Applied Forecasting in the Technology Industry
“The distinction between past, present, and future is only a stubbornly persistent illusion”
Albert Einstein
Today forecasting is a major part of any decision-making process across all industries. However, the process of crossing the divide between the forecasted figures and the strategic decision that follows is one that is still a gray area.
This article focuses on impact of forecasting and the subsequent effect on decision making in the technology industry. To be able to understand this conundrum a little better we need to have an overview of the process of forecasting and strategic decision making.
Forecasting in the technological industry deals with the assessment of a new product’s potential as compared to its alternatives. Forecasting, however, is not the art of prediction. Paul Saffo, a technology forecaster based in the Silicon Valley, put it so elegantly in a Harvard Business Review article, “the primary goal of forecasting is to identify the full range of possibilities, not a limited set of illusory certainties.”
There are several instances of failures in forecasting in the technological industry. Apart from some notable instances of success like Moore’s Law, there have been other instances of failures in the technological forecasting and decision making. Chairman Lewis Strauss of the U.S. Atomic Energy Commission told the National Association of Science writers that their children would enjoy “electrical energy too cheap to meter” while IBM waited for seven years before deciding to compete with Digital Computer over minicomputers. Even Microsoft was delayed in making use of the opportunity provided by the Internet.
However, it is a tricky to predict the “next big thing.” Marketing has it exactly right here: The Customer is the King. Many analysts come up with forecasts and predictions only to find that the customers are not interested in the product’s benefit profile and the “innovation” ends up being a damp squib.
Technological forecasting and subsequent strategic decisions, therefore, are fraught with pitfalls. Some of the most common mistakes include a lack of in depth research into the market to determine product reception and competition, objective estimates of costs and future changes in the financial models and other external factors (such as the current market scenario and the introduction of other products before or after the introduction of target product which may affect it adversely or support its marketability).
The Delphi method is possibly the most well known technological forecasting tool used. The word “Delphi” is derived from the name of the hallowed ground in ancient Greece where prophecies were said to have been made. The current Delphi prediction method is quite the opposite. It consists of a panel of experts utilizing a structured process for filtering knowledge by means of questionnaires and providing feedback. Technology forecasting studies eventually led to the Delphi method in 1944. The Delphi method acknowledges the fact that a single person may be swayed by his biases or opinions but there is lesser chance of that in a panel where discussion and feedback are based on logic and thoughtful exchanges.
Sometimes the greatest unpredictability of the forecasting models lay in the uncertainty of consumer reactions. A product marketed with a narrow purpose may turn out to be of broad spectrum utility to a wide range of consumers and prove to be a success in the marketplace.
From a marketing perspective, keeping an eye on the customer’s preferences and constantly monitoring any shift in market sentiments is important. Forecasting is based on historical data to a great extent and past market movements and present market sentiments are highly valuable inputs for the process of forecasting. Knowing that there was an opportunity for niche marketing for music players, Apple was able to market its IPods successfully and create a product that was successful beyond imagination.
From an accounting or finance perspective, tools like ROI, ROE, cost-benefit analysis are some of the ways one can use to calculate and substantiate the possible scenarios. But at the end of this process, many people tend to use the figures as a means to their ends or as a justification for their intuitive opinions.
The important fact to remember is that forecasting from any perspective is not a method of confirmation of beliefs or opinions, rather it is the revelation of the possibilities of situations in the future.
In conclusion, forecasting is still a science in its infancy with a great deal of potential to help us prepare for the future in the technological industry and there is a long way to go before we achieve the full potential benefit of forecasting.