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

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.

2020 ◽  
Vol 9 (11) ◽  
pp. 671
Author(s):  
Alexander Bustamante ◽  
Laura Sebastia ◽  
Eva Onaindia

Integrating collaborative data in data-driven Business Intelligence (BI) system brings an opportunity to foster the decision-making process towards improving tourism competitiveness. This article presents BITOUR, a BI platform that integrates four collaborative data sources (Twitter, Openstreetmap, Tripadvisor and Airbnb). BITOUR follows a classical BI architecture and provides functionalities for data transformation, data processing, data analysis and data visualization. At the core of the data processing, BITOUR offers mechanisms to identify tourists in Twitter, assign tweets to attractions and accommodation sites from Tripadvisor and Airbnb, analyze sentiments in opinions issued by tourists, and all this using geolocation objects in Openstreetmap. With all these ingredients, BITOUR enables data analysis and visualization to answer questions like the most frequented places by tourists, the average stay length or the view of visitors of some particular destination.


2008 ◽  
Vol 2 (2) ◽  
pp. 111 ◽  
Author(s):  
Eka Miranda

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


2019 ◽  
Vol 8 (4) ◽  
pp. 12365-12372

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.


2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Abdul Hamid Arribathi ◽  
Maimunah Maimunah ◽  
Devi Nurfitriani

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.


2018 ◽  
Vol 28 (5) ◽  
pp. 1489-1496
Author(s):  
Branislav Stanisavljević

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Danielle Sponder Testa ◽  
Elena E. Karpova

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.


2019 ◽  
Vol 1 (1) ◽  
pp. 51-57
Author(s):  
Maria Liana Lacatus

The paper presents important issues of decision making processes with an emphasis on rational and irrational components of these processes. After a short introduction outlining the need for a deeper understanding of rational and non-rational factors that affect the decisions people make, the rationality of people decisions in daily life is questioned and the role of non-rational factors such as intuition are analyzed. The economic understanding of the decision making process is presented and principles of rational decision-making are explained. Different methods used and recommended by economists in order to make decisions are presented and applied in different life situations in order to demonstrate their value in daily life. Special emphasis is put on factors such as imperfect information, illusion of control, or risk aversion that may affect the rationality of the decision making processes. In the final section of the paper the concept of bounded rationality is introduced and explained along with new theories in economics that are challenging the classic economic perspective on the decision making process


Author(s):  
Agata Mardosz-Grabowska

Organizations are expected to act rationally; however, mythical thinking is often present among their members. It refers also to myths related to technology. New inventions and technologies are often mythologized in organizations. People do not understand how new technologies work and usually overestimate their possibilities. Also, myths are useful in dealing with ambivalent feelings, such as fears and hopes. The text focuses on the so-called “big data myth” and its impact on the decision-making process in modern marketing management. Mythical thinking related to big data in organizations has been observed both by scholars and practitioners. The aim of the chapter is to discuss the foundation of the myth, its components, and its impact on the decision-making process. Among others, a presence of a “big data myth” may be manifested by over-reliance on data, neglecting biases in the process of data analysis, and undermining the role of other factors, including intuition and individual experience of marketing professionals or qualitative data.


Data Mining ◽  
2013 ◽  
pp. 550-566 ◽  
Author(s):  
Zaidoun Alzoabi ◽  
Faek Diko ◽  
Saiid Hanna

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.


Author(s):  
Andrea Ko

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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