Organizations should make extensive use of analyzing large databases and use of other IT resources to formulate basic business strategy. Large Databases and other IT resources can be used to determine decision-making strategy, whether Bottom-Up or Top-Down. In addition, Big Data Analytics is a burgeoning and highly useful development in IT. Finally, top global competitors understand that the effective analysis of large databases is a differentiator in the business success, particularly for the development of a competitive edge.
Health Care -- Databases and Other it for Basic Strategy
The purpose of this paper is decide to what degree organizations should depend on the analysis of large databases and other it resources to formulate basic strategy. Organizations should depend on the analysis of large databases and other it resources to a high degree to formulate basic strategy. Basic decision-making, state-of -- the art and proven business-enhancing methods and reassessment/improvement of some very basic business elements are all enhanced by the analysis of large databases and other it resources.
Organizations Should Depend on the Analysis of Large Databases and other it Resources to a High Degree to Formulate Basic Strategy?
Organizations should depend on the analysis of large databases and other it resources to a high degree to formulate basic strategy. First, large Databases and other it resources can be used to determine even the most basic business strategy of an organization. Decision-making strategy, for example, is largely determined and helped/hampered by it systems and databases within an organization. Systems making the acquisition of information easier at lower levels make it easier for people in lower positions to make decisions "Bottom-Up" without consulting "higher ups" within the organization. These systems are deemed "information-based" systems, including Enterprise Resource Planning (ERP), Computer-Aided Design (CAD) and/or Computer-Aided Manufacturing (CAM) software that make data essential to decision making readily available to workers, forepersons and managers (Nobel, 2010). The "opposite" approach to decision-making, involving the higher echelons of an organization all the way up to the CEO, are established and enhanced by databases, software and other systems that enhancing communications throughout the organization. These measures may include an organization's well-developed intranet, e-mail, instant messaging and/or Skype (Nobel, 2010). In those situations, because "higher ups" are readily privy to organization-wide information, upper management is able to micromanage decision-making in virtually all aspects of the organization and make "Top-Down" decisions for the organization.
Secondly, Big Data Analytics is a burgeoning and highly useful development in it. It is supported by major Internet players such as Oracle and IBM (Webster, 2011). In addition, it is developing in aspects/formats such as MapReduce, which parallels web-based data's processing in order to effectively process unprocessed data (Webster, 2011), real-time analytics on multiple data streams, big data appliances that integrate servers, networking, storage and analysis, and scalable databases for high traffic and streaming media (Webster, 2011). Furthermore, developments such as the "Internet of Things" is ultimately aimed at making the tens of billions of electronic devices connected to the internet ultimately function the way our brains function (Webster, 2011). Obviously, this is a rapidly developing, exciting and highly useful aspect of the internet.
Third, top global organizations claim that effective analysis of "Big Data" is a "differentiator," making them more highly competitive with their competitors and giving them the edge in business (LaValle, Lesser, Shockley, Hopkins, & Kruschwitz, 2011, p. 22). Research has revealed notable differences in business capabilities among businesses that are merely "aspirational," lacking adequate resources to analyze and use large data stores, from organizations that are "experienced," moving beyond mere cost effectiveness and having some history of exploring data analysis, ultimately to "transformed" organizations that efficiently manage resources and people to analyze and use large stores of data (LaValle, Lesser, Shockley, Hopkins, & Kruschwitz, 2011, pp. 22-3). Research has shown that "transformed" organizations vastly outperform competitors (LaValle, Lesser, Shockley, Hopkins, & Kruschwitz, 2011, p. 23). Consequently, there is a proven track record correlating the effective use of big data analysis and high performance in business.
Third, the use of it resources forces an organization to better develop its goals, missions and objectives in order to most effectively use it (Hayles, Jr., 2007, p. 13). The effective use of it resources requires an organization to define and manage its client base (Hayles, Jr., 2007, p. 14), its products (Hayles, Jr., 2007, p. 15), its human resources (Hayles, Jr., 2007, p. 16), and its delivery of both the products and supporting services (Hayles, Jr., 2007, pp. 17-8). Clearly, concentration on the optimum use of it resources forces an organization to reexamine and "tweak" itself in major business aspects, thereby significantly improving the organization.
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