this matter. It also assumes that the future of these lines of business will mimic the past.
Another approach to choosing the DR is to use the interest rate the firm pays to borrow funds. The idea is that delaying receipts of cash flows will, in effect at least, require the firm to borrow the amounts involved now. The firm will then have to pay interest on the borrowed monies until the future cash flows are received and the loans are repaid.
Yet another common practice is to adjust the DR to reflect perceived uncertainties associated with future cash flows. In effect, investors may feel that the projected returns, usually expressed in terms of point estimates, are actually means of distributions with very significant variances. These point estimates may also be perceived as inflated estimates of these means. Thus, it is not unusual for venture capitalists to employ DRs of 50% or more.
Clearly, investors tend to convolve many phenomena in their use of this single parameter. This is an understandable, but inappropriate, practice. The time value of money reflects the fact that future cash flows are worth less than current cash flows, for the reasons outlined above. The uncertainties and risks associated with these cash flows are related but different phenomena. This issue is revisited later in this chapter and in Chapter 9.
8.3.1.1 Net Present Value (NPV)
NPV and internal rate of return are the classic metrics associated with DCF (Brigham and Gapenski, 1988). NPV is given by
NPV reflects the amount one should be willing to pay now for benefits received in the future. These future benefits are discounted by the interest paid now to offset the delays in receiving these later benefits.
Note that NPV assumes that costs continue to be incurred over the set of time periods of interest regardless of the results in previous periods. Thus, multistage investments are assumed to succeed at each stage and justify continued investments. This assumption is relaxed in Chapter 9.
8.3.1.2 Internal Rate of Return
This metric enables comparing alternative investments by forcing the NPV of each investment to zero. Note that this assumes a fixed interest rate and reinvestment of intermediate returns at the internal rate of return. This can be problematic when there are no investment opportunities available that provide this rate of return. This difficulty is explained in detail in Chapter 6.
NPV and IRR are used pervasively across types of investments and industry domains. As discussed above, these metrics are rather assumption laden. Unfortunately, users of these metrics often forget the assumptions they have, in effect, made in adopting these metrics.
8.3.2 Example—Even Returns Versus Lump Sum Returns
Consider a time series of free cash flow of $1000 per year for 10 years versus $0 for 9 years and X in year 10: what value of X is needed for these two series to be equivalent for DRs of 5% and 10%?
Using Equation 8.11, the NPV of the even returns (i.e., $1000 per year) is $7722 and $6145 for DRs of 5% and 10%, respectively. Thus, the higher the DR, the lower the NPV. For equal NPV for the lump sum returns (i.e., $X at year 10), the value of X must be $12,578 and $15,938 for DRs of 5% and 10%, respectively.
Thus, one can see that the DR has a very significant impact. To see this, recalculate the NPV and X for a DR of 20%. The value of X needed to provide an equivalent NPV for both types of returns is $25,955. Thus, one needs 260% greater return if one has to wait 10 years to get this return.
8.3.3 Capital Asset Pricing Model
The CAPM provides a classic approach to estimating the likely returns on an asset (Luenberger, 1997). It relates the return on an asset (RA) to the risk-free rate of return (RF) and the correlation (β) of asset returns to market returns (RM):
Once RA is determined, one can project future cash flows by multiplying RA times the asset value. One can then calculate the NPV of these cash flows.
Aggressive investments or highly leveraged investments will have high β, while conservative investments whose performance is unrelated to general market behavior will have low β. Table 8.2 shows examples of β and volatility, excerpted from Luenberger (1997).
TABLE 8.2. Examples of β and Volatility
| Company | β | Volatility (σiM), % |
| 3M | 1.00 | 17 |
| Coca-Cola | 1.19 | 18 |
| General Electric | 1.26 | 15 |
| Eastman Kodak | 1.43 | 34 |
| Texas Instruments | 1.46 | 23 |
| McDonalds | 1.56 | 21 |
| Hewlett-Packard | 1.65 | 21 |
| Disney Productions | 2.23 | 22 |
| Holiday Inns | 2.56 | 39 |
| Lockheed Martin | 3.02 | 43 |
Note that CAPM is concerned with how the market is likely to view an asset, for example, an equity share in a company. This reflects, of course, past company performance. It also is highly affected by the investors’ perceptions of the company and its prospects.
8.3.4 Holt’s Cash Flow ROI Valuation
A deeper assessment focuses not just on share price but also on cash flows over time. Holt’s Value Associates has developed such a finer-grain metric, which they term CFROI (Madden, 1999). They estimate the warranted value of a firm using
Here, the first term in this equation reflects the returns on existing assets. The second term reflects returns on future investments.
This distinction is important. Classic economic theory asserts that the share price of a firm should be the NPV of future earnings, multiplied by the price–earnings ratio of the firm. For high-growth firms, this metric significantly underestimates share value because such firms have “options” to enter future markets with new offerings that will provide returns much greater than those likely from current market offerings.
If one looks at high-growth companies such as Apple, one is likely to find that their share price cannot be justified even if everyone on the world buys an iPod, iPhone, and iPad. However, the reason the company’s stock is valued so highly is that people believe the company will provide continued new innovations in future years—in other words, Apple has options on future offerings that will provide strong revenue and profit growth. We return to the distinction between returns on current and future assets in Chapter 9 and discuss metrics that go beyond NPV.
The term “warranted” is italicized in the above discussion. CFROI is concerned with what the value of a firm should be rather than what it is. If the warranted value of a firm is greater than the market value of the firm, then investing in the shares of the company is probably attractive. On the other hand, if the warranted value is less than the market value, then one should disinvest in the company.
CFROI is essentially the IRR calculated over streams of gross cash flows and current values of gross assets. Cash in equals gross cash flows per year (income, depreciation, interest, rental, etc.), while cash out equals the current value of gross assets of capital (monetary, inventories, plant, land, etc.). As with all IRR calculations, this assumes that each year all profits are reinvested with a rate of return equal to the IRR, which is often difficult to justify. This will inflate the estimated returns when one cannot get the same return from free cash flows.
We note that the warranted value includes the realizable value of nonoperating assets. Thus, it includes the liquidation value of the firm as well as its abilities to generate free cash flows. This is especially important when a firm has a significant portion of its assets that are not associated with generating its operating income.
8.3.5 Stern–Stewart Economic Value Added
CAPM is concerned with projecting the market value of an asset, while CFROI is concerned with assessing the warranted value of an asset. Another issue concerns the profit generation abilities of a firm. Stern et al. (2001) and Stewart (1991) have addressed this issue and developed a metric termed EVA as given by
where NOPAT is the net operating profit after tax, WACC is the weighted average cost of capital, and K is the capital employed. The market value added over time is given by
More specifically, NOPAT is the free cash at year-end, adjusted for R&D, inventory, depreciation, amortization of goodwill, etc. WACC is a complex function of capital structure, that is, proportion of debt and equity on the balance sheet; stock volatility, as measured by its β; and market risk premium.
Use of this metric involves addressing two challenges. First, one has to estimate the capital employed to earn the NOPAT. If this just involves financial assets, this is more straightforward than if it involves physical assets, for example, plant and equipment, or overhead assets that have to be attributed to lines of business. Second, one needs to estimate WACC that, as indicated above, can also be complicated.
Considering the nature of Equation 8.16, it is quite possible for EVA to be negative. This means that the earnings on an investment are less than the interest being paid on the capital needed to make the investment. In this case, the capital would have been better deployed elsewhere. Of course, this requires that the capital be fungible (i.e., freely usable for other purposes), which is possible with money but not necessarily with facilities and equipment. Thus, it is possible that investors may accept a negative EVA if that is the only way to stay in business and employ existing assets. Another interpretation is that the value of the assets employed is not as high as management estimates. Given that they are not fungible, perhaps they are worth less than estimated.
8.3.6 Comparison of Methods
To better understand the differences among these four metrics (i.e., DCF, CAPM, CFROI, and EVA), consider the example R&D investment summarized in Table 8.3. In this example, the firm invests $100 million in years 1 and 2 to perform the R&D to enable new market offerings. Assuming the R&D is successful, the firm then projects it will need to invest $500 million in years 3 and 4 to develop and refine the capacity to bring the new offerings to market. In year 5, the firm intends to launch the new offerings and expects annual revenues will grow from $1 billion to $3 billion over six years, while free annual cash flows grow from $200 million to $600 million.
TABLE 8.3. Example R&D Investment
The input data are shown in the top rows of Table 8.3. In the rows below this input data, one can find the results of using the four metrics discussed earlier. Using DCF, we find that NPV equals $435 million and IRR equals 20%. This appears to be a very attractive investment. CAPM has the same NPV as the cash flow time series has not changed. RA equals 25%, based on an assumed risk-free rate of 5%. Thus, we would project an annual return, or appreciation, of $109 million (i.e., 25% times the asset value of $435 million).
CFROI adds asset values into the calculation, including the capital investments on the balance sheet for years 1 to 4. These assets might, of course, depreciate but perhaps not significantly over so few years. Including these assets increases the NPV to $2420 million and the IRR to 47%. This makes the investment very attractive. The assumed fungibility of the capital investments multiplies the NPV by a factor of over five.
EVA results in an NPV of $101 million and an IRR of 12%. This is due to free cash flow being decreased by the charge for use of assets. Contrary to CFROI, investing in and leveraging assets decreases EVA. The basic premise is that these resources were, in effect at least, borrowed to enable the project, and the carrying cost of this loan needs to be paid first. Only earnings above this amount should be counted in valuation of this investment. The value added by this investment is the monies earned beyond the cost of borrowing the funds to make the investment.
Table 8.4 provides an overall comparison of results of employing these four different methods for investment valuation. Clearly, EVA is the most conservative and CFROI is the most liberal. DCF and CAPM fall in the middle. Which method is right? One could argue that the answer depends on whether one is buying or selling the asset in question. However, the real answer is that the choice depends on one’s intent for valuation of the asset.
TABLE 8.4. Comparison of Methods
| Financial metrics | Comments | |
| DCF | $435, IRR = 20% | DCF emphasizes the value of a stream of costs and returns |
| CAPM | $435, RA = 25% | CAPM emphasizes the market valuation of a firm, that is, stock price × number of shares outstanding |
| CFROI | $2420, IRR = 47% | CFROI emphasizes the warranted value of a firm, including both cash flows and asset value |
| EVA | $101, IRR = 12% | EVA emphasizes the profit generation capacity of a firm, adjusted for the cost of capital of the firm |
If one is concerned with the likely market valuation of an asset, then CAPM is likely to be a good choice, assuming estimates of β and volatility are available. On the other hand, if the concern is with the warranted value of an asset, CFROI provides an estimate of the value of projected earnings plus the value of assets, assuming that one can make reasonable estimates of the value of liquidating assets. Finally, if one wants to own the asset to gain the cash flows it can yield beyond the interest payable on loans secured to provide the monies to invest in creating these earnings, then EVA is a reasonable metric, assuming that one can attribute use of assets appropriately and determine the weighted cost of capital.
Yet, NPV and IRR are very straightforward and much less laced with assumptions, at least none that are not already underlying the other three metrics. Thus, it is reasonable to argue that one should use NPV and/or IRR unless the special purposes of CAPM, CFROI, and/or EVA are important to the investment opportunity at hand.
One concern with all four approaches is what one should assume for year 11 and beyond. As this example stands, we are assuming that the asset is of no value after the 10 years shown in Table 8.3. In fact, one may have an asset that can be monetized, but how should it be valued?
The value at the end of the period of interest is referred to as the terminal value (TV). One way to represent TV is as an annuity that provides a growing, diminishing, or constant return in perpetuity, that is, forever. The best estimate of the return for year 11 is the return for year 10, that is, $600 million. If we assume that this holds constant in perpetuity, the NPV in year 11 is $600 million divided by the DR, in this case 10%. Thus, the TV equals $6000 million. We can either hold this annuity or sell it for its NPV at that time.
Adding this TV to year 11 and recomputing the overall NPV and IRR for years 1 to 11, we obtain an NPV of $2538 million and IRR of 36%. Thus, the TV dominates the overall value of this investment, regardless of which assessment method we employ. For this reason, most investors are very wary of TV projections. They think it is most unwise to have a valuation that is dominated by an assumed value so far in the future when markets and technologies are very likely to have substantially changed. Many investors have a practice of assuming that TV equals zero. Any value that eventually emerges in year 11 and beyond is viewed as a bonus.
8.3.7 Limitations of Approaches
As indicated above, the approaches discussed and illustrated in this chapter differ in the intent for which they were developed. They have in common, however, two limitations. First, sources of uncertainty are not explicitly addressed. The DR is often used to compensate for this, but this requires one parameter to handle too many phenomena.
Ideally, one would like the three times series of interest—investments, operating costs, and profits—to be represented as probability distributions at each point in time with means and variances based on some agreed-upon logic or rationale. These inputs would then be used to compute the probability distribution of NPV or IRR, or one of the other metrics. Variations in the input assumptions would be used to assess the sensitivity of the outputs to these variations. In this way, one could project both returns and risks—a topic considered in more detail in Chapter 9.
Beyond needing a more robust approach to uncertainty and risk, the approaches in this chapter are limited by the fact that the multistage nature of decisions is not considered. Staging of decisions provides enormous value for hedging downside risks. Such staging is of economic value because it limits, perhaps truncates, the downside of the valuation probability distributions. If after a particular stage, one finds that the investment no longer makes sense, the plug is pulled and potential losses, or mediocre returns, are stopped. The approaches presented in this chapter assume that, once started, an investment is always continued. This assumption is removed in Chapter 9.
It is important to note that many situations do not warrant multiple stages of decisions. When the lion’s share of the investment must occur upfront, then the assumptions underlying NPV and IRR are not as troublesome. In contrast, when the initial investment is relatively small and later investments are relatively large, the possibility for multiple stages can make an enormous difference to the investment valuation.
This chapter first reviewed some basic principles of microeconomics from earlier chapters to frame the discussion of investment valuation. The investment problem was then outlined and two case studies described—these case studies are revisited in Chapter 9. Four standard approaches to investment valuation were then discussed—DCF, CAPM, CFROI, and EVA. A comparison of these methods, using one of the case studies, indicated substantial differences in assessment results. This can be attributed to the different intents for which each method was developed. Two important limitations of all these methods were discussed: the representation of uncertainty and the possibilities for multistage decisions. In Chapter 9, the approaches we discuss are not burdened by these limitations.
It is important to also emphasize the fact that noneconomic attributes are often also very important in investment analysis, perhaps of even greater importance than the economic attributes. The second or third best alternative from an economic point of view might be the best alternative once one considers strategic fit, leveraging of core competencies, and possibilities of sustainable competitive advantage. Nevertheless, while the numbers are not all that counts, one needs to count the numbers right.
BIBLIOGRAPHY AND REFERENCES
Brigham EF, Gapenski LC. Financial management: theory and practice. Chicago, IL: Dryden; 1988.
Luenberger DG. Investment science. Oxford, UK: Oxford University Press; 1997.
Madden BJ. CFROI valuation: a total system approach to valuing the firm. Woburn, MA: Butterworth-Heinemann; 1999.
Rouse WB. Essential challenges of strategic management. New York: Wiley; 2001.
Rouse WB. Impacts of healthcare price controls: potential unintended consequences of firms’ responses to price policies. IEEE Syst J 2010;4(1):34–38.
Rouse WB, Howard CW, Carns WE, Prendergast EJ. Technology investment advisor: an options-based approach to technology strategy. Inf Knowl Syst Manag 2000;2(1):63–81.
Stern JM, Shiely JS, Ross I. The EVA challenge: implementing value added change in an organization. New York: Wiley; 2001.
Stewart GB. The quest for value. New York: Collins; 1991.