Application of Business Analytics
An increasing amount of businesses are exploring this new concept of analytics. In today’s tech-savvy era, the use of analytics can be seen as a necessity rather than a competitive advantage. More companies are realizing the benefits that come with the use of analytics within the business environment. Like anything else, there are both pros and cons that come with this approach. However, the benefits far outweigh the negatives. Business analytics are the future of the business world. This paper will describe a general overview of business analytics and its application to the real world.
Definition of Business Analytics
Analytics can be a difficult term to explain. In simple terms, analytics converts data
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It is through these three types of analytics, that business analytics can be distinguished from just being the plain process of analytics. These three types of analytics help make this process useful in the business environment. It requires “a clear relevancy to business, a resulting insight that will be implementable, and performance and value measurement to ensure a successful result.” Business analytics includes a combination of all three types to generate new information used for business organization decision-making. Descriptive analytics basically gives you a general idea of the data you are looking at. Predictive analytics takes the next step and predicts what is likely to happen next. Finally, prescriptive analytics figures out what is the best course of action. All three of these types of analytics can be very useful when used in combination with one another. Business analytics can be instrumental to a business’ success when implemented properly. (Schniederjans et al., 2014).
Pros and Cons
The benefits in relation to business analytics far outweigh the negatives within any business. Despite this, however, there still are drawbacks related to business analytics. The three major issues relating to business analytics are ease of use, speed, and scalability. These three factors are the main priority executives are looking for when it comes to data analytics in the business environment. Unfortunately, many executives feel as if they are not
Just like in baseball there are large and small businesses. Businesses have to make decisions, decisions that will help the business in the long run. By using analytics business can measure their performance to know where they stand financially and economically. Numbers are very important in a
Decision making and communication are at the center of business success and efficient business analytics would only be effective through the use of proper information systems and that are up to date with current trends as well as optimizing on the available channels.
As we discuss the possibility of emerging into business intelligence software we must keep in mind the overall purpose of using any type of software is to reach strategic goals in order to increase market shares. I will discuss how business intelligence software will allow us to meet those strategic goals. We will establish what type of information and analysis capabilities will be available once this business intelligence software is implemented. We will discuss hardware and system software that will be required to run specific business intelligence software. Lastly, I will give a brief synopsis on three vendors (IBM, Microsoft Microsoft and Oracle) that are dominating the business information software
Our company is located in downtown Pittsburgh. Based off of location alone, we are the leading competitor in our region. I discuss below how we can use this as a competitive advantage with analytics. River’s Casino has multiple employees and departments within the organization who contribute to competing with analytics in various ways.
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).
A fundamental transformation is being observed in the field of healthcare industry as it moved from volume based business to value based business. With increasing demands from consumers for better healthcare quality, plans and increased care, healthcare providers are expected to provide better outcomes. The cost dynamics of health care industry is changing globally, which is driven mainly by longer life expectancy, pervasiveness of chronic illness and infectious disease. New market entrants, new medical approaches have made the things more complicated. All these challenges in the industry open the way for analytics work to expand more. Here in this document, we would like to mainly focus on the following aspects to understand the use of analytics in day to day industry operations.
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.
In today’s companies, the analytics software plays the important role and guides the future activities to a great extent.
Each type of analytics as seen on the diagram above, could share a common sub group which could in turn have additional classifications. understanding and reviewing the different types of analytics systems and choosing those that best suite an organization is very helpful in determining the analytic plan for the future of the business. Succeeding in this, will definitely give a boost to the overall value of a business platform.
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.
Businesses today have access to significantly more data than any other time in history; however, most businesses are not capturing or using the data effectively. A report by the Aberdeen Group, “The Executive’s Guide to Effective Analytics,” indicates that “44 percent of executives are dissatisfied with the analytic capabilities available to them today, and that they often make critical decisions based on inaccurate or inadequate data” (Forbes, 2014). Luckily, CEO’s are beginning to recognize the need for analytics and more and more businesses are making a shift towards a data-driven business culture.
Business analytics is different to Business intelligence which also uses statistical methods. Business analytics uses statistical methods and data to arrive at fresh understanding and illumination of a situation, whereas business intelligence uses statical data to serve as querying, reporting or alerts. Business analytics, therefore, is, one may say, the detective side of business using the statistics to develop and progress the business or direct it in new directions rather than revamping it with existent and supportive data. Business intelligence, in other words, uses the data to inform stakeholders and others what is occurring with the business, what the action is, and what steps are being taken.
“Competing on Analytics” defines an analytical competitor “as an organization that uses analytics extensively and systematically to outthink and out execute the competition.”(1) Business analytics is a new way for companies to separate themselves from their competitors. I recently completed an internship at the firm PricewaterhouseCoopers (PwC) and will work there full-time upon completion of this program. PwC uses analytics to help solve complex business issues and to identify opportunities across different industries. PwC is the largest professional service company in the world and is part of the Big Four accounting firms. PwC operates in over 157 countries with more than 750 offices throughout the world.(2) PwC is structured into three service lines, which are Assurance, Advisory and Tax. The assurance practice audits almost 30% of the global fortune 500 companies.(2) The advisory practice is mainly consulting activities that cover strategy, cyber security and privacy, human resources, deals and forensics. (2) These three practices generated $35.4 billion in revenue in 2015. (2)
Broadly, there are two types of Analytics i.e. Business/Cube Analytics and Predictive Analytics. Business Analytics is a traditional way where historical measures (revenue, profit, loss etc.) available are extracted, transformed, modeled and stored for analysis. It is about getting insights on events that already happened. E.g. Year-on-Year sales report. In the contrary, Predictive analysis applies data mining and statistics on large volume of data for Forecasting, projecting, and predicting. E.g. KFC giving combo offer based on prediction of consumer’s possible purchase behavior to increase overall sales.
In every long term strategic planning, many companies considered data collection and analysis as a fundamental activity. Big companies that strive to achieve a sustainable advantage over their competition made use of information management system to help them analyze their data. These activities have evolved to what is now known as business intelligence of BI.