Big Data Analysis

The data analytic process is one in which a large amount of information is collected using software specifically geared towards collecting, identifying and storing information for use by the company. The information is gleaned from different forums, with social media being the most rich and useful. The information is then quickly sorted and organized for use by the collecting agency (Turban, Volonino, Wood, & Sipior, 2002, p. 6). The use of data analytics really took flight in 2010 when different companies offered software that enabled a company to implement their own data analytics. This led to better marketing campaigns, improved customer relations and it gave companies using the software a bigger advantage over their competitors (Savitz, 2012).

The ability to compete on analytics is made possible by certain qualities some companies possess which allows them to collect and use immense amounts of data in a way that differentiates the success and practices of those companies amongst any other businesses. Davenport and Harris (2007) define analytics as “extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions” (p. 7). Therefore, to be able to compete on analytics, a firm must not only use the data to extrapolate and execute strategies and models in order to drive business, but also to use that data better and smarter than their competitors. This requires forward thinking and continual developments of current analyses and practices. With regard to Davenport and Harris’s criteria and concepts on the ability to compete on analytics, Old Navy LLC’s practices will be analyzed to find whether the company is able to compete, is a competitor, and how it competes, if at all.

The ability of companies, governments and healthcare to harness data is important to find hidden information about how things are working in their organization. These organizations can then decide how thing should work and how things might work better depending on management decisions. Companies and governments use big data to track and analyze processes and customers for profit and efficiency. In healthcare big data is analyzed to understand how effective treatments and facilities are and make necessary changes. The bigger the data set the more necessary it is to use proper analytic techniques, types of analytic techniques are descriptive, predictive and prescriptive.

There is at least one field that is largely underutilizing big data and big analytics. This field is small business. Small businesses provide more than half of the jobs in the U.S. (Baldwin, 2015, para. 1), and yet, many of these businesses do not take advantage of the information that big data and big analytics can provide them. There are many ways big data and analytics can increase profits for small businesses, as long as these small businesses identify the opportunities that allow big data to work for them and as long as they work through the challenges that discourage small businesses from utilizing big data and analytics. This paper will discuss these opportunities and challenges in detail.

In Competing on Analytics by Thomas Davenport and Jeanne Harris, the pillars of analytic completion are stated as: “(1) analytics supported a strategic, distinctive capability; (2) the approach to and management of analytics was enterprise-wide; (3) senior management was committed to the use of analytics; and (4) the company made a significant strategic bet on analytics-based competition” (Davenport & Harris, 2007, pp. 511-512) . This section will describe Aramark’s position within these pillars.

Stage 4, Analytical Companies – Analytics have been applied at an enterprise-wide level and are being used to drive decision-making, performance, and innovation, but results may not yet have been realized

In the New Science of Winning book, (Davenport & Harris, 2007, p.7) analytics is defined as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” [1]. To be successful in today’s competition, my current employer, DLL Financial Solutions Partner (DLL), is competing on analytics and fully aligned its core strategies to be supported by extensive statistical and computer based decisions. DLL is a global financial services company with operation in 36 countries, and its main focus is in the commercial equipment finance sector. In the following paragraph, I will explain DLL’s position in the industry and its ability to successfully compete on analytics with regards to its core business functions.

New organizations can leverage Big Data in such a way that it provides benefits that can prove valuable especially to an organization seeking to establish itself and grow. One of these benefits is faster and better decision making. Particularly with the analytics of Big Data, organizations have access to real-time data

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

Today, the world’s trend in operating business focuses on data availability to enact the best suitable decision to improve, develop, and increase business revenues. Moreover, the availability of data helps to monitor and control the quality of provided products or services. However, the availability of data without proper analytics operations would have no meaning (1). Data analytics provide an important aid to an organization to figure out their position in the market in comparison with their competitors. Also, data analytics helps to identify what is the organization’s competitive ability in the market, what they should bet on, and what they should strive for. With that being said, many of today’s most successful organizations utilize

The sections below go into greater detail about how organizations can use analytics as a competitive weapon to introduce new goods and services and support existing ones.

Analytics has been used as isolated initiatives within my company. Different levels of applications of analytics is a reality. Historically, quality department has leading the way in data-driven decision process by using several statistical and quality

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Companies are facing a highly uncertain environment due to financial-crisis, global economy, and dealing with high-competitiveness. The value encompassing the culture of leveraging people, process, data and technology. The shared core-values and priorities of an organization has becoming essential for intelligent enterprise (Stubbs, 2014) . As Evan Stubbs described in his book (Stubbs, 2014), we need skilled employees who are involved in applying business analytics, comfortable leaders with uncertain environments and planning for unknown unknowns. Process must be linked to achieve an outcome and strongly defined, further to create specific steps that can be automated. Not less important – data and measure process for future analysis and decision-making process; convert simple data to valuable information for executives. And the technology enables to produce assets.

In today 's mind boggling business environment, the field of data analytics is developing in acknowledgment and significance (Grant and Jordan, 2015). It is assuming a basic part as a basic leadership resource for officials, particularly those overseeing expansive organizations. Notwithstanding the development in significance of Planned/Analytical and its prospects for the future, other focal subjects emerged, incorporating the differed routes in which Planned/Analytical is organized and oversaw inside these ventures (Grant and Jordan, 2015). This flags the act of analytics, while advancing as a decision-making resource, stays in its initial advancement organizes and will proceed to develop and develop the length of it creates unmistakable budgetary advantages for the company.