Thursday, 27 November 2014

Productivity paradox

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The productivity paradox was analyzed and popularized in a widely cited article[1] by Erik Brynjolfsson, which noted the apparent contradiction between the remarkable advances in computer power and the relatively slow growth of productivity at the level of the whole economy, individual firms and many specific applications. The concept is sometimes referred to as the Solow computer paradox in reference to Robert Solow's 1987 quip, "You can see the computer age everywhere but in the productivity statistics."[2] The paradox has been defined as the “discrepancy between measures of investment in information technology and measures of output at the national level.”[3]
It was widely believed that office automation was boosting labor productivity (or total factor productivity). However, the growth accounts didn't seem to confirm the idea. From the early 1970s to the early 1990s there was a massive slow-down in growth as the machines were becoming ubiquitous. (Other variables in countries' economies were changing simultaneously; growth accounting separates out the improvement in production output using the same capital and labour resources as input by calculating growth in total factor productivity, AKA the "Solow residual".)
The productivity paradox has attracted a lot of attention because technology seems no longer to be able to create the kind of productivity gains that occurred until the early 1970s. Some, such as economist Robert J. Gordon, are now arguing that technology in general is subject to diminishing returns in its ability to increase economic growth.[4][5]


Different authors have explained the paradox in different ways. In his original article, Brynjolfsson (1993) identified five possible explanations:
  • Mismeasurement: the gains are real, but our current measures miss them;
  • Redistribution: there are private gains, but they come at the expense of other firms and individuals, leaving little net gain;
  • Time lags: the gains take a long time to show up; and
  • Mismanagement: there are no gains because of the unusual difficulties in managing IT or information itself.
  • Feedback effects: Lower labor requirements lead to fewer customers, negating any economies of scale achievable with computers.
He stressed the first explanation, noting weaknesses with then-existing studies and measurement methods, and pointing out that "a shortfall of evidence is not evidence of a shortfall."
Turban, et al. (2008), mention that understanding the paradox requires an understanding of the concept of productivity. Pinsonneault et al. (1998) state that for untangling the paradox an “understanding of how IT usage is related to the nature of managerial work and the context in which it is deployed” is required.
One hypothesis to explain the productivity paradox is that computers are productive, yet their productive gains are realized only after a lag period, during which complementary capital investments must be developed to allow for the use of computers to their full potential.[6]
Diminishing marginal returns from computers, the opposite of the time lag hypothesis, is that computers, in the form of mainframes, were used in the most productive areas, like high volume transactions of banking, accounting and airline reservations, over two decades before personal computers. Also, computers replaced a sophisticated system of data processing that used unit record equipment. Therefore the important productivity opportunities were exhausted before computers were everywhere. We were looking at the wrong time period.
Another hypothesis states that computers are simply not very productivity enhancing because they require time, a scarce complementary human input.[citation needed] This theory holds that although computers perform a variety of tasks, these tasks are not done in any particularly new or efficient manner, but rather they are only done faster. Current data does not confirm the validity of either hypothesis. It could very well be that increases in productivity due to computers are not captured in GDP measures, but rather in quality changes and new products.
Economists have done research in the productivity issue and concluded that there are three possible explanations for the paradox. The explanations can be divided in three categories:
  • Data and analytical problems hide "productivity-revenues". The ratios for input and output are sometimes difficult to measure, especially in the service sector.
  • Revenues gained by a company through productivity will be hard to notice because there might be losses in other divisions/departments of the company. So it is again hard to measure the profits made only through investments in productivity.
  • There is complexity in designing, administering and maintaining IT systems. IT projects, especially software development, are notorious for cost overruns and schedule delays. Adding to cost are rapid obsolescence of equipment and software, incompatible software and network platforms and issues with security such as data theft and viruses. This causes constant spending for replacement. One time changes also occur, such as the Year 2000 problem and the changeover from Novell NetWare by many companies.
Other economists have made a more controversial charge against the utility of computers: that they pale into insignificance as a source of productivity advantage when compared to the industrial revolution, electrification, infrastructures (canals and waterways, railroads, highway system), Fordist mass production and the replacement of human and animal power with machines. [7] High productivity growth occurred from last decades of the 19th century until the 1973, with a peak from 1929 to 1973, then declined to levels of the early 19th century. [8][9] There was a rebound in productivity after 2000. Much of the productivity from 1985 to 2000 came in the computer and related industries.[9]
A number of explanations of this have been advanced, including:
  • The tendency – at least initially – of computer technology to be used for applications that have little impact on overall productivity, e.g. word processing.
  • Inefficiencies arising from running manual paper-based and computer-based processes in parallel, requiring two separate sets of activities and human effort to mediate between them – usually considered a technology alignment problem
  • Poor user interfaces that confuse users, prevent or slow access to time-saving facilities, are internally inconsistent both with each other and with terms used in work processes – a concern addressed in part by enterprise taxonomy
  • Extremely poor hardware and related boot image control standards that forced users into endless "fixes" as operating systems and applications clashed – addressed in part by single board computers and simpler more automated re-install procedures, and the rise of software specifically to solve this problem, e.g. Norton Ghost
  • Technology-driven change driven by companies such as Microsoft which profit directly from more rapid "upgrades"
  • An emphasis on presentation technology and even persuasion technology such as PowerPoint, at the direct expense of core business processes and learning – addressed in some companies including IBM and Sun Microsystems by creating a PowerPoint-Free Zone[citation needed]
  • The blind assumption that introducing new technology must be good
  • The fact that computers handle office functions that, in most cases, are not related to the actual production of goods and services.
  • Factories were automated decades before computers. Adding computer control to existing factories resulted in only slight productivity gains in most cases.
A paper by Triplett (1999) reviews Solow’s paradox from seven other often given explanations. They are:
  • You don’t see computers “everywhere,” in a meaningful economic sense
  • You only think you see computers everywhere
  • You may not see computers everywhere, but in the industrial sectors where you most see them, output is poorly measured
  • Whether or not you see computer everywhere, some of what they do is not counted in economic statistics
  • You don’t see computers in the productivity yet, but wait a bit and you will
  • You see computers everywhere but in the productivity statistics because computers are not as productive as you think
  • There is no paradox: some economists are counting innovations and new products on an arithmetic scale when they should count on a logarithmic scale.

Effects of economic sector share changes[edit]

Gordon J. Bjork points out that manufacturing productivity gains continued, although at a decreasing rate than in decades past; however, the cost reductions in manufacturing shrank the sector size. The services and government sectors, where productivity growth is very low, gained in share, dragging down the overall productivity number. Because government services are priced at cost with no value added, government productivity growth is near zero as an artifact of the way in which it is measured. Bjork also points out that manufacturing uses more capital per unit of output than government or services.[10]

Miscellaneous causes[edit]

Before computers: Data processing with unit record equipment[edit]

Main articles: Unit record equipment and Plugboard
Early IBM tabulating machine. Common applications were accounts receivable, payroll and billing.
Control panel for an IBM 402 Accounting Machine
When computers for general business applications appeared in the 1950s, a sophisticated industry for data processing existed in the form of unit record equipment. These systems processed data on punched cards by running the cards through tabulating machines, the holes in the cards allowing electrical contact to activate relays and solenoids to keep a count. The flow of punched cards could be arranged in various program-like sequences to allow sophisticated data processing. Some unit record equipment was programmable by wiring a plug board, with the plug boards being removable allowing for quick replacement with another pre-wired program.[11]
In 1949 vacuum tube calculators were added to unit record equipment. In 1955 the first completely transistorized calculator with magnetic cores for dynamic memory, the IBM 608, was introduced.[11]
The first computers were an improvement over unit record equipment, but not by a great amount. This was partly due to low level software used, low performance capability and failure of vacuum tubes and other components. Also, the data input to early computers used punched cards. Most of these hardware and software shortcomings were solved by the late 1960s, but punched cards did not become fully displaced until the 1980s.

Analog process control[edit]

Computers did not revolutionize manufacturing because automation, in the form of control systems, had already been in existence for decades, although computers did allow more sophisticated control, which led to improved product quality and process optimization. Pre-computer control was known as analog control and computerized control is called digital.

Parasitic losses of cashless transactions[edit]

Credit card transactions now represent a large percentage of low value transactions on which credit card companies charge merchants. Most of such credit card transactions are more of a habit than an actual need for credit and to the extent that such purchases represent convenience or lack of planning to carry cash on the part of consumers, these transactions add a layer of unnecessary expense. However, debit or check card transactions are cheaper than processing paper checks.

Online commerce[edit]

Despite high expectations for online retail sales, individual item and small quantity handling and transportation costs may offset the savings of not having to maintain "bricks and mortar" stores.[citation needed] Online retail sales has proven successful in specialty items, collectibles and higher priced goods. Some airline and hotel retailers and aggregators have also witnessed great success.
Online commerce has been extremely successful in banking, airline, hotel, and rental car reservations, to name a few.

Restructured office[edit]

The personal computer restructured the office by reducing the secretarial and clerical staffs. Prior to computers, secretaries transcribed Dictaphone recordings or live speech into shorthand, and typed the information, typically a memo or letter. All filing was done with paper copies.
A new position in the office staff was the information technologist, or department. With networking came information overload in the form of e-mail, with some office workers receiving several hundred each day, most of which are not necessary information for the recipient.
Some hold that one of the main productivity boosts from information technology is still to come: large-scale reductions in traditional offices as home offices become widespread, but this requires large and major changes in work culture and remains to be proven.

Cost overruns of software projects[edit]

It is well known by software developers that projects typically run over budget and finish behind schedule.
Software development is typically for new applications that are unique. The project's analyst is responsible for interviewing the stakeholders, individually and in group meetings, to gather the requirements and incorporate them into a logical format for review by the stakeholders and developers. This sequence is repeated in successive iterations, with partially completed screens available for review in the latter stages.
Unfortunately, stakeholders often have a vague idea of what the functionality should be, and tend to add a lot of unnecessary features, resulting in schedule delays and cost overruns.


By the late 1990s there were some signs that productivity in the workplace been improved by the introduction of IT, especially in the United States. In fact, Erik Brynjolfsson and his colleagues found a significant positive relationship between IT investments and productivity, at least when these investments were made to complement organizational changes.[12][13][14] A large share of the productivity gains outside the IT-equipment industry itself have been in retail, wholesale and finance.[15] A major advance was computerized stock market transaction processing, which replaced the system that had been in place since the Civil War but by the last half of 1968 caused the U. S. stock market to close most Wednesday afternoons processing.[16]
Computers revolutionized accounting, billing, record keeping and many other office functions; however, early computers used punched cards for data and programming input. Until the 1980s it was common to receive monthly utility bills printed on a punched card that was returned with the customer’s payment.
In 1973 IBM introduced point of sale (POS) terminals in which electronic cash registers were networked to the store mainframe computer. By the 1980s bar code readers were added. These technologies automated inventory management. Wal-Mart Stores was an early adopter of POS.
Computers also greatly increased productivity of the communications sector, especially in areas like the elimination of telephone operators. In engineering, computers replaced manual drafting with CAD and software was developed for calculations used in electronic circuits, stress analysis, heat and material balances, etc.
Automated teller machines (ATMs) became popular in recent decades and self checkout at retailers appeared in the 1990s.
The Airline Reservations System and banking are areas where computers are practically essential. Modern military systems also rely on computers.

See also[edit]


  1. Jump up ^ Brynjolfsson, Erik (1993). "The productivity paradox of information technology". Communications of the ACM 36 (12): 66–77. doi:10.1145/163298.163309. ISSN 0001-0782. 
  2. Jump up ^ Robert Solow, "We'd better watch out", New York Times Book Review, July 12, 1987, page 36. See here.
  3. Jump up ^ Wetherbe, James C.; Turban, Efraim; Leidner, Dorothy E.; McLean, Ephraim R. (2007). Information Technology for Management: Transforming Organizations in the Digital Economy (6th ed.). New York: Wiley. ISBN 0-471-78712-4. 
  4. Jump up ^ Gordon, Robert J. (2000). "Interpreting the "One Big Wave" in U.S. Long Term Productivity Growth , National Bureau of Economic Research Working paper 7752". 
  5. Jump up ^ Gordon, Robert J. (2012). "Is U.S. Economic Growth Over? Faltering innovation confronts the six headwinds". Center for Economic Policy Research (Policy Insight No. 63). 
  6. Jump up ^ David P.A., "The Dynamo and the Computer: A Historical Perspective on the Modern Productivity Paradox", American Economic Review Papers and Proceedings, 1990, 355–61
  7. Jump up ^ Gordon, Robert J. (2000). "Does the "New Economy" Measure up to the Great Inventions of the Past? , NBER Working Paper No. 7833". 
  8. Jump up ^ Kendrick, John (1991). "U.S. productivity performance in perspective , Business Economics, October 1, 1991". 
  9. ^ Jump up to: a b Field, Alexander J (2007). "U.S. economic growth in the gilded age 31, Journal of Macroeconomics (2009) 173-190". 
  10. Jump up ^ Bjork, Gordon J. (1999). The Way It Worked and Why It Won’t: Structural Change and the Slowdown of U.S. Economic Growth. Westport, CT; London: Praeger. ISBN 0-275-96532-5. 
  11. ^ Jump up to: a b Fierheller, George A. (2006). Do not fold, spindle or mutilate: the "hole" story of punched cards. Stewart Pub. ISBN 1-894183-86-X. 
  12. Jump up ^ E.Brynjolfsson and L.Hitt, "Beyond the Productivity Paradox: Computers are the Catalyst for Bigger Changes", CACM, August 1998
  13. Jump up ^ E. Brynjolfsson, S. Yang, “The Intangible Costs and Benefits of Computer Investments: Evidence from the Financial Markets,” MIT Sloan School of Management, December 1999
  14. Jump up ^ Paolo Magrassi, A.Panarella, B.Hayward, “The 'IT and Economy' Discussion: A Review”, GartnerGroup, Stamford (CT), USA, June 2002 [1]
  15. Jump up ^ Stiroh, Kevin (2002). "Information Technology and the US Productivity Revival: What Do the Industry Data Say?". American Economic Review 92 (5): 1559–1576. doi:10.1257/000282802762024638. JSTOR 3083263. 
  16. Jump up ^ Field, Alexander J. (2011). A Great Leap Forward: 1930s Depression and U.S. Economic Growth. New Haven, London: Yale University Press. p. 67. ISBN 978-0-300-15109-1. 

Further reading[edit]

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