Predictive Analytics Today

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An example of one of the ways that the world is very different is the health of the stock market as a reflective device about the wealth of the nation. While the stock market has been showing better numbers in recent months, the nation, on the whole, is not thriving at the same level with unemployment still high. As well, the level of CEO salaries is over 300% that of the average worker. It used to be that the level of salary of a CEO reflected the health of the salaries of the employees. In 1980 the ratio between the CEO and the worker was 42-1 (Carroll amp. Buchholtz, 2010. What this reflects is the continuing disparity of wealth in the United States. And while this existed in 2007, the economic downturn of 2008 established the destruction of the Middle class, creating a whole new way in which consumer predictions needed to be approached. The cost of living has gone up and working class people and the remnants of the middle class have very little disposable income. Davenport, Harris, and Morison (2010) discuss some of the reasons to not use analytics. One of these reasons is when history misleads the results of the analytics. Because of the changes that have occurred in the last six years, the historical interconnections of different indicators are not necessarily still meaningful. The example of the stock market and how it no longer indicates overall wealth is an example of how predictors can now be misleading for the future from today. Willis (2011) writes that in the last century the stock market has always been an indicator of overall wealth, but since the economic downturn that has changed. This example shows how a number of factors have changed in the new economy and in order to create a predictive analysis, these factors must be taken into consideration. What has not changed, however, is the power of distinction. People are still finding ways to buy items and distinction has created enough power for many companies to thrive in this stifled economy. One example of this is the iPad which launched in 2009 and sold over 25 million of the units in a few short years. The distinction has created the market for the iPad and its competitors have not come near to duplicating that success (Bell, 2011). It is the one that comes out first that will get the attention and this is how a distinction is still a powerful factor. This can also be seen in the iPhone which has decent competitors, but all one has to do is watch the commercials to see that the competition is doing its best to diminish the cult status of the Apple phones. Through trying to insinuate that they are at the end of their life-cycle competitors like Galaxy and Microsoft are using a thin stick to strike a mighty mountain. In order to gain the power of predictive analytics, then, it is important to recognize what has changed in the last six years but to realize that the most important part of the business has not changed. When a new idea is good and has a great deal of consumer value the idea will succeed. Demand can be predicted through distinction, but where there is no distinction and an idea is being recycled or improved upon, the predictive analytics will have to take into consideration the real status.Standard Chartered Bank uses analytics in order to create success by engaging the direct needs of their customers.