Business Intelligence in Management of Organizations

The Essence of Business Intelligence

The first chapter of the book stresses that the environment in which modern organizations operate is extremely complex and unstable. To respond quickly to market needs, organizations face the imperative to utilize various technologies and decision support systems. Organizations need intelligent solutions that would be able to analyze a variety of data from different, distributed sources and discover new knowledge for the decision-making process (Bui, 2000; Carlsson & Turban, 2002; Gray, 2003; Gray & Watson, 1998; Laudon & Laudon, 2004).

In the opinion of many authors, the solution that responds to the needs of modern organizations is Business Intelligence (BI) systems. Global reports from firms such as the Gartner Group, the Australian Computer Society, and Oracle and Teradata indicate that BI and advanced analytics have become an important area of research that reflects the importance of information in solving the problems of a modern organization. Research results reveal that BI systems can contribute to streamlining the decision-making process, improving customer relationship management, monitoring the environment, as well as detecting anomalies and business fraud (Kalakota & Robinson, 1999; Liautaud & Hammond, 2001; Moss & Alert, 2003; Olszak, 2016).

It is argued that a special role of BI was marked when managers faced the necessity of (a) taking into account many data in the decision-making process, often from different sources; (b) handling historical data; (c) manipulating synthetic data; (d) predicting the future and creating long-term plans; (e) conducting continuous control over the implementation of actions taken, both operational and strategic in nature; and (f) responding quickly to market changes and taking into account competition activities.

Although the BI issue has been developing for many years, there is still no consistency with the interpretation of this term. There are many reasons for this. The very term intelligence can be understood differently. Intelligence is sometimes associated with the intellectual abilities of a human being, skills in abstract thinking and learning, as well as perceiving the relationships between different facts and drawing various conclusions on this basis. The term “intelligence” can also mean the ability to adapt to new conditions and perform new tasks using the means of thinking. It is worth stressing that intelligent behavior and action have been attributed only to human beings for many years. Nowadays, this characteristic is also attributed to computers, software, various objects, products, as well as entire industries (sectors) and organizations. As a consequence, the term Business Intelligence (BI) appeared.

It is believed that the term Business Intelligence was first used in the 1980s by H. Dresner of the Gartner Group. However, some say that as early as 1958, H. P. Luhn used this term to describe data analysis tools (Anandarajan Sc Srinivasan, 2004). Today, it is often identified with: (a) data analysis tools and technologies, data warehouse (Inmon, Strauss, Sc Neushloss, 2008); (b) a decision support system (Alter, 2004; Baaras Sc Kemper, 2008; Negash, 2004); (c) Competitive Intelligence (Albescu, Pugna, & Paraschiv, 2008; Sauter, 2010; Styl, 2012); (d) knowledge management (Negash Sc Gray, 2008; Wells, 2008); (e) information- and knowledge- based organizational culture (Liautaud Sc Hammond, 2001); (f) process focused on collecting, analyzing and sharing information (Jourdan, Rainer, Sc Marschall, 2008); (g) analytics (Davenport Sc Harris, 2007); (h) Big Data (Schmarzo, 2013); and (i) a research field, denoting a holistic view of decision support (Gray, 2003; Liautaud Sc Hammond, 2001; Moss Sc Alert, 2003; Simmers, 2004). Selected interpretations of the term BI are presented in Table 2.1.

While interpreting the BI term, it is important to consider its two main approaches (Isik, Jones, Sc Sidorova, 2011; Moss Sc Atre, 2003): technical and managerial. In technical terms (and this first appeared in describing the essence of BI), BI means an integrated set of tools, technologies, and software products for collecting heterogeneous data from various distributed sources, integrating, analyzing, and sharing them (Reinschmidt Sc Francoise, 2000). These primarily include a data warehouse, Online Analytical Processing (OLAP) tools, and data mining techniques. The data warehouse is responsible for integrating various data from distributed sources. In turn, OLAP tools enable their multidimensional analysis, and data mining techniques are used to detect previously unknown correlations and relationships between data.

In a managerial approach, it is emphasized that information and knowledge are strategic resources of an organization, andhadvanced data analysis allows not only

Table 2.1 Selected Definitions of Business Intelligence



Adelman and Moss (2000)

A term comprising a wide range of software for collecting, consolidating, analyzing and sharing information that enables better decision-making for organizations

Alter (2004)

A term referring to decision support

Business Objects (2007)

Providing various data, information, and analyses to employees, customers, and suppliers to improve decision-making

Cognos (2007)

Bl connects people and data, offering various ways of looking at information that support decision-making

Chang (2005)

Accurate, timely, and relevant data, information, and knowledge that support strategic and operational decisions, risk assessment in an uncertain and dynamic environment of the organization

Chung, Chen, and Nunamaker (2005)

Results obtained by collecting, analyzing, assessing, and using information in business

Davenport, Harris, and Morison (2010); Watson, (2010)

An umbrella that is commonly used to describe the technologies, applications, and processes for gathering, storing, accessing, and analyzing data to help users make better decisions

Dresner et al. (2002)

A term comprising a set of concepts and methods used to improve decision-making using decision support systems

Eckerson (2005)

A system that transforms data into various information products

Cangadharan and Swami (2004)

The result of using deep analyses on business data in databases

Gartner Research (Hostmann, 2007)

A term comprising analytical applications, infrastructure, platforms, and best practices

Hannula and Pirttimaki (2003)

An organized and systemic process that is used to collect, analyze, and share information to support operational and strategic decisions

IBM (Whitehorn & Whitehorn, 1999)

A term comprising a broadly understood process aimed at extracting valuable information from various organization's data resources


Table 2.1 Continued



Informatica, Teradata, MicroStrategy, Markarian, Brobst, and Bedell (2007)

Interactive process of exploration and analysis of structured, domain-specific information (stored in data warehouses) aimed at discovering trends and patterns

Isik, Jones, and Sidorova (2011)

Bl means a holistic and sophisticated approach to cross-organizational decision support

Jourdan et al. (2008)

Processes and products that are used to create relevant information necessary for functioning in a global economy and predicting the behavior of the business environment

Kulkarni and King (1997)

A product of business data analysis using intelligent tools

Lonnqvist and Pirttimaki (2006)

Management philosophy and a tool that helps manage and make more effective decisions

Moss and Atre (2003)

Architecture and a collection of integrated operations as well as decision support applications and data warehouses that provide organizations with easy access to business data

Moss and Hoberman (2004)

Processes, technologies and tools that are necessary to transform data into information, information into knowledge, and knowledge into activities that benefit an organization. Bl comprises data warehouses, analytical tools, and knowledge and content management

Negash (2004)

A system that integrates and stores data, manages knowledge using analytical tools so that decisionmakers can convert information into a competitive advantage

Olszak and Ziemba (2006)

A set of concepts, methods, and processes whose goal is not only to improve business decisions but also to support an organization's strategy

Oracle (2007)

A portfolio of technologies and applications that provide an integrated organization management system, including finance, management, Bl applications, and data warehouses

Table 2.1 Continued



SAS Institute (Ing, 2011)

Providing the right information to the right people, at the right time, to support better decision-making and competitive advantage

Turban et al. (2014)

A term that comprises tools, architectures, databases, data warehouses, performance management and methodologies which are integrated within unified software

Watson, Fuller, and Ariyachandra (2004)

A system that assists users in managing large quantities of data and in making decisions

White (2004)

A term comprising data warehouses, reporting, analytical processes, performance management, and predictive analyses

Williams and Williams (2007)

A combination of products, technologies, and methods for discovering key information to improve profits and productivity within the organization

faster decision-making but also enables the discovery of new business opportunities and the identification of factors on which this development depends (Laudon &C Laudon, 2018). In other words, BI stands for the synergy of data, information, processes, tools, and technologies for data mining and multidimensional analysis (Wells & Hess, 2004; Liautaud & Hammond, 2001). Such synergy, according to many researchers (Kalakota & Robinson, 1999; Turban et ah, 2014), serves to improve the decision-making process, in particular to improve the quality of expertise, forecasting event scenarios, developing good business practices, as well as building a network of experts and competence centers. It is also claimed that BI enables discovering new knowledge that is important from the point of organization’s competitiveness, entering new markets, acquiring new customers, and introducing new sales channels. In the opinion of some authors, BI means a new work culture based on information sharing (Gray, 2003). It is also highlighted that BI facilitates the development of various strategic initiatives aimed at (Figure 2.1): (a) carrying out fundamental changes in an organization, establishing new relationships and introducing innovative products; (b) optimizing relationships with customers, suppliers, and other stakeholders; (c) modifying and improving business strategies in order to obtain a competitive advantage, improving business processes, increasing profitability and achieving set management goals; and (d) a better understanding of the functioning of organization, minimizing the risk of business operations, and improving organization’s performance.

Business Intelligence in reinforcing organization's management

Figure 2.1 Business Intelligence in reinforcing organization's management.

Source: Own elaboration based on (Dresner et a!., 2002).

The difficulty in interpreting the term Business Intelligence stems from the fact that BI can relate to various fields. Terms such as Marketing Intelligence, Finance Intelligence, and Competitive Intelligence are used more often. Marketing Intelligence primarily focuses on comprehensive customer analysis, market segmentation, direct marketing, as well as modeling and predicting market events. In turn, Financial Intelligence means integrating financial information from many sources, which is particularly important for capital groups and international corporations. It serves, inter alia, multidimensional financial reporting, and processing what-if scenarios using real-time data such as cash flow, financial performance, and measuring effectiveness of an organization using a scorecard. Competitive Intelligence, on the other hand, involves systematic identification and analysis all competitors’ activities. This term is sometimes identified with BI, including all activities involving the search, processing, and dissemination of information useful to various economic entities (Kalakota & Robinson, 1999).

Analyzing the essence of BI, it is hard not to refer to the relationship of BI with decision support systems. Many authors are of the opinion that BI represents

Place of Business Intelligence in decision-making

Figure 2.2 Place of Business Intelligence in decision-making.

a new generation of decision support systems aimed at transforming specific data into information and knowledge. Their goal is to increase the efficiency of decisionmaking at all levels of management, improve business processes and relations with stakeholders, and ultimately achieve organizational success (Figure 2.2).

It is stressed that BI systems differ from previous decision support systems (DSS, EIS, ES) not only in architecture, construction techniques but, above all, in much wider functionality (O’Brien & Marakas, 2007). BI systems integrate the possibilities of the mentioned solutions, which previously operated independently. They focus on supporting various business functions and supporting decisions at all levels of management, using advanced analytical techniques (Glancy & Yadav, 2011). In strategic planning, BI allows firms to precisely set goals and track their implementation. They allow for making various comparisons, e.g., historical results, profitability of individual offers, effectiveness of distribution channels, as well as conducting simulations and forecasting future results. By contrast, at the tactical level, BI systems provide the basis for making decisions in the areas of marketing, sales, finance, and capital management. They allow users to optimize future activities and properly modify the organizational, financial, and technological aspects of the enterprise’s operation so that it can more effectively achieve its strategic goals. In turn, at the operational level, BI systems are used to perform ad hoc analyses, answer questions related to the current state of finances, sales, and the state of cooperation with suppliers, recipients, and customers.

BI systems, unlike earlier decision support systems, enable work with multidimensional, personalized information and knowledge (Reinschmidt & Francoise, 2000). Multidimensional analyses provide a holistic view of business processes, decision making, anticipation of the future, projection of various business event scenarios, as well as in-depth analysis and monitoring of organization’s current situation.

It is emphasized that BI systems offer access to static and dynamic knowledge (created on the basis of ad. hoc queries and information obtained from databases and data warehouses). Thus, they encourage decision-makers to seek new knowledge and show them the information in a new light. This can become an inspiration for the development of new forms of cooperation, new ways of acquiring customers, as well as creating new markets and original offers for customers. It is believed that by sharing various techniques in the field of analysis, data mining, and visualization, the openness, activeness, commitment, and creativity of users of such systems increase.

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