Analytics Analysis : Senior Management Commitment Essay

What are the MOST unusual characteristics of your product/service that will be considered as a competitive edge in your industry?

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.

Quality is the perception of value of product from the customer’s point of view. Quality plays an important role in increase in the competition and customers being well informed and educated.

Quality is one of the five performance objectives and having a high-quality product or service often represents an essential element when being considered by the customer. Quality is a

Quality in my view is meeting or exceeding customer expectation in terms of products and services rendered.

Performance – this is the primary operating characteristics of a product (David, 1987). A customer usually looks for this particular quality in availing product or service. This quality dimension involves elements which can be assessed, they can be ranked factually on separate aspect of performance. A customers’ decision making is usually influenced by this dimension of the product or service.

Analytics can help a firm capture more value and create more competitive advantage in comparison to other firms by better decision making due to better strategic planning. Better strategic planning is a result of

The importance of analytics in big and small companies could not be overestimated. Every organization uses big data in order to manage their processes and improve its business. The term of "analytics" is commonly defined as "the extensive use of data, statistical and quantitative analysis, explanatory and predictive models and fact-based management to drive predictive models" (Davenport & Harris, 2007). Analytics appears to be a useful tool, which helps to gain necessary information and provide extensive support to all departments in the enterprise. Nowadays analytical innovations play a big role on the market as they help an organization to gain a competitive advantage and become a market leader. According to the researcher Svetlana Sicular, analytics helps the companies to organize big data and divide all the information into relevant and irrelevant. In such a way organization receive an opportunity to process this data and deliver necessary information to a customer faster and more efficient. Furthermore, new tools and applications help to build up a reliable channel of communication between clients and a support team (Wagner, 2016). That is why almost all the companies are constantly trying to improve their analytical methods in order to attract more customers and investors to their business. The examples of such organization as Netflix Inc., Harrah 's Entertainment and Amazon show that analytics could help an enterprise to develop in its field and gain a strong

More than any other subject of interest to business people the world over in the past decade, Quality has become a focal point of activity. But unfortunately, the most

Analytics is defined, according to online-behavior.com, as the “process of obtaining an optimal or realistic decision based on existing data.” [1]. Davenport and Harris (2007), defined analytics, as the “extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” [2]. An article titled Outsmart the Competition by Jackie Zack in Teradata Online magazine states that “analytics can help an organization optimize their business processes to make them effective as possible.” [3]. It is a proven fact that proper use of analytics can lead an organizations to success, providing them with that distinctive advantage over their competitors. In

The discerning customers nowadays are better educated and are able to recognize the quality of products or services, rather than just looking at the price. As competition between organizations grows more intense, many different factors and dimensions would be considered by the customers when they are going to measure the quality (Stevenson, 1999). In order to remain competitive among those rigorous competitions in the dynamic changing business environment, organizations have to maintain and enhance the quality of the products or services being delivered.

Many organizations worldwide are focusing today on quality to restore their competitive edge. We know now that an emphasis on quality improves overall productivity and reduces costs.

Firms must also exercise some caution when making decisions based on order winners and qualifiers. Take, for example, a firm producing a high quality product (where high quality is the order-winning criteria). If the cost of producing at such a high level of quality forces the cost of the product to exceed a certain price level (which is an order-qualifying criteria), the end result may be lost sales, thereby making "quality" an order-losing attribute.

Distinctive capability: Citibank has a distinctive capability in answering customer queries in a very less time. This aspect of its business makes it apart from competitors and makes it successful in the market place.

It is said that analytics works best when it’s a natural part of people’s workflow. In 2017, analytics will be embedded into applications people use every day, be it Salesforce or internal portals. This seamless integration will drive visibility and action on these analytics, often by people who’ve never explored data, like store clerks, call-center workers, and truck drivers.