Decision Support of Business Intelligence - Essay Example

This refers to the finding and communicating of important patterns in data, particularly in significant areas full of recorded info, and relies on the synchronized application of operations research, statistics, and computer software to ascertain performance. Business analytics makes sense of BI and relates them to trends and statistical algorithms to predict business outcomes. Brown (2007) offers a simpler explanation by asserting that they are gauges on the organizational platform that inform leaders and managers how the organizations are performing.

This is a piece of technology used in the organization of big business databases and offers sustenance to business intelligence, and the databases are split into cubes, and each is organized and planned to fit the way one retrieves and analyzes data.

Key Performance Indicators are measurable business values estimated beforehand, that show the critical success factors of an organization (Parmenter, 2012). These assist organizations to predict, defining, and quantify progress toward the achievement of organizational objectives and targets. People often misconstrue KPIs and metrics and use them interchangeably, in fact, KPI is a metric, but the converse cannot be true. KPI has ten distinguishing characteristics, and include:

KPIs reflect Strategic Value Drivers-and they are actions when executed perfectly can lead to success in the future. Second, KPIs are defined by the Executives, and the latter characterize value drivers in estimating sessions that predict both the short-term and the long-term tactical course of a company. Third, KPIs spill throughout a company, and every group and at any level in a company is managed by ‘an executive’, and the title is represented by divisional heads, managers, directors, and supervisors amongst others. Others include being based on corporate standards, based on valid data, and easy comprehension, KPIs are always relevant, provide context, empower users and they lead to positive action.

Financial metrics performance measures profitability amongst other key financial measures, but they are limited compared to other performance measurements most often associated with Kaplan and Norton’s Balanced Scorecard comprehensive measurement. The drawbacks of wholly relying on financial metrics for performance measurement include:

First, financial metrics lack a close link to long-term organizational strategies and instead focus merely on annual and short-term projections. They do not handle progress regarding customer requirements, competitors, and other non-financial objectives which will ultimately guarantee profitability.

Financial metrics are often referred to as traditional measures in the wake of new performance measures, and most experts argue that the drivers of success in organizations are intangible assets such as intellectual capital and customer loyalty more than quantified assets on the balance sheets. Financial metrics cannot measure intangible assets, rather other nonfinancial measures provides an accurate picture of these.

Third, financial metrics are poor estimators of future financial performance, and that may arise from a long-term decision made in the present period. For instance, R&D investments, or even customer satisfaction programs made currently.

Fourth, financial measures are more susceptible to external changes in the performance measure that are beyond the manager or even company control and can range from changes in the economy to political situations.

Legal, privacy, and ethical issues in business intelligence are the principles, rules, and contractual conducts that govern an individual and an organization specifically and are generally respected. Privacy is the claim by individuals against the access of data, and often the threat posed by the internet challenges the protection of privacy as data flow can be easily captured, monitored, and stored during the movement in a network. In BI management, BI professionals similar to other professions face risks of making unethical practices in their decisions concerning consumer, business, and employee data. These three concepts; legal, privacy, and ethics are touchy and controversies surround how organizations handle business decisions. In general legal issues govern data and the applications differ from jurisprudence to another as a law applied in one country on business intelligence is different from another applied in another country.

An ethical issue that might confront a manager would be the use of cheap data mining options to save money while at the same time putting the quality to the test. Further, the rapid growth in the use of mobile platforms as enterprise devices has thrown privacy, legal and ethical issues into question. The rapid improvement in the delivery of charts, graphs and other data visualization that have become legible on mobile platforms that manifests in smartphones and tablets, from the BI software vendors are facing these critical issues.