Melody Jacob

Technology Foresight is a combination of creative thinking, expert views, and alternative scenarios to make a contribution to strategic planning. Technological Forecasting (TF) is concerned with the investigation of new trends, radically new technologies, and new forces that could arise from the interplay of factors such as new public concerns, national policies, and scientific discoveries. Many of these forces are beyond the control, influence, and knowledge of individual companies. 

The development of a technology forecast can be divided into three separate actions:

• Framing the problem and defining the desired outcome of the forecast,

• Gathering and analyzing the data using a variety of methodologies, and

• Interpreting the results and assembling the forecast from the available information.

Technology forecasting has existed in one form or another for more than a century, but it was not until after World War II (WWII) that it began to evolve as a structured discipline. The motivation for this evolution was the U.S. government’s desire to identify technology areas that would have significant military importance.

Theories of technological forecasting

Neoclassical theories Technological change takes place in the form of shifts of the production function towards the origin.

Marxist theory

Karl marl perceived technology as not self-generating, but as a process directed by willful. Conscious, active people and moulded by useful forces. He held that technology changes the development of the productive forces which was the prime mover of history.

Schumpeter’s theory

Schumpeter's theory of development assigns a paramount role to the entrepreneur and innovations introduced by him in the process of economic development. According to Schumpeter, the process of production is marked by a combination of material and immaterial productive forces. The Schumpeterian production function can, therefore, be written as –

Q = ƒ [k, r, I, u, ν) …(1)

Where Q stands for the output, k for the Schumpeterian concept of “produced means of production”, r for natural resources, l for the employed labor force.

Evolutionary theory

This suggests a biological analogy to explain technological change. The Darwinian two-state process of mutation (invention) and selection (innovation) has been employed to understand the evolution of technology.

Market pull theory

Market Pull', refers to the need/requirement for a new product or a solution to a problem, which comes from the market place. The need is identified by potential customers or market research. A product or a range of products are developed, to solve the original need.

Technology push theory

Technology is defined as an autonomous or quasi-autonomous factor. It assumes a one-way casual determination approach ie from science to the economy.

Methods of technological forecasting

Commonly adopted methods of technology forecasting include the 

• Delphi method : 

The Delphi technique is used where a consensus of expert opinion is required on the timing, probability, and identification of future technological goals or consumer needs and the factors likely to affect their achievement. It is best used in making long-term forecasts and revealing how new technologies and other factors could trigger discontinuities in technological trajectories. The choice of experts and the identification of their level and area of expertise are important; the structuring of the questions is even more important. Experts in non-technological fields can be included to ensure that trends in economic, social, and environmental fields are not overlooked.

• Exploratory technique: The formal forecasting techniques are standard components that are described in many textbooks on forecasting techniques (see specific techniques). Specific techniques for forecasting fall into two main categories, exploratory and normative. Information about each technique is available in various references.

Exploratory techniques are primarily concerned with the analysis of historical data. Selected attributes such as functional performance, technical parameters, economic performance, etc. are plotted against time. Since it is usually assumed that progress is evolutionary and that technological progress is not random, it is possible to generate characteristic curves or patterns from the data, and from these patterns, forecasts can be made with varying degrees of certainty. However, changes do occur and the influence and impact of new or surprising factors must not be disregarded. Examples of relevant exploratory techniques are:

                          S-curves

                              cycles

                            trend extrapolation

                            technology substitution

— all of which rely on a large amount of statistical data, which may or may not be available freely.