Business Intelligence Implementation Research Articles

Factors driving business intelligence adoption: an extended technology-organization-environment framework

Business intelligence (BI) is a vital component for businesses of all scales, offering actionable insights crucial for timely decision-making. This technology has become integral across diverse enterprises. Recognizing the factors influencing BI adoption is imperative, and this article employs the organization, complexity, knowledge, technology, user perception and experience, economic, environmental, and social (OCKTUEES) framework to identify key aspects. Building upon the TOE framework, it pinpoints significant variables, emphasizing the importance of factors like user perception and experience, technology, social, economical, and environmental. Employing structural equation modelling on primary data yields actionable insights to address BI adoption challenges. Analysis reveals the user perception and experience, technology, social, economic, and environmental as the top factors. However, the organization appears vulnerable, necessitating a mitigation strategy for successful BI adoption. The study predicts insignificant variables requiring mitigation, such as high costs, inadequate resources, organizational size, security and privacy concerns, risk of open-source adoption, and perception of analytics impacting jobs. This research aids those navigating the BI implementation journey.

Business Intelligence System and Firms’ Adaptive Ability: Evidence from Developing Country

Purpose: This study assessed the relationship between business intelligence system and firm ability for adaptation Method: A survey research design and sample of one hundred and twenty-four (124) employees of Fintech firms were used. Essentially, three (3) business intelligence systems were used such as technology skill, business forecasting and strategic planning. Data obtained in the survey were analyzed using independent sample t-test statistical too Results and Conclusion: Findings revealed strong and significant variations in business forecasting, strategic planning and technology skill and ability of Fintech companies to adapt. The study concludes that there is relationship between business intelligence system and firm ability for adaptation. Implication of the Research: The implication of the finding is that systems of business intelligence are vital particularly in areas of technology skill, forecasting and strategic planning which aid the ability of Fintech companies to adapt Originality/Value: This study assessed how business forecasting, strategic planning and technology skills which are vital elements of business intelligence can be carried out constantly and collaboratively by including all units/departments concerned with process and implementation of business intelligence

Roadmap for Implementing Business Intelligence Systems in Higher Education Institutions: Systematic Literature Review

Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs.

Healthcare Value Chain and the Impact of Analytics & BI

This study aims to investigate how the existing healthcare value chain system has significantly been impacted as a result of the increasing adoption and implementation of analytics and business intelligence (A&BI) capabilities. Given the increasing interest and investment in A&BI, it is important to have a good understanding of what A&BI capabilities healthcare organizations are utilizing to enhance value. Based on extensive search of the literature and a follow-up case study of a large regional hospital, it was found that the existing healthcare value chain (HCVC) framework is outdated and no longer effective. We therefore revised and updated the existing framework to meet the current needs of modern healthcare practices. Moreover, A&BI applications currently being deployed in healthcare organizations were identified and mapped onto the revised framework. The study contributes by illustrating how healthcare organizations currently utilize or should be using A&BI capabilities to enable them close the quality gaps.

Leveraging Business Intelligence Systems for Enhanced Corporate Competitiveness: Strategy and Evolution

This study contextualizes the transformative role of Business Intelligence (BI) over the past two decades, emphasizing its impact on business strategy and competitive advantage. Employing a dual-method approach, it integrates a bibliometric analysis using SciMAT with a qualitative examination of six key articles from the Web of Science (WoS), analyzed through the Gioia methodology, focusing on BI and competitiveness. The aim is to examine the metamorphosis of Business Intelligence (BI) and how it has evolved from a traditionally supporting role to a central strategic player in shaping corporate strategy and business competitive advantage over the past two decades. It discusses the overall transformation of BI and provides an in-depth examination of the specific ways in which Business Intelligence tools have redefined the landscape in contemporary business practices. Key findings reveal BI’s pivotal role in enhancing knowledge management, innovation, and marketing capabilities. Challenges in BI implementation, such as the necessity for skilled personnel and adaptability to swift technological shifts, are also highlighted. Results advocate for a dynamic BI approach, adaptable to market trends and technological evolutions. The research demonstrates that BI tools, especially when integrated with technologies like AI, IoT, and machine learning, significantly enhances decision making and efficiency in socio–technical and management systems, leading to a paradigm shift in handling complex systems and adapting to changing environments.

Impacto de las tecnologías de la Información en la Inteligencia de Negocios

Technological advancement has allowed computer tools to be fed with constant information due to the processing of data that people share through social networks or purchasing platforms. This is an opportunity for large companies since they can make sales or segmentation projections of market in an efficient way and running less risk of failure by having data on the purchasing behavior of potential customers. Once the data is processed using statistical algorithms, focused business rules can be established that allow customers to be offered products that adapt to their needs, generating an important value chain for the growth of the sales margin and mainly thanks to measurement tools. Data visualization can control the daily progress of goals from the mobile device and make appropriate management decisions for the effective implementation of business intelligence.

Business Intelligence applied to inventory management: case of a small retail company

Business Intelligence (BI) is a set of techniques that assist organizations in making data-driven decisions, enabling interactive access to information, often in real-time. In this way, its application provides precise business analyses, contributing to goal tracking, results projection, identification of opportunities, and anticipation of risks. Therefore, the objective of this work is to create a BI solution using data extracted from an Enterprise Resource Planning (ERP) to assist inventory management in a small-scale retail company specializing in party supplies. Factors such as shelf stockouts and inconsistencies between the system and the real environment have driven the development of this project. Facing ineffective inventory management and limited access to strategic information, a BI solution was developed in the company following steps such as problem analysis, data selection, extraction and processing, database modeling, BI implementation, and testing and evaluation. Thus, two focused dashboards were developed, one for the overall inventory report and another for monitoring safety stock. Through these dashboards, it is possible to assess inventory levels and product movement, devise strategies based on historical analyses, and identify the need to issue new purchase orders by product. The achieved results were positive, highlighting significant improvements in inventory management effectiveness and consolidating decision-making processes through quick and interactive access to strategic information.

Data analysis as a digital competence for information technology professionals: implementation and use of business intelligence

Competitiveness in the business market is becoming increasingly strong due to the constant advancement of technology, which makes it necessary to search for positive results and the systematization of processes, in such a situation, new opportunities arise in which it is possible to extract the maximum potential of all data obtained in a systemic way, applying the concepts of data analysis based on business intelligence. This research aims to present the main methodologies and tools used to perform in-depth data analysis, exploring and defining the use of the concepts of data warehouse, data marts, OLAP, data mining, ETL, business analytics and also business intelligence tools. With the aim of demonstrating the importance of such concepts as a digital competence to IT professionals and also to support decision-making in organizations, so that an understanding on the aforementioned subject becomes possible. You will also be able to understand how data analysis along with all the other concepts mentioned impact on the life of a company, helping in the definition of strategies, the assembly of plans and especially in decision making.

Impact of business intelligence on incident management in the control center of a security company

The main objective of this article is to implement business intelligence (BI) technology to improve incident management in the control center of a security company; making use of the Ralph Kimball method for the development of the data mart, contemplating the phases: planning of projects, definition of requirements, design of technological architecture, performing a dimensional modeling a star with 9 dimensions and 1 table made, also used the structured query language (MySQL) database, extract, transform, and load (ETL). Development the pentaho data integration, which allowed the migration, transformation and cleaning of the data from the online transaction processing (OLTP) and online analytical processing (OLAP) database, obtaining as a result that the BI managed to increase the level of the service by 28.42% and reducing the frequency index by 25%.

Unlocking Organizational Potential: Assessing the Impact of Technology through SmartPLS in Advancing Management Excellence

This study aims to explore the organizational potential in facing the impact of implementing Business Intelligence System (BIS) technology using Partial Least Squares Structural Equation Modeling (SmartPLS) as the analytical tool. We conducted research on several organizations that have adopted Business Intelligence (BIS) with the goal of enhancing managerial excellence. Data collection was carried out online, involving 150 respondents from 5 organizations in Indonesia, the majority of whom are already familiar with and have implemented BIS technology in their organizations. We evaluated the impact of this technology, particularly on organizational performance, decision-making processes, and business process optimization. This research not only synthesizes knowledge from relevant literature but also provides a holistic understanding of the impact of Business Intelligence System (BIS) technology, specifically through its success within an organizational context. The findings of this research are expected to offer a profound insight into how the adoption of BIS can transform organizational paradigms in managing information, deciding strategies, and improving operational efficiency.

ANALYSIS OF THE INFLUENCE OF BUSINESS INTELLIGENCE ON BEVERAGE SALES KONNICHIWA COFFEE USING THE METHOD EQUIVALENCE CLASS TRANSFORMATION

Konnichiwa Coffee shop is one of the business beverage that sells various types of drinks. Determination of price discounts or product promotions sometimes doesn’t match what customers wants and needs. Another obstacle found was that there were no promotions for consumers who bought directly at Konnichiwa Coffee outlets. This causes less than optimal sales strategies and store promotion strategies. Determining menus that are often purchased simultaneously by consumers can be a reference for owners in determining promotional strategies. Therefore, this research was conducted to look for association patterns between menus that can implement business intelligence (BI) in the association rules method. One of the association rules algorithms is the ECLAT algorithm. The ECLAT algorithm is used because it is more efficient and faster in terms of time. The data used in this research were 214 products from 100 transactions with 26 types of drink menus. The resulting pattern refers to a minimum support value of 3% and a minimum confidence of 30%. This means that transaction data that has association patterns or that were purchased together is only 3% of the total transaction data with a confidence level of 30%. From the results obtained, the Java Latte, Kopi Latte and Sapporo Latte menus are the menus that are most often purchased together so they can be used as a marketing strategy for Konnichiwa Coffee.

“Understanding Business Intelligence Implementation Failure from Technology, Organization, and Process Perspectives”

“Understanding Business Intelligence Implementation Failure from Technology, Organization, and Process Perspectives”

The Influence of Strategic Planning and Analytical Maturity on Organizational Performance in Implementing Business Intelligence in Indonesia

This research delves into the dynamics of intricate Business Intelligence (BI) deployments in Indonesian startups, emphasizing the interplay of organizational performance, analytical maturity, and strategic planning. Structural Equation Modeling with Partial Least Squares (SEM-PLS) was utilized in the study, which had 187 individuals from several industries, to examine the linkages and extract significant findings. The results showed three strong positive relationships: organizational performance is positively impacted by strategic planning, analytic maturity has a considerable impact on organizational performance, and strategic planning influences analytic maturity. Large impact sizes and statistical robustness characterize these practically meaningful associations. This study adds to our understanding of BI adoption in the particular setting of startups by highlighting the crucial roles that mature analytics and strategic planning play in fostering organizational success.

Driving Business Success: Exploring the Implementation and Improvement of Big Data Analysis and Business Intelligence in Selected Companies in Zheijiang, China

The study investigates the application and enhancement of big data analysis and business intelligence in selected companies in Zheijiang province, focusing on aspects such as business profile, adoption levels, benefits, implications, and challenges. Limited to selected companies in Zheijiang, the research aims to propose a tailored enhancement plan based on survey data. While it doesn't compare with other organizations and relies on self-reported data, the study delves into specific aspects of the selected companies, potentially requiring customization for wider applicability. Conducted from June to October 2023, the research utilizes a descriptive-quantitative design, emphasizing systematic data collection. With Zhejiang, China as the locale, 100 respondents from five companies are chosen through purposive sampling. A comprehensive survey questionnaire covers demographics, adoption levels, benefits, and challenges.
 Results highlight the selected companies in Zheijiang's adaptability in Healthcare, Finance, and Marketing sectors, emphasizing strong data analytics for real-time insights and strategic decisions. The system excels in data accuracy, integration, governance, security, compliance, scalability, and skills development. Recommendations include cross-sector collaborations, continuous training, customer-centric strategies, addressing skills gaps, and fostering interdepartmental collaboration, ensuring the selected companies optimize strengths and foster innovation and adaptability.

A Proposed Framework for the Implementation of a Business Intelligence System

A lot of focus can be attributed to the rising importance of Business Intelligence Systems (BIS), which have been viewed as a broad category of technologies, applications, and processes for analyzing data to help its users make better decisions. Although Business Intelligence (BI) can help improve a company’s performance, many companies often fail to realize the expected benefits of BI, and these projects are considered failures in themselves. Hence, it is essential to consider Critical Success Factors (CSFs) to obtain a successful implementation. However, very few existing research papers have associated CSFs with the various implementation stages and roles. This research study aims to design a framework that will embed various CSFs for BIS, categorized by the different stages, categories, priorities, and roles involved. Following the evaluation process, the study’s main results show that the proposed framework was beneficial for BI implementation as there was no such framework that interconnects multiple components such as CSFs, implementation stages, categorization of CSFs, prioritization of CSFs and implementation roles.

The Implementation of Business Intelligence to Analyze Sales Trends in the Indofishing Online Store Using Power BI

The growth of online sales businesses by utilizing E-Commerce is increasing rapidly. One way that can be used as a tool to face competition is to apply Business Intelligence as a basis for making the right business strategy decisions. Indofishing Shop is an online shop selling various fishing gear and equipment. So far, online sales transaction data processing uses Microsoft Excel, which has created problems with the need for more information to analyze product trends. This research applies Business Intelligence to detect data extracted and collected in a data warehouse. The data will be analyzed statistically and visualized using Microsoft Power BI. Data warehouse design uses Kimball's Nine-Step method. The results of this research are in the form of a visualization dashboard that is used to analyze sales trends for the most sold fishing equipment products from the Indofishing Shop. Diagram visualization helps Indofishing understand the trend conditions of the most in-demand products and the cities of origin of the buyers who buy the most products.

Impact of Business Intelligence on Company Performance: A System Dynamics Approach

Abstract Research background Businesses struggle with operational optimisation and seek a solution by implementing Business Intelligence (BI) to boost sales. But, due to the lack of research that use actual data from real-world situations; the impetus of this research is to exploit BI parameters to enhance company performance. Purpose This research aims to develop a System Dynamics (SD) based model to assess whether a Japanese company which manufactures Printed Circuit Boards (PCB) should invest in BI to improve its operations based on the rate of information processing, thereby leading to increased financial performance. Research methodology The authors requested financial statements for three years (2019 to 2021) from the management of the PCB company, followed by validation based on subject experts’ assessments. The model was developed and simulated step-by-step with consideration of the SD approach involving problem identification, model prototyping, trouble shooting and error analysis. Results If BI was used to process data at a rate of 40%, the endogenous factors considered in this study would increase the company’s net profit and accumulated earnings by 25.77% and 48.28%, respectively. Novelty The research is unique in the sense that the model was developed based on inter-relationships between the variables, and the data is based on a real-life situation. Furthermore, the methodology could be applied with the necessary modifications to industries such as service, media, and education.

Business Intelligence Applied in the Corporate Sector: A Systematic Review

Companies rely on technological tools like Business Intelligence (BI) to make efficient decisions and gain a competitive edge in the market. This study investigates the implementation of BI in various company areas, methodologies used, benefits obtained, tools applied, and elements of BI in the business sector. Following the Kitchenham and Charters methodology, a bibliographic search in 5 databases yielded 16 relevant articles. According to the main results of the work: logistics was one of the areas where BI was most implemented, followed by sales and finance; the most used methodology was Ralph Kimball; also, the most cited benefits were decision-making, cost optimization, and knowledge generation; the most used BI tool was Power BI, followed by QlikView; and the BI elements most applied in the business area were ETL and OLAP, closely followed by dashboards.

Systematic Literature and Expert Review of Agile Methodology Usage in Business Intelligence Projects

Background: Agile methodology is known for delivering effective projects with added value within a shorter timeframe, especially in Business Intelligence (BI) system which is a valuable tool for informed decision-making. However, identifying impactful elements for successful BI implementation is complex due to the wide range of Agile attributes. Objective: This research aims to systematically review and analyze the integration of BI within Agile methodology, providing valuable guidance for future projects implementation, enhancing the understanding of effective application, and identifying influential factors. Methods: Based on the Kitchenham method, 19 papers were analyzed from 288 papers, sourced from databases like Scopus, ACM, IEEE, and others published in 2016-2022. Meanwhile the extracted key factors impacting agile BI implementation were validated by qualified expert. Results: Agile was discovered to provide numerous benefits to BI projects by promoting flexibility, collaboration, and rapid iteration for enhanced adaptability, while effectively addressing challenges including those related to technology, management, and skills gaps. In addition, Agile methods, including tasks such as calculating cycle time, measuring defect backlogs, mapping code ownership, and engaging end users, offered practical solutions. The advantages included adaptability, success, value enhancement, cost reduction, shortened timelines, and improved precision. The research additionally considered other critical Agile elements such as BI tools, Agile Practices, Manifesto, and Methods, thereby enhancing insights for successful implementation. Conclusion: In conclusion, the research outlined Agile BI implementation into seven key factor groups, validated by qualified expert, providing guidance for BI integration and practices, and establishing a fundamental baseline for future applications. Keywords: Agile Methodology, Business Intelligence (BI), Expert Judgement, Kitchenham, Systematic Literature Review (SLR)

Strategic Insights: Navigating Business Intelligence Implementation - Phases, Tasks, and Risks: A Case Study on an International Manufacturing Company

Strategic Insights: Navigating Business Intelligence Implementation - Phases, Tasks, and Risks: A Case Study on an International Manufacturing Company