People’s taste changes over time, as a result of such factors as past consumption, social influence, and changes in the environment. Decision making often requires a person to predict and take account of future changes in tastes; therefore, past knowledge and experience play a pivotal role in the outcome. This paper takes a critical analysis of prediction, actual results and factors that influence future outcomes. Most of the times, positive results are expected in prediction, but sometimes negative results are generated as past experience and knowledge doesn’t play any significant factor. There is a reason why people confidently make assertions about the future because they always believe in a better future. The perception of the people about the future lead to decision-making biases. These biases are either classified as anchoring or confirmation bias. According to the anchoring bias theory, people tend to rely on initial information gained rather than subsequent information that affirms their decisions. This type of bias can probably lead individuals to feel overconfident in their judgment especially when making decisions. However, the random error theory stipulates that when people make a prediction, it gives them a sense of control over their control, therefore, people like to predict the future because they do not feel safe with uncertainty.

Prediction is also based on availability bias, which applies to these predictions because they might have projected a decision based on information that is readily available. Despite the fact that their decision may have a high probability of occurrence at first, they should have also sought alternatives and develop it in order to maximize the accuracy of their prediction. We can also apply the theory of escalation of commitment, in prediction. This refers to sticking with one decision even though there is negative information about the decision. Predictions should have approached the decision from a different prospective as possible and considered if the decision is reasonable and balanced. Moreover, they may have overestimated or underestimated their performance when they made decisions, thereby leading them to end up with a wrong decision.

A good example of prediction; When a new restaurant was opened near my house, I went there with a couple of my friends, though the customer service of the place was quite good, food quality was below my expectation. I was certain that this place would not be able to attract many customers in the future, with a view that other people would feel exactly the same way as I did. However, every day I passed by the restaurant on my way home, it turned out that there was always a long queue of people being served, and among them were my friends too. Looking back on it, I realized that my selective perception of the restaurant made I selectively interpret the place as I wanted to think of it.

In my prediction, I had viewed the restaurant to be out of business in the long run but the prediction generated the negative outcome. It is sometimes very hard to make positive predictions because the consequences can change drastically depending on various factors. Thus, there is a tendency that we would rely on biased speculation that often lead us to make the inaccurate prediction. One may predict the expected outcome of a certain future, but it can turn out to be incorrect, for instance in weather, in this scenario the future event cannot be absolutely sure of whether or not it will happen. In conclusion even though, one has past knowledge and experience in prediction, many factors play a role which subsequently results in generation of either positive or negative outcome.


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