Capital Budgeting: Managing Efficient IT Project Portfolios
Appendix B: Optimization
Optimization is the process of trying to find the best solution to a problem that may have many possible solutions. Evolver, the optimization tool cited above, is easy to use because an understanding of the complex techniques it uses is usually unnecessary. Evolver doesn't care about the "nuts and bolts" of your problem; it just needs a spreadsheet model that can evaluate how good different scenarios are. You select the spreadsheet cells that contain the variables and tell Evolver what you are looking for. Using Evolver requires only that the user set the variables (the cells which contain values that can be adjusted), the goal (the cell that contains the output), and a description of what values Evolver may use when searching for optimal solutions.
A number of assumptions are behind the theory outlined in Figure 1. One, the assumption of normally distributed returns, leads to problems when trying to extend the analysis to longer time periods or to multiple time periods, because long-term returns are usually far from normally distributed. Although mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet, many decision makers don't appreciate or have the resources to deal with the highly statistical models that take this empirical evidence into consideration. Reference 10 examines this dilemma and offers readers a look at how portfolio selection and risk management can and should be undertaken when the assumption of a normal distribution for asset returns is violated. "Fat-Tailed and Skewed Asset Return Distributions" provides a bridge between highly technical theory and real-world risk management and investments. Although the material in this book is intended more for the investor in portfolios of stocks and bonds than for the investor in portfolios of IT projects, the book drives home the point that application of the Central Limit Theorem—under certain conditions the sum of independent random variables will tend to be normally distributed—to many real-world situations can be inappropriate because the conditions necessary for its application are not met.
Appendix D: Cash Flow
Appendix E: Depreciation, Taxes, and so Forth
At acquisition, many tangible assets—including computer hardware and software—are recorded at cost. But, when these assets generate cash flows over several accounting periods as the assets are used in operations, the firm transfers a portion of the cost of these assets to an expense account systematically over the periods in which the firm uses the assets. The amount transferred to expense each period is called depreciation. The objective of the depreciation process is to match the cost invested in the asset with the benefits derived in the form of revenues or savings. Intangible assets such as patents, copyrights, and trademarks—valuable because of the rights and privileges that they convey to their owner—also can produce benefits over several time periods. Consequently, intangible assets are also generally reported at cost less accumulated amortization, which is the term used to describe the amount of cost transferred to expense each period. And, of course, the amounts of these expenses play a role in determining cash flows that are so important in the project selection/rejection process. For a detailed account of U.S. Tax information on this topic, read Publication 946 (http://www.irs.gov/pub/irs-pdf/p946.pdf) ... and talk with your tax advisor.
Note that depreciation and amortization for tax purposes and depreciation and amortization for financial statement purposes do not always match up, as tax codes may differ from GAAP (Generally Accepted Accounting Principles) and FASB (the Financial Accounting Standards Board) pronouncements. Moreover, how you depreciate software for tax purposes depends on how you acquired it (for example, as a package deal along with a computer), how it's licensed (for example, is it governed by a proprietary or open source license?). Some licenses allow you to resell the software (and therefore depreciate it) whereas other licenses do not.
Statement of Financial Accounting Standards No. 86 specifies that the cost of developing and producing computer software products that will be available for sale or lease should be capitalized and amortized over their economic lives. Prior to this standard, all such costs incurred prior to the development of a prototype were expensed, and many small software development companies claimed that this practice understated net income, making it very difficult to attract outside capital.
Finally, the cost of developing software internally can sometimes be considered a research and development cost and either expensed or capitalized and depreciated over several years, depending on its size and length of service (see Reference 12 for an account of how one institution, Johns Hopkins Hospital, treats these issues). In addition, there's another option exploited by many firms: a tax credit. Unlike a deduction, which simply reduces taxable income, a credit is a dollar-for-dollar reduction of your tax bill. But, there are a few catches: The R&D credit is authorized by Congress on an on-and-off-again basis (it's there when Congress thinks it will stimulate the economy), exists in some countries but not others, and requires detailed record keeping and highly-specialized tax expertise to obtain. However, when the size of your software development project is large enough, the benefit to cost ratio can reward you handsomely for your trouble.
Qualified R&D expenditures include direct labor, outside software vendor implementation costs, and so forth. Examples of qualifying R&D activities for a financial institution would include (but are not limited to):
- Investment in the development of Internet credit security applications (in other words, smart Internet security credit cards).
- Investment in the development of wireless banking programs (in other words, PDA applications).
- Investment in the development of a software program that consolidates various branch and account activities into one, new reporting system (in other words, consolidation of bank computer systems for loans, trusts, deposit accounts, and the like).
For most large companies, an Internal Revenue Service (IRS) agent will refer a Research Tax Credit claim to an IRS engineer, whether or not the claim includes internal-use software. The IRS engineer will begin the examination of the claim by getting an understanding of the methodology used in compiling the data for the claim (in other words, project approach vs. cost center approach, type of development activities, and so forth). After reviewing the taxpayer's work papers supporting the claim, the IRS engineer will want to interview the company IT personnel who were directly involved in the development process of a particular project. As a result, it's important to find the appropriate person within your organization who can address the questions posed during the interview. This person needs to explain the project from an overall perspective, including business purpose and competitive information.
Conclusion: collaboration among IT, Accounting, and Finance personnel is an important part of the project portfolio management process because issues usually understood best by Information Technology (IT) can influence the bottom line of accounting, financial, and tax reports prepared by other departments.
- Kerzner, H., Project Management, Wiley (2006)
- Pratt, J., Financial Accounting in an Economic Context, 6th Ed., Wiley (2006)
- Williams, J., Haka, S., Bettner, M. Financial and Managerial Accounting, McGraw-Hill/Irwin (2005)
- Brealey, R., Meyers, S., Allen, F., Principals of Corporate Finance, McGraw-Hill/Irwin (2006)
- Winston, W., Financial Models Using Simulation and Optimization, Palisade (2000)
- Winston, W., Financial Models Using Simulation and Optimization II, Palisade (2001)
- Baker, K., Optimization Modeling with Spreadsheets, Thomson (2006)
- Myerson, R., Probability Models for Economic Decisions, Thomson (2005)
- Albright, S., Winston, W., Zappe, C. Data Analysis and Decision Making with Microsoft Excel, Thomson (2003)
- Rachev, S., Menn, C., Fabozzi, F. Fat-Tailed and Skewed Asset Return Distributions, Wiley (2005)
- Laplant, P., Costello, T. CIO Wisdom II, Prentice Hall (2006)
Author's Note: The chapter on Utility Theory is suitable for advanced readers.
About the Author
Marcia Gulesian has served as Software Developer, Project Manager, CTO, and CIO over an eighteen-year career. She is author of well more than 100 feature articles on Information Technology, its economics, and its management. You can e-mail Marcia at firstname.lastname@example.org.
© 2006 Marcia Gulesian
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