Business Intelligence for Human Capital Management

This article presents the results of an exploratory study of the use of business intelligence (BI) tools to help to make decisions about human resources management in Portuguese organizations. The purpose of this article is to analyze the effective use of BI tools in integrating reports, analytics, dashboards, and metrics, which impacts on the decision making the process of human resource managers. The methodology approach was quantitative based on the results of a survey to 43 human resource managers and technicians. The data analysis technique was correlation coefficient and regression analysis performed by IBM SPSS software. It was also applied qualitative analysis based on a focus group to identify the impacts of business intelligence on the human resources strategies of Portuguese companies. The findings of this study are that: business intelligence is positively associated with HRM decision-making, and business intelligence will significantly predict HRM decision making. The research also examines the process of the information gathered with BI tools from the human resources information system on the decisions of the human resources managers and that impacts the performance of the organizations. The study also gives indications about the practices and gaps, both in terms of human resources management and in processes related to business intelligence (BI) tools. It points out the different factors that must work together to facilitate effective decision-making. The article is structured as follows: a literature review concerning the use of the business intelligence concept and tools and the link between BI and human resources management, methodology, and the main findings and conclusions.info:eu-repo/semantics/publishedVersio

Developing Strategic Capability through Business Intelligence Applications: A case study from the German Healthcare Insurance Industry

Wynn, M. and Brinkmann, D., (2018), in Yeoh, W. and Miah, S. (eds) Business Intelligence in Organisational Settings, IGI-Global. Company performance can be measured at all levels across an organisation, and in the German healthcare industry, Business Intelligence systems play a crucial role in achieving this. For one major health insurance company (discussed here as an alias - AK Healthcare), the deployment of Business Intelligence applications has supported sustained growth in turnover and market share in the past five years. In this article, these tools are classified within an appropriate conceptual framework which encompasses the organisation’s information infrastructure and associated processes. Different components of the framework are identified and examples are given - systems infrastructure, data provision/access control, the BI tools and technologies, report generation, and information users. The use and integration of Business Intelligence tools in the strategy development process is then analyzed, and the key functions and features of these tools for strategic capability development are discussed. Research findings encompass system access, report characteristics, and end-users capabilities

Analogy of intelligence with other disciplines

Intelligence analysis has many important epistemological resemblances with science (problem solving, discovery, skillful use of tools, knowledge verification) and is more interested in a posteriori than a priori knowledge, on how or the basis on which a proposition may be known. The puzzle metaphor is used in both information and archeology. Both disciplines involve collecting evidence to build as complete a picture as possible. The process of converting raw information into actionable processed intelligence is almost identical for governmental and business organizations. The medical practice of diagnosing identification, collection, analysis and dissemination is similar to that of intelligence. DOI: 10.13140/RG.2.2.26511.1296

Using dashboards for the business processes status analysis

This paper describes business process status analysis using the dashboards. The dashboards are considered as those, which belong to the most preferred Business Intelligence tools nowadays, which are used by both higher managers and ordinary employees. Existing software tools for dashboard design were reviewed, as well as the most popular visualization charts were outlined. The place and role of analytical dashboards as part of business process management is described

Understanding the Business Value Creation Process for Business Intelligence Tools in the UAE

Background: In today’s dynamically changing business environment, organizations are constantly striving to improve their organizational performance, and the use of business intelligence (BI) aids in this process. This is a key reason why BI has captured the attention of many academicians and practitioners. Most of the research on BI highlights its importance and the ways in which it facilitates decision-making; however, there is limited research on how the use of BI tools and applications benefits the organization by enabling it to convert the millions of dollars spent on BI investment into business value. This study validates the “business value of BI” framework by evaluating the business value creation process for BI tools in the UAE. Method: The data for this empirical study were collected via interviews with 15 middle managers from various industries in the UAE, with a focus on BI tools and the use of BI in their organizations. Results: The results show that a business value creation process for BI exists and that it is divided into three subprocesses: the BI conversion process, BI use process, and BI competitive process. Conclusions: The use of BI has become necessary for organizations to compete effectually. The results of this study identify the various BI tools that organizations in the UAE use. Furthermore, the results highlight the business value creation process of BI tools and how the effective use BI offers an information advantage that facilitates decision-making and eventually promotes financial and non-financial benefits for the organization. Available at: https://aisel.aisnet.org/pajais/vol11/iss3/4

Unified Approach in the DSS Development Process

The structure of today's decision support environment become very complex due to new generation of Business Intelligence applications and technologies like Data Warehouse, OLAP (On Line Analytical Processing) and Data Mining. In this respect DSS development process are not simple and needs an adequate methodology or framework able to manage different tools and platforms to achieve manager's requirements. The DSS development process must be view like a unified and iterative set of activities and operations. The new techniques based on Unified Process (UP) methodology and UML (Unified Modeling Language) it seems to be appropriate for DSS development using prototyping and RAD (Rapid Application Development) techniques. In this paper we present a conceptual framework for development and integrate Decision Support Systems using Unified Process Methodology and UML.Decision Support Systems, Unified Process, UML, Prototyping, DSS Tools

Business Intelligence: Evolution And Future Trends

Business Intelligence systems play a critical role in the business development process. They help make critical decisions based on meaningful information culled from a huge, complicated database system. Business intelligence also plays a key role in business growth and profitability by capturing real-time information and data pieces for market forecasting. As electronics media advance, companies are looking for the best data integration processes to integrate important information through electronic and computer devices to their business intelligence systems. The real challenge that organizations are facing is how to get real information in real time. In the past, organizations have adopted different solutions to integrate data into their business intelligence tools. Therefore, in terms of data and information integration, business intelligence has made significant improvements within the past three decades to meet ad hoc requirements of business intelligence users. Over the past two decades, there has been great progress in consuming and automating data in business intelligence, and there are trends and influences that are true inflection points in the industry. Periodically, trends in the industry have significantly changed important aspects of business intelligence applications: what they do, how they do it, or how they are used, either individually or collectively. This thesis discusses the evolution of business intelligence throughout different periods of time, and future trends in business intelligence

Market Segmentation Analysis and Visualization Using K-Mode Clustering Algorithm for E-Commerce Business

Today all business organizations are adopting data driven strategies to generate more revenue out of their business. Growing startups are investing a lot of money in data economy to maximize profits of business organizations by developing intelligent tools backed by machine learning and artificial intelligence. The nature of BI tool depends on factor like business goals, size, model, technology etc. In this paper architecture of business intelligence tool and decision process has been discussed with a focus on market segmentation, based on user behavior analysis using k-mode clustering algorithm and user geographical distributions. The proposed toolkit also incorporates interactive visualizations and maps

IDENTIFYING ENTERPRISE RISK BASED ON BUSINESS CONTEXT WITH THREAT INTELLIGENCE

Presented herein are techniques that facilitate prioritizing risk mitigation efforts for business-critical services and transactions through the incorporation of a business context into threat intelligence scoring. Under aspects of the presented techniques, traditional threat intelligence tools may be employed to evaluate the risk that is associated with an enterprise asset; the results of such an evaluation may then be augmented with an enterprise-assigned business value for the asset to derive the asset’s business risk; and such a business risk may be leveraged to prioritize risk mitigation efforts, may be combined with other business risks, etc. The above-described process may be referred to herein as Business Risk Management (BRM)