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Information Technology and the Productivity Paradox

Paul Attewell

At first glance, it would seem impossible that anyone could argue that information technology (IT) has been ineffective in the U.S. economy. Over the past 25 years, microelectronics has revolutionized many services and products, the way goods are produced, and the life-styles of consumers. Advances in medicine, from computerized axial tomography (CAT) scanners to ordinary laboratory equipment, are totally dependent on microelectronics. The round-the-clock availability of automatic teller machines (ATMs) and the capability to send facsimiles of documents thousands of miles in seconds also attest to the impact of micro-electronics. And more somberly, the intact but empty facades of government buildings in Baghdad are reminders of the power of microelectronic ''smart bombs" to destroy their targets with surgical precision.

Despite these and numerous other examples of the power of IT, a growing body of scholarly research indicates that the information revolution has failed to deliver in one important respect. That is, for all its accomplishments over the past quarter century, IT has not improved the productivity of the U.S. economy or U.S. firms.

As discussed in Chapter 1, the term productivity can take on several meanings. In this chapter it refers to the ratio of output (e.g., goods produced or total sales) to inputs (labor, capital, raw materials) for a firm or for an entire economic sector. This ratio is sometimes called throughput productivity, and it is measured in physical or monetary terms. The expectation for microelectronics was that it would enable



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Organizational Linkages: Understanding the Productivity Paradox 2 Information Technology and the Productivity Paradox Paul Attewell At first glance, it would seem impossible that anyone could argue that information technology (IT) has been ineffective in the U.S. economy. Over the past 25 years, microelectronics has revolutionized many services and products, the way goods are produced, and the life-styles of consumers. Advances in medicine, from computerized axial tomography (CAT) scanners to ordinary laboratory equipment, are totally dependent on microelectronics. The round-the-clock availability of automatic teller machines (ATMs) and the capability to send facsimiles of documents thousands of miles in seconds also attest to the impact of micro-electronics. And more somberly, the intact but empty facades of government buildings in Baghdad are reminders of the power of microelectronic ''smart bombs" to destroy their targets with surgical precision. Despite these and numerous other examples of the power of IT, a growing body of scholarly research indicates that the information revolution has failed to deliver in one important respect. That is, for all its accomplishments over the past quarter century, IT has not improved the productivity of the U.S. economy or U.S. firms. As discussed in Chapter 1, the term productivity can take on several meanings. In this chapter it refers to the ratio of output (e.g., goods produced or total sales) to inputs (labor, capital, raw materials) for a firm or for an entire economic sector. This ratio is sometimes called throughput productivity, and it is measured in physical or monetary terms. The expectation for microelectronics was that it would enable

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Organizational Linkages: Understanding the Productivity Paradox factories and offices to produce more productively—that the ratio of output per unit of input would increase. Several scholars who have attempted to measure the benefits of computer technology in the U.S. economy in a systematic fashion were unable to find overall productivity improvements due to IT. Some used government data on the productivity of the economy as a whole. Others examined specific industrial sectors, such as services. Still others collected data on representative samples of firms within one industry and found little or no payoff, even in industries that have invested very heavily in IT, such as the banking and insurance industries. A few researchers did find a positive contribution of IT, but sometimes of such small magnitude that it underlines rather than contradicts the concerns of other researchers regarding productivity. It is the combination of such evidence (detailed below) that leads to the belief that there is a productivity paradox regarding IT. In this chapter I review the emerging literature on the IT productivity paradox and discuss the major studies. I also identify a series of mechanisms that explain how the potential productivity payoffs of IT are attenuated or negated. Some of the mechanisms have been well documented; others are more speculative—hypotheses with partial evidence. Taken together they begin to chart the causes of the productivity paradox. But before undertaking those parts of the chapter, I frame the discussion by explaining why the productivity paradox is so profoundly puzzling to scholars and why it should also be taken very seriously by the public at large and, especially, the computing community. BACKGROUND The computer revolution would appear to have been extremely successful. Initial improvements in electronics unleashed a wave of innovation, and computers rapidly diffused across an enormous range of industries. Today, computers are indispensable parts of all manner of enterprises, from multinational corporations to mom-and-pop groceries. Further, there have been dramatic improvements in the productivity of the basic technology. Microprocessors continue to provide improvements in the processing power per dollar for central processing units on the order of 20 percent a year. Almost everyone expected the next step to be a marked improvement in productivity in the broad range of industries that had adopted computers. The need for such a productivity breakthrough was acute: Since the late 1960s the productivity of U.S. factories, service industries, and offices had been virtually stagnant, while that of the nation's international economic competitors had been rising. Firms in the United

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Organizational Linkages: Understanding the Productivity Paradox States were losing market share, in part because of their higher cost structure (National Academy of Engineering, 1988). The promises made for IT were lavish and typically centered on productivity payoffs. Vendors of the technology, from office automation to computer-aided design to computer-aided software engineering, assured buyers that the technology would increase productivity by requiring fewer workers to perform a given amount of work or by allowing expensive skilled labor to be replaced by cheaper semiskilled labor. American industry believed the promises. The levels of investment in IT have been staggering. In 1990 alone, U.S. businesses invested about $61 billion in hardware, about $18 billion in purchased software, and about $75 billion in data processing and computer services (U.S. Department of Commerce, 1991). (These amounts exclude investment in telecommunications per se, beyond computers.) Within a U.S. corporation today, IT often accounts for a quarter or more of the firm's capital stock, the total value of its equipment and plant (Roach, 1988b, 1991). For two decades IT has consumed an ever-increasing proportion of the investment dollar in U.S. industry. Overall industrial investment, however, has been roughly constant over the same period, which implies that investment in other types of machinery and equipment, as well as investment in employee training and other "soft" investments, has been lessened or deferred in favor of IT. This pattern differs from that of the nation's major international competitors. While they too have put large sums into IT, their investment in computing (especially in white-collar automation) falls far behind that of the United States (Picot, 1989). In one sense then, U.S. industrialists have taken a huge gamble on IT, in terms of the success of their individual firms and, most especially, the nation's competitive standing. It is in the context of international competitiveness that the apparent lack of productivity gains is so shocking. It begins to look as if the gamble is failing. Thus, those who believe in the productivity paradox do not argue that computers are a bad thing. Nor do they disregard the important improvements in goods, services, and the quality of life that have resulted from IT. Rather, they are profoundly disquieted by the fact that IT does not appear to have fulfilled its most important promise, that of increasing economic productivity and thereby improving the competitiveness of U.S. industry. The challenge is to understand the basis of the productivity paradox, to unravel the reasons why IT investments as a whole have not paid off. Has the investment gone into the wrong applications? Are some applications productive while others are not? Are there positive

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Organizational Linkages: Understanding the Productivity Paradox productivity contributions of IT that are being offset or frittered away by psychological, sociological, or organizational dynamics within firms? To what extent do design and technological factors contribute to the paradox? Only when the nation gains an understanding of the dynamics of IT and productivity inside economic organizations and answers these questions can it expect to reverse the productivity paradox and realize the productivity potential of IT. PRIOR RESEARCH Research Designs The studies that suggest a paucity or lack of productivity payoff from IT are of three types, each of which involves a different level of aggregation, a different unit of analysis. The first type analyzes productivity levels and IT investments in an entire economic sector, such as services, for a period of years. The expectation is that increases in IT investment over time will be reflected in improvements in sectoral profitability or productivity over time (albeit with lags). A second type compares productivity and IT investment across several industries. The expectation is that those industries with greater penetration of IT will show greater productivity increases over time. If no relationship between IT intensity and productivity change is found, there is a prima facie case that IT is ineffective in terms of increasing productivity. A third type focuses on representative samples of firms within one industry and looks at whether those firms with higher levels of IT investment have higher productivity or profitability (net of other factors) than similar firms with less IT. By specifically controlling for differences in size, capitalization, and other plausible determinants of productivity, this kind of study most effectively isolates the contribution of IT investment to increases in productivity. A fourth type exists, studies of single firms, but is not discussed here. Individual case studies can be very useful in identifying mechanisms underlying productivity, and they are used for that purpose in Chapters 9–11. But one cannot determine from a collection of individual case studies whether productivity is improving in the economy as a whole. For that, one needs representative samples of firms or sector-level data. (For a synopsis of case studies of IT and productivity in individual firms, see Crowston and Treacy, 1986.) Each of the first three approaches above has strengths and weaknesses, but in combination they are most powerful because the analytic strengths of one approach tend to offset the weaknesses of the others.

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Organizational Linkages: Understanding the Productivity Paradox For example, confronted with sectoral evidence that increased expenditures on IT over time have coincided with stagnant productivity, Bowen (1986) suggested that without the currently high level of IT investment, the productivity trend might have been even more dismal. This is a perfectly tenable rejoinder to sectoral studies, but it fails to explain why in interindustry studies, industries with higher levels of IT investment tend to have lower levels of productivity improvement than industries with far less IT investment, or why in several studies of firms within one industry, IT-intensive firms perform no better than low-IT firms. Thus, findings on IT and productivity that hold across all three levels of analysis should be more convincing than findings limited to one type of study design, and theoretical objections to findings from one level of analysis should be viewed with caution unless they also negate findings from other levels of analysis. Findings Sectoral Analyses Roach (1983, 1984, 1986, 1988a–c, 1991; Gay and Roach, 1986) has conducted a series of studies of the relationship between IT investment and productivity within the service sector. Conditions in the early 1980s did not seem auspicious for a dramatic leap in productivity in this sector. The rate of growth of the nation's capital stock had slowed from the 1960s to the 1980s, which did not augur well for investment-driven productivity growth (Roach, 1983). Nevertheless, in the early and mid-1980s, Roach expected that as the information sector became more capital intensive, its productivity would surge (Roach, 1984). That did not happen, however. Investment in white-collar work did indeed catch up: By 1983 the amount of "high-tech capital" per information worker achieved parity with the amount of "basic industrial capital" per production worker in manufacturing (Roach, 1986:13). But despite this infusion of capital, white-collar productivity in the service sector grew at a miserly rate of 0.7 percent a year between 1982 and 1987. Roach is aware of the many possible causes of the nation's productivity slowdown, but he has become increasingly critical of investments in computers and other IT. He has documented the very large investments in IT in service industries over the past two decades and the extent to which those industries have become highly IT dependent. For example, he reported that 38 percent of the entire capital stock of insurance carriers is invested in IT; 26 percent for banks, and 53 percent for the communications industry (Roach, 1988b). Yet productivity has been falling in the finance and insurance industries since 1973, and

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Organizational Linkages: Understanding the Productivity Paradox the greatest drop has occurred since 1979. The communications industry has experienced modest productivity growth, but that growth has been slowing over time, despite continuing IT investment. Even with the infusion of 84 percent of the nation's multibillion dollar IT investment, "the level of white-collar productivity in 1987 was actually no higher than it was in the mid 1960s" (Roach, 1988c:1). Roach (1988b) has suggested that executives in charge of IT investments have been "rolling the dice" (i.e., spending large sums on projects whose productivity and profitability outcomes are uncertain while tolerating internal measurement systems that are incapable of telling them whether their investments are really paying off). He points out that the investment in IT has occurred in a period when total investment has been stagnating. In this zero-sum situation, precious investment capital has been committed to a low-payoff technology. In contrast, the goods-producing sector in the United States has experienced a significant increase in productivity, despite its relatively low investment in IT. The implication is that IT investment in the service sector has been excessive: In Roach's (1988a:6) words, "We have over-MIP'd ourselves" (refers to a computer's capability to process millions of instructions per second). Such sentiments produced a flurry of comment in the business press (Business Week, 1988; Roach, 1988a), but that apparently did not affect IT investment. In 1988, IT absorbed 42 percent of total corporate outlays on capital equipment, and the proportion is still climbing. A dramatically different sectoral approach to assessing the value produced by IT investments is to be found in Bresnahan's (1986) study of the financial services sector. Bresnahan used a welfare economics framework that has been applied to several other technological innovations (Mansfield, 1977). Within this framework economists conceptualize advances in one sector as providing spillovers in the form of reduced costs or extra value to downstream users of the product of that innovation. For example, advances in computer design and manufacturing techniques spill over from computer manufacturers into benefits for the immediate user of less expensive computers (the financial services sector) and the customers of that sector. What is striking about Bresnahan's approach is that he did not measure changes in output or productivity in the downstream sector (here, financial services) in order to assess the value produced by computers in that sector. Instead he inferred "the value of the technology from the adopters' willingness to pay." More specifically, "the value spilled over [is] inferred from the demand curve of the downstream sector for the output of the advancing sector [computer manufacturing]" (Bresnahan, 1986:742). Thus, by analyzing the relationship between

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Organizational Linkages: Understanding the Productivity Paradox the quality-adjusted price of computers in 1958 and 1982 and the demand for them (expenditures) by financial services in those two years, Bresnahan obtained a derived demand curve. The area under the curve is then conceptualized as a welfare index—the value of the spillover. Using this technique, Bresnahan concluded that between 1958 and 1982, the value of mainframe computers to the financial services industry and its customers was at least 1.5 to 2 times the expenditures on those computers. There is "a very large social gain to computerization" (p. 742). Bresnahan drew on models that are widely accepted by economists of innovation but highly problematic for other scholars. Treating productivity and related benefits as a direct function of the demand curve for computers enabled him to bypass the thorny problem of empirically determining the magnitude of productivity changes. Moreover, the possibility that a sector could make large (and increasing) investments in a technology without obtaining benefits is ruled out by the theoretical assumptions under which Bresnahan and his colleagues work. Bresnahan's most important assumption is that the volume of computer purchases at a given price (the demand curve) is a function of the actual value produced by computers for the buyer (rather than a function of the buyer's hopes or expectations of produced value). To the extent that purchases of a new and complex technology are like a "jump in the dark," in which productivity or profitability benefits are hoped for but not known in advance, the welfare approach is suspect. Thus, it is prudent to treat Bresnahan's findings as estimates of what benefits would obtain from computers under stringent, but questionable, theoretical premises, rather than as measures of the actual historical payoff from computers. A striking contrast to Bresnahan's research is to be found in Franke's (1989) analyses of computerization in the financial services sector (insurance and banking) based on government time series data on industry inputs and outputs from 1958 to 1983. Capital intensity has grown very steeply in this sector since the early 1960s, largely because of the introduction of computer technologies. Disaggregating trends over time in capital productivity versus labor productivity, Franke found that while labor productivity has risen modestly, the productivity of capital has dropped precipitously since the mid-1950s. Through regression analysis, he linked changes in capital productivity to specific technological innovations, for example, magnetic ink character recognition (MICR), second-generation mainframes, and ATMs. In general, these innovations were associated with drops in capital productivity: They lowered the return on investment (ROI), rather than improving it, to the point that capital productivity in 1983 was only 22 percent of its 1957 peak.

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Organizational Linkages: Understanding the Productivity Paradox Franke's models provide some reasons for optimism about the future, however. Microcomputers and fourth-generation computers appear to be improving productivity somewhat, although ATMs are reducing it. Thus, Franke interprets the productivity paradox as an essentially transitional phenomenon, albeit one that has resulted in three decades of declining capital productivity in financial services. He expects productivity improvements in future decades. Interindustry Comparisons Osterman (1986) examined productivity using government data on employment and capital stock in 40 two-digit Standard Industrial Classification (SIC) industrial groups and survey data on the computer stock of each industry (a two-digit industrial group aggregates a number of different products). His focus was the effects of computers on managerial and clerical employment between 1972 and 1978, net of changes in output and wages. He observed a positive and statistically significant effect of computers on clerical productivity: For each 10 percent increase in computer stock, clerical employment decreased by 1.8 percent between 1972 and 1978 (net of changes in output). He also found a similar, but smaller, effect for managerial productivity. Osterman's findings indicate that computers do have measurable productivity effects, but one must be cautious in reading them as a direct refutation of Roach's findings. Osterman's analyses included manufacturing and service industries. In order to address Roach's findings directly, one would have to know whether the productivity effect was created primarily by manufacturing or whether computers also displaced labor in service industries. It is also hard to gauge the size of the productivity effect from Osterman's measures. He described the displacement of clerks as "substantial." But whether a 1.8 percent reduction in clerical labor per 10 percent increase in computer stock is substantial depends on how much investment in IT is necessary to produce that 1.8 percent shift. Unfortunately, the measures as reported do not permit a practical assessment of the size of the effect. Berndt and Morrison (1991) used a combination of government data sets to examine the effects of IT investment, defined broadly (computers, communications equipment, photocopiers, and the like), on profitability and productivity for a sample of 20 two-digit SIC manufacturing industries from 1976 to 1986. In most of the industries, IT's share of investment increased dramatically during the period. Berndt and Morrison carried out a variety of econometric analyses—within-industry, across-industry, and pooled models. Their major finding on the profitability of IT was that there was "no significant

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Organizational Linkages: Understanding the Productivity Paradox relationship," although they found a "modest but significant" positive effect in one pooled analysis. In terms of labor productivity, they found a consistent pattern indicating that IT "has not been labor saving, but is instead correlated with increases in labor intensivity and decreases in average labor productivity" (p. 28). They found a similarly negative effect when studying the impact of IT on multifactor productivity: IT investment had degraded rather than enhanced productivity during the period. Multifirm Analyses Strassmann (1985:159–162) presented data collected by the Strategic Planning Institute in a pilot study of 40 large firms. Although published details of the study are very sketchy, he reported that there was no correlation between IT costs and his measure of productivity. In a subsequent analysis, Strassmann (1990) elaborated on his earlier study. First, he examined data sets that linked financial performance (long-term shareholder return) to an index of computer intensity for two industries, food and banking. In neither industry did he find any relationship between amount of IT investment and financial performance. He then plotted computer intensity against financial performance for some 100 manufacturing and service-sector firms, using survey data published by the magazine Computerworld. In neither the service nor manufacturing firms was financial performance correlated with computer use. Survey data from Information Week produced similarly unfruitful results. Strassmann did not interpret all these null findings as indicating that computers did not have an impact. Rather, he decided that better measures of firm performance and computer use were needed. He developed a methodology for calculating several value-added measures of performance, which he demonstrated were good predictors of more traditional firm-level performance measures but which were, he argued, superior. Using the PIMS (profit impact of market strategies) approach (Buzzell and Gale, 1987), he surveyed some 292 predominantly manufacturing businesses to obtain value-added measures of performance and detailed information on IT. With these custom-designed measures, he found the following: (1) There was no relationship between IT expenditures and his productivity measure: "Over-achievers deliver their results with a level of [IT] spending equivalent to below-average performers" (Strassmann, 1990:138). (2) In most firms, IT expenditures on management information systems (MIS) dwarfed IT expenditures on operations, on the order of 18 to 1. (Applications in operations include point-of-sales, order-entry, and decision support systems.)

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Organizational Linkages: Understanding the Productivity Paradox (3) Superior firms, in terms of productivity, spent less than average-performance firms did on IT (p. 139). (4) Some superior performers tended to spend proportionally more of their IT investment on operations than on MIS. In sum, even with a methodology and data collection tailored to the purpose, Strassmann found no correlation between IT expenditures and superior productivity. He found limited evidence that low performance was related to where firms deployed their IT: Stinting operations on IT and spending a lot on MIS appeared to undercut productivity. This idea of misallocation of IT investment recurs in research reviewed below. Loveman (1988) examined the productivity effects of IT investments on 60 U.S. and European manufacturers from 1978 to 1984. The data refer to business units (predominantly large manufacturing divisions of Fortune 500-sized firms). The data set includes quite detailed information on IT and non-IT investments and stock, as well as information on output, market share, wages, and so on. He defined productivity as the increase in output from an incremental increase in IT, net of other changes (in wages, non-IT investment, organizational structure, and so on). Loveman used a range of econometric models, but he found that "the data speak unequivocally: In this sample, there is no evidence of strong productivity gains from IT investments" (p. 1). In most of the models, the productivity gain from IT investment was zero. Despite efforts to find IT effects for subsamples (e.g., for high-IT investors) and careful assessment of model biases and their magnitudes, Loveman could not find a statistically significant or a substantively significant effect of IT investment on productivity for the manufacturers. Weill (1988) studied 33 strategic business units in the valve-manufacturing industry. He examined the impact of IT investment from 1982 to 1987 on return on assets (ROA) and other performance variables in 1987. He found no significant relationship between total IT investment and any performance measure, despite testing for various lags or time periods. This parallels Loveman's results. Weill, however, took his analysis an additional step by dividing IT investment into three qualitatively different types: (1) strategic IT, intended to increase sales or market share (e.g., an inventory system allowing sales staff to give accurate delivery time estimates); (2) transactional IT, such as accounts payable and order entry; and (3) informational IT, including electronic mail (email), accounting, and other infrastructural purposes. His analyses then revealed that transactional IT investment was related to better performance in terms of improved ROA and lowering nonproduction labor adjusted for sales. In contrast, strategic IT investment was not

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Organizational Linkages: Understanding the Productivity Paradox associated generally with performance (and in the short term appeared to lower performance on two measures). Informational IT was not related in any way to any performance measure. Thus, Weill's findings suggest that the 22 percent of IT investment directed into transactional activity had some impact on performance, but the remaining 78 percent of IT investment did not. Unfortunately, he did not report the size of the transactional IT effect, only the fact that it was statistically significant (i.e., positive and nonzero). Turner (1983) studied a representative sample of 58 mutual savings banks of diverse size. Although he documented different patterns of computerization among banks (often a function of size), he observed that ''unexpectedly, no relationship is found between organizational performance and the relative proportion of resources allocated to data processing" (p. 1). Cron and Sobol (1983) examined 138 medical supply warehousing firms and linked the extent of computer use (determined primarily by number of software uses) and several performance measures. Analysis of variance did not reveal a significant relationship between computer use and performance measures. In fact, extensively computerized firms exhibited a bimodal distribution in performance: They performed either very well or very badly. Cron and Sobol noted that the two groups (high versus low performance) differed on dimensions such as size and growth rate, but they did not attempt a multivariate analysis controlling for such variables. They concluded, despite the bimodal findings, that "extensive and appropriate use of computer capabilities is most likely to be associated with top quartile performance" (p. 178). Bender (1986) looked at the financial impact of information processing on a sample of 40 firms in the insurance industry. In a cross-sectional analysis, he found that IT was related to performance, defined as a firm's ratio of expenses to premium income. However, the relationship was curvilinear: Those firms with very little IT expenditure and those with a lot were worse performers than those in between. Investment in applications software was not related to performance, but investment in hardware was positively related. Bender presented a series of bivariate relationships between a performance measure and one aspect of computerization. He did not assess the combined effects of the various IT aspects (e.g., through regression) on performance, nor did he control for size, market share, type of insurance, or other possible sources of spurious correlation.1 1   Companies providing different kinds of insurance had very different values on Bender's dependent variable (operating expense ratio), which suggests that this should be controlled for when assessing the effect of IT (Harris and Katz, 1988:127).

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Organizational Linkages: Understanding the Productivity Paradox Firm-Level Mechanisms Competition versus Productivity In the 1960s, information technologies were primarily conceived of as methods for lowering the unit cost of processing various kinds of highly routinized paperwork (e.g., transaction-processing systems). In the 1980s, computer systems were characterized as ''strategic information systems," competitive weapons to wrest market share from rival firms. While the two uses of information systems are not mutually exclusive, they have quite different implications for productivity. A firm that uses IT as a strategic weapon seeks to increase its market share, and thereby its profits, at the expense of its competitors. This will typically mean that the successful firm expands to accommodate the increased market share. But the firm need not necessarily improve its productivity (output per unit of input) to increase its profits: An increase in output/sales at the old level of productivity will still generate increased profits. Thus, profitability is divorced from productivity. Nor will the productivity or profitability of the industry as a whole be improved through this strategic use of IT: The firm is redistributing market share, not creating more wealth with less input. In such a situation there is a disjuncture between what benefits an individual firm and what benefits an industry or economy. Increased market share clearly benefits individual firms, but the economy at large benefits only if productivity or quality is also increased (see Bailey and Chakrabarti, 1988). If this hypothetical situation was common, one would expect to find large investments in strategic IT yielding increased market share (but not increased productivity) for some successful firms but with negligible impact on industry-wide productivity or profitability. This industry-level outcome is consistent with Roach's findings (see above), and one can find illustrative evidence (not proof) in some of the most lauded firm-level examples of strategic information systems. American Hospital Supply (AHS) Corporation has been portrayed as an outstanding example of successful IT use. It is widely used as a case study in business school curriculums (e.g., Harvard Business School, 1986). By installing order-entry terminals in the purchasing departments of its hospital customers, and later providing inventory management software to them, AHS made it easier for its customers to order medical supplies and speeded its response to orders. Based on this innovative use of IT, which required large investments in hardware, software, and systems personnel, AHS was able to develop an enviable degree of customer loyalty, and its sales and market share zoomed.

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Organizational Linkages: Understanding the Productivity Paradox Table 2-1 presents the performance ratios of AHS during a decade of investment in IT and rapid growth in market share. Sales and profits boomed. But several indices of productivity—gross profit as a percentage of sales, operating expenses as a percentage of sales, operating earnings as a percentage of sales—showed no improvement at all, or had decreased, at the end of the period. This did not hurt the firm: It was growing and generating more profits, even though it was no more efficient than before. This becomes a cause of concern, however, when translated into an industry-wide or economy-wide phenomenon. For if IT investment is focused on the strategic goal of increasing market share and is shunted away from productivity-enhancing areas, costs may increase and productivity will stagnate. In the long run, this could leave those industries in which strategic IT investment dominates highly vulnerable to competition from firms that maintain a cost-lowering strategy. IT and the Service Approach Although American Hospital Supply illustrates the effects of strategic investment in IT, it is also an example of the use of IT to gain customers through improved service. In recent years a powerful current among American managerial theorists has extolled the importance of customer service for the overall success of a business (e.g., In Search of Excellence). IT is often used to actualize this philosophy—computerized inventory systems enable salespeople to give accurate assurances about availability of products, order-entry systems are used to speed delivery times, and so on. American companies have allocated substantial proportions of IT investment to service activities in the hope of winning customer approval and market share. If IT investments in service succeeded in attracting market share or allowed prices to be raised to reflect the improved service component, there would be a payoff at least to those who first adopted the technology. And, as discussed in the prior section, firms like AHS did just that. But one can also identify forces that make it rather difficult to earn profits from IT-assisted service provision. To capture profits, firms need (1) a period of time during which investments in a new service give them a temporary monopoly, thereby differentiating them from the competition, and (2) a willingness on the part of customers to pay a premium for the service-enhanced product. Such conditions have occurred for certain IT services, for example, airline reservations systems. But other IT pioneers have found themselves with a very short period in which to capture market share and capital-

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Organizational Linkages: Understanding the Productivity Paradox TABLE 2-1 Performance Ratios of American Hospital Supply Corporation, 1974–1984 Year 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 Sales ($ million) 915 1,065 1,238 1,363 1,619 1,928 2,261 2,660 2,965 3,310 3,448 Net earnings ($ million) 42.4 50.2 58.5 70.1 81.3 100.0 117.1 133.5 170.0 211.9 237.8 Performance Ratios:                       Gross profit/sales (%) 34 34 34 34 34 34 34 34 34 34 34 Operating expenses/sales (%) 25 25 25 25 25 25 25 25 25 25 25 Operating earnings/sales (%) 9.1 8.5 8.8 9.4 8.7 8.3 8.1 8.4 9.2 9.8 8.6 NOTE: These performance figures cover the period during which the ASAP computerized inventory and ordering system was first implemented and subsequently elaborated and expanded. Net earnings are post-tax. Performance ratios are based on pre-tax figures. SOURCE: Harvard Business School (1986).

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Organizational Linkages: Understanding the Productivity Paradox ize on IT investment. The introduction of ATMs by banks proved enormously popular with customers. However, it took relatively little time for other banks to follow suit. Moreover, although no consumer bank can hope to survive today without having them, ATMs have not generated large new profits for banks. On the contrary, the highly competitive environment in banking has made it difficult to charge customers for ATM service. Nor have ATMs enabled banks to cut costs by employing fewer tellers (Haynes, 1990). Available evidence suggests that customers use them for transactions they would not have made before. For example, they take out smaller sums of money at more frequent intervals. There is nothing new to the idea that technological innovation gives the first-comer a short-term advantage that is soon lost as the industry as a whole adopts the technology. Karl Marx, for example, noted the phenomenon in his comments on nineteenth-century textile manufacturing in Britain. What is new is the rapidity with which IT-based service innovations can be copied by competitors, the short window for recouping one's investment in the innovation, and the apparent reluctance of customers to pay for service improvements compared with their willingness to pay for better tangible goods. Taken together, these developments place an unusual burden on IT investors. More and more industries (like the banks with ATMs) have to make large IT investments to "stay in the game," whether or not an improvement in firm level profitability or productivity results. Consumers, and thus society at large, clearly benefit from the below-cost provision of IT services. The phenomenon looks less benign, however, when viewed from the perspective of corporations. Having to invest in IT in order to stay in the game and suffering poor returns on IT investment as a result detracts from capital accumulation. This would not be serious, except for the fact that it occurs during an era of intense competition and productivity stagnation, when investment should be productively deployed. Interorganizational Processes Information technology has led organizations to place greater demands on their suppliers and customers for information. Such demands can often only be met by further investments in IT. For example, in the early 1970s, insurance companies that processed medical insurance claims began to install costly mainframe-based interactive claims payment systems. There were several reasons why the companies chose to shift from manual or batch processing of claims to interactive computerized processing, but two are relevant here. At the time, the installation of computers in hospitals and doctors' offices for generating bills

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Organizational Linkages: Understanding the Productivity Paradox had resulted in a dramatic increase in the number of duplicate bills being generated by such computers and presented by clients for payment. This placed extraordinary burdens on manual claims processors, who had to avoid paying for the same medical service twice. Claims payment had to be computerized to deal with this double-billing assault from others' computers. Simultaneously, firms that paid for group health insurance for their employees began asking the claims payment companies for ever more detailed breakdowns of how each dollar was expended—on what medical procedures, for which covered person, and so on. Detailed reports had not been feasible, and had therefore not been provided, when recordkeeping was entirely manual. But with the advent of on-line claims processing, those insurance companies that had not developed computerized systems capable of analyzing payments found themselves losing clients to highly computerized competitors. In these examples one can see the truth in Ellul's (1954) macabre vision of technology, in which technologies create needs that only more of the technology can fulfill. The possibility of computerized data has enabled government to demand more and more detailed information from hospitals, military contractors, banks, and so on. It has stimulated bank customers to expect 24-hour information on their accounts, and users of overnight delivery services to expect rapid tracing of their packages. Whatever the long-term implications of such phenomena for profitability and economic growth, in the immediate term computers are placing greater burdens of information work upon organizations. In highly competitive environments, or when faced with legally mandated demands, firms may have no way of capturing the cost of this investment. Their provision of information therefore reduces, rather than increases, their efficiency. CONCLUSION The relationship between investment in IT and productivity is paradoxical. Research suggests that the strong productivity gains that were expected from IT have not manifested themselves—in the economy as a whole, in particular industries, or for representative samples of firms. The empirical evidence on the question is mixed, and this review has considered issues of data and methodology that might "explain away" the paradox. While more research on this question is clearly needed, the preponderance of evidence suggests that the shortfall of productivity payoff from IT should be treated as credible and that the next step—looking for forces that are undermining or attenuating potential gains from IT—should be taken.

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Organizational Linkages: Understanding the Productivity Paradox Pointing to a productivity paradox does not mean that IT investments have been ineffectual. In this chapter the focus has been specifically on productivity, not on other important goals or areas of impact, such as increasing market share, improving service, or improving quality. Market share is critical for the competitiveness of individual firms, and quality and service are important to consumers and for economic competitiveness. Nevertheless, one should not shrug off the importance of a productivity shortfall because of market share, quality, service, or other potential benefits of IT. To reiterate an earlier point, increases in productivity are central to keeping unit costs down and, thus, to enabling firms to compete successfully in the international arena. Increased productivity is also a major source of salary increases for the industrial labor force. If firms can produce more per person, they can afford to pay higher wages. Anemic progress in productivity has been a prime cause of two decades of stagnant wages for a large proportion of the working U.S. population. Conversely, generating higher productivity is the key to higher living standards in the future. If IT is to achieve its promise, then, it must enhance productivity as well as quality and service. Going beyond the evidence suggesting a productivity paradox, this chapter sought to identify several mechanisms that undercut or attenuate the potential productivity payoffs from IT in organizations. Some of the mechanisms identified are firmly grounded in research, others are more tentative. All would benefit from additional empirical scrutiny. The general pattern that emerged from the discussion of mechanisms is that IT creates a series of trade-offs at various levels of an organization. The potential benefits of the technology may be channeled into alternative directions—either doing the original work more efficiently (productivity enhancing) or doing a different kind of activity or the same activity more often. Such trade-offs were identified at different levels, from the individual to the organizational. At the individual level, various researchers have found that employees may channel the technology's potential into improvements of quality and appearance, rather than quantity of work. Initial evidence suggests that employees often favor the former, thereby attenuating potential productivity gains. At the group level, IT can result in an expansion of the work to be done or its complexity, rather than accomplishing the original amount of work with fewer inputs. A great deal of IT resources are also invested in managerial information systems and management by numbers, rather than in automating direct operations. According to data from Weill (1988) and Strassmann (1985, 1990), this trade-off seems to be associated with lower performance. Finally, at the organizational level, IT is sometimes channeled toward strategic, competitive, or service activi-

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Organizational Linkages: Understanding the Productivity Paradox ties that, while laudable in their own right, may be achieved at the expense of potential productivity gains. The next step is to document, through additional research, the magnitude and full implications of these trade-offs and to study the articulations of levels: how individual-level, group-level, and firm-level processes intertwine and affect one another such that productivity improvements at one level do not simply translate into productivity improvements at higher levels. Several of the chapters that follow focus on assessing productivity dynamics across levels of an organization. REFERENCES Anderson, J.C., R.G. Schroeder, and S.E. Tupy. 1982. Material requirements planning systems: The state of the art. Production and Inventory Management Fourth Quarter:51–66. Attewell, P. 1987. Big brother and the sweatshop: Computer surveillance in the automated office. Sociological Theory 5(Spring):87–99. 1992a. Technology diffusion and organizational learning. Organization Science 2(4):1–19. 1992b. Skill and occupational changes in U.S. manufacturing. Ch. 3 in P. Adler, ed., Technology and the Future of Work. London: Oxford University Press. Bailey, M., and A. Chakrabarti. 1988. Innovation and the Productivity Crisis. Washington, D.C.: The Brookings Institution. Bailey, M., and R. Gordon. 1988. Measurement issues, the economic slowdown and the explosion of computing power. Brookings Papers on Economic Activity 2:347–430. Barua, A., C. Kriebel, and T. Mukhopadhyay. 1989. A New Approach to Measuring the Business Value of Information Technologies. Unpublished manuscript, Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh. Benbasat, I., and A.S. Dexter. 1982. Individual differences in the use of decision support aids. Journal of Accounting Research 20(1):1–11. Bender, D. 1986. Financial impact of information processing. Journal of Management Information Systems 3(2):232–238. Beniger, J.R. 1986. The Control Revolution. Cambridge, Mass.: Harvard University Press. Berndt, E., and C. Morrison. 1991. High Tech Capital, Economic Performance, and Labor Composition in U.S. Manufacturing Industries: An Exploratory Analysis. Unpublished manuscript, National Bureau of Economic Research, Cambridge, Mass. Bikson, T.K., B. Gutek, and D.A. Mankin. 1987. Implementing Computerized Procedures in Office Settings. Santa Monica, Calif.: RAND. Bikson, T.K., C. Stasz, and J.D. Eveland. 1990. Plus Ça Change, Plus Ça Change: A Long-Term Look at One Technological Innovation . Santa Monica, Calif.: RAND.

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