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Valuing TechnologyRichard A. H o w e yIn order to make intelligent decisions about implementing and managing a technology, managers must be able to estimate the value of the technology ex ante and to measure that value ex post. If it is going to be of practical use, any overall theory of technology must include methods for estimating and measuring the value of technology. While some of this value is tangible and relatively easy to estimate and measure, much of the value is intangible and very difficult to estimate and measure. Unfortunately, the state of the art in estimating and measuring the value of technology, particularly intangible value, is primitive at best. The bursting of the dot-com bubble is only the most recent example that illustrates the inadequacy of current practice. Using information technology as an example, this paper explores techniques for estimating and measuring the intangible value of technology. T e c h n o l o g y has been defined as "created c o m p e t e n c e as manifested in devices, procedures, and acquired human skills" (Van Wyk, 1999: 16). The term " c o m p e t e n c e " refers to an ability to do something. Thus, this definition implies that t e c h n o l o g y exists to be used for some purpose. It isn't just passive knowledge. Hopefully, use of the technology will benefit somebody such as a c o r p o r a t i o n or society as a whole. H o w e v e r , it usually takes s o m e kind o f investment to develop or implement a technology. It doesn't c o m e free. Thus, if a corporation, government, non-governmental agency, etc. is going to implement a technology, they need to be convinced that there is at least a reasonable c h a n c e that the benefit will be worth the investment. T h e y need to be able to estimate the value they will receive from i m p l e m e n t i n g the technology. Richard A. Howey is an information systems consultant in the Human Resources Management practice at IBM Business Consulting Services where he applies data warehousing and other advanced analytical software technologies to satisfy the information needs of HR management professionals. He has over 27 years of experience in information systems as a software developer, project manager, and consultant. In addition to his professional activities, he recently completed a Master of Science degree in management of technology at the University of Minnesota. He may be reached at .

Knowledge, Technology, & Policy, Fall 2004-Winter 2005, Vol. 17, No. 3-4, pp. 44-64.



Unfortunately, this isn't easy. One of the most difficult aspects of technology is predicting its value. Yet, predicting the value of a new technology, ex ante, is critical if business and society as a whole are going to invest in it and benefit from its use. It must also be possible to measure its value, ex post, to see whether value was actually created. It is widely accepted that if you can't measure it, you can't manage it. Any overall theory of technology must include approaches to predicting and measuring its value if it is going to help us manage technology effectively. In recent years, the value of information technology (IT) has been of considerable interest. IT provides an evocative example of just how hard it is to predict and measure the value of technology. In fact, Nobel Laureate economist Robert Solow stated, "We see computers everywhere, except in the productivity statistics" (Brynjolfsson and Hitt, 1998: 4). This led to coining of the term "IT Productivity Paradox." It just doesn't appear that IT investments have the value they are expected to have. This paper explores the IT productivity paradox and summarizes lessons that the paradox teaches us about valuating technology. Next, we analyze methods that are typically used to predict the value of technology, ex ante. The specific methods discussed are discounted cash flow (DCF) and real option analysis. A hypothetical example is presented illustrating the use of these techniques to value an IT investment. We then turn to the measurement of technology value, ex post. Since many technology-based assets are intangible, we examine intangible asset accounting techniques. Specifically, we discuss the work of Baruch Lev and of Paul Strassmann in measuring the value of intangible assets.

The IT Productivity ParadoxmWhat Can It Teach Us about the Value of Technology?When Robert Solow made his famous statement in the 1980s, he was probably looking at statistics that showed U.S. labor productivity had declined to an annual growth rate of only 0.8 percent while computer technology purchases were rising at an annual rate of 11 percent. Indeed, this does seem to show that computers and information systems do not pull their own weight (Strassmann, 1997: 83). Other statistics, at a corporate level, verify the apparent lack of return from IT. Paul Strassmann, who has served as chief information officer of General Foods, Kraft, and Xerox, has tried to correlate corporate IT spending per employee with return on equity. The result was that the relationship appeared random. He also tried other measures such as return on assets and return on net investment. The results were the same (Strassmann, 1997: 34-35). Certainly, some investments in IT seem to have large paybacks. For example, Wal-Mart spends more on IT than the average in the discount retail industry and has reaped large rewards. (Foley and Mahmood, 1996: 8) However, overall, while higher levels of IT spending may lead to higher financial returns, they do not necessarily lead to higher financial returns. Investments in IT are not sufficient to guarantee profitable returns.


Knowledge, Technology, & Policy / Fall 2004-Winter 2005

Erik Brynjolfsson of MIT and other researchers have taken a different approach to valuing IT investments. Their approach is to correlate IT expenditures to the market value of the corporation. The difference in results when this approach is taken is striking: Using eight years of data for 820 non-financial firms in the United States, we find that an increase of one dollar in the quantity of computer capital installed by a firm is associated with an increase of about ten dollars in the financial markets' valuation of the firm. Other forms of capital do not exhibit these high valuations (Brynjolfsson and Yang, 1999: 1). It has also been observed that announcements in the business press of IT investments may have a significant effect on a firm's market value. The magnitude of this effect is directly related to the degree to which IT capabilities are considered to be critical to competitive advantage in the industry (Richardson and Zmud, 2002: 3). Clearly IT is valued as an intangible asset by the investment community. Indeed, intangible assets now make up the majority of the market value of most companies. We can see this by observing the mean market-to-book ratio of publicly traded companies. During the late 1970s and early 1980s, this ratio for the Standard & Poor (S&P) 500 companies was around 1. This meant that most of the market value of a company was based on its physical or tangible assets as reflected in its financial statements. However, throughout the 1980s and 1990s, this ratio has increased. In March 2001 this ratio was approximately 6. That means that for every $6 of market value, only $1 (17 percent) appears on the company's balance sheet as a tangible asset. The other $5 (83 percent) represents intangible assets. Even when replacement values rather than book values of tangible assets are considered, the ratio still exceeds 3 (Lev, 2001: 8). If intangible assets are indeed so important, then why don't investments in the IT intangible asset show up in the productivity statistics? Productivity is the ratio of outputs produced divided by the inputs consumed to produce those outputs. At least one possibility is the difficulty of measuring inputs and outputs so that productivity can be computed: Properly measured, output should include not just the number of widgets coming out of a factory, or the lines of code produced by a programming team, but rather the value created for the consumers. Fifty years ago, tons of steel or bushels of corn were a reasonable proxy for the value of output. In today's economy, value depends increasingly on product quality, timeliness, customization, convenience, variety and other "intangibles." Similarly, a proper measure of inputs includes not only labor hours, but also the quantity and quality of capital equipment used, materials and other resources consumed, worker training and education, even the amount of "organizational capital" required, such as supplier relationships cultivated and investments in new business processes. The irony is that while we have more raw data today on all sorts of inputs and outputs then ever before, productivity in the information economy has proven harder to measure than it ever was in the industrial economy. (Brynjolfsson and Hitt, 1998: 1)



By this theory, the improvements are there but they are intangible and so are hard to measure. Economists admit that their measures, such as gross domestic product (GDP), cannot account for all effects and thus may not be truly adequate measures. (Gwartney, Stroup, and Sobel, 2000: 181-182) For example, a modern luxury car that includes today's safety and convenience features wasn't available at any price 30 years ago. So is it really valid to compare productivity across 30 years in the automobile industry by dividing the total price of cars produced by the total cost of producing them? The measurement theory is a possible explanation of the paradox, at least in part. Another complicating factor is the time lag between IT investments and their payoff. Most studies of IT examine the payoff question at a certain point in time. Unfortunately, IT implementations take time to realize their full