Predictive Analytics – Which Side Outweighs?

Introduction to predictive analytics

Going deeper into the topic of predictive analytics and trying to find more opinions and angles on the matter, I started the research where I left off last week, with the negative side to data mining…

Critical Approach to Predictive Analytics

Eric Siegel informs us that predictive analytics can be very sensitive when they are made about private matters of a customer’s or employee’s data and can even stand in conflict with civil liberties, as illustrated in this interview . It is no surprise that complaints about invasion of privacy and civil liberties become louder, while predictive analytics is a booming practice taking hold across many industries. Computers predicting our most likely behavior, determining if a person should stay in prison or valuating which employee is most likely to quit his/ her job. To support this statement, we can see in another article that unconventional use of predictive analytics and big data is a very frequent matter and is being used on a large scale, which makes peoples personal, business and online lives a part of business platforms. Interesting and informative blogs on predictive analytics and data mining by Will Dwinnell, which examine the matter critically, can be found here. Inevitably, during my research, I stumble back to the positive side of predictive analytics, which leads me to…

How Important is Big Data?

We evaluate another side of predictive analytics, where positive outcomes may be that police patrols are becoming more effective, as well as the reduction of fraud or improvement of health care. Businesses have to survive in a very competitive market and data mining helps to improve decision making and the efficiency of a firm. It may help with the launching of a global product in record time, not by building a new factory, but by building a social network, or the American presidential campaign not relying on opinion polling but on predictions. For government entities, companies, agencies or non-profit organizations, data will be the basis of competitive advantage. Virginia Rometty, of IBM, states that “data will be the next natural resource” and that it goes along with three principles, which are “1. Change how you make decisions, 2. Change how you in fact create value and 3. Change how you deliver value”. Going from link to link, researching, I come to…

The Technical Side

Yan Krupnik emphasizes that predictive analytics should be built specifically to every business, to consider all its influencing factors and how they relate and affect each other. This would give the most accurate prediction results possible.

Leading me to a more technical approach on data mining, it is of a great importance that the creators of predictive models, data scientists and the final users keep in mind, what they are analyzing and what to do with the valuations. It is of interest to all of the parties that an understanding of the decisions, which are intended to be changed or improved, stays in the focus as well as what the model is being used for in the end. In reality there are so many variables to consider, how can they all be calculated in one model?!



Reading more and more about this topic, I can see that data mining leads to a huge amount of important information, often on private individuals, and has to be treated as such.
The further my research goes, the more I find information and opinions about the negative side of predictive analytics and data mining, but equally a lot about the positive side. It is stressed by the necessity which data mining has in our modern society, where predicting human behavior provides an advantage in every field it is used. Coming to a final conclusion on which side outweighs the other, positive or negative, seems still impossible to me, even after reading and researching so much about it. I lean towards being in favor of data mining because no real harm is caused by predictive analytics but a lot can be prevented. Still, I cannot really answer my final question and end this post openly…

Which Side Do You Think Outweighs?


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