Business Intelligence Systems
Within the ever-changing work environment, the need for newer business systems has become more evident than ever before. Currently, these newer systems are manifested as “business intelligence systems” (BISs). These systems, not technical expertise, are the important means to growing a business organization. “Business intelligence systems” require vision, money, and patience in their development and implementation. Essentially, BISs center on a full understanding of information and knowledge that is derived from data.
The current increase in available data is useless without an effective way to access and synthesize vast amounts of information and knowledge (Senge, 1990). To get a handle on the tie-in of data to past system approaches, reference can be made to recent developments. Data mining tools allow organizations to capture all the fundamental particles about customers, suppliers, internal transactions, and so on that make up the real picture of a business’s life. Also, data warehouse applications are used to catalog, index, and cross-reference these raw materials.
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In essence, there is need for the alchemy that transforms basic business data into actionable business intelligence. Data becomes business intelligence when it is in the hands of decision makers who know what to do with it. (Kleinschrod, 1995) It should be noted that there are a number of information systems that are related directly to “business intelligence systems”.
They include: (1) Knowledge management systems (2) On-line analytical processing systems, (3) “Decision support systems”, and (4) Executive information systems. For the most part, these systems are helpful in making comparisons, analyzing trends and patterns in business, and presenting historical and current information to decision makers. Essentially, these systems assist decision makers in making better informed decisions that affect all aspects of a company’s operations. In contrast, “business intelligence systems” go a step further by providing decision makers with a thorough understanding of their operations today and tomorrow.
In a few words, “business intelligence systems” give decision makers the ability to keep their fingers on the pulse of their businesses every step of the way. Concerning the need for actionable business intelligence, management expert Peter Drucker saw this a long time ago. Because most information systems have been and still are, to a large degree, built on accounting data, they tend to be inwardly focused. If led by these systems, decision makers are consumed with what they already know a lot about—costs. In contrast, decision makers need to focus on what they find more difficult: the creation of value and wealth.
Drucker’s related belief is that newer system approaches must provide decision makers with more pertinent external data. There are certainly technology-based efforts to capture market and customer data and to make sense out of it. But the information that is created does not seem to be helping decision makers make the really tough and important decisions. What is needed are real “business intelligence systems” that are capable of providing decision makers with much more than queries, report generation, and warehousing.
Rather, “business intelligence systems” are the culmination of major system technologies that provide the ability to take a proactive stance rather than a passive or, at best, a reactive approach to a company’s operations. Based on the foregoing elements, a business intelligence system makes great use of the organization, codification, and dissemination of appropriate information, knowledge, and intelligence in an organization. As such, it represents a collaborative work environment in which all three are collected, structured, and made accessible organization-wide to facilitate better and faster decision making.
Basically, a business intelligence system is designed to capture appropriate information and knowledge and produce business intelligence in order to better understand a company’s operations. Because a long time frame is taken into consideration, it provides a broader view of the organization than was possible with past systems. The end result is that there is a focus on a total understanding of a company’s operations so as to improve the effectiveness of a company’s decision makers over time. (Stewart, 1991)