Business intelligence certainly has a tremendous potential for helping both public and private sector organizations become increasingly successful. It has already shown value in many areas of the business and promises to show increased value throughout the business as it matures. It is the primary support for developing an intelligent learning organization.
Any new technology, however, must have a solid foundation if it is to be successful and provide benefit to an organization. One major problem is that business intelligence, and information technology in general, is very lexically-challenged. Words and terms are used, misused, abused, and discarded resulting in general confusion. Another major problem is that business intelligence is not put in the perspective with how it supports the business through a value-added process.
Lexical Richness The first place to start building a solid foundation is a lexicon of words and terms relating to business intelligence. Intelligence is the ability to learn, to understand or deal with new or trying situations; the skilled use of reason; the ability to apply knowledge to manipulate one's environment or to think abstractly. Business intelligence is a set of concepts, methods, and processes to improve business decisions using information from multiple sources and applying experience and assumptions to develop an accurate understanding of business dynamics. It is the gathering, management, and analysis of data to produce information that is distributed to people throughout the organization to improve strategic and tactical decisions.
Business intelligence involves the coordination of core information with relevant contextual information to detect significant events and illuminate unclear issues. It includes the ability to evaluate business trends, to evolve and adjust to changing situations, and to make intelligent decisions based on uncertain judgments and contradictory information. It relies on exploration and analysis of unrelated information to provide relevant insights, identify trends, and discover opportunities.
Business intelligence requires high-quality information which is derived only from a high-quality data resource. Organizations must understand the need for, and the value of, a high-quality data resource. Technology will support business intelligence, but the real issue is how to achieve and maintain a high-quality data resource to support business intelligence.
Data are the individual raw facts that are out of context, have no meaning, and are difficult to understand. Facts are numbers, characters, character strings, text, images, voice, video, and so on. Data in context are facts that have meaning and can be readily understood. They are the raw facts with meaning and understanding, but are not yet information.
Information is a set of data in context that is relevant to one or more people at a point in time or for a period of time. It is data in context with respect to understanding what the facts mean. It is data imbued with meaning, relevance, and purpose. A set of data in context is a message that only becomes information when someone readily accepts that message and it is relevant to their needs. Information must have relevance and a time frame.
Knowledge is cognizance, cognition, the fact or condition of knowing something with familiarity gained through experience or association. It is the acquaintance with or the understanding of something, the fact or condition of being aware of something, of apprehending truth or fact. Tacit knowledge is the knowledge that is in people's heads or the heads of a community of people, such as an organization. It is what makes people smart and act intelligently. Explicit knowledge is knowledge that has been rendered explicitly to a community of people, such as an organization, and is what they deem to know. Organizational knowledge is information that is of significance to the organization, is combined with experience and understanding, and is retained. It is information in context with respect to understanding what is relevant and significant to business issues.
Knowledge management is the management of an environment where people generate tacit knowledge, renders it into explicit knowledge, and feed it back to the organization. It is the process of creating, institutionalizing, and distributing information between people. This process forms the base for more tacit knowledge, which keeps the cycle going in an intelligent learning organization.
Value Added Process The second place to start building a solid foundation is to describe a value added process that includes business intelligence. Every organization has a demand for information. The business information demand is an organization's continuously increasing, constantly changing need for current, accurate, integrated information, often on short or very short notice, to support its business activities.
Information quality is a measure of how well the business information demand is met. It is the ability to get the right data, to the right people, in the right place, at the right time, in the right form, at the right cost, so they can make the right decisions, and take the right actions. Data resource quality is a measure of how well the data resource supports the current and future business information demand. It is providing the right data to support information quality.
The business intelligence value chain is a chain where value is added from the data resource, through each step in the value chain, to the support of business goals. The data resource supports the development of information through the information engineering process. Information, in turn, supports the knowledge worker in a knowledge environment, and the knowledge worker supports business intelligence in the intelligent, learning organization. Business intelligence supports the business strategies, which support the business goals of the organization.
Any level in the business intelligence value chain has no better quality than its supporting level. Since the data resource is the foundation of the business intelligence value chain, the quality of any higher level can be no better than the quality of the data resource. The degree to which the business goals are met can be no better than the quality of the data resource.
The data resource is like the foundation of a house. If the foundation is not level or square, the carpenter fights the error clear to the last shingle on the roof. If the foundation is level and square, the house remains level and square. If the data resource is low-quality, it will impact the business intelligence value chain clear to the business goals. But, if the data resource is high quality, it will adequately support the business intelligence value chain.
The bottom two levels in the business intelligence value chain, the data resource and information, are in the information technology realm. The middle two levels, the knowledge environment and business intelligence, are in the human resource realm. The top two levels, business strategies and business goals, are in the business realm.
The information technology function should be responsible for managing the information technology realm and supporting the human resource realm with emphasis on high-quality data and high-quality information. They should not be responsible for managing the human resource realm. Human resources should be responsible for managing the human resource realm, with emphasis on knowledge workers and the development of an intelligent, learning organization. Business managers and executives should be responsible for managing the business realm.
The value begins with a high-quality data resource that is the raw material for preparing high-quality information. The value continues with high-quality information supporting knowledge workers and an intelligent, learning organization. Finally the value continues to the support of business strategies and goals.
Similarly, the business information demand begins with the business goals and strategies, continues down through the business intelligence and knowledge worker levels, and through information to the data resource. When the business information demand is well defined down through the business intelligence value chain, the data resource will be better prepared to support that demand.
Conclusion The foundation to support a viable and successful business intelligence initiative in any public or private sector organization must be lexically rich and value added. To be lexically rich, it must have a formal set of terms with formal, well-understood definitions. To be value added it must be part of a value chain where value is added from the data resource up through the chain to the business goals, and the business information demand is defined down through the chain. To do otherwise only compromises the ultimate success of the initiative.
