Information Management

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A week ago, I posted a blog in which I expressed some of the fears that come with the rise of big data. Now it’s not all threatening. In fact, I might have exaggerated slightly at the time of writing, in order to make my point clear. Of course, there are a lot of positive sides to Big Data, which create tremendous value for businesses and consumers alike. I will now highlight some of these advantages, and thereby provide a counter-view to my previous post.

These are only a few of the advantages of Big Data. The list of possibilities is simply too large to write down.

The value coming from Big Data originates in several ways. Big data can increase the transparency in business processes, making information more organized and usable. These processes can be further analyzed using Big Data, allowing for more well-reasoned decisions and ultimately higher performance. Big Data allows the business to target more specific groups of customers, increasing the amount of personalization. Consumers will therefore receive promotions that are more tailored to their own preferences, increasing their convenience (Manyika et. al, 2011).

Furthermore, a TED-talk by Marco Annunziata about the advantage of the Internet-Industrial revolution, in which machines inhibit properties that allow them to self-learn and analyze their problems (Annunziata, 2013). These problems being analyzed and solved automatically, while the human eye does not even notice it. As a result, we reduce the risk of unplanned downtime, optimistically to a point where we don’t have to treat risks anymore.

Reducing unplanned downtime will lead to a diminishment of costs, stress and time lost.

There are significant risks, and there are significant advantages. We can choose to only focus on the advantages of Big Data and IoT, but the risks will remain. It’s important to always stay on guard, in order to maximally utilize the advantages (Fardost, 2015).

Link to my previous blog post: http://wp.me/p7TpsB-3fg

References:

Annunziata, M. (2013, December 17). Welcome to the age of the industrial internet. Retrieved from https://www.youtube.com/watch?v=QBDShp6U7tU&feature=youtu.be

Fardost, A. (2015, March 18). Internet of things – beyond our current imagination. Retrieved from https://www.youtube.com/watch?v=sgMG7zRrcPk

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.

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In 2012, Harvard Business Review labeled Data Science as “the sexiest job of the 21^st century”. In that article, the authors explained that there will be a shortage of data scientists in the upcoming years. Due to this there will be a high demand for data scientists, who are professionals that can deal with big data. Furthermore, it is only until recent years did most companies start realizing the benefits of dealing with big data and thus there was a sudden appearance and demand for data scientists in the business field. It is true those data scientists always existed and were mostly employed by start-ups. However, today with the mainstreaming of Big Data, we have seen a significant decline in the proportion of data scientists employed by startups. The figure declined from 29% in 2014 to 14% in 2015 as data science became adopted by all organizations in all industries.

A better question to ask is what does it mean for managers who can’t deal with Big Data? Well this means that managers need to start focusing on attracting the best talents around the world. This would be especially challenging as the talent pool is fairly fresh and small. Furthermore, managers could also use formal or on-the-job training to develop their own employees and give them the analytical skills required. However there will still be another challenge to overcome. That is the challenge of turning analytical insights into business actions. This is due to the fact that managers are not necessarily analytical and cannot translate business needs and goals to technical terms. On the other hand, data scientists are too technical and do not have the business background to communicate and translate information into business actions.

As a result of this gap between business and data science, many companies today have started creating new roles and changing their organizational structure. New roles such as chief data officers, chief analytics officer, or chief information officers have emerged to ensure big data can be properly translated into effective business actions. This is why studying Business Information Management will be rewarded later on in your careers as yoy
embark to close the gap between big data and business actions.

The Future of Data Science and its Managerial Implications

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