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expertise for evaluating many scenarios and variables. The advantages and disadvantages of using modeling and simulation approaches in assessing investments and the IT portfolio are listed in Exhibit 5.35.
Nonnumeric models are based on must-have investments where the cost of not investing in a particular project or ongoing investment far exceeds the cost of the investment. These include investments that address mandatory/regulatory
STAGE 4: ASSESSING 241 EXHIBIT 5.32 COMMONLY APPLIED FINANCIAL MODELS
Net present value: discounts outstanding cash flows at a suitable cost of capital (hurdle rate or weighted average cost of capital). The net present value is positive if an investment earns a rate of return above the cost of capital (or hurdle rate). Since projects can have varying degrees of risk, the hurdle rate should take this into account and be set higher for riskier projects. Since net present value only assigns one specific figure, it might not be applicable to analyze investments that may have a range of possible outcomes.
Internal rate of return: related to net present value, internal rate of return is the rate at which the net present value is zero. If the internal rate of return is greater than the hurdle rate, the net present value must be greater than zero. There is a chance that a project could yield multiple internal rates of return. Internal rates of return provide the same discount rates to both costs and revenues, which in some cases is undesirable.
Expected commercial value: determines the commercial worth of an investment by considering the future stream of costs and benefits, the probability of technical and commercial success, and the strategic importance of an investment.
Economic value added: is equal to the after-tax operating profit generated by an investment less the dollar cost of the capital employed to finance the investment.
Sources: Adapted from:
Eric Burke, “Portfolio Analysis, Key Metrics, and Techniques for Analyzing the Portfolio,” Portfolio Knowledge.
Alastair L. Day, Mastering Financial Modelling, Financial Times/Prentice-Hall, 2001.
Gabriel Hawawini and Claude Viallet, Finance for Executives, 2nd edition, South Western, 2002. Joel G. Siegel, Jae K. Shim, and David Minars, The Complete Book of Business Math, McGraw-Hill, 1995.
requirements, operational necessities whereby sizable losses will occur if investments are not made, and competitive responses in order to at least remain on par with competitors.
Assess the Performance of the IT Portfolio
The balanced scorecard created by Robert S. Kaplan and David P. Norton12 is essentially a navigational tool for managing performance against business objectives. A balanced scorecard translates business and strategic objectives into a set of performance measures. The use of the word balance refers not only to cost and benefit, shareholder and customer, efficiency and effectiveness, and/or long and short term but also to dependencies between investments and the priorities that drive
242 CHAPTER 5 BUILDING THE IT PORTFOLIO
EXHIBIT 5.33 ADVANTAGES AND DISADVANTAGES OF FINANCIAL MODELS
Financial Models Used to Assess IT Investments
• Accepted practices, easy to use, standard definitions • Do not account for intangible value (except for risk)
• Variable can be altered for what-if analysis • Timing of cash flow needs not considered
• Leverage accounting data • Multiple gating decision points not considered
• Primarily a single numerical output • Can be biased toward short-term investments
• Risk is incorporated in some models • Criteria based on financial return/profitability
Sources: Adapted from:
Archer, N. P., Ghasemzadeh, F. (1996), “Project Portfolio Selection Techniques: A Review and a Suggested Integration Approach,” Innovation Research Working Group Working Paper No. 46, McMaster University.
Henriksen, A. D., Traynor, A. J. (1999). “A Practical R&D Project-Selection Scoring Tool,” IEEE Transactions on Engineering Management, 46/2, pp. 158—170.
Martikainen, Juha (2002). “Portfolio Management of Strategic Investment in the Metal Industry,” master’s thesis, Helsinki University of Technology, January.
Matejcik, F. J. “TM 665 Project Planning & Control,” South Dakota School of Mines and Technology.
Meredith, J. R., Mantel, S. R., Jr. (2000). Project Management—A Managerial Approach, John Wiley & Sons.
Steele, L. W. (1988). “What We’ve Learned—Selecting R&D Programs and Objectives,” Research Technology Management, Mar.—Apr., pp. 17—36.
success. The word scorecard implies measurement against goals and targets. Unlike dashboards that monitor progress and key indicators on an ongoing basis, balanced scorecards act as lenses for seeing targets and navigating the best course of action.