Friday, November 4, 2016

Big Data In Business

Sashi Reddi, vice president and general manager of CSC’s Big Data and Analytics group wrote a very interesting article called, “4 Ways Big Data Will Transform Business”. In this article he discusses expansion of customer intelligence, improvement to operational efficiencies, new business processes when combining big data and mobile, and how big data and analytics go “as a service”.  Reddi believes big data is drastically changing the way businesses operate and gives companies a competitive advantage over competitors.

Reddi’s argument that I agree most with is that big data improves operational efficiencies. He is spot on when he talks about how data being combined with machine-to-machine interaction is improving predictive analytics. Taking his point one step further, I believe big data will also improve analytics in terms of understanding how machines work with each other to understand how to improve efficiencies. If machines can interact with one another through big data (without human intervention) then the machines can determine how to become more efficient on their own. This will improve production time in a plant as well as reducing lag time between different parts of the setup. In addition to improving the airline production industry, this big data can also be applied to the construction industry in terms of making cranes and other equipment used for construction. When data is able to be collected, and analyzed on its own this allows for improvement in the manufacturing of large scale equipment and will help improve efficiencies and consequently reduce costs if it doesn’t take as long to produce.

While Reddi explains that big data combined with the mobile industry will lead to customers being able to implement new business processes, he is ignoring the fact that mobile phones and technology are constantly changing. Due to this fact it will be difficult for companies to continuously allow their customers to have access to the data and in turn help companies with decision-making. It will be challenging for companies to keep up with pace at which mobile technology continues to develop. Also, not everyone has a smartphone (especially in other less developed countries) so this system will not reach a companies’ entire market. Due to this constraint I feel companies should be wary about how much time and effort they spend trying to combine their big data with customers’ mobile technology.

Overall, I believe all companies should adopt this technology and accept big data to use it to its fullest potential. I do not believe it should be mandated, but if a company can afford to use this data they should. While Reddi does not touch on the costs of big data and implementing it into a company this is most certainly something that needs to be considered. I would imagine this is not a cheap venture so companies must take costs into consideration before implementing the usage of big data into their every day operations.



  1. I think there is another side to the argument you could look at in terms of big data being useful to businesses, specifically in the mobile world. Sure, the mobile industry is always changing and evolving, making some big data useless or outdated. I see the personal laptop computer going down this trend with the improving capabilities of most smartphones and hand-held tablets. However, on the flip side of the argument, new technology creates new opportunities for new big data to be collected and likewise used by companies to create bigger and better changes for the world. Your article discusses machine-to-machine interaction in terms of large scale industrial equipment, but certainly the same principle applies even on the smaller scales, such as mobile device-to-device capabilities. I think of something such as iPhone backups or AirDrop to be able to automatically exchange information intelligently with minimal human interaction. These concepts are definitely used in daily life, and are improving with every new iOS release that Apple undergoes.

    I think businesses are really able to utilize big data well so long as they properly sort said data. Like we talked about in class during the beginning of the year, if all data sits in a tier 2 storage location and becomes convoluted and congested, then businesses will probably have a lower chance of being successful than those who properly organize and take care of that data. And like you say, companies have to struggle to keep up with the ever-evolving data. However, I think that the problem doesn’t stem from the company’s ability to use the data, but rather the human individuals who are creating automated programs with this evolving form of big data.

    One other thing that came to mind when I read this article is the cost of storing all of this big data. I’m not so sure that a crane-manufacturing business is fully educated in the power of big data and what it can do for production (other than the obvious automated machine building that you mention in your post). Once again, I think that in order for businesses to keep up with the evolving technologies that are coming out of your stereotypical tech companies in Silicon Valley, those humans in charge of utilizing their technology systems have to be educated and constantly in-tune as well. Otherwise, all of this powerful technology goes to waste, or is not used to its full potential.

  2. Being an information systems minor, I enjoy reading about the various ways that Big Data raises the bar in different industries and this blog post was not different. As I have mentioned before, I am currently taking Business Policy which is a class all about learning how to construct an individualized business strategy that will give a firm a competitive advantage over all of their competitors. So, I could not help but continually think about what I have learned in the class and how I can apply this article to what I am doing in the class. Also, in my operations management class, we had done a lesson about productivity and efficiency, which deals with the elimination of bottlenecks, areas of production that slow down the process. Using Big Data to improve operational efficiencies would be extremely useful for eliminating bottlenecks in production and would significantly improve output for a firm, in turn increasing the selling possibilities for the firm.
    I agree with Meghan’s point that combining Big Data and the mobile industry is good in theory, but not very practical nor realistic. It would be nice for customers to be able to implement new business processes and help with decision-making, but there is no way that they would also keep tracking the new data and be able to make completely informed choices or suggestions. It is also fair to say that that those without smartphones are left out of this so this aspect should not have a large focus on it. But, on the other hand, it could turn out to be a valuable to a company, so it should not be ruled out.
    While I do agree with all that Meghan has stated, I did see a downside when considering her ideas when it comes to machines becoming even smarter and being more reliant on Big Data. The improvement in machines would eliminate the need for actual people working in production. This is not ideal for workers and only benefits the company as they are increasing their capacity and increasing their profits, while also eliminating the cost of workers. Furthering use of Big Data in this capacity would be something that a company would have to think about in terms of whether or not they would want to have to reduce their working staff or not. It is a decision not to be taken lightly or hastily.


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