Reference no: EM132434798

The Risks of misscategorization

In discussing risk management and analytics, you should recognize that there is risk inherent simply in the conducting of analytics - especially predictive analytics. What if our predictions are false? What if the data upon which the predictions are based is incomplete or inherently flawed in some way? The purpose of this week's discussion is to analyze the risks associated with categorical predictive analytics.

Research an instance where categorical prediction has been used by a business or governmental organization. Simply typing "categorical prediction" into Google news will reveal a number of news articles relating to this topic.

Make sure you identify the risks that your article addresses into one of the four quadrants of a risk matrix: High Probability/High Impact; High Probability/Low Impact; Low Probability/High Impact; Low Probability/Low Impact. Justify your classification with information from your article. Then, discuss the potential problems that could (or did) arise if the predictive activities discussed in your chosen article yielded bad results. What could (or did) happen as a result of erroneous or unreliable categorization through predictive modeling?