scholarly journals PENGEMBANGAN BUSINESS INTELLIGENCE BAGI PERKEMBANGAN BISNIS PERUSAHAAN

2008 ◽  
Vol 2 (2) ◽  
pp. 111 ◽  
Author(s):  
Eka Miranda
Keyword(s):  
Decision Making ◽  
Competitive Advantage ◽  
Business Intelligence ◽  
Raw Material ◽  
Decision Making Process ◽  
Business Decision

This article discusses the Business Intelligence and its role to improve the company’s competitive advantage through the utilization of various data, information and knowledge held by the company as a raw material in the decision making process. This article also explains the elements of Business Intelligence applications, Business Intelligence Environment, integrating BI into the enterprise and the challenges faced by organizations in giving effect to Business Intelligence.Keywords: Business Intelligence, business decision

BUSINESS INTELLIGENCE AND POWER OF KNOWLEDGE

2018 ◽  
Vol 28 (5) ◽  
pp. 1489-1496
Author(s):  
Branislav Stanisavljević
Keyword(s):  
Decision Making ◽  
Financial Performance ◽  
Competitive Advantage ◽  
Business Intelligence ◽  
National Economy ◽  
Business Performance ◽  
Medium Size ◽  
Business Decision ◽  
Economic Point ◽  
Insight Into

Research carried out in the last few years as the example of companies belonging to the category of medium-size enterprises has shown that, for example, typical enterprises, of the total number of data processed in information of importance for its business, seriously takes into consideration and process only 10% of the observed firms. It is justifiable to ask whether these 10% of the processed and analyzed business information can have an adequate potential or motive power to direct the organization to success that is measured by competitive advantages and on a sustainable basis? Or, the question can be formulated: what happens to the rest, mostly 90% of the information that the enterprise does not transform into a form suitable for business analysis and decision-making. It is precisely the task of business intelligence to find a way to utilize all the data collected and processed in the business decision-making process. In this regard, we can conclude that Business Intelligence is, in fact, the framework title for all tools and / or applications that will enable the collection, processing, analysis, distribution to decision-making bodies in the business system in order to derivate from this information valid business decisions - as the most important and / or most important task of the manager. Of course, from an economic point of view, the best decisions are management decisions that provide a lasting competitive advantage and achieve maximum financial performance. This means that business intelligence actually allows a more complete and / or comprehensive view of the overall business performance of all its parts and subsystems. But the system functions can be measured essential and positive economic and financial performance, as well as the position in the branch of the business to which it belongs, and wider, within the national economy. (Of course, today the boundaries of the national economy have become too crowded for many companies, bearing in mind globalization and competitiveness in the light of organization of work and business function). The advantage of business intelligence as a model, if accepted at the organization level, ensures that each subsystem in the organization receives precisely the information needed to make development decisions, but also decisions regarding operational activities. So, it should be born in mind that business intelligence does not imply that information is shared on some key words, on the contrary, the goal is to look at the context of the business, or in general, and that anyone in the further decision hierarchy can manage exactly the same information that is necessary for achieving excellent business performance. Because, if the insight into the information is not complete, the analysis is based on the description of individual parts, i.e. proving partial performance in the realization of individual information, which can certainly create a space for the loss of the expensive time and energy. Illustratively, if the view, or insight into the information, is not 100%, then all business decision-making is like the song of J.J. Zmaj "Elephant", about an elephant and a blindmen, where everyone feels and act only on the base of the experienced work, and brings judgment on what is what or what can be. As in this song for children, everyone thinks that he touches different animals and when they make claims about what they feel, everyone describes a completely different life. Therefore, business intelligence implies that information is fully considered and it is basically the basis or knowledge base, and therefore the basis of business excellence. In doing so, the main problem is how information is transformed into knowledge and based on it in business decision making. It is precisely in this segment that the main advantage of business intelligence is its contribution to the knowledge and business of the company based on power of knowledge. Therefore, for modern business conditions, it is characteristic that the management of the company is realized on the basis of partial knowledge about stakeholders (buyers, suppliers, competitors, shareholders, governments, institutional framework, legislation), and only a complete overview of managers at the highest level in all these partial interest groups allows managers to have a “boat” called the organization of labor leading a safe hand through the storm, Scile and Haribde threatens to endanger business, towards a calm sea and a safe harbor - called a sustainable competitive advantage based on power and knowledge.

scholarly journals Evaluation of application of new decision-making methods in selected companies: the use of business intelligence in practice

ACC Journal ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 29-40
Author(s):  
Petra Kašparová
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Business Intelligence ◽  
Questionnaire Survey ◽  
Human Life ◽  
Utilization Rate ◽  
Decision Making Process ◽  
Short Introduction ◽  
Business Decision

Growing pressure on increasing decision-making speed in all spheres of human life is one of the basic phenomena of today. Immediately after the first wave of the coronavirus pandemic, we can consider the ability of making good decisions quickly as one of the most important aspects of our being. The main objective of this article is to find out the utilization rate of several basic decision-making approaches in selected companies with an emphasis on newly used methods such as data analysis and business intelligence tools. The first part of the article presents a short introduction of the decision-making process and an overview of hitherto known and used tools facilitating the whole procedure. The submitted study of available literature leads to the presentation of own classification of the most widely used decisionmaking methods. Based on a questionnaire survey, in the second section, the pilot research examines the involvement of five different groups of methods in business decision-making, such as intuition and previous experiences, consultation with colleagues, data analysis (historical), MCDM methods and consultation with experts. Afterwards, the most common obstacles that employees must face in introducing new tools have been identified. In general, the results show that time and the associated pressure on decision-making speed play a crucial role in the decision-making process.

scholarly journals Data Warehouse Testing: A Step Towards using Business Intelligence in Banking

2019 ◽  
Vol 8 (4) ◽  
pp. 12365-12372
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Intelligence ◽  
Business Performance ◽  
Quality Analysis ◽  
Decision Making Process ◽  
Management Problem ◽  
Process Data ◽  
Report Generation ◽  
Business Decision

In the modern era, technology plays a vital role by contributing in the development of business by providing various tools and techniques to enhance the business decision-making process. Data warehouse is an important entity that contributes to the decision-making process, which can be seen in the literature available over the years. Data warehouse provides the basis for quality analysis of available data by deriving accurate information from data. Like many other industries, banking sector is also facing challenges due to various reasons like large over-dues, non-performing assets, changing customer demographics, matching customer expectation levels, increased competition from financial technological companies and banking competitors, etc. Thus data warehouse system serves to be the best solution for the banks to overcome challenges as data warehouse system integrates all the data at one place and provides a consolidated view of the past transactions which can be used for report generation and performing analytical analysis in order to help the management to maximize business performance. In addition to making strategic decisions, data warehouse also assist in helping the banks to improve customer retention, optimize discounting, market segmentation, business performance, customer deposits, etc. Thus, a data warehouse system provides a solution to all data management problem and generate patterns and reports for analytical end users for enhancing decision making processes. In this research paper, we shall be representing a bank model that focuses on the loan department of a bank data warehouse and shall be explaining how business intelligence plays a role in improving the loan analysis for the banks. Loan analysis may include summarizing the classified loans, analyzing loans within and exceeding the threshold limits of Loan-To-Value (LTV) ratio, analysis of loan rejections and other analysis pertaining to loans.

Implementation System of Business Intelligence System In The Company

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Research Library ◽  
Decision Making Process ◽  
Intelligence System ◽  
Business Intelligence Systems

This study aims to determine the stages that must be implemented in building a Business Intelligence System structured and appropriate in building Business Intelligence Systems in an organization, and understand the important aspects that must be considered for investment development Business Intelligence System is increasing. Business must be based on the conditions and needs of the organization in achieving the desired goals. If these conditions occur, then the decision-making process will be better and more accurate. The purpose of this study is to determine the important aspects that must be understood and prepared in using the Business Intelligence System in an organization. The method used is the explanation as well as the research library of several books, articles and other literature.

Achieving Global Competitive Human Resources in the Industrial Revolution

2021 ◽  
Author(s):  
Pang william panggantara
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Human Resources ◽  
Competitive Advantage ◽  
Industrial Revolution ◽  
Global Market ◽  
Massive Transformation ◽  
Business Decision ◽  
Fourth Wave

Fourth wave of industrial revolution is marked by the use of information technology, artificial inteligence (A.I), and automatic engines. Competitive advantage has become a necessity for every business actor when they wants to competing in the global market. The current condition definitely encouraging the occurence of massive transformation at all business levels and units this condition happens because every business actor can enter from and any other countries markets easily. this condition making professionalism of every business actor is highly prioritized like many case in the business decision making and continous innovation.

scholarly journals Executive decision-making in fashion retail: a phenomenological exploration of resources and strategies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Danielle Sponder Testa ◽  
Elena E. Karpova
Keyword(s):  
Decision Making ◽  
Academic Research ◽  
Phenomenological Approach ◽  
Study Data ◽  
Decision Making Process ◽  
Business Decision ◽  
Content Type ◽  
External Data ◽  
Executive Decision Making ◽  
Fashion Retail

PurposeDecision-makers must be well-informed to successfully impact the future of the business. The purpose of this study was to explore experiences of US fashion retail executives when making business decisions to understand what resources and strategies are utilized within the decision-making process. Additionally, the role of academic research within executive decision-making process was explored.Design/methodology/approachThis study utilized a phenomenological approach to understand the experiences of fashion retail executives when engaging in business decision-making. Fifteen US fashion retail executives participated in the study. Data were collected through in-depth individual interviews and thematically coded to gain a holistic perspective of the decision-making process within the fashion retail industry.FindingsAs the result of the data analysis and interpretation, three topical areas emerged:: “Incredible Amounts of Information,” “Industry Specific Academic Research” and “Have a Clear Road Map.” The findings suggested that while the facts gleaned from internal and external data are of great importance to fashion professionals, insights gathered from social media are equally influential within the decision-making process. The authors identified five major strategies utilized consistently by fashion retail executives regardless of the type of business they represented: collaboration, adaptability, speed, gut instinct and creativity.Research limitations/implicationsThe results are important to fashion retail companies for improving internal decision-making processes. The identified resources and strategies of the decision-making process can be incorporated into fashion program curricula and considered as learning outcomes when preparing future industry professionals.Originality/valueLimited studies have explored the decision-making process specific to the fashion retail environment, an uncertain and ever-changing industry. Further, the study shed light on the opportunity for academic research use in fashion retail decision-making and contributes to the literature by developing a fashion retail decision-making model.

Convergence Marketing

2012 ◽  
pp. 274-290
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Competitive Advantage ◽  
Relationship Marketing ◽  
Customer Value ◽  
Emerging Technologies ◽  
Market Competition ◽  
Customer Management ◽  
Decision Making Process ◽  
Customer Knowledge

The convergence marketing has emerged as an outgrowth of relationship marketing. Many firms in the competitive marketplace prefer on developing strategies by convergence of technology with customer value in promoting products and services. It is argued in this chapter that such convergence among the firms involve consumers, social networks, and technology that influence the decision making process for gaining competitive advantage. This chapter discusses the attributes of convergence of technology with customer value that provides higher competitive advantage to the business through frequent interactions among the market players and customers. The convergence marketing emphasizes on strategic, reflective, and organizational look at relationship marketing and contributes to existing knowledge within three fundamental elements including organizational customer focus, customer management focus, and customer knowledge focus. This chapter also examines how convergence of technology and customer value drives value co-creation in the firms and discuss that in an increasing market competition, customers interact with emerging technologies, and consumer communities co-create value with firms.

Suggested Model for Business Intelligence in Higher Education

Data Mining ◽  
2013 ◽  
pp. 550-566 ◽  
Author(s):  
Zaidoun Alzoabi ◽  
Faek Diko ◽  
Saiid Hanna
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Business Intelligence ◽  
University Management ◽  
Suggested Model ◽  
Business Decision ◽  
Data Mining Approach ◽  
Input Processing ◽  
The University

BI is playing a major role in achieving competitive advantage in almost every sector of the market, and the higher education sector is no exception. Universities, in general, maintain huge databases comprising data of students, human resources, researches, facilities, and others. Data in these databases may contain decisive information for decision making. In this chapter we will describe a data mining approach as one of the business intelligence methodologies for possible use in higher education. The importance of the model arises from the reality that it starts from a system approach to university management, looking at the university as input, processing, output, and feedback, and then applies different business intelligence tools and methods to every part of the system in order to enhance the business decision making process. The chapter also shows an application of the suggested model on a real case study at the Arab International University.

Organizational Data Mining (ODM)

2011 ◽  
pp. 1-8
Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Competitive Advantage ◽  
Current Status ◽  
Decision Making Process ◽  
Actionable Knowledge ◽  
The Core ◽  
Mining Tools

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.

Risks Evaluation and IT Audit Aspects of Business Intelligence Solutions

2010 ◽  
pp. 17-40
Author(s):  
Andrea Ko
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Information Systems ◽  
Business Intelligence ◽  
Decision Making Process ◽  
Future Trends ◽  
Security Risks ◽  
Business Intelligence Systems ◽  
Audit Approach ◽  
It Audit

Many organizations are struggling with a vast amount of data in order to gain valuable insights and get support in their decision-making process. Decision-making quality depends increasingly on information and the systems that deliver this information. These services are vulnerable and risky from security aspects, and they have to satisfy several requirements, like transparency, availability, accessibility, convenience, and compliance. IT environments are more and more complex and fragmented, which means additional security risks. Business intelligence solutions provide assistance in these complex business situations. Their main goal is to assist organizations to make better decisions. Better decisions means that these solutions support the management of risks, and they have a key role in raising revenue and in reducing cost. The objectives of this chapter are to give an overview of the business intelligence field and its future trends, to demonstrate the most important business intelligence solutions, meanwhile highlighting their risks, business continuity challenges, and IT audit issues. In spite of the fact that this chapter focuses on the business intelligence solutions and their specialities, risk management and the related IT audit approach can be applied for other categories of information systems. IT audit guidelines, best practices, and standards are presented as well, because they give effective tools in controlling process of business intelligence systems.

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