Concept Of Business Intelligence Research Articles

Natural intelligence applications for business intelligence in online and catalogue retailing firms: a case study

The rapid proliferation of business intelligence (BI) applications and customer relationship management (CRM) over the past decades has created many opportunities for natural intelligence theory to be used in business applications. The theory of natural intelligence can help to explain some of the strategies in the e-commerce arena. Indeed, companies have been using herd behaviour and swarm applications of natural intelligence to solve complex business operation problems. The sudden and unexpected failure and liquidation of one of the largest catalogue sales companies in the USA presents an opportunity for a unique case study for natural intelligence (NI) applications in retailing. This paper uses the experiences of three separate Fingerhut Companies (now Bluestem Brands) to validate the NI and BI concepts. For nearly two decades the authors have had the rare opportunity to interview executives and other representatives of critical members of the Fingerhut community. The paper ends with lessons learned and discussions of new insights.

Role of knowledge management and analytical CRM in business: data mining based framework

PurposeThe purpose of the paper is to provide a thorough analysis of the concepts of business intelligence (BI), knowledge management (KM) and analytical CRM (aCRM) and to establish a framework for integrating all the three to each other. The paper also seeks to establish a KM and aCRM based framework using data mining (DM) techniques, which helps in the enterprise decision‐making. The objective is to share how KM and aCRM can be integrated into this seamless analytics framework to sustain excellence in decision making using effective data mining techniques and to explore how working on such aCRM system can be effective for enabling organizations delivering complete solutions.Design/methodology/approachThis paper is based on focused and dedicated study of the literature present on the aCRM, KM and data mining techniques. The paper considered how to develop a strategy and operational framework that would build aCRM on the foundation of existing DM techniques and KM approach to meet the business challenges. Based on this research, a customized, integrated framework, to match the needs of business was designed.FindingsKM focuses on managing knowledge within the organization and aCRM focuses on gaining analytical information from the customer data. Both KM and aCRM help in the decision making process and understanding. This knowledge is difficult to uncover. Hence, this paper explains the importance of data mining tools and techniques to uncover knowledge by the integration between KM and aCRM. This paper presents an integrated KM and aCRM based framework using DM techniques.Research limitations/implicationsAll the firms may not be in favor of adopting KM while implementing aCRM. The KM requires a convalesce of organizational culture, technology innovations, effective work force in culminating knowledge dissemination in all business domains.Practical implicationsThe organizations implementing this knowledge enabled aCRM framework would be easily able to convert their business knowledge via the analytical CRM to solve many business issues, such as increase response rates from direct mail, telephone, e‐mail, and internet delivered marketing campaigns, increased sales and increased services. With aCRM, firms can identify their most profitable customers and use this knowledge for promotional schemes for those customers as well as identify future customers with prediction on ROI.Originality/valueThe need for the integration of KM and aCRM is clear. It is written for practitioners who are looking for approaches to improve business performance and maintain high profits for their business by incorporating knowledge‐enabled aCRM in their setup.

What is Business Intelligence?

There has been growing corporate interest in business intelligence (BI) as a path to reduced costs, improved service quality, and better decision-making processes. However, while BI has existed for years, it has difficulties reaching what specialists in the field consider its full potential. In this paper, the authors examine disparities in how the constructs of business intelligence are defined and understood, which may impede an understanding of what BI represents to business leaders and researchers. The main objective of this study is to clearly understand this emerging concept of BI. In this regard, the authors analyze articles from the scientific and professional literature to have a comprehensive understanding of business intelligence as both a product and a process. This research proposes a global overview of the conceptual foundations of BI, which can help companies understand their BI initiative and leverage them to the strategic level.

Business Intelligence – Fundamental Discipline Versus Industrial Espionage: Mutations Occured in Romanian Postintegration Strategic Management

The concept of Business Intelligence (BI ) was introduced in 1989 by the analist Howard Dresner from Gartner Group.The roots of this concept find itself in the '70 in the repport systems of the mainfrems, when the repports were static, bydimenssional and without analytical facilities, the demand for dynamic repporting systems, multi-dimensional, with support for predictive decisions determined the development of BI, that became reallity with the new technologies emergency. BI represents the art of knowing and putting in good use the informations, gaining competitional advantages. BI can offer answers at the essential problems of an organizations, helping he to take decisions for resolving it. The difference between BI and espionage is unclear delimited. For example, Robert Gates, the former director of CIA declared through the analyses of national security we prove the grown importance of international economic business intelligence. Approximately 40% of the new demands are of economic nature.

BUSINESS INTELLIGENCE: KONSEP DAN METODE

Recently, usage of Information Technology (IT) as assisting tools in business activities is becoming more common. Business transactions are conducted with support of IT tools so that they can be well processed by system. This is only a small part of IT usage in supporting business activities. IT role can be increased by designing and implementing a system which can extract and change business information from existing operational data so that in the end it can give support in formulating business decisions. This research will discuss the concept, benefits, categories, and method of Business Intelligence implementation.Keywords: business intelligence, method, balanced scorecard

Human Capital Management Process Based on Information Technology Models and Governance

Human capital management (HCM) inside large systems is very complex and demanding, to achieve successful accomplishment high quality information support is necessary. There are many cases where human capital management process is not conducted in a satisfactory way. Key decisions usually come late, very often because of impossibility to consider a problem in its entirety. The cause of it usually lies in weakness and understatement of the human capital management itself and in this connection data management is not given adequate consideration. Data originating from inside and outside sources within information system (IS) are not integrated in a way which will provide an optimal use. In this connection, this article examines possibilities to innovate the entire human capital management process through the integration of respective data. Data warehousing (DW) possibilities and position within the integral business intelligence (BI) concept are noted as a first step towards its realization. In this article the necessity to innovate and promote permanently the quality of human capital management process is considered; the main features of the process are given as well. Business process innovation (BPI) as a systematic approach with a view to achieve significant business process change is presented; its connection with data aspect of IS is given too. According to the research of this article, HCM BPI is achieved by the data integration within existing IS. DW model intended for HCM has been elaborated as a solution which will innovate the process itself. The position and the role of DW within entire BI organization concept have been established as well. Finally, the benefits achieved by the research are explained.

Real time business intelligence in supply chain analytics

PurposeRapid innovation and globalization have generated tremendous opportunities and choices in the marketplace for firms and customers. Competitive pressures have led to sourcing and manufacturing on a global scale resulting in a significant increase in products. The paper tries to identify the need for real time business intelligence (BI) in supply chain analytics.Design/methodology/approachThe paper provides argument and analysis of the advantages and hurdles in BI.FindingsThe paper focuses on the necessity to revisit the traditional BI concept that integrates and consolidates information in an organization in order to support firms that are service oriented and seeking customer loyalty and retention. Enhancing effectiveness and efficiency of supply chain analytics using a BI approach is a critical component in a company's ability to achieve its competitive advantage.Originality/valueThis paper furthers understanding of the issues surrounding the use of BI systems in supply chains.

Global sourcing strategy alignment using business intelligence: a conceptual framework

Many organisations do not have well-developed global sourcing measurement strategies in place, and thereby lose out on attractive business opportunities. Realising these opportunities requires a detailed understanding of global sourcing performance, which can be facilitated through Business Intelligence (BI) concepts applied in other areas of supply chain management. This requires amending inadequate one dimensional cost accounts of global sourcing with BI based inferencing. In this regard, this study aims to answer three questions: what are the determinants of successful global sourcing, what are the characteristics of such a BI system, and how can BI applications and strategies leverage global sourcing to achieve better performance? A conceptual framework is developed that integrates BI within the larger global sourcing framework, including macro- and microenvironmental factors, supply chain structure, optimisation and control, and global sourcing performance.

Conceptual analysis of business intelligence

The literature review shows that business intelligence (BI) has a long history even though its systematic use in the business context is more recent. Despite the importance of systematic BI, the concept is still trying to find a footing in both academia and the business world. From the literature review, one sees that there are numerous intelligence concepts and that their categorization is ambiguous. The BI concept is also multidimensional as there is no precise or universal conception of what BI is. The article aims to provide an analysis of BI definitions and related intelligence concepts, such as the content of each key concept, what it describes and how intelligence concepts relate to each other. Another objective of the article is to increase the academic understanding and status of this recent field of research on intelligence activities.

BUSINESS INTELLIGENCE AND KNOWLEDGE MANAGEMENT AS SUPPORT PRACTICES FOR STRATEGIC DECISION MAKING

This article is characterized as a theoretical rehearsal and treats of the capture, treatment and use of information as support to the strategic decision making, more specifically of the administration of the originated knowledge from competitive intelligence or business intelligence. Its objective is presents and to discuss the concepts of competitive intelligence and business intelligence, the differences between them and its approach as knowledge management function. The article analyzes the interface among business intelligence and knowledge management , and the complementarities of the two concepts, using as support the proposal of Anderson's approach (2006) known as The Long Tail (long tail). It concludes that the intelligence business or competitive is constituted in a linked managerial practice to the knowledge management, fundamental for the identification, capture and spread the useful information for strategic decisions.

Ontology-driven intelligent service for configuration support in networked organizations

Nowadays, organizations must continually adapt to market and organizational changes to achieve their most important goals. Migration to business services and service-oriented architectures provides a valuable opportunity to attain the organization objectives. This migration causes evolution both in organizational structure and in technology-enabling businesses to dynamically change vendors and services. One of the forms of organizational structures is the form of networked organization. Technologies of business intelligence and Web intelligence effectively support business processes within the networked organizations. While business intelligence focuses on development of services for consumer needs recognition, information search, and evaluation of alternatives; Web intelligence addresses advancement of Web-empowered systems, services, and environments. The paper proposes a technological ontology-driven framework for configuration support as applied to networked organization. The framework integrates concepts of business intelligence and Web intelligence into a collaboration environment of a networked organization on the base of attainment of knowledge logistics purposes. This framework referred to as KSNet is based on the integration of software agent technology and Web services. Knowledge logistics functions of KSNet are complemented by technological functions of knowledge-gathering agents. The services of these agents are implemented with CAPNET, a FIPA compliant agent platform. CAPNET allows consuming services of agents in a service-oriented way. Applicability of the approach is illustrated through a “Binni scenario”-based case study of a portable field hospital configuration.

Need for real time Business Intelligence

For companies maintaining direct contact with large numbers of customers, a growing number of channel-oriented applications (e.g. e-commerce support, call centre support) is creating a new data management challenge: that is effective ways of integrating enterprise applications in real time. To learn from the past and forecast the future, many companies are adopting Business Intelligence (BI) tools and systems. This paper argues that in order to support firms that are service oriented and desperately seeking customer loyalty and retention, it is necessary to revisit the BI concept that integrates and consolidates information in an organisation. To support the argument, the paper presents a case scenario to illustrate the role of BI in the supply chain.

Advances in intelligent information processing

Advances in intelligent information processing

Intelligent information processing in human resource management: an implementation case in China

Abstract: Information systems have been applied to human resource management (HRM) for decades. However, the way of using information systems and the way of processing information for HRM have evolved and dramatically improved over the last decade. More and more HRM systems today are being changed to e‐HRM systems. This is mainly due to the advent of Internet technology and the emerging concept of business intelligence. Our study shows the evolution of information systems and information processing in the HRM domain and provides an implementation case in a large Chinese state‐run factory. The experiences and lessons learned from this case reveal several common problems in developing information systems in the HRM domain.

Geotecnologias na Geografia aplicada

Geotechnologies are the set of technologies for collection, processing, analysis and presentation of information with geographic reference. The geotechnologies are composed for solutions in hardware, software and peopleware that together they constitute powerful tools for decision taking. Among the geotechnologies we can detach: geographic information systems, digital cartography, remote sensing, global positioning system and georeferenced topography. The extension of Brazilian territory and low knowledge about natural resources, besides the high cost of getting information by the use of conventional methods comprised decisive factors that led the country to the remote sensing by satellite program. Currently, it is estimated that about 80% of the activities provided by a city hall are dependent on localization. New concepts of business intelligence cannot to do without geoprocessing tools, which are able to map some critical factors needed to reach success in business. As well as in public services, like sanitation, electric energy supply and telecommunication, geotechnologic tools can be used to relate their distribution nets to the remaining information contained in their databases.

Regional intelligence: distributed localised information systems for innovation and development

Technological information is recognised as an important factor shaping regional systems of innovation and innovative regions. However, little has been written on how regions set up and manage this vital resource. This paper focuses on regional intelligence: distributed information systems localised over a region allowing continuous update and learning on technologies, competitors, markets, and the environment. We start by defining regional intelligence with respect to the concepts of business intelligence, organisational, and collective intelligence. We look at a number of case studies and experiences gained in the context of EU regional innovation and regional economic strategies, which highlight early forms of regional intelligence. We examine the fundamental information modules making up regional intelligence, including, R&D dissemination, technology and market watch, company benchmarking and competition analysis, regional foresight, and regional performance. We discuss the integration of distributed information systems and solutions which may be given to consolidate public content applications with the internal information systems of companies, and the role of information integration in the continuous making and remaking of innovative regions.

Web Business Intelligence: Mining the Web for Actionable Knowledge

It is estimated that over seven billion static pages exist in the Web today, and backend databases can potentially produce at least three times as many dynamic pages. However, the best search engines index only approximately 20% of the static pages. So the real question is: While the Web is certainly the most amazing and comprehensive information source ever created, are you really getting all the information you need for your specific purpose? The answer to this question is mostly “yes” for the individual user, who uses the Web as an information source for casual purposes. However, for an individual who uses the Web as an essential and comprehensive source of information—for business or research—the answer is quite the opposite. Even a sophisticated Web user requires a significant amount of time and effort to find all of the information needed for a given task. In this paper the concept of Web Business Intelligence (WBI) is introduced, an emerging class of software that leverages the unprecedented content on the Web to extract actionable knowledge in an organizational setting. The contributions include an architecture for WBI, a survey of technologies relevant to the various components of the architecture, and illustration of the value of WBI by means of a detailed example from the e-finance domain. This article concludes with a discussion on the future of WBI.

A Recipe for Business Intelligence Success

Much of corporate America has accepted the concept of competitor or business intelligence. As evidence of this, many Fortune 500 companies have already established intelligence departments and are beginning to build databases dedicated to competitor or marketplace intelligence.