Is IT Worth it?

The Business Value of Information Technology

Espen Andersen, 1992


  1. Introduction--the accusing chorus
  2. A framework for investigating IT
    1. The role of IT in each quadrant
      1. Quadrant 2: Design and diagnosis (physical product, unstructured process)
      2. Quadrant 4: Knowledge worker (information product, unstructured process)
    2. Movements between quadrants: IT and the redefining of tasks
      1. Moving West: Industrialization
      2. Moving East: Informating
      3. Moving North: embedding information
      4. Moving South: manipulating information rather than physical product
  3. How are we doing: Evaluating the contribution of IT
    1. Manufacturing: increased productivity, but how much is IT?
    2. Design and diagnosis: Quality at a price
    3. Back office: the easy things are done
    4. Knowledge worker: a matter of personal learning
    5. IT and movement between quadrants: the loss of measurability
  4. Conclusions -- a CIO's strategy of defence
  5. Tables
  6. Endnotes
  7. References

Introduction--the accusing chorus

The 1990s promise to be a rather tough period for many CIOs. An increasing number of academic and business writers hold that information technology has not delivered on its many promises of increased business value. In fact, information technology, according to a number of writers, often is detrimental to profitability: computers raise costs, seemingly without contributing to income.

It all started with Lester Thurow, then dean of MIT Sloan School of Management. In May 1986 he gave a speech at the American Association for the Advancement of Science, showing that while the number of blue-collar workers in the US was reduced by 6% between the 1978 and 1985, total output rose 15%. Fewer people produced more--a growth in productivity comparable to Europe and Japan during the same period. At the same time, however, the number of white-collar workers (including managers) grew 21%, swallowing the productivity growth in the blue-collar industry and making the United States less competitive (Thurow, 1986). This period of sagging productivity coincided with a period of high investments in office automation, technologies that intuitively should have increased, not decreased, productivity of white-collar workers.

Stephen S. Roach, an economist of Morgan Stanley, found through an elaborate analysis of labor statistics that productivity1 in the US service sector had not increased since the late 1960s (Roach, 1987). Martin Neil Baily, an economist at the Brookings Institution, showed that the investments in technology in the white collar industries has been immense, particularly in banks (Baily & Gordon, 1988, p. 390) where information technology has gone from representing 3.9% of capital during 1970-79 to 34.1% as of 1987. For insurance carriers the figures are 7.2% to 63.8%, respectively (see Exhibit 2). Much of this investment is in personal computers: The number of PCs used in Fortune 1000 companies rose from 2.5 million in 1983 to 18.4 million in 1985, and the percent of white-collar staff using them from 7% to 56% (Jeffery, 1991).

Paul A. Strassmann (1990, pp. 31-58) has shown that there is no correlation between financial return (as measured in profitability, sales per employee etc.) and the various measures used by the computer trade press for technological excellence (IT investments as a percentages of revenues, PCs per employee, etc.).

Books and articles like these, or rather the references to them in business journals, is causing difficult questions from CEOs to CIOs all over: Are they really getting any value out of having information systems--or should they maybe spend their money on something else instead--like advertising?2

Unfortunately for the CIO, there are vast differences between what economic analysis and overall statistics tell us, and what is found when we look at individual companies. The picture is far from clear, partly because the data is lacking and faulty for large parts of the economy, but also because the role of information technology is not well understood. In this note, I will try to bring some clarity to the picture by examining the role of IT in providing business value on two steps: First, I define a framework to discuss the role of IT in supporting different types of tasks. Within this framework, I try to show what effects use of IT can produce, and how these effects can provide business value. Second, I try to assess how successful the use of information technology been so far. Third, I try to give a strategy for the plagued CIO: how to respond to the challenges posed by the debate over the value of information technology in business.

A framework for investigating IT

To look closer at the role of information technology in work and its effect on business value, I will categorize tasks into one of four types. These types are derived by looking at the end results--the products--of a task, and the processes through which the results are achieved. The products can be divided into physical goods and information (following Jonscher's (1983) division of the economy into a production and an information sector)3. The processes through which products are made can be divided into structured (that is, known and repeatable procedures) and unstructured (where either the process has to be reinvented each time or is not explicable or replicable by another person). These two dimensions give us the matrix which forms the basis for the framework4 in Figure 1. More details are provided in Table 1.
                 Structured       Unstructured
              *                *                * 
  Physical    *   Manu-        *  Design and    * 
  goods       *   facturing    *  diagnosis     * 
              *                *                * 
              *              1 * 2              * 
PRODUCT       ***********************************
              *              3 * 4              * 
              *  Back office/  *   Knowledge    * 
  Information *  office        *   worker       * 
              *  factory       *                *
              *                *                *
The framework is imprecise in the sense that it is not readily apparent in which quadrant a task falls: most work contains elements of all these categories5, the distinction between physical and information product may be dubious6, and furthermore, the axes are continuous rather than dichotomic. Still, using this rather crude categorization enables us to focus on the effect of information technology and on singular types of tasks, a more precise viewpoint than looking at computers in management, the service industries or productivity statistics. I believe information technology can be used to improve productivity in the traditional sense only in some of these quadrants, either by increasing the capacity within the quadrant or by creatively moving tasks, or portions of tasks, from one quadrant to another. This implies that the kinds of systems that improve performance in one quadrant, as well as the measures used to gauge its success, might be useless or even counterproductive in other quadrants.

The role of IT in each quadrant

Quadrant 1: Manufacturing (physical product, structured process).

The first quadrant typifies the production and distribution of physical goods, primarily industrial manufacturing, but it encompasses service production to the extent that production or delivery of a physical product is important to the business7. The typical image this quadrant evokes is that of a worker standing by a machine, producing a tangible product. The work is routinized and standardized, the routine generally not designed by the person doing it, and is traditionally only changed through outside intervention. This is part of a long tradition of productivity enhancing industrial engineering, beginning with Frederick Taylor's Scientific Management movement during the early decades of the century, currently culminating in the Japanese methods of JIT manufacturing and linking to suppliers. There is little doubt about what the end product is and how it is measured: quantity is relatively directly observable, quality measured against standards. Traditionally, the skill level necessary to perform a task in this quadrant is not very high, although there can be significant differences in quantity and quality of output depending on how skilled the person performing the task is.

In this quadrant, information technology can increase capacity by improving quality and quantity of products through faster, more reliable, more precise and more continuous operations. In- dustrial robots, for example, do not need coffee breaks, sanitary facilities and fringe benefits, and can be put to use in dangerous or dirty environments where humans prefer not to work. Information technology, being electronic, is less prone to wear than mechanical devices--there is no need to grease a microprocessor. The effects of IT translates into business value through lower cost and increasing flexibility in the production process.

Quadrant 2: Design and diagnosis (physical product, unstructured process)

The second quadrant is the production (and repair) of physical products where the production process is not routinized. There may be several reasons for this: The product may be unique in each instance, as for instance the building of a ship, an office block. It might require creativity or knowledge that is not readily explicable, as in art or industrial design. It might be that the product, though simple in itself, is new and that routinized procedures have yet to be implemented.

Although the products in this quadrant are complex, there is little doubt about what they are. Quantity is readily observable, quality is measured by comparing to standards or to equivalent products from other sources. Although errors in design and diagnosis often are traceable, there may be considerable disagreement as to which inputs provide increases in quality. Although quality of output may be measurable, the value of increased quality may be difficult to measure: how much more secure should a car be, how much should be spent on "hopeless" injuries or sicknesses, etc. Even though the production process is unstructured, there are often standards for what constitutes a good process and what does not.

Tasks in the second quadrant are often taught through apprenticeship: since the process of, say, blowing glass or taking out appendixes is not as easily conveyed verbally as it is shown. The student of these arts learn by watching experienced performers and copying their techniques through a closely monitored process of trial and error. Apprenticeship time may be long, often because the product is costly or dangerous and the student cannot proceed to more difficult levels of performance before mastering the basic skills. The skill level necessary is high, often not only because of the dexterity necessary but because making decision on what to do is part of the task.

Information technology's main effect in this quadrant is to increase quality of the product by allowing experimentation, increasing information available for decision making, and shortening process time. A flight simulator's main advantage is that it allows trial and error without risk to life and property: through crashing many simulated planes the pilot-in-being learns how not to crash the real ones. And the experienced pilot may try out hair-raising new maneuvers without risking his or her pension. Information technology-based exploratory tools like computer tomography can guide a surgeon's knife in real time.

This translates into business value by increasing the demand for the product, because the product is of higher quality, or is designed or processed faster and more accurately than without the technology.

Quadrant 3: Back Office (information product, structured process)

The third quadrant--often referred to as the office factory or the back office--is where routine information is handled in a standardized way. This is the place we would expect to find the majority of white-collar or service workers. Banking, insurance and much of the public sector fall mainly in this quadrant. A typical worker here is a bank clerk, a cashier at a supermarket, or an IRS officer. Most large corporations have a sizeable fraction of their employees in this quadrant, doing chores that support the main business, such as updating customer and employee databases, handling orders and facilitating internal communication. Tasks in this quadrant are well specified, quantity is measurable, although measuring individuals is often done by measuring activity rather than output. Quality measurement is done through accuracy or timeliness standards. The necessary skill level in this quadrant is often very low.

Increases in capacity in this quadrant is achieved by increasing the number of operations performed per employee - much like in the first quadrant. Information technology may support this process through moving the recording of information out of specialized back office departments to where the transaction takes place. POS (point of sale) systems, which registers all information about a sale right at the customer checkouts, is an example of this. "Business process redesign"--a fashionable approach to information systems analysis that uses IT heavily--aims at vastly improving the productivity in this quadrant (Hammer, 1990).

The business value should come through record-keeping tasks needing relatively fewer people than before, through allowing vast increases in transaction volume, and in providing aggregated information to decision-makers, most of whom reside in the fourth quadrant.

Quadrant 4: Knowledge worker (information product, unstructured process)

In the this quadrant, we find unstructured information work. This is the realm of the knowledge worker: "managers, executives and a variety of professionals ranging from scientists to lawyers to entertainers" (Roach, 1991). Even though work here can have a surprisingly high routine content (Mintzberg, 1973), knowledge work is generally characterized by dealing with problems that do not lend themselves easily to direct automation8. Judgment and specific knowledge, either from specialized education or relevant experience, are important, and the problems encountered are mul- tifaceted, abstract and often varying. The quality of the product is more important than quantity, but contrary to the second quadrant, quality is not readily measurable, and the relative contribution of various inputs is a matter of post fact judgment and open to interpretation and often controversy. Since quality is so difficult to measure, quantity is often measured instead.

The effect of IT in this quadrant should be to increase the knowledge workers capacity to process and communicate information. This comes from two sources: automation what can be automated in the knowledge worker's job, freeing him or her to do what the computer cannot, and by increasing amount and quality of information available through technological media. Here we find the end users of DSSs and EISs, as well as personal computers and electronic communication services. The knowledge worker often designs the production process him- or herself, including the question of how and when to use information technology. This means that the frequency of use is often an important measure for the quality of the services IT provides.

The automated parts of a knowledge workers job, such as word processing and spreadsheet calculations, are a much smaller part of the time at work than the time spent simply communicating with people. Extensive use of electronic mail and conferencing systems thus should have a great productivity potential, especially if an organization is geographically dispersed. Strassmann (1990, pp. 357-359) argues that the largest potential is found in electronic communications, since 30-70% of an employee's time is spent in face-to-face communication, in addition to time spent in the telephone.

The business value provided should be products of higher quality and quantity: primarily better and faster decisions.

Movements between quadrants: IT and the redefining of tasks

Information technology can facilitate the relocation of a job or a task from one quadrant to another, and thereby increase its value to the organization. In general, the task can be moved either horizontally or vertically, giving four distinct movements, here termed North, South, East and West.

Moving West: Industrialization

Transfer of tasks from the second to the first quadrant is classic industrialization. Traditionally, when a task is industrialized, all or most of the physical steps involved in it are identified, set up as singular, sequential processes, and then performed by machines to the extent that machines can outperform humans. The rationale for industrialization has usually been to increase capacity and thereby draw down unit costs. In the process, products are standardized and simplified to better suit manufacturing needs. Information technology extends the scope of industrialization: by using information technology, more complex products can be produced in an in- dustrialized manner. Flexible manufacturing can alleviates some of the rigidity in the process, making shorter production profitable. CAD/CAM can be used both as a more efficient coor- dinator of production machines and as an effective tool to help the engineering and production functions of a manufacturing enterprise communicate.

Transfer of tasks from the fourth to the third quadrant is the industrialization of clerical work. This shift increases productivity for two reasons: the tasks, when automated, can in many cases be performed by less trained (and presumably cheaper) personnel; and the tasks become more measurable, meaning that the effects of changes in procedure can be documented better. This process is similar to industrialization in many respects. Unstructured processes are automated by reducing the process to identifiable, replicable steps, and then redesigning the process so it takes advantage of the speed and reliability of information technology. This constitutes an explication of the knowledge formerly contained in the minds and bodies of the people performing the tasks (Zuboff, 1988). Explicating and standardizing tasks through specialization has been the traditional way of increasing productivity: the most visible effect being "electronic sweatshops" (Garson, 1988); data entry departments in large organizations, typically banks and insurance companies, where large numbers of employees with low education enter data into mainframes.

Moving East: Informating

Transfer of tasks from the first to the second quadrant happens every time a manufacturing operation is moved or changed materially. This may be a temporary shake-down period, but it can significantly impact operations. Information technology can help during the transformation by simulating the new environment and allowing workers to test and practice new skills. A firm that changes strategy from offering commodity products to providing a stream of distinctive ones will move manufacturing operations towards the unstructured end of the spectrum more-or-less permanently. By committing to flexibility and continuous change, a firm forgoes some of the comfort of structured work. Productivity increases comes from driving down the cost of change, usually enabling the firm to compete in smaller, more profitable segments. IT can be crucial both because it help the organization switch between configurations quickly and because it can "remember" the precise state of each configuration. In principle this is the same thing as the automated features of certain luxury cars: each person driving the car adjusts the seat, mirrors, etc. perfectly. The car has a small computer that stores the settings, and reproduces them at the driver's command.

Transfer of tasks from the third to the fourth quadrant is seen in companies that use information technology to automate the routine aspects of clerical work, thereby orienting the job of the employee towards things that are less automatable, such as dealing with customers. Employees shift from specialization in one repetitive step of a complex task to handling all aspects of it. USAA corporation, a large insurance company based in San Antonio, Texas, has used this approach to advantage: They use imaging technology and a job distribution system to banish paper from its operations. This frees up insurance clerks to communicate with customers, and concentrate on the judgement and relationship aspects of cases, rather than spending most of their time keeping the files in order (Harvey & Ryan, 1991; Henkoff, 1991). A problem in this process is that the necessary skill level normally is higher in the fourth than in the third quadrant: although a task may move, the worker performing it may not.

Moving North: embedding information

Transfer of tasks from the third to the first quadrant means embedding information in the physical product. One example of this might be bar codes. When a truck full of boxes is unloaded onto a conveyor belt, each box passes a bar code reader, which registers the box in a computer system. Clerks checking packages at the loading dock are gone--the information they recorded is now embedded in the product itself. The process is repeated at a supermarket: A scanner reads the codes at the checkouts counter and enters it into the computer system. For the most part, the cashier does the physical chores the computer cannot do: putting the groceries in bags, physically receiving the payment, and making sure the customer does not run away with the goods.

Transfer of tasks from the fourth to the second quadrant: Although it may seem counterintuitive, information technology can be used to transfer, at least in a limited sense, tasks from being manipulation of information to being handcraft. Some of the research being done under the heading virtual reality asks people do things physically because the information is not readily explicable in any other way9. An example of this is an experimental system developed at the Tsukuba university in Japan, where a camera designer can put his hand into a "steel glove", which lets him "pick up" a camera from a screen. The "steel glove" not only lets him "lift" the image of the camera on the screen, but also lets him feel the balance of the camera -- a feature not easily modelled in a conventional CAD system.

Moving South: manipulating information rather than physical product

Transfer of tasks from the first to the third quadrant is manipulating information rather than physical product. JIT (Just-In-Time) is an example of this from the factory, EDI and other interorganizational systems examples from distribution. It is generally cheaper to move information than physical product: by increasing the quality of the information, the transportation of physical product can be delayed up to the point in time when it is needed, thus reducing the quantity of products and materials in the chain.

Information technology helps transfer tasks from the second to the fourth quadrant by substituting an electronic representation for a physical product under design. Engineers, architects and designers who once worked with drawings and physical models can now create designs through CAD or mathematical software. Computer-based drawings and 3-D models not only automate the step of actually making drawings and models, but allow designs to be tested electronically. Cars are now safety-tested by computer simulation rather than actual crashes. Electronic designs are more readily communicable than physical drawings and models, and may more easily incorporate or- ganization-wide standards, such as using common piece parts wherever possible.

Diagonal movements

Although most diagonal task shifts are indirect, we see some examples of "pure" cross-movements. These are predominantly from the first to the fourth quadrant. This is what Shoshana Zuboff, professor at the Harvard Business School, terms informating a task: using information technology to increase the richness of the job. (The term informating also applies to transfers from the third to the fourth quadrant). She gives a vivid example of this in her acclaimed book In the Age of the Smart Machine (1988), describing how the knowledge of workers in a paper plant changed from being "within the body" to being systemic: instead of knowing from experience how to set machines (by looking at and feeling the paper pulp) the workers monitored the whole process through a computer system. The productivity increased when the workers, sometimes clandestinely, started experimenting with the system to increase the output10.

How are we doing: Evaluating the contribution of IT

Manufacturing: increased productivity, but how much is IT?

The availability of data for the industrial sector of the economy is relatively good in most countries. In the US, the Bureau of Labor Statistics (BLS) collects data on employment, output and profitability. However, the data may be flawed. Overall industry statistics, starting with the venerable SIC code, is fraught with possible measurement errors. For instance, contrary to common practice in most other countries, in the US a company is classified under one SIC code only, even though it may have large divisions in several. ITT, for instance, was for many years classified in the baking industry. Also, figures on how much capital is spent on IT run into definition problems as to what expenses may be considered to be IT-related and what is not. For instance, since the capitalized value of a computer normally is just 25% of the total expense (the rest being software development and maintenance), huge differences in IT spending are not captured by the available data.

The picture seems to be that although the manufacturing sector's role in the US economy is decreasing, productivity of blue-collar workers has increased steadily (Drucker, 1991; Thurow, 1986), causing the industrial share of the workforce to drop to 25% of the US total in 1990 (Roach, 1988). The role of information technology in the increased productivity remains unclear, however: several studies (Berndt & Morrison, 1991; Loveman, 1988) indicate that investments in information technology have little or no correlation with increased productivity or profitability in US manufacturing industries. Loveman's study of 250 US manufac- turing business units did find a small, but significant correlation between IT investments and productivity increases three years hence, indicating that it may take time before the investments pay off.

The MIT Commission on Industrial Productivity study (Berger, et al., 1989) shows that US productivity has improved, but productivity in other countries has improved more. They propose that productivity improves not only by adding automation, but in how the automated features are taken advantage of. There is evidence to suggest that US companies are investing in automated factories, but not changing the way production is organized. In particular, flexible manufacturing equipment is not exploited: the machines are used for producing a few products in high volumes rather than taking advantage of the new machines' ability to produce many different products with a very low switching cost (Jaikumar, 1986).

One of CAD/CAM's key benefits is its ability to facilitate integration between the design, production and marketing functions of an industrial enterprise. The problem is often that it is relatively easy to have two of these functions on good terms with each other, but very difficult to have all three pull together--and more often than not, manufacturing gets low priority (Riggs, 1983). Proposed solutions for these problems have been many--most of them not including information technology explicitly, but instead focusing on project management (such as having dedicated projects with high-powered individuals as managers) (Clark & Fujimoto, 1991), using "overlapping" problem solving (Clark & Fujimoto, 1987), and designing for manufacturability (Dean & Susman, 1989).

The research available in this area indicate that there may be a long way to go before this potential is properly exploited. A study by Adler (1988) shows that companies have not found CAD/CAM to be a competitive advantage, mainly because they have failed to take organizational issues into consideration. Some success stories are available: Northrop, in the creation of the B2 Stealth Bomber, went directly from an electronic description of the system to manufacturing, skipping wind tunnel testing. Gleason Manufacturing uses CAD as a communication tool between design and manufacturing, directly feeding CAD drawings into manufacturing processes. And IBM, through its Proprinter project, rendered an automated factory largely obsolete because a better design reduced the number of parts to the point where it was faster assembled manually (Berger, et al., 1989).

Using the framework, we could conclude that productivity improvements within the manufacturing quadrant have been well-mined when it comes to increasing capacity within the quadrant. However, the external environment now values quality and flexibility in addition to low price. This should indicate that there is more productivity to be gained from transferring tasks from the first to the third and fourth quadrant: move information instead of physical product and exploit the specific knowledge gained by those close to the production process by giving them more decision power.

Design and diagnosis: Quality at a price

In the design and diagnosis quadrant, the health care industry is the one that has got most attention because of sagging productivity. The dramatically rising health care costs, not only in the US, but in most developed countries, are partly attributable to the increased use of technology in diagnosis, treatment and research. Sophisticated technology has increased the quality of diagnosis and treatment available to patients, but at a very high price. In this case, there is little question that information technology has increased the quality of the product: diseases and injuries that meant a certain death not long ago can now be successfully treated, often routinely.

The increased quality offered by the new technology carries some problems, however. One is the unclear pricing of increased quality: The new technologies, including information technology, now offers the ability to spend enormous amounts of money on marginally prolonging the life or increasing the probability of survival of a patient. The second is the unclear implications of how increased patient care translates into business value: since hospitals profit from using expensive technology, at least as long as public or private insurance is willing to pay for it, the use of technology becomes a quality measurement in itself. The tools, rather than the results, becomes the criterion against which performance is measured.

The combination of available new tools, the use of tools as an indication of quality, and the impossibility of pricing human life, has meant that the minimum acceptable investment level has risen dramatically for hospitals. A "normal" hospital has now become a "labor-intensive and capital-intensive monstrosity", because in this kind of work, capital is not a substitute for labor (Drucker, 1991).

Within the framework, we may conclude that information technology has been successful in increasing quality, which again has increased demand. The problem seem to be that this increased demand has not translated into profitability in a way that shows up in productivity statistics. The exception may be cases where information technology has been able to move tasks to other quadrants: through industrialization or through electronic rather than physical design representations.

Back office: the easy things are done

The back office is where information technology has been used the longest, the traditional business tasks of computers being clerical work like payrolls and billing. There are statistics available showing the use of information technology in the third and the fourth quadrant; the problem is often that it is difficult to separate the two. The industry-wide statistics do not match the conclusions of in-depth case stories of companies that were pioneers in exploiting information technology. James McKenney, professor of Harvard Business School, has studied the development of the bank transaction and airline reservation systems in Bank of America and American Airlines, respectively. In both these companies, information technology not only increased productivity, but enabled the businesses to grow and exploit tremendous economies of scale (McKenney, 1991). The Bank of America became the largest bank in the world and essentially eliminated clerical work in the 1960s through its heavy investments in check and loan transaction systems. American Airlines realized returns on investment of over 500% on their reservation systems (Copeland & McKenney, 1988). Both these companies were technological leaders in their businesses, spending enormous amounts of money on technology that was at best promising at the time the decisions were taken.

Since the effect of information technology, like in the second quadrant, seem to be more to make things possible than to reduce costs, productivity statistics will be misleading. They will be misleading because they measure the wrong things, and because advantage held by investors in information technology is soon competed away. The story of automated teller machines show this: The output per hour in commercial banks grew at only .9% per year from 1973 to 1979, compared to 2.3% per year from 1967 to 1973 (Baily, 1986). This apparent productivity decline is mainly due to a change in what banks do: instead of focusing on increasing the volume of checks processed and loans made (which constituted the basis for measurement by the BLS), banks tried to become more profitable by offering expanded and tailored services, such as ATM's. The investments in new services such as ATMs, and in the people who maintained and expanded them, looked like unnecessary overhead in the productivity statistics. In reality, ATMs have become a requirement for being in the consumer banking market.

The second important effect of information technology has been the ability to vastly expand scale and complexity of operations, since record-keeping is no longer a limit on operations. Without computers to coordinate and keep track of passengers, maintenance and scheduling, New York would probably have had to build one or two new airports to handle the present traffic (Penzias, 1991). Stock Exchanges around the world could not even be close to the transaction volumes they have today without computers. Financial services of the scale and complexity they are today could not have been available. These facts do not show up in productivity statistics, however: the reason being that we have a different world because of computers, but not necessarily a cheaper or more profitable one.

It has been argued that organizations, as a result of reductions in the lower ranks, no longer have the traditional pyramidal shape--instead they are diamond-shaped, with the bulk of the employees in middle management or staff positions (Attewell & Rule, 1984). In terms of the framework, productivity increases in the third quadrant have been eaten up by the fourth: the work on the third quadrant has shifted from doing the transactions to assisting the knowledge workers, mainly by input of more information.

How these effects of information technology translate into business value becomes a function of how well the information is used. May Department stores offers a good example: buying decisions are taken by top management, who knows by Monday morning how every product has sold compared to budget the week before (Pliner & Springer, 1990). This translates to business value because in retailing buying decisions are both extremely important and easy to centralize by computer.

Knowledge worker: a matter of personal learning

The fourth quadrant is where the bulk of the IT investments in the 1980s were done, with PCs and new communication tools as the main investment objects. At the same time, this is an area where each individual has a relatively large say in how and when to use information technology, coupled with huge difficulties in measurement: both specification of what the final product is and determining its quality is often extremely difficult, if not impossible.

There is little question that the ability for knowledge workers to process and communicate information has been vastly expanded because of information technology the last ten years. Portable telephones, fax, personal and portable computers have all meant that information can be sought faster and from a wider range of sources than before. There is considerable doubt, however, about to what extent this has contributed to business value. Strassmann (1990, pp. 117-120) argues that management is the real heavy user of information technology in most industries: "mission critical systems are few and inexpensive as compared with costly management information systems." While a number of successful case stories are available11, the overall picture is that of "staff infection" (Thurow, 1986). Instead of fulfil- ling the demand for information, computers instead create an ever larger demand for data of dubious incremental value.

There are indications that many investments in IT are not economically motivated. Some organizational theorists have argued that organizations make decisions based not on what is economically best, but what is considered good practice at the time (Meyer & Rowan, 1977). From this it can be argued that many IT investments are "me too"-investments, related more to fad, fashion and available funds than crisp economic analysis. One manufacturing firm traced its IT spending over a decade and found that it was closely correlated to what it called "spending appetite"--last years profitability.

Since the use of information technology in many cases is a personal decision for the knowledge worker, the impact on productivity often is, too. Shelby Foote, historian, novelist and noted commentator of the TV serial The Civil War, writes everything with an inkwell pen -- to ensure that every sentence is thought out before it gets on paper and that there is no temptation to change anything once it is down there12. On a smaller scale, this has been called the First Law of Word Processing: "Time saved in using a word processor is spent fiddling with layout and fonts." While word processing and desktop publishing have made many writers more prolific, there are no indication that the quality of what is written is higher. Similarly, since information technology has produced a tremendous increase in the amount of readily available information, more information will be considered--with uncertain implications for decision quality.

It may be argued that a lax attitude to spending and profitability of the technology is necessary in a period of technology introduction: since many of the new technologies cannot provide business value until they are adopted by many users, adoption should be encouraged. The rapid adoption of PCs, for one thing, has had an effect of lacking interoperability13: moving information between different kinds of computer systems has been difficult and laborious. The result is a situation where IT is locally efficient, but a lack of standards and planning results in "people running errands between machines" (Penzias, 1991).

Most executives are not terribly concerned about the productivity of their white-collar workers (Erdmann, 1991), a finding consistent with Lester Thurow's attribution of the sagging white-collar productivity to an incapacity in the American managerial culture. According to Thurow, there can be no productivity gains until American managers shed some of their entrenched attitudes:

These [attitudes] have to do with power (American bosses exist to boss); style (a good boss should know everything and, in principle, have the knowledge to make all decisions); institutions (most middle-level managers get paid based on the number of people who report to them); peer pressure (it is harder to fire those who directly work with you than those at a distance); and beliefs (if the system is based solely upon individual effort, there is no need for group motivation, voluntary cooperation, or teamwork). (Thurow, 1986)
In terms of the framework: IT may provide a beneficiary effect, as illustrated by numerous cases of "successful systems". However, the translation into business value is dubious, because we have not learned how to do this, and because the main problems in doing it is organizational, not a feature of the technology.

IT and movement between quadrants: the loss of measurability

Although it is difficult to determine how much of the movement between quadrants is due to information technology, at least we can say something about changes in content of jobs and who occupies them. The last 100 years has seen a transformation of the economy of the US (as well as all other developed countrires) from agriculture via manufacturing to information services (see exhibit 3). In the 70s and 80s, the main movements in terms of economical importance (rather than in numbers of employees), seem to be Roach found that almost all new jobs created in the seventies and eighties were in the service industries, and of those, most of them were "support" jobs (as opposed to knowledge workers). From 1982 to 1988 the number of "support" jobs has been reduced relative to knowledge workers, from 1.34 information support workers per knowledge worker to 1.2 in 1988 (1988). Although the framework does not exactly fit these definitions, the informating movement towards the knowledge worker quadrant is obvious (although it is unclear to what extent this is due to IT).

The movement from the design to the knowledge worker quadrant is merely a deduction from the fact that a lot more is done on electronic representations of reality than what is done with physical representations of information. The movement from manufacturing to design/diagnosis is due to the quality movement: since products are getting more complex, more knowledge is required by the individual worker.

There are other movements, of course, automation still being a key reason for introducing information technology into tasks. Pure automation of existing tasks, however, is no longer a very attractive alternative for IT introduction: most of what could be automated now is. Although there are many ways to increase the efficiency of these automated solutions, I will hold that it is unlikely to move many tasks over from the fourth to the third quadrant.

Conclusions -- a CIO's strategy of defence

If you don't know where you are going,
computers will take you there faster
and more expensively.
Arno Penzias14

From what we have seen so far, what conclusions should a CIO draw, and what can he or she do about the situation? Possible measurement errors aside, the discrepancies between what IT has promised and what it has delivered so far seems substantial.

The best strategy would probably be to acknowledge that, yes, there is a discrepancy, but that there are good reasons for it. These reasons are:

The CIO should not despair, however--the current debate about productivity can be used to advantage. The situation can be mitigated by This is a time when demand for results are higher than ever before and the potential of information technology still largely untapped. The CIO should be uniquely positioned to take on this challenge.


Exhibit 1: Some characteristics of each quadrant

Quadrant 1 2 3 4
Short name manufacturing design back office knowledge worker
Product Physical Physical Information Information
Process Structured Unstructured Structured Unstructured
Productivity measures quantity, quality of output time in process, quality of design, successful final outcome quantity of tasks performed, accuracy, time in process quality of outcome
Necessary skill level low to medium, fairly specialized high, specialized low to medium, fairly general high, both specialized and general
Compensation level low to medium medium to high low medium to high
Measurability of output high low in the short run medium low
Measurability of activity high low to medium high medium to high
Size and growth (Based on Roach (1988) and Drucker (1991)). substantial but declining small, stable large, stable after high growth substantial, growing
Effect of IT Increasing capacity and flexibility Increasing quality of product Increasing detail capacity and information overview Increasing information availability and communication capacity

Exhibit 2: Information technology investments, by industry

Industry IT %
IT %
IT %
Manufacturing 1.6% 2.8% 10.1% 763.30 77.25

Nonmanufacturing 4.4 6.7 16.2 2810.00 454.07
..Mining 0.1 0.1 0.1 256.80 0.18
..Construction 0.7 0.5 4.3 50.10 2.15
..Transportation 0.5 0.6 1.1 254.34 2.88
....Rail 0.5 0.7 0.5 96.18 0.50
....Nonrail 0.7 0.5 1.5 158.16 2.38
......Air 0.7 0.4 2.3 36.69 0.86
......Trucking 0.5 0.1 0.4 48.20 0.17
......Other 0.8 0.8 1.8 73.27 1.34

..Communications 30.6 40.8 54.4 317.66 172.73
..Public utilities 0.6 1.1 4.4 448.86 19.74
..Total trade 0.9 2.5 12.8 413.48 52.82
....Retail 0.5 1.1 3.8 237.59 9.02
....Wholesale 1.8 4.9 24.9 175.89 43.80

..FIRE 5.7 6.0 20.0 719.78 143.94
....Finance and insurance 3.5 4.7 38.6 234.73 90.51
......Banks 1.9 3.9 34.1 109.15 37.17
......Credit agencies 3.1 3.3 26.5 68.61 18.19
......Securities 3.9 8.3 58.7 6.61 3.88
......Insurance carriers 4.4 7.2 63.8 47.24 30.12
......Insurance agents 15.6 12.0 37.2 3.12 1.16
......Holding companies 8.0 10.2 53.8 16.90 9.10
....Real estate 6.1 6.3 9.5 468.15 44.32

..Services 6.5 8.3 17.1 348.98 59.63
....Hotels 0.1 0.2 2.2 61.34 1.36
....Personal 9.3 13.6 13.8 13.00 1.79
....Business 7.9 10.9 27.9 92.04 25.68
....Auto repair 0.5 0.2 1.7 60.34 1.01
....Miscellaneous repair 0.4 0.5 3.7 7.53 0.28
....Motion pictures 15.0 31.5 47.0 6.32 2.97
....Amusement 9.7 12.3 21.5 21.65 4.65
....Other 12.2 13.3 26.8 81.76 21.89
......Health 16.0 19.2 31.3 52.37 16.39
......Legal 2.9 4.0 18.7 7.06 1.32
......Educational 9.5 12.2 57.8 2.06 1.19
......Other 10.0 6.6 14.7 20.27 2.98
Source: Baily & Gordon (1988)
Exhibit 3: U.S. Work Force Distribution

1880 1920 1955 1975 2000(est.)
Agriculture & extractive 50% 28% 14% 4% 2%
Manufacturing, commerce, industry 36 53 37 29 22
Other services 12 10 20 17 10
Information, knowledge, education 2 9 29 50 66
Source: Boettinger, 1984 


  1. Productivity means output (value, volume) relative to input (labor, capital). In general, productivity is productivity of labor, that is, output per person (or even more precise, output per person/time unit). Productivity of capital is the same as return on investment (ROI) over a given period.
  2. Information technology is not the only potential culprit for the sagging productivity. Some even argue that information technology may well be the one thing keeping productivity up: that the lacking productivity is a result of external factors that counterbalance the productivity gained by use of information technology (Bowen, 1986). These "other things" include increases in government-related paperwork, changes in labor requirements, increasing danger of litigation which necessitate use of more lawyers, and international competition. Lack of competition in the service sector has also been held up as a reason for lacking productivity growth (Julius, 1992). And some economists are quietly beginning to suspect that the whole productivity slump of the 80s is just measurement error.
  3. An alternative definition, could be concrete and abstract: concreteness in the sense that the product is identifiable and directly comparable to others.
  4. Alternative frameworks include the three (by now, four) economic stages: the agrarian, industrial, service and information economy. The problem with this framework is that although the preceding stages do not disappear, their importance in the economy diminishes, and to a certain extent their economic rationale changes (witness the large transfers of resources from public to agricutlutre and traditional manufacturing in developed countries. Strategic planning literature often focus on the role of IT in supporting layers in an organizational hierarchy (e.g. strategic, tactical and operational systems). While more operational from an information technology viewpoint, this framework presupposes a hierarchical organizational structure, traditionally determining which systems are which by which organizational level that uses them. An operational system (such as a POS system) may very well provide a strategic advantage, making this framework less useful.
  5. As noted by Jonscher: a line worker (which is a physical production job) might spend time filling out a time card (which is an information task).
  6. An alternative division, at least for physical products, is where the knowledge of the task resides: in the body (that is, gained through physical training) or in the head (that is, achieved through systematic education) of the person performing it (Zuboff, 1988).
  7. "Hamburger flipping", most often considered a service task, belongs in this quadrant.
  8. In fact, most of the work (in terms of time etc.) may be routine, but the tasks most important to the job is unstructured and requires information processing.
  9. At University of North Carolina Chapel Hill, researchers are using a robotic arm which gives tactile feedback to construct models of molecules. The idea is that the construction of molecules is so complex mathematically that it is easier to model the different forces in a computer, and then have the researcher try to manipulate a model, projected out in the room, and receive feedback on the feasibility of his constructions via how hard it is to put the individual atoms in place.
  10. Zuboff notes how, in the process, the distinction between manager and worker changed: the managers were the ones that previously had the systemic knowledge of how the plant worked. When the workers started gaining systemic knowledge, many managers tried stopping this by imposing standard settings for each machine, even though the workers in many cases managed to increase the output of the factory by experimenting. It could be argued that this example is not "pure": no one asked or expected the workers to start experimenting. Had it been done consciously, it would have represented a "pure" diagonal move, not a movement via the third quadrant. Nothing in the example suggests it could not have been done consciously: as an example of an alternative use of IT it is still valid.
  11. A well known example is the Phillips 66 oil company, which survived a 40% cut in its managerial personnel through use of an Executive Information System (Applegate & Osborn, 1988).
  12. As noted in interview in People, October 15, 1990, pp. 60-62.
  13. Interoperability: the extent to which information systems can exchange data directly. A good example of interoperability are word processors like Word Perfect and Microsoft Word: these programs are available on a number of different kinds of computers, but they can exchange files directly.
  14. From Keynote Address at the International Conference on Information Systems, New York, December 17, 1992. Arno Penzias is VP of Research at AT&T Bell Laboratories, and a Nobel Laureate.
  15. An example: An electronic mail system at an educational institution was used a lot, partly because top management endorsed it and demanded that communication to them should go through the system. The frequency of use went up dramatically, and the system became a communication backbone in the organization. As seen from the point of measurement: frequency of use went up because top management was involved, and since the use of the system by many people made it more valuable to all of them, this was effective.



    On the other hand, when the users of the IBM 438L expert system used by the Strategic Air Command in the 1960s turned out not to be used, top managment solved this by ordering personnel on duty to ask at least two questions of the system on each shift. The number of questions asked consequently rose to twice the number of officers on duty (Earnest, 1990). In this case, frequency of use went up because of top management involvement, making the system seem more successful.


Copyright © 1992 Espen Andersen.
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