- Email: [email protected]
Real options analysis of the timing of IS investment decisions
Information & Management 39 (2002) 337±344
Real options analysis of the timing of IS investment decisions John A. Campbell* School of Management, Faculty of Commerce and Management, Grif®th University, Meadowbrook 4131, Australia Received 20 November 2000; accepted 21 April 2001
Abstract Many information systems (IS) investments belong to a class of capital budgeting problem where there is an option: the investment may be made straight away or delayed for some period. A real options analysis could allow decision-makers to add value to these investment decisions by providing a framework that explicitly recognises uncertainty. This paper uses options pricing theory to determine the optimal timing of IS investments and to explore the effect of different investment review cycles. The ®ndings provide support for the common industry practice of demanding short payback periods for IS investments. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Real options; IS investments; Investment timing
1. Introduction Under conditions of uncertainty, investment ¯exibility is an important and valuable consideration. There is a growing view that the techniques used to evaluate ®nancial options might be appropriate, in certain circumstances, for evaluating capital investments that have option like characteristics [6,8,13,17,18]. These types of investment choices are often referred to as real options, as the investment opportunities typically involve real assets (information systems (IS), factories, new products, etc.) rather than paper-based assets (stocks, bonds, currencies, etc.). For many approved capital projects there is often an option to delay the project start-up to a more suitable date if circumstances are not supportive. For example, management faced with implementing several large projects at the same time may opt for a staggered * Tel.: 61-7338-21119; fax: 61-7338-21408. E-mail address: [email protected] (J.A. Campbell).
series of start-up dates to maximise resource availability and utilisation. This and other option-like characteristics are found in many IS projects. In recent times, strong arguments have been put forward for using options pricing theory to evaluate IS project investments (see, e.g. [3,4,9,20]). This literature advocates various innovative means of valuing investment ¯exibility using relevant aspects of options pricing theories. The range of investment options studied in this way are notably diverse and include growth, deferment, abandonment, switching inputs, altering operating scale, and phased research and development options. One signi®cant aspect of this research is the use of the real options approach to determine the optimal start-up date of IS investments. The common approach has been to determine the optimal time to begin the development of a project by deriving and analysing the value of waiting to invest [1,11]. An alternative approach is to draw an analogy between the theoretical effect of stock dividends on the early exercise of an American style call option and the impact of
0378-7206/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 7 2 0 6 ( 0 1 ) 0 0 1 0 1 - X
338
J.A. Campbell / Information & Management 39 (2002) 337±344
investment deferral decisions on foregone project cash ¯ow [7]. Although both approaches evaluate the opportunity cost of waiting to invest, the latter provides an explicit articulation of the investment decision criteria. This paper extends this work by using options pricing theory to assess the optimal timing of IS investments and the impact of different investment review cycles on the decision to invest. 2. Valuing IS investment options Although several alternative options pricing techniques exist, the Black±Scholes model remains an accepted standard because of its computational simplicity and relative accuracy [5]. The formula can easily be programmed into a computer or ®nancial calculator and uses ®ve readily obtainable input variables. This model has been shown to price European call options accurately when there are no dividends and more than 2 months to expiration [19]. As a European call option can only be exercised when the option expires, its value is given by subtracting the expected present value of exercising the option from the expected terminal value of the underlying asset. That is C VN d1
Xe
rT
N d2
(1)
where d1
ln V=X r 0:5s2 T p s T
d2 d1
s
p T
and N() is the cumulative normal distribution function, V the value of the underlying asset, X the option exercise price, s the volatility, r the risk-free interest rate, T the option life Unlike European call options, American call options can be exercised at any point in time for the life of the option. The Black±Scholes model can also be used to provide a reliable estimate of the value of an American call option, as long as there are no dividends paid during the life of the option [10]. However, the valuation of an in-the-money American call option becomes problematic if the underlying asset pays a dividend, as it may be better for the option holder to exercise it immediately prior to the ex-dividend instant. The problem facing the American call option holder is depicted in Fig. 1. The option holder will obtain the cum-dividend value of the asset less the option exercise price if the option is exercised immediately prior to the dividend payment. However, if left unexercised, the dividend is forfeited and the value of the option is reduced.
Fig. 1. American call option price as a function of the ex-dividend value of the underlying asset.
J.A. Campbell / Information & Management 39 (2002) 337±344
Vt is the critical ex-dividend asset value at which point the option holder is indifferent to exercising or continuing to hold the option. This indifference value is given by C Vt ; T
t; X Vt D
X
(2)
The two functions shown in Fig. 1, Vt D X and C Vt ; T t; X, intersect only if the ex-dividend decline in the asset price is more than the present value of the interest income that would be earned by deferring investment [2,21]. Therefore, an in-themoney cum-dividend American call option should only be exercised early when Eq. (3) is satis®ed. Dt > X1
e
r T t
(3)
The foregone free cash ¯ows of an investment project are analogous to the dividends paid on a stock. Many organisations routinely review investment opportunities at discrete time intervals on a quarterly, 6monthly, or yearly basis. If a project is deferred at one of these periodic reviews, the effect is to forfeit, at that instant, all project cash ¯ows up to the next investment review. In this way, investment reviews have a similar effect on the value of an investment option as dividends have on the value of an American call option. However, unlike stock option holders, investment option holders have control over the size of foregone revenues through the choice of investment review frequency. Greater frequency will result in less foregone revenue between decision instances, while less frequent reviews will result in the forfeiting of larger amounts. 3. Modelling information technology investment options Benaroch and Kauffman [2,3] use the example of an investment decision for identifying the most appropriate timing for the development and deployment of a point-of-sale debit card services system. In contrast, a hypothetical case of an investment in online logistics will be used to illustrate the concepts of real options as they relate to investment timing and the investment review cycle.1 Online logistics can substantially 1
The hypothetical case presented here uses the same 6-monthly data values as used by Benaroch and Kauffman in their Yankee 24 debit card services case. This data link allows a comparison of results while providing an alternative application context (reduced costs versus increased revenues).
339
reduce the costs associated with purchasing, storing, administrating and distributing inventory through better supply-chain management. Online logistics have enabled some organisations to reduce costs to such an extent that pro®t margins have almost doubled [12]. Human Systems Inc. (HUM) is a manufacturing organisation that has became aware of the merits of investment in online logistics because of the potential for large cost savings and the entry barriers such a system would create for new and existing competitors. While HUM could invest right away, it was also realised that the option to defer investment could allow the project start to be timed to maximise investment returns. HUM could defer investment, as there was no immediate competitive threat from any existing or potential competitor. While some savings would be given up, waiting before investing could yield additional bene®ts by providing time for rectifying some of the uncertainties about the project and the degree of organisational readiness. Therefore, the primary problem is to determine how long, if at all, HUM should defer investment in the online logistics project. At each investment review, HUM can obtain the present value of all future cash ¯ows (cost savings) by investing in the project. If it decides to defer investment, then all cost savings up to the next investment review date will be forfeited. Applying the same principles used to de®ne Eq. (3), HUM should not invest in the project unless these foregone cash ¯ows are more than the present value of the interest income that would be earned by deferring investment. The value of this interest income is the opportunity cost of giving up the option to defer project start-up. Consequently, the derivation of the optimal project start-up date requires a reconciliation of these two conditional expected values. Thus, an investment should not be made unless FCt > Xt 1
e
r T t
(4)
where FCt is the present value of foregone cash ¯ow from delaying investment, Xt the discounted investment cost, T the maximum deferral period in years, t the length of the investment deferral period in years and r the annual risk free rate. Table 1 shows the online logistics investment data and related assumptions based on a 6-monthly investment review cycle. An analysis of this data indicates
340
J.A. Campbell / Information & Management 39 (2002) 337±344
Table 1 Optimal project start-up based on 6-monthly investment reviewsa t
0
At (US$) Xt (US$) FCt (US$) Xt 1 e r T t (US$) FCt Xt 1 e r T t (US$)
0.5 323233 400000 18983 104993 123976
342216 393179 17867 94842 112709
1.0 360083 386473 16147 84342 100489
1.5
2.0
376230 379883 12977 73481 86458
389207 373404 6359 62246 68605
2.5
3.0
3.5
4.0
395566 367036 8400 50625 42225
387166 360777 42353 38603 3750
344813 354625 121518 26168 95350
223295 348577 223295 13305 209990
a Assumptions: The project is not in operation until 12 months after the project start-up date. The rate of in¯ation is 3.5%. Investment opportunities are reviewed every 6 months. A is the present value of cost savings less operational costs; X is the discounted cost of investment, X0 US$ 400,000; FC is the foregone cash ¯ow from delaying project start-up, At At0:5 ; Xt 1 e r T t is the interest income that would be earned by deferring project start-up; T is the maximum deferral period in years (5.5 years); t is the length of the investment deferral period in years; r is the annual risk free rate (7%).
that the optimal time to wait before investing in online logistics is approximately 3 years. Note that the present value of cost savings (At) increases at each review for the ®rst 2.5 years, indicating that early negative cash ¯ow is more than compensated for by the present value of larger cash ¯ow in later years. Fig. 2 graphs the two investment decision variables over time. The graphing of these two functions better illustrates how optimal investment timing is deter-
mined by the size of foregone cash ¯ow in comparison to the potential interest income that could be earned from investing in an alternative risk-free investment. The intersection of the two functions indicates when the project should proceed. From Fig. 2, this should occur a little before the 3-year deferment implied by a tabular representation of the data. However, if 6-monthly reviews are strictly adhered to, the optimal deferral period remains 3 years.
Fig. 2. Interest income and foregone cash ¯ow associated with a 6-monthly investment review cycle.
J.A. Campbell / Information & Management 39 (2002) 337±344
341
Fig. 3. Interest income and foregone cash ¯ow associated with investment review frequency.
However, we need to assess the sensitivity of this result to the frequency that the investment opportunity is reviewed. As discussed earlier, the quantum of foregone cash ¯ow is reduced or increased depending upon the length of time between reviews. Fig. 3 illustrates how different investment review cycles impact optimum investment timing by aggregating and interpolating the original 6-monthly data into different time-setsÐmonthly, quarterly, and yearly. It can be readily seen how less frequent investment reviews increase foregone cash ¯ow. However, the investment review criterion is also shown to be remarkably robust when applied to this case data. The optimal time to invest is given by the ®rst review where foregone cash ¯ow during the next period is greater than the investment opportunity cost. This occurs after 3 years for the yearly and 6-monthly data, after 3 and a quarter years for the quarterly data, and some time after 3 and a half years for the monthly data. Despite these differences, the results must be interpreted cautiously as other cash ¯ow series may produce different effects.
4. Modelling assumptions of investment timing options Inputs for the timing method presented here are either directly observable or can be estimated with a reasonable level of con®dence. For example, the in¯ation and risk-free interest rates are readily obtainable from market data. While estimates of project life, cash ¯ow and investment value can be inferred from previous experience with similar projects or through the judicious use of expert opinion. However, there are a number of more fundamental issues that threaten the validity of using options pricing theory to evaluate investment timing [14]. These issues relate to assumptions about the characteristics and behaviour of the variables used to de®ne options pricing models (see [18] for an excellent discussion of appropriate option pricing models for different states of input variables). As can be seen in Table 2, the characteristics of stock options are somewhat different to the characteristics of real investment options. In particular, there
342
Table 2 Comparison between stock options and real investment option parameters Characteristics of stock options
Characteristics of investment options
Value of the underlying asset (V)
Stock price is set by a market and cannot be negative
Project value is not directly observable, can be negative, and is directly dependent on the present value of the net operating income or loss during the life of the project Project values are more sensitive than stock prices to changes in interest rates
Exercise price (X)
A single known payment
An uncertain stream of payments over an extended time period
Volatility (s)
Annualised standard deviation of stock price returns Volatility can either increase or decrease during the life of the option Volatility can be estimated using historical or implied variance data
Annualised standard deviation of project free cash flow Volatility tends to decrease during the life of the investment option Volatility estimates can be derived from organisational project data, or from data from listed companies involved in similar project activities
Life of the option (T)
Finite and defined in advance The life of most stock options tend to be short to medium-term (<2 years)
The life of an investment option is uncertain The life of most investment options tend to be medium to long-term (2±5 years) The life of some investment options can be extended by modifying the project to suit emerging conditions
Risk-free interest rate (r) An increase in interest rates reduces the present value of future dividends but increases the expected growth rate of the underlying asset The value of a stock call options tend to increase as interest rates increase ([10], p. 153)
An increase in interest rates reduces the present value of future cash flows but increases the value of waiting to invest Because of the importance of interest rates in the calculation of project value, the value of investment options could be more sensitive than stock options to interest rate changes
Dividends (D)
Continuous free cash flows foregone by delaying investment Timing and quantum can be difficult to estimate Project cash-flows at any point in time can be either negative or positive and, therefore, can either reduce or increase the investment option value
Discrete dividend payments occurring at regular points in time Timing and quantum is usually highly predictable Dividends reduce the value of call stock options as they reduce the price of the underlying asset and are not paid to option holders
J.A. Campbell / Information & Management 39 (2002) 337±344
Option variables
J.A. Campbell / Information & Management 39 (2002) 337±344
are important differences between project cash ¯ows and stock dividends that need recognition. First, the timing and quantum of stock dividends are usually highly predictable, while project cash ¯ows can be dif®cult to estimate accurately. Second, dividends always reduce the value of call stock options while forfeited project cash ¯ows can be either negative or positive and, therefore, can either reduce or increase the value of an investment option. Another concern is the speci®cation of the life of an investment option. The time to expiration for most ®nancial options is ®nite and ®xed in advance. However, the life of an investment option can increase or decrease, depending on new technological developments or sudden changes in the competitive environment. An organisation may also seek to manage its investment options actively by pursuing strategies and supporting tactics aimed at maximising the value and useful life of investment options [15,16]. Clearly, the optimal time to invest in a project is highly sensitive to the duration of the option. Substantial increases or decreases in the life of an investment option could signi®cantly reduce accuracy when estimating the optimal time to invest. The approach here has signi®cant advantages over other valuation methods that are based on options pricing theory. First, the method does not require an estimation of the variance of future project cash ¯ows. This is a major strength, as options pricing models are very sensitive to small changes in variance and it is often dif®cult to obtain reliable estimates of variance in real-world settings. A second advantage is that the investment timing decision criterion is easy to understand and requires little calculation. It provides practitioners and researchers with a useful tool for studying the timing of IS investment. 5. Discussion A special feature of many IS investments is that there is often an option for the investment to be undertaken immediately or to be delayed, sometimes for several years. The problem, where a project may be delayed, is to quantify the waiting period that will maximise the value of the project. When considering information technology investments, managers should recognise that the characteristics of project ¯exibility
343
are important and valuable considerations, particularly when there is a high degree of uncertainty about the investment outcome. While the initial net-presentvalue of many information technology projects can be negative, an option pricing approach can sometimes reveal a positive project valuation by recognising the value of investment ¯exibility. Discounted cash ¯ow methods are highly dependent on the arbitrarily determined risk-adjusted discount rate applied to the project cash ¯ows. In contrast, real option approaches avoid this dif®culty by using risk-free interest rates that can be easily obtained from market data. Most importantly, the investment decision-making process is better informed by modelling project contingencies as real options with speci®c value characteristics that can be used to identify an optimal project start-up date. Unlike other real option approaches, the method presented here seeks to exploit the certainty of early cash ¯ows by providing a rationale for the early exercise of an investment option. The decision criterion has several implications for managers and researchers, some of which might appear on face value to be counter-intuitive. For example, it has long been accepted that many strategic investments are better undertaken sooner rather than later so that strategic impact is maximised. However, our model suggests that immediate investment is not always preferred. One testable implication is that highly agile organisations that continuously review their investment options should tend to defer projects for longer periods. This is because early investment will tend to reduce agility by limiting the range of future courses of action available to the organisation. Based on the study results, early investment should occur only when a project has a very-high positive cash ¯ow immediately after system implementation. The method, therefore, emphasises the importance and value of strong early cash ¯ow. This is an important feature, as these closer cash ¯ow numbers will generally be more certain and, therefore, more predictable than later ones. This agrees with the common industry practice of demanding comparatively short pay back periods from IS investments. Although the results were shown to be robust with respect to investment review frequency, further research is required to establish the generality of the approach. For example, the case data used here ignored the costs and savings associated with
344
J.A. Campbell / Information & Management 39 (2002) 337±344
suspending or completely abandoning the project at some future date. Further, if project cash ¯ow has high serial correlation and dependence on the start-up date itself, then a matrix of values might be needed.
[12]
References
[14]
[1] M. Amram, N. Kulatilaka, Real Options: Managing Strategic Investment in an Uncertain World, Harvard University Press, Boston MA, 1999. [2] G. Barone-Adesi, R.E. Whaley, The valuation of American call options and the expected ex-dividend stock price decline, Journal of Financial Economics 17, 1986, pp. 91±111. [3] M. Benaroch, R.J. Kauffman, A case for using real options pricing analysis to evaluate information technology project investments, Information Systems Research 10 (1), 1999, pp. 70±86. [4] M. Benaroch, R.J. Kauffman, Justifying electronic banking network expansion using real options analysis, MIS Quarterly 24 (2), 2000, pp. 197±225. [5] F. Black, M. Scholes, The pricing of options and corporate liabilities, Journal of Political Economy 81, 1973, pp. 637± 654. [6] N.P. Bollen, Real options and product life cycles, Management Science 45 (5), 1999, pp. 670±684. [7] J.A. Campbell, Identifying an optimal start-up date for information technology investments: a real options approach, Working Paper, Faculty of Commerce and Management, Grif®th University, Australia, 2000. [8] A.K. Dixit, R.S. Pindyck, The options approach to capital investment, Harvard Business Review 73 (3), 1995, pp. 105± 115. [9] T.W. Faulkner, Applying `options thinking' to R&D valuation, Research Technology Management 39 (3), 1996, pp. 50± 56. [10] J.C. Hull, Options, Futures, and Other Derivative Securities, 2nd Edition, Prentice-Hall, Englewood Cliffs, NJ, 1993. [11] N. Kulatilaka, The value of ¯exibility: a general model of real options, in: L. Trigeorgis (Ed.), Real Options in Capital
[13]
[15] [16] [17]
[18] [19] [20] [21]
Investment: Models, Strategies, and Applications, Praeger, Westport, CT, 1995, pp. 121±132. P.G.W. Keen, IT's value in the chain, Computerworld 34 (7), 2000, pp. 48. R.L. Kumar, A note on project risk and option values of investment in information technologies, Journal of Management Information Systems 13 (1), 1996, pp. 187±193. D.M. Lander, G.E. Pinches, Challenges to the practical implementation of modelling and valuing real options, Quarterly Review of Economics & Finance 38, 1998, pp. 537±567. T.A. Luehrman, Investment opportunities as real options: getting started on the numbers, Harvard Business Review 76 (4), 1998a, pp. 51±67. T.A. Luehrman, Strategy as a portfolio of real options, Harvard Business Review 76 (5), 1998b, pp. 89±99. C.S. Park, H.S.B. Herath, Exploiting uncertainty-investment opportunities as real options: a new way of thinking in engineering economics, The Engineering Economist 45 (1), 2000, pp. 1±36. M. Perlitz, T. Peske, R. Schrank, Real options valuation: the new frontier in R&D project evaluation, R&D Management 29 (3), 1999, pp. 255±269. P. Ritchken, Options: Theories, Strategy, and Applications, Scott Foresman, London, 1987. A. Taudes, M. Feurstein, A. Mild, Options analysis of software platform decisions: a case study, MIS Quarterly 24 (2), 2000, pp. 227±243. R.E. Whaley, On the evaluation of American call options on stocks with known dividends, Journal of Financial Economics 9, 1981, pp. 207±211.
John A. Campbell is a Senior Lecturer in the School of Management, Griffith University, Australia. His publications include topics on business finance, asset valuation models, executive information systems, group support systems, organisational communication and strategic IT management. His current research interests are focused on strategies for managing networked organisations in changing marketplaces and include topics in electronic-commerce, computer mediated communication and virtual communities.
Real options analysis of the timing of IS investment decisions John A. Campbell* School of Management, Faculty of Commerce and Management, Grif®th University, Meadowbrook 4131, Australia Received 20 November 2000; accepted 21 April 2001
Abstract Many information systems (IS) investments belong to a class of capital budgeting problem where there is an option: the investment may be made straight away or delayed for some period. A real options analysis could allow decision-makers to add value to these investment decisions by providing a framework that explicitly recognises uncertainty. This paper uses options pricing theory to determine the optimal timing of IS investments and to explore the effect of different investment review cycles. The ®ndings provide support for the common industry practice of demanding short payback periods for IS investments. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Real options; IS investments; Investment timing
1. Introduction Under conditions of uncertainty, investment ¯exibility is an important and valuable consideration. There is a growing view that the techniques used to evaluate ®nancial options might be appropriate, in certain circumstances, for evaluating capital investments that have option like characteristics [6,8,13,17,18]. These types of investment choices are often referred to as real options, as the investment opportunities typically involve real assets (information systems (IS), factories, new products, etc.) rather than paper-based assets (stocks, bonds, currencies, etc.). For many approved capital projects there is often an option to delay the project start-up to a more suitable date if circumstances are not supportive. For example, management faced with implementing several large projects at the same time may opt for a staggered * Tel.: 61-7338-21119; fax: 61-7338-21408. E-mail address: [email protected] (J.A. Campbell).
series of start-up dates to maximise resource availability and utilisation. This and other option-like characteristics are found in many IS projects. In recent times, strong arguments have been put forward for using options pricing theory to evaluate IS project investments (see, e.g. [3,4,9,20]). This literature advocates various innovative means of valuing investment ¯exibility using relevant aspects of options pricing theories. The range of investment options studied in this way are notably diverse and include growth, deferment, abandonment, switching inputs, altering operating scale, and phased research and development options. One signi®cant aspect of this research is the use of the real options approach to determine the optimal start-up date of IS investments. The common approach has been to determine the optimal time to begin the development of a project by deriving and analysing the value of waiting to invest [1,11]. An alternative approach is to draw an analogy between the theoretical effect of stock dividends on the early exercise of an American style call option and the impact of
0378-7206/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 7 2 0 6 ( 0 1 ) 0 0 1 0 1 - X
338
J.A. Campbell / Information & Management 39 (2002) 337±344
investment deferral decisions on foregone project cash ¯ow [7]. Although both approaches evaluate the opportunity cost of waiting to invest, the latter provides an explicit articulation of the investment decision criteria. This paper extends this work by using options pricing theory to assess the optimal timing of IS investments and the impact of different investment review cycles on the decision to invest. 2. Valuing IS investment options Although several alternative options pricing techniques exist, the Black±Scholes model remains an accepted standard because of its computational simplicity and relative accuracy [5]. The formula can easily be programmed into a computer or ®nancial calculator and uses ®ve readily obtainable input variables. This model has been shown to price European call options accurately when there are no dividends and more than 2 months to expiration [19]. As a European call option can only be exercised when the option expires, its value is given by subtracting the expected present value of exercising the option from the expected terminal value of the underlying asset. That is C VN d1
Xe
rT
N d2
(1)
where d1
ln V=X r 0:5s2 T p s T
d2 d1
s
p T
and N() is the cumulative normal distribution function, V the value of the underlying asset, X the option exercise price, s the volatility, r the risk-free interest rate, T the option life Unlike European call options, American call options can be exercised at any point in time for the life of the option. The Black±Scholes model can also be used to provide a reliable estimate of the value of an American call option, as long as there are no dividends paid during the life of the option [10]. However, the valuation of an in-the-money American call option becomes problematic if the underlying asset pays a dividend, as it may be better for the option holder to exercise it immediately prior to the ex-dividend instant. The problem facing the American call option holder is depicted in Fig. 1. The option holder will obtain the cum-dividend value of the asset less the option exercise price if the option is exercised immediately prior to the dividend payment. However, if left unexercised, the dividend is forfeited and the value of the option is reduced.
Fig. 1. American call option price as a function of the ex-dividend value of the underlying asset.
J.A. Campbell / Information & Management 39 (2002) 337±344
Vt is the critical ex-dividend asset value at which point the option holder is indifferent to exercising or continuing to hold the option. This indifference value is given by C Vt ; T
t; X Vt D
X
(2)
The two functions shown in Fig. 1, Vt D X and C Vt ; T t; X, intersect only if the ex-dividend decline in the asset price is more than the present value of the interest income that would be earned by deferring investment [2,21]. Therefore, an in-themoney cum-dividend American call option should only be exercised early when Eq. (3) is satis®ed. Dt > X1
e
r T t
(3)
The foregone free cash ¯ows of an investment project are analogous to the dividends paid on a stock. Many organisations routinely review investment opportunities at discrete time intervals on a quarterly, 6monthly, or yearly basis. If a project is deferred at one of these periodic reviews, the effect is to forfeit, at that instant, all project cash ¯ows up to the next investment review. In this way, investment reviews have a similar effect on the value of an investment option as dividends have on the value of an American call option. However, unlike stock option holders, investment option holders have control over the size of foregone revenues through the choice of investment review frequency. Greater frequency will result in less foregone revenue between decision instances, while less frequent reviews will result in the forfeiting of larger amounts. 3. Modelling information technology investment options Benaroch and Kauffman [2,3] use the example of an investment decision for identifying the most appropriate timing for the development and deployment of a point-of-sale debit card services system. In contrast, a hypothetical case of an investment in online logistics will be used to illustrate the concepts of real options as they relate to investment timing and the investment review cycle.1 Online logistics can substantially 1
The hypothetical case presented here uses the same 6-monthly data values as used by Benaroch and Kauffman in their Yankee 24 debit card services case. This data link allows a comparison of results while providing an alternative application context (reduced costs versus increased revenues).
339
reduce the costs associated with purchasing, storing, administrating and distributing inventory through better supply-chain management. Online logistics have enabled some organisations to reduce costs to such an extent that pro®t margins have almost doubled [12]. Human Systems Inc. (HUM) is a manufacturing organisation that has became aware of the merits of investment in online logistics because of the potential for large cost savings and the entry barriers such a system would create for new and existing competitors. While HUM could invest right away, it was also realised that the option to defer investment could allow the project start to be timed to maximise investment returns. HUM could defer investment, as there was no immediate competitive threat from any existing or potential competitor. While some savings would be given up, waiting before investing could yield additional bene®ts by providing time for rectifying some of the uncertainties about the project and the degree of organisational readiness. Therefore, the primary problem is to determine how long, if at all, HUM should defer investment in the online logistics project. At each investment review, HUM can obtain the present value of all future cash ¯ows (cost savings) by investing in the project. If it decides to defer investment, then all cost savings up to the next investment review date will be forfeited. Applying the same principles used to de®ne Eq. (3), HUM should not invest in the project unless these foregone cash ¯ows are more than the present value of the interest income that would be earned by deferring investment. The value of this interest income is the opportunity cost of giving up the option to defer project start-up. Consequently, the derivation of the optimal project start-up date requires a reconciliation of these two conditional expected values. Thus, an investment should not be made unless FCt > Xt 1
e
r T t
(4)
where FCt is the present value of foregone cash ¯ow from delaying investment, Xt the discounted investment cost, T the maximum deferral period in years, t the length of the investment deferral period in years and r the annual risk free rate. Table 1 shows the online logistics investment data and related assumptions based on a 6-monthly investment review cycle. An analysis of this data indicates
340
J.A. Campbell / Information & Management 39 (2002) 337±344
Table 1 Optimal project start-up based on 6-monthly investment reviewsa t
0
At (US$) Xt (US$) FCt (US$) Xt 1 e r T t (US$) FCt Xt 1 e r T t (US$)
0.5 323233 400000 18983 104993 123976
342216 393179 17867 94842 112709
1.0 360083 386473 16147 84342 100489
1.5
2.0
376230 379883 12977 73481 86458
389207 373404 6359 62246 68605
2.5
3.0
3.5
4.0
395566 367036 8400 50625 42225
387166 360777 42353 38603 3750
344813 354625 121518 26168 95350
223295 348577 223295 13305 209990
a Assumptions: The project is not in operation until 12 months after the project start-up date. The rate of in¯ation is 3.5%. Investment opportunities are reviewed every 6 months. A is the present value of cost savings less operational costs; X is the discounted cost of investment, X0 US$ 400,000; FC is the foregone cash ¯ow from delaying project start-up, At At0:5 ; Xt 1 e r T t is the interest income that would be earned by deferring project start-up; T is the maximum deferral period in years (5.5 years); t is the length of the investment deferral period in years; r is the annual risk free rate (7%).
that the optimal time to wait before investing in online logistics is approximately 3 years. Note that the present value of cost savings (At) increases at each review for the ®rst 2.5 years, indicating that early negative cash ¯ow is more than compensated for by the present value of larger cash ¯ow in later years. Fig. 2 graphs the two investment decision variables over time. The graphing of these two functions better illustrates how optimal investment timing is deter-
mined by the size of foregone cash ¯ow in comparison to the potential interest income that could be earned from investing in an alternative risk-free investment. The intersection of the two functions indicates when the project should proceed. From Fig. 2, this should occur a little before the 3-year deferment implied by a tabular representation of the data. However, if 6-monthly reviews are strictly adhered to, the optimal deferral period remains 3 years.
Fig. 2. Interest income and foregone cash ¯ow associated with a 6-monthly investment review cycle.
J.A. Campbell / Information & Management 39 (2002) 337±344
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Fig. 3. Interest income and foregone cash ¯ow associated with investment review frequency.
However, we need to assess the sensitivity of this result to the frequency that the investment opportunity is reviewed. As discussed earlier, the quantum of foregone cash ¯ow is reduced or increased depending upon the length of time between reviews. Fig. 3 illustrates how different investment review cycles impact optimum investment timing by aggregating and interpolating the original 6-monthly data into different time-setsÐmonthly, quarterly, and yearly. It can be readily seen how less frequent investment reviews increase foregone cash ¯ow. However, the investment review criterion is also shown to be remarkably robust when applied to this case data. The optimal time to invest is given by the ®rst review where foregone cash ¯ow during the next period is greater than the investment opportunity cost. This occurs after 3 years for the yearly and 6-monthly data, after 3 and a quarter years for the quarterly data, and some time after 3 and a half years for the monthly data. Despite these differences, the results must be interpreted cautiously as other cash ¯ow series may produce different effects.
4. Modelling assumptions of investment timing options Inputs for the timing method presented here are either directly observable or can be estimated with a reasonable level of con®dence. For example, the in¯ation and risk-free interest rates are readily obtainable from market data. While estimates of project life, cash ¯ow and investment value can be inferred from previous experience with similar projects or through the judicious use of expert opinion. However, there are a number of more fundamental issues that threaten the validity of using options pricing theory to evaluate investment timing [14]. These issues relate to assumptions about the characteristics and behaviour of the variables used to de®ne options pricing models (see [18] for an excellent discussion of appropriate option pricing models for different states of input variables). As can be seen in Table 2, the characteristics of stock options are somewhat different to the characteristics of real investment options. In particular, there
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Table 2 Comparison between stock options and real investment option parameters Characteristics of stock options
Characteristics of investment options
Value of the underlying asset (V)
Stock price is set by a market and cannot be negative
Project value is not directly observable, can be negative, and is directly dependent on the present value of the net operating income or loss during the life of the project Project values are more sensitive than stock prices to changes in interest rates
Exercise price (X)
A single known payment
An uncertain stream of payments over an extended time period
Volatility (s)
Annualised standard deviation of stock price returns Volatility can either increase or decrease during the life of the option Volatility can be estimated using historical or implied variance data
Annualised standard deviation of project free cash flow Volatility tends to decrease during the life of the investment option Volatility estimates can be derived from organisational project data, or from data from listed companies involved in similar project activities
Life of the option (T)
Finite and defined in advance The life of most stock options tend to be short to medium-term (<2 years)
The life of an investment option is uncertain The life of most investment options tend to be medium to long-term (2±5 years) The life of some investment options can be extended by modifying the project to suit emerging conditions
Risk-free interest rate (r) An increase in interest rates reduces the present value of future dividends but increases the expected growth rate of the underlying asset The value of a stock call options tend to increase as interest rates increase ([10], p. 153)
An increase in interest rates reduces the present value of future cash flows but increases the value of waiting to invest Because of the importance of interest rates in the calculation of project value, the value of investment options could be more sensitive than stock options to interest rate changes
Dividends (D)
Continuous free cash flows foregone by delaying investment Timing and quantum can be difficult to estimate Project cash-flows at any point in time can be either negative or positive and, therefore, can either reduce or increase the investment option value
Discrete dividend payments occurring at regular points in time Timing and quantum is usually highly predictable Dividends reduce the value of call stock options as they reduce the price of the underlying asset and are not paid to option holders
J.A. Campbell / Information & Management 39 (2002) 337±344
Option variables
J.A. Campbell / Information & Management 39 (2002) 337±344
are important differences between project cash ¯ows and stock dividends that need recognition. First, the timing and quantum of stock dividends are usually highly predictable, while project cash ¯ows can be dif®cult to estimate accurately. Second, dividends always reduce the value of call stock options while forfeited project cash ¯ows can be either negative or positive and, therefore, can either reduce or increase the value of an investment option. Another concern is the speci®cation of the life of an investment option. The time to expiration for most ®nancial options is ®nite and ®xed in advance. However, the life of an investment option can increase or decrease, depending on new technological developments or sudden changes in the competitive environment. An organisation may also seek to manage its investment options actively by pursuing strategies and supporting tactics aimed at maximising the value and useful life of investment options [15,16]. Clearly, the optimal time to invest in a project is highly sensitive to the duration of the option. Substantial increases or decreases in the life of an investment option could signi®cantly reduce accuracy when estimating the optimal time to invest. The approach here has signi®cant advantages over other valuation methods that are based on options pricing theory. First, the method does not require an estimation of the variance of future project cash ¯ows. This is a major strength, as options pricing models are very sensitive to small changes in variance and it is often dif®cult to obtain reliable estimates of variance in real-world settings. A second advantage is that the investment timing decision criterion is easy to understand and requires little calculation. It provides practitioners and researchers with a useful tool for studying the timing of IS investment. 5. Discussion A special feature of many IS investments is that there is often an option for the investment to be undertaken immediately or to be delayed, sometimes for several years. The problem, where a project may be delayed, is to quantify the waiting period that will maximise the value of the project. When considering information technology investments, managers should recognise that the characteristics of project ¯exibility
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are important and valuable considerations, particularly when there is a high degree of uncertainty about the investment outcome. While the initial net-presentvalue of many information technology projects can be negative, an option pricing approach can sometimes reveal a positive project valuation by recognising the value of investment ¯exibility. Discounted cash ¯ow methods are highly dependent on the arbitrarily determined risk-adjusted discount rate applied to the project cash ¯ows. In contrast, real option approaches avoid this dif®culty by using risk-free interest rates that can be easily obtained from market data. Most importantly, the investment decision-making process is better informed by modelling project contingencies as real options with speci®c value characteristics that can be used to identify an optimal project start-up date. Unlike other real option approaches, the method presented here seeks to exploit the certainty of early cash ¯ows by providing a rationale for the early exercise of an investment option. The decision criterion has several implications for managers and researchers, some of which might appear on face value to be counter-intuitive. For example, it has long been accepted that many strategic investments are better undertaken sooner rather than later so that strategic impact is maximised. However, our model suggests that immediate investment is not always preferred. One testable implication is that highly agile organisations that continuously review their investment options should tend to defer projects for longer periods. This is because early investment will tend to reduce agility by limiting the range of future courses of action available to the organisation. Based on the study results, early investment should occur only when a project has a very-high positive cash ¯ow immediately after system implementation. The method, therefore, emphasises the importance and value of strong early cash ¯ow. This is an important feature, as these closer cash ¯ow numbers will generally be more certain and, therefore, more predictable than later ones. This agrees with the common industry practice of demanding comparatively short pay back periods from IS investments. Although the results were shown to be robust with respect to investment review frequency, further research is required to establish the generality of the approach. For example, the case data used here ignored the costs and savings associated with
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suspending or completely abandoning the project at some future date. Further, if project cash ¯ow has high serial correlation and dependence on the start-up date itself, then a matrix of values might be needed.
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John A. Campbell is a Senior Lecturer in the School of Management, Griffith University, Australia. His publications include topics on business finance, asset valuation models, executive information systems, group support systems, organisational communication and strategic IT management. His current research interests are focused on strategies for managing networked organisations in changing marketplaces and include topics in electronic-commerce, computer mediated communication and virtual communities.