The concepts of forecasting and prediction are geared towards future occurrences. Though this similarity in orientation or focus, both concepts has a thin line of differentiation that through could be blurred by contextual usage still shows the existence of a difference between these two concepts. By definition the process of forecasting entails gathering requirements and making a future-state related prediction. Forecasting is data driven and leverages the available data comprising of current and previous data points in predicting the outcome of future event occurrences. In other words, the processes and procedures involved in determining what the future market trends, sales revenue, new product adoption, etc., and the impact vis-à-vis the organizational impact. To greater extent forecasting is classifiable as a sub-discipline of prediction as it generally focused on leveraging time series approaches in prediction making (Döring, 2018).
Prediction has the objective of attempting to provide an explanation for the possibilities surrounding a future or predetermined event outcome. Prediction also employs statistical techniques which entails making an estimation of an outcome for unseen data after training and fitting a model to a train dataset and then getting a prediction coefficient f(a) which is then applied in the making of predictions in a new or unseen dataset. It is important to mention that multiple combinations of forecasting could be applied in identifying and predicting the likelihood or probability of takeover targets at an early stage thereby providing investors with information that guiding their investment interest into potential target firms (Rodrigues & Stevenson, 2013). Companies and governments use predictions determined by experts to guide through uncertain projects despite their uncertainty. They are highly risky and the actual results may deviate from predictions made. A prediction is a definitive and specific statement about when and where an occurrence is expected, whereas a forecast is a probabilistic statement, usually over a longer time scale: that describes the chances of an occurrence occurring (Döring, 2018; Rodrigues & Stevenson, 2013).
The identified infamous prediction become a reality is the 1909 prediction by Nikola Tesla regarding smartphone wireless devices. He envisioned, there would be an application of wireless technology in some sort of an IoT environment whereby communications would be both audio and visual whereby individuals will be able to see each other face to face as though, they were in the same location distance notwithstanding; furthermore he stated the devices would be very portable such that they could be carried in the pocket. He described using words for such as audio as telephony and visual as television which is an outstanding prediction of the portable wireless smartphones we have today making communication seamless and a unique experience. (Tesla, 2018).
The two forces impacted the success of this innovation, was technological advancement and sociological advancement. Technological advancement is also a major force impacting the success at the time. The technology was not very much advanced to deliver such an innovative technological breakthrough at the time, because of lack of advanced tools, skillsets and frameworks to facilitate development. It is expedient to mention that this limitations only gave way in recent years and thus research teams in phone manufacturing companies could design and build such portable operating systems into such devices and making the audio visual portable smartphone communication devices a reality. Sociological advancement because the society was not very much advanced, considering the fact that technological innovations have always been an integral part of the society that is the primary consumer of such innovations and innovative ideas that set the trail. Thus, acceptance of such ideas by society from which there are researchers, technology enthusiast, technology institutions, could be a major driving force towards bringing such predictions to the limelight and making them a reality. Company’s often tries to manufacture goods or provide services meeting consumer needs and that puts social influence as a major moderating factor for innovative technological ideas consumption which in this case at the time society (Kulviwat et al., 2009). This attests to the fact that there is a relationship existing between adoption of a technology and social influence especially for a publicly consumed innovation (Kulviwat et al., 2009).
References
Döring, M. (2018). Prediction vs Forecasting. Data Science Blog. Retrieved from https://www.datascienceblog.net/post/machine-learning/forecasting_vs_prediction/
Kulviwat, S., Bruner, G. C., Al-Shuridah, Obaid. (2009). The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2007.04.014
Rodrigues, B. D., & Stevenson, M. J. (2013). Takeover prediction using forecast combinations. International Journal of Forecasting, 29(4), 628-641.
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