For the past decade, economists and information technology specialists have argued back and forth whether IT investments have generated return on investments and increased national output of goods and services. Businesses, fueled by high expectations on productivity growth generated by IT investments, heavily invested into computing power between the mid 1980s and the 1990s. It was generally accepted that IT spending would prove to be a valuable investments and would pay for itself in the long run. Growth and high return on investment were expected. A few years later, managers and business leaders were beginning to question the gains in productivity, which at best seemed to be in a state of status quo (Brynjolfsson, 1993). Though a few success stories were recorded and praised, for most, information technology became a source of frustration and disillusion. The notion of the productivity paradox emerged. Companies, learning from the wasted billions in questionable IT investments, had to reinvent the way they did business to integrate their IT investments into their strategic planning. Today IT resources are specialized, tailored and customized to the needs of the company, and optimized to maximize companies' efficiency and output level. This transition has been slow, lengthy, and painfully costly.
This paper presents an analysis of the evolution of the philosophy of investments in IT projects--by both pubic as well as private sector companies. The paper discusses the empirical evidence--both at macro and micro levels--that led to questioning of the contribution of IT investments to productivity gains and other measurable returns such as ROI (return on investment), an analysis of three major examples of high profile failed IT projects, and four periods of evolution of IT investments starting from the time of euphoria when no one questioned IT investments to the current (fourth) period of the total (IT) integration management.
Questioning the Return on IT Investments
In recent years computers have revolutionized the way companies do business with customers and other businesses; yet business data and other productivity statistics do not reflect any added growth. To solve this mystery, academic economists and scholars began collecting macroeconomic data.
The focus of the research mainly concerned many factors and labor productivity statistics. Economists discovered that both indices and the GDP dropped after 1973 when the first mainframe was introduced in the business world (Hubbard, 2003). In the late 1990s, the threatening Y2K bug forced companies to invest even more in IT resources to prevent a massive loss of data that many IT specialists predicted. Nothing happened and companies had more technology than needed and productivity growth was not seen.
Many have written books and articles explaining this paradox. A great deal of time was also spent on detailing how to measure productivity. Economists just could not assess whether technology contributed to growth or negatively affected it. Productivity and GDP were still growing but at a much slower pace. Many argued that most analysts measured macro data when computer contribution can only be noticed on a micro level (Devaraj & Kohli, 2002). Finally, the argued theories of the old economy and the new economy did not answer the problem or explain the paradox.
Researchers came to the conclusion that this paradox exists due to seven factors that mask proper measurements and analysis. These factors are: (1) IT investments only represent a small share of GDP. (2) Computers have a rapid rate of depreciation and obsolescence. (3) Old measurements do not apply in the new economy. (4) Poor analogy exists between the service sector (where productivity slowed down the most) and its heavy reliance on computers. (5) Computers have provided many intangible benefits. (6) A time lag exists between technology arrival and productivity benefits. …