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Big Date - Is It a Strategic Tool - Essay Example

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The paper "Big Date - Is It a Strategic Tool" is a perfect example of a management essay.   New technologies have changed not only the way we live but also the way businesses function. Today it is hardly possible to imagine a company without its own web page or at list a profile in a social network…
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Extract of sample "Big Date - Is It a Strategic Tool"

New technologies have changed not only the way we live but also the way businesses function. Today it is hardly possible to imagine a company without its own web page or at list a profile in a social network. While this online representation is for sure a great tool for business in terms of attracting customers, keeping them loyal, and informing them about the new products and services, it is also a great tool for retrieving data about the customers, their preferences, purchasing behaviors, likes, and dislikes. This is where the term ‘big data’ comes into play. Hence, within a framework of this paper, I am going to critically discuss the phenomenon of the big data and examine its importance to the success or even survival of modern business.

At the outset, there is a need to clearly define what exactly needs to be understood by the term ‘big data’. According to the definition provided by the Oxford Dictionaries, the term ‘big data’ stands for ‘extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions’ (Oxford Dictionaries 2016). Cambridge Dictionary Online, in its turn, defines big data as ‘very large sets of data that are produced by people using the Internet, and that can only be stored, understood, and used with the help of special tools and methods’ (Cambridge Dictionary Online 2016). One more great definition of big data belongs to a world-recognized figure in the field of business intelligence and data warehousing Philip Russom. He defines big data as ‘an electric mix of structured data (relational data), unstructured data (human language text), semi-structured data (RFID, XML), and streaming data (from machines, sensors, Web applications, and social media)’ (Russom 2016). As we can see, all the three definitions consider big data from different perspectives hence there are three major peculiarities about a big data we should remember. First of all, it is used to reveal trends and patterns. Second of all, it can only be understood by the application of special methods and tools. Third of all, it is an electric mix of many different types of data retrieved from different sources.

Now, as it is clear enough what exactly the big data is, it is time to move forward toward answering the main question of this paper, which is whether or not should big data be considered a vital tool for business survival. The first thought that comes to my mind with this question is related to the growing importance of competitive advantage. As we know, in today’s world, the scale of supply is largely higher than the scale of demand. It means that customers have plenty of options to choose from while companies are forced to seek for the strongest competitive advantages in order to be chosen. Taking into account the fact that some experts claim that big data, as well as data-driven strategies, are going to become ‘an increasingly important point of competitive advantage’, it appears to be obvious that the role of big data is rather significant (Barton and Court 2012).

Statistics from the MIT experts state that even today those companies that decide to use the benefits of big data management demonstrate 5-6 percent higher levels of profitability and productivity. This particular phenomenon is obviously related to the fact that big data is associated with ‘the ability to see what was previously invisible’ (Barton and Court 2012). As a result of the availability of new data, a lot of improvements related to customer experience, strategy and business operations appear to be possible. According to the opinion of Tim McGuire James Manyika, and his colleagues, big data should be seen as the new competitive advantage, which means that a smart usage of big data can be a crucial tool for leading businesses to outperform even their strongest competitors.

It is forecasted that rather soon the growth of the completely new companies will begin, and these companies will be sitting in the middle of immensely big information flows when different benefits of big data related to buyers, suppliers, consumer preferences and their intents will be retrieved, analyzed and managed. Proceeding from this, it becomes clear that in order to remain competitive, today’s companies should start to be seriously concerned about building big data capabilities of their organizations (McGuire, Manyika et al 2012).

While it is clear enough that the benefits of big data are rather serious, it also needs to be taken into account that big data is only beneficial when analyzed and managed in a proper way. The problem of the most companies today is that they have plenty of data that can be extremely beneficial for their businesses, but they have no idea what can be done about all these data. What such companies need to do is to learn how to use data in order to make better decisions (Barton and Court 2012). In other words, the major benefit associated with using big data is the ability to make smarter predictions and better decisions and translate all the information retrieved from big data into a business advantage (McAfee and Brynjolfsson 2012). This particular idea leads as to the fact that one of the most important aspects of big data is big data management. Hence, the following part of the paper will be focused on the topic of big data management and possible tools that make this management more efficient.

Speaking about big data management, it is necessary to define what exactly does this term stand for. According to the opinion of Philip Russom, big data management also known as BDM is the process involving ‘the collection and storage of data, plus its processing and delivery through the application of old and new skills and tools to managing data’ (Russom 2013). Although the process of big data management seems to be very similar to data analytics and does not look as something outstandingly complicated, in fact, the majority of companies today are struggling to manage their big data (Savitz 2012). They accumulate more and more information with a hope that it might be helpful but have no clue what to do about those dozens of information as a result. This is where the role of big data management as well as such people as data scientists appear to become obvious.

According to the opinion of Davenport and Patil, in order to remain competitive and be able to manage big data appropriately, today’s companies need to transform their patterns of doing business and pay more attention to those employees who seem to have skills necessary for big data management. It is already evident that the key role in the most organizations in the future will be played by those forward-thinking experts with strong analytical and creative skills, and they position will be known as the data scientist. The major role of these experts will be to use their natural curiosity and creative thinking in order to make discoveries in the strange and complicated world of big data.

Apart from it, such a specialist in big data is expected to have an ability of writing codes, to demonstrate a high level of curiosity, and possess the associative type of thinking (Davenport and Patil 2012). Speaking of data scientists, it is necessary to mention one of the biggest problems associated with them. This problem is that the position of data scientist has been around for only a couple of years now, and no university or special education programs at this moment offer courses that can be used to train such specialists. Proceeding from this, it becomes clear why at this moment of life the demand for these specialists has raced far ahead of supply.

From all written above, it becomes clear that at this moment there are not enough big data specialists to fill a vacant position in each and every company that is willing to hire one. Hence, today the only choice those companies have is to get familiar with management tools associated with a successful and efficient usage of big data. In order to grasp the scale of the problem associated with a lack of efficient big data management, it makes sense to use statistical data according to which as much as 80 percent of the big data within companies is either unstructured or unfit for the traditional processing (Ernst and Young Pulications 2014).

Speaking of the key tools and principles of a successful big data management, it is necessary to consider at least three of them. First of all, the right data needs to be chosen for an analysis and management. This means that employees should seek for extraordinary and new sources of information, and for those sources that are most likely to contain specific information related to the current problems of organizations. Second of all, companies need to build such types of analytical models that optimize and predict business outcomes. As for this, it needs to be pointed out that the most effective approach is to identify the business opportunity and determine in what particular way does this model can improve performance. Third of all, it is vital to focus on transforming the opportunities for a company, which means that the culture of an organization needs to be adjusted to the new standards and analytical models (Barton and Court 2012).

Proceeding from all said above, it is possible to make a logic conclusion that a smart management of big data should definitely be considered one of the most up-to-date strategic tools. Since a smart usage of big data is associated with making better decisions, gaining competitive advantage, and being able to make business forecasts, it is safe to say that under the circumstances of the modern world big data is a vital part of business success and survival.

Reference List

Barton, D & Court, D 2012, 'Making advanced analytics work for you', Harward Business Review.

Davenport, T & Paril, D 2012, 'Data scientist: The sexiest job of the 21st century', Harward Business Review.

McAfee, A & Brynjolfsson, E 2012, 'Big Data: The Management revolution', Harward Business Review.

McGuire, T, Manyika, J et al 2012, Why big data is the new competitive advantage, Ivey Business Journal. Available from: < http://iveybusinessjournal.com/publication/why-big-data-is-the-new-competitive-advantage/>. [6 April 2016].

NA 2014, 'Big data: Changing the way businesses compete and operate', Ernst and Young Publications.

NA 2016, Definition: big data, Cambridge Dictionaries Online. Available from: < http://dictionary.cambridge.org/dictionary/english/big-data>. [6 April 2016].

NA 2016, Definition: big data, Oxford Dictionaries. Available from: < http://www.oxforddictionaries.com/definition/english/big-data>. [6 April 2016].

O'Toole, K 2013, 'Susan Athey: How big data changes business management', Insight by Stanford Business. Available from: < https://www.gsb.stanford.edu/insights/susan-athey-how-big-data-changes-business-management>. [6 April 2016].

Russom, P 2013, Managing big data, The Data Warehousing Institute. Available from: < https://www.sas.com/content/dam/SAS/en_us/doc/whitepaper2/tdwi-managing-big-data-106702.pdf>. [6 April 2016].

Savitz, E 2012, Best practicies for managing big data, Forbes. Available from: < http://www.forbes.com/sites/ciocentral/2012/07/05/best-practices-for-managing-big-data/#5d669997ef02>. [6 April 2016].

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