Abstract
This paper will discuss and evaluate the significance of business intelligence from a manager’s and internal decision maker’s point of view. It would also cover an overview of what business intelligence is, what are its relevant and associative terms, what are its general uses, and especially how it is helpful to a company’s management. In the contemporary corporate sector set up, the competition among various business entities has gone far beyond. Companies use all tactics to meet this strategic competition on al levels. Business Intelligence has become inevitable now for survival in the business market nowadays.
Introduction
Most people do some form of analysis on a regular basis throughout their lives—when they buy a house, a car, or go on a holiday, for example. Every business also does some form of analysis, whether it is looking at productivity improvements, benchmarking, cost savings, or using the balanced scorecard.
However, change is passing by every business that is focusing internally and on information derived from internal data. Strategic and industry risk to any organization come from the external environment. Despite this, many organizations and their decision-makers today are investing a vast amount of resources in attempts to obtain the solutions to their (external) market and industry challenges via enhanced information technology (IT) and information systems capabilities. Management guru Peter Drucker (1997) has noted that managers have come to rely too heavily on computerization and systems and that this fails the manager when they cannot gather the necessary data in the first place. He further notes that a large number of executives spend all their time with data that is both internal and incomplete. Drucker concludes that the information that executives need the most is about the “outside world, ” and that most important decisions should be focused on data gathered about what is going on externally to, rather than inside, the company (Drucker 1997, 46-54).
Definitions of Business Intelligence (BI)
There are two popular BI definitions: one is broad and the other is narrower. The broad definition suggests that BI is information concerning the business environment in which a company operates (Prior 1998, 66-68), including customers, competitors, industry trends, public policy, and other STEEP (Social, Technical, Economic, Environmental, and Political) factors.
This is viewed to be broader and more inclusive than CI in that it includes these “noncompetitive” or indirectly competitive facets of the environment. This use of the term BI reached its height of popularity, as measured in a number of publications and studies, during the 1970s when it was viewed as an effective new way for organizations to respond over the longer-term to what were then viewed to be fundamental or structural changes to the macro-environment of business (Fleisher and Bensoussan 2003, 85-87). The term “business” intelligence also provided a sharp contrast with “government” intelligence activities, and as such helped to differentiate it from the intelligence activities performed by government agencies such as the U.S. Central Intelligence Agency (CIA), Britain’s MI-5, or Israel’s Mossad.
The narrower version of BI became very popular in the late 1990s and remains so at the present time. In its narrower sense, BI is commonly a technologically driven process of discovering hidden data among and within an organization’s own variety of databases (Halliman 2001, 133-40). This narrower form of BI has primarily an internal focus, is focused on shorter-term horizons than its broader cousin, and includes various data-mining technologies to help the organization better understand itself and its own abilities (Kudyba and Hoptroff 2001, 56-61). It is also an electronic-commerce-oriented and IT-intensive form of information-resource management, possibly done at the expense of human intelligence or with the provision of non-technical solutions. BI is particularly used to assist operating managers, business-unit managers, marketing managers, and product managers in their decision-making. It is not generally provided to the organization’s top decision-maker. One negative aspect of referring to the field as “BI” is that the term has been associated recently with the one company that has appropriated its trade-mark, namely, IBM.
Relevant and Associative Terms of Business Intelligence
Competitor Intelligence (CI)
Although often employed as a synonym for business intelligence, it is widely regarded to be more restrictive or limited in scope (Prior 1998, 66-68). This restricted scope appears in terms of both its range of focus and its shorter time horizon. Competitor intelligence uses public information about specific competitor organizations and analyzes it in order to identify a competitor’s potential actions or to identify potential new competitors themselves. It primarily serves the needs of strategic planners, strategic business unit (SBU) operating managers, business-development specialists, mergers-and-acquisitions officers, and/or marketing managers concerned with product or brand management. The time horizon of competitor intelligence can vary from the very near term when it is used to provide marketing managers with operational intelligence about pricing or distribution, to the long-term as support for strategic planners. (Vibert, 2000, pp. 77-81) It has been in use for several decades and is generally viewed to be an institutionalized task of most long-standing competitive organizations.
A majority of companies that perform competitive intelligence will include competitor intelligence as one of the larger set of activities that occurs under the CI umbrella. Sharp (2000, pp. 37-40) provides examples of companies such as Apple, IBM, and Xerox that have encountered competitive problems due to an over-reliance on competitor intelligence, only to be blind-sided by changes in the marketplace. The main drawback of competitor intelligence is the tendency to overrate the activities and intentions of obvious competitors while overlooking indirect competitors, upstarts, or those that may provide substitute products/services.
Knowledge Management (KM)
Knowledge management (KM) is a term that became popular in the late 1990s. Broadbent (1998, pp. 23-36) suggests that KM is about enhancing the use of organizational knowledge through sound practices of information management and organizational learning. In practice, KM is a loosely used term applied to a broad range of organizational approaches that encompasses identifying and mapping intellectual assets within the organization, generating new knowledge for competitive advantage within the organization, making vast amounts of corporate information accessible, sharing of best practices, and using technology that enables all of the above—including groupware and intranets (Denning 1998, pp. 89-97).
Different activities that could potentially fall under the KM umbrella include such things as knowledge-mapping, data- or knowledge-mining, knowledge audits, knowledge databases, corporate intranets or digital library development and maintenance, personal and virtual navigation, corporate knowledge directories, FAQ (frequently asked questions) development, and so on. Some authors might be interpreted to have argued that CI falls under KM as well (Peters 1997, pp. 14-16). KM mainly serves the needs of functional and operating unit managers and is only very occasionally used in strategic decision-making by senior executives.
Problems that CI practitioners have with KM include the fact that it has been heavily driven by systems and technology assets and under-plays the impact that intuition, creativity, and human analysis can achieve, especially in dealing with the kinds of non-repetitive or first-time matters like surprise or serendipity that CI analysts often encounter and need to address. 8 KM is generally mostly inwardly focused, gathering together the tacit and explicit data already within the organization’s walls, while CI utilizes both internal and externally generated data to serve its purposes. CI practitioners also think that subsuming CI under KM, as some KM supporters have argued should be the case, would only add one more layer between themselves and decision-makers, thereby further decreasing CI’s potential effectiveness. As CI expert Ben Gilad (2001) recently stated:
KM is dying a quick death, and not a minute too soon. As a consultant-driven discipline, KM has always been ambiguous, re-inventing the wheel in many cases and complicating existing wheels in others. It has now become an empty title, reduced to a few data warehousing, intranet-connectivity initiatives. Placing CI there is nonsense, of course. (Gilad, 2001, p. 23)
Market Intelligence (MI)
Market intelligence (MI) is industry-targeted intelligence that is developed on real-time (i.e., dynamic) aspects of competitive events taking place among the 4Ps of the marketing mix (i.e., pricing, place, promotion, and product) in the product or service marketplace in order to better understand the attractiveness of the market. Prior (1998, pp. 66-68) suggests that like marketing research, market intelligence looks at the attitudes, opinion, behavior, and needs of individuals and organizations within their broader context. Aaker (1998) notes that MI will include dimensions such as actual and potential market size, market growth, profitability, cost structure, distribution systems, market trends and developments, and key success factors. Advances in electronic commerce now allow it to encompass things like real-time sales data and demand assessment, real-time customer-purchasing-pattern assessment, and ongoing monitoring and assessment of competitors’ pricing. (Aaker, 1998, pp. 115-16)
Market intelligence has been popular for decades and is now mostly institutionalized among competitive marketplace players in the business-to-consumer (B2C) and, increasingly in the business-to-business (B2B) marketplaces. A time-based competitive tactic, MI insights are used by marketing and sales managers to hone their marketing efforts so as to more quickly respond to consumers in a fast-moving, vertical (i.e., industry) marketplace. It is not distributed as widely as some forms of CI, which are distributed to other (non-marketing) decision-makers as well. Market intelligence also has a shorter-term time horizon than many other intelligence areas and is usually measured in days, weeks, or, in some slower-moving industries, a handful of months. (Nolan, 2004, pp. 121-28)
STRATEGIC INTELLIGENCE (SI)
Strategic intelligence (SI) is a radar-like intelligence process that is primarily focused on the long-term, overall environment-shaping industry and marketplace competition for an organization now and in the future (McGonagle and Vella 1999, 208-11). It is determined by and supports top executives in strategic planning and decision-making about capital investment, mergers and acquisitions, long-term R&D planning, market expansion and country risk, and strategic alliances and partnerships, among other things. This is defined in contrast to tactical or operational intelligence, which may be focused on day-to-day marketing or operational concerns that are not necessarily long-term but are still likely to be competitive in nature. Although it has been used irregularly in business organizations for years, mostly since the 1970s, strategic intelligence has remained popular in government intelligence circles. (Prescott, 1998, pp. 4-12)
Role of (BI) in managerial and internal decision making process
With this prevalent internal focus, it is unfortunate that so few executives are delivered the right intelligence to enhance their decision-making and to assist them with managing industry and market risk, the primary bases of business intelligence focus (Hammonds 2001, pp. 150-56). No matter how many customer relationship management (CRM), knowledge management (KM), or business intelligence (BI) systems an organization implements and pays for, they are not going to dramatically improve its competitiveness. Companies need to focus on the external aspects of their environment if they are to succeed today and in the future. Customer learning is clearly important, but equally important is competitor learning that comes through competitor analysis (Fahey 1998, pp. 110-13). Good strategies come from making effective choices (Porter 1996, pp. 61-78) about what both the external environment and the internal organization can tell the decision-maker.
Numerous strategy scholars have noted that organizations have to constantly reinvent and reposition themselves in order to stay ahead of the competition, and in many instances they have to do this just to stay in the game. Of the 500 companies making up the S&P 500 in 1957, only 74 remained on the list in 1997. Of the original Dow Dozen in 1896, only one remains—General Electric. All the others have fallen aside, been absorbed, or been unable to compete. (Werther, 2001, pp. 41-47)
Business intelligence (BI) is defined as a systematic process for gathering and analyzing information to derive insights about the competitive environment and business trends in order to further the organization’s business goals. It is about managing the opportunities and risks in the competitive battle and delivering to decision-makers the capacity to act. The opportunities and risks today are many, and include the increasing pace of business, information overload, increasing global competition from new competitors, more aggressive existing competition, massive political effects, and rapid technological change, among other things.
Every important business decision entails opportunity or risk. So how are strategies formulated and how do firms ensure that the chosen strategy is the right one? The answer: It is only through the careful collection, examination, and evaluation of the facts that appropriate strategic alternatives can be weighed in light of organizational resources and requirements.
Every good manager recognizes the need for systematic analysis of his or her competitors and the external environment. Analysis has been described as an obvious weak link in many public and private intelligence programs (Werther 2000, pp. 19-22). Compounding the matter, so few managers actually receive analyzed information for their decision-making or even have a strategy (Hammonds 2001, pp. 150-56).
Called by one expert (Herring 1998, pp. 13-16) the “brain” of a modern BI system, analysis is one of the more difficult roles that a BI specialist is called upon to perform and that a manager is called upon to oversee. The brain requires a good flow of oxygenated blood, or, in the case of BI, accurate and reliable data flow. The brain is a muscle, and like all muscles, it requires constant exercise to be fully effective. This exercise comes in the form of deep and regular thinking, which results in and causes enhanced learning. What does this all mean for the job of an analyst?
The job of an intelligence analyst is to protect and enhance his or her company’s competitive market interests by providing useful and high-quality analysis to decision-makers, policy-makers, and resource allocators (otherwise known as their “clients”). Analysis is given to these clients in the form of analysis process outputs such as assessments, briefs, bulletins, charts, conclusions, estimates, forecasts, issue reports, maps, premonitory reports, profiles, recommendations, and/or warnings. These analytical products are the most tangible manifestations of the outcomes of the analytical process.
So what is analysis? Analysis involves a variety of scientific and non-scientific techniques to create insights or inferences from data or information. For the purposes of this chapter, the working definition given previously suggests that analysis is the multifaceted combination of processes by which collected information are systematically interpreted to create intelligence findings and recommendations for actions. Analysis answers that critical “so what?” question about the information gathered, and brings insight to bear directly on the decision-maker’s needs, helping the client to make enlightened decisions. It is therefore both a process and a product (Fleisher 2001, pp. 176-80).
What purposes does analysis serve? In his influential 1980 book Competitive Strategy, Michael Porter asserted the need for sophisticated competitor analysis in organizations, and subsequently the need for an organized and systematized mechanism—some sort of competitor intelligence system—to make the process efficient (Porter 1980, pp. 147-52). Most managers in today’s competitive environments implicitly or explicitly recognize the need for more systematic analysis of their competitors, competition, and competitive landscape. However, recognizing that there is a need for the capability and putting into place the systems, structures, and skills needed to exploit that capability are very different things.
Numerous researchers through the years have identified enduring gaps between what is viewed as being needed for decision-making in organizations i.e., expectations) and what is actually being delivered by organizational competitor-analysis systems (i.e., performance). Langley (1995, pp. 63-76) notes that the analysis process serves intermediate decision-making purposes such as reducing the number of input variables, providing more time for decision-making as opposed to facts absorption, providing connections among seemingly unrelated data and information, providing a context by relating information to organizational mission, objectives, and strategy and creating a “working hypothesis” by making a story out of disparate business-environment information. Analysis usually takes place at multiple levels within an organization.
Strategic analysis is arguably the most vital form of intelligence, because it provides a framework within which other forms of intelligence collection and analysis take place, offers an overall assessment from the top down rather than from the bottom up, and helps to provide a basis for policy formulation, resource allocation, and strategy development. Tactical analysis is a necessary and important complement to work done at the strategic level. It is the natural linking element between macro-level analysis and the micro-level focus on individual cases. Operational intelligence analysis overlaps with investigation and is often single-case oriented. It involves technological assessments of the methods used for marketplace battles, specific investigations of competitive threats, and the like.
An important component of operational analysis is identifying the particular vulnerability or vulnerabilities that have been exploited and providing guidance on how it or they can be minimized or eliminated. Each of these analytical levels requires a direction or focus, a methodology, and some experience. To simply try to answer “tell me what you know” leaves one at a loss as to how to satisfy a manager’s requirements. Similarly “tell me everything about x” does little to support good analysis or an executive’s decision-making process. Poor analysis will in turn provide little room for quality decision-making.
The skill-set that the BI team leader possesses is vital to team success. Managers need to be able to understand the degree of management their particular team requires. Due to the creative and sometimes ambiguous nature of BI, team leaders must know when to step in and give direction or when to let the BI team members find their own resolution. Micromanagement from the team leader will likely undermine team effectiveness and inhibit team performance as members become dependent upon guidance or possibly resentful of interference (Simon 2000, pp. 8-10).
Too little direction from the team leader may lead to confusion with regards to the composition of team deliverables. The team does, however, need a certain level of direction, as a lack of team and project structure can decrease BI effectiveness (Simon 2000, 8-10). Effective planning can enhance team performance, as it allows the team to gain greater understanding of the thought processes and concerns of their colleagues. Proper planning can also ensure project alignment with the clients’ demands, and thus create a strategy that will fulfill the project’s overall purpose (Simon 2000, pp. 8-10).
It is important that BI managers also possess heightened communication and organizational skills, as it is their role to coordinate the BI function with that of the organization. More importantly the BI manager must build effective networks with the organization’s decision-makers in order to clearly and effectively relay project requirements to the team as well as communicate output from the team.
All team members need to possess certain skills to be effective BI professionals. They must be creative and resourceful, have a passion for delving deeply into issues, and be able to deliver finished intelligence products in a form that executives can utilize (Simon 2000, pp. 8-10). The skill-set of the BI team should invariably incorporate a broad array of expertise. By including members with only one type of educational or work background, the BI manager may inadvertently create a team that lacks vital skills. For instance, a team in which members consist only of scientists “may produce a report that lacks a business or social perspective, ” whereas a disproportionately “tactical team may lack strategy evaluation or strategic insights” (Simon 2000, pp. 8-10).
Strategic intelligence is information that helps the firms to direct and scope an organization over the long-run to meet the needs of markets and to maximize the shareholders’ wealth. In others words, strategic intelligence is intelligence that help the firms to create competitive strategy. Business intelligence is the application created to help the firms to use the advantage from the information transformed into intelligence. The management could create competitive strategy based on the intelligence that they receive from the application. We could say that Strategic Intelligence is the business intelligence in competitive strategy.
To be leader, firms should penetrate their market globally. Doing business in different markets mean that firms have to stay in the different environment. As a result, they have to handle with the huge amount of information. The bigger we are the more complicate we face. Luckily, the advance in business intelligence technologies enables the global companies to run business more efficiency. Information Technology is the main factor that helps firms to integrate the business function all over the world to unify the organization. Wherever the branches are, the information could transfer to the main server at the head quarter.
Today, external environment change rapidly. To create any strategy, customers and suppliers are the elements that firms should rely on. Customers are our market, we can not ignore their needs otherwise we will be out of business. Also, suppliers are the person that send raw material to us. To be partnership is the way to streamline the production process. The innovative management such as Enterprise Resource Management: ERP, Customer Relation Management: CRM and Supply Chain Management: SCM are the trendy knowledge management for businesses. These knowledge managements integrate the external environment (customers’ data and suppliers’ data) to strengthen the internal organization.
The analytical capability of business intelligence allows a company to move towards being a truly customer-oriented organization. CRM solutions employ a business strategy that merges business intelligence technologies with innovative marketing practices to retain customer relationship. The data is collected from the buying or using habits, age, sex, education of customers. Customers’ information helps business to determine lifetime value of customers, prioritize prospects and develop new products.
List of Some Business Intelligence and Solution Provider Companies
- ITtoolbox Business Intelligence. Web. – A business intelligence community for IT professionals. Focusing on data mining, reporting, queries, and other business intelligence disciplines.
- CRM Today – Business Intelligence – Provides news, events, articles, research reports, white papers and reviews.
- Business Intelligence.com – Communications platform for business & technical users, consultants, software vendors and analysts. Offers articles, research, white papers, industry news, jobs and training information.
- The Business Intelligence and Data Warehousing Glossary – Technology tour displays terms in logical order. Features alphabetical listing of terms and recommended reading.
- Strategic Assets – Provides advice on using an organization’s intellectual property to gain a competitive advantage. Features news, reports and links to related sites.
- Business Intelligence Toolbox – A business weblog with articles by professionals about business intelligence and market research.
- Meeting Industry-Specific Challenges With Business Intelligence Solutions – White paper discusses the changes affecting the financial services, telecommunications and retail industries and how BI solutions address industry-specific needs. By Erik Johnson and Megan Lordeon.
- Montague Institute – Membership organization for information professionals engaged in all aspects of managing intellectual assets in a business context. Features events, articles and membership information
- Business Intelligence Value Chain – Business Intelligence – How Agencies Can Breathe New Life Into Old Data
Conclusion
Information technology has forced many firms to take a serious look at their BI systems. Since large quantities of information are now available to BI professionals, organizations need to take a very close look at the strengths and weaknesses of both employees within the firm who are responsible for the BI function and the IT infrastructure that exists within the firm. A careful analysis of these two elements is essential in order to establish a good balance of TI and PI to ensure that the firm’s data, information, and intelligence needs are met.
Creating a healthy balance of PI and TI will increase the effectiveness of capturing the behavior of competitors, regulators, technologies, and other external influences. Additionally, a good balance between PI and TI will systematically integrate a wealth of internal and external information that was previously scattered among a variety of media.
How a company analyzes the data and disseminates the required information to the necessary people within the organization are essential. Front-line workers, such as sales and marketing employees, require current competitive information to ensure future success. The impact that the intelligence information has on the company for both short- and long-term decision-making is critical to the success of an organization’s current and future strategy. A company with a healthy BI system will have achieved an optimal balance of PI and TI, enabling it to thrive on industry change.
As is the case in many relatively youthful fields that have not yet reached maturity, the term business intelligence (BI) has both positive and negative connotations for its various stakeholders’ dimensions. This chapter has sought to systematically identify and assess these arguments. It does not suggest whether CI should or should not be replaced, but hopefully it delivers a balanced and fair view of arguments being offered on both sides.
Internet allows people to search for the information that they want to know. There are tons of choices provided for customers via the internet. They could search for the information that they want to know easily before making a choice. Also, the internet enhances companies to serve their customers 24 hours a day. The gap of profit is shortened time to time. Any businesses that provide the huge amount of profit will lead other parties to join in this market and then the profit would be less or no more profit at all. Only the stronger could be alive in the market.
We are living in the world of chaos and uncertainty. To deal with this world, we have to adapt ourselves to fit into the new environment. Be differentiate, be innovative, be creative and be customize, be quick are the powerful phrases for doing business in this edge. Businesses have to be creative, be innovative to differentiate themselves from the others. Otherwise, it’s no place for them in the market. To maintain one’s place in the market, business intelligence must be the top priority and core issue.
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