Business analytics

About: Business analytics is a research topic. Over the lifetime, 3593 publications have been published within this topic receiving 84601 citations. The topic is also known as: Business Analytics & business analytics.

An Ambidextrous Perspective on Business Intelligence and Analytics Support in Decision Processes: Insights from a Multiple Case Study

Abstract: Providing data-centric decision support for organizational decision processes is a crucial but challenging task. Business intelligence and analytics (BI&A) equips analytics experts with the technological capabilities to support decision processes with reliable information and analytic insights, thus potentially raising the quality of managerial decision making. However, the very nature of organizational decision processes imposes conflicting task requirements regarding adaptability and rigor. This research proposes ambidexterity as a theoretical lens to investigate data-centric decision support. Based on an in-depth multiple case study of BI&A-supported decision processes, we identify and discuss tensions that arise from the conflicting task requirements and that pose a challenge for effective BI&A support. We also provide insights into tactics for managing these tensions and thus achieving ambidexterity. Additionally, we shed light on the relationship between ambidexterity and decision quality. Integrating the empirical findings from this research, we propose a theory of ambidexterity in decision support, which explains how such ambidexterity can be facilitated and how it affects decision outcomes. Finally, we discuss the study's implications for theory and practice.

Cross-Cultural Business Behavior: A Guide for Global Management

Abstract: “I wrote this book because I believe that there is a serious gap in what has been written and communicated about cross-cultural management and what people actually struggle with on the ground.”—From the Introduction What does it mean to be a global worker and a true “citizen of the world” today? It goes beyond merely acknowledging cultural differences. In reality, it means you are able to adapt your behavior to conform to new cultural contexts without losing your authentic self in the process. Not only is this difficult, it’s a frightening prospect for most people and something completely outside their comfort zone. But managing and communicating with people from other cultures is an essential skill today. Most of us collaborate with teams across borders and cultures on a regular basis, whether we spend our time in the office or out on the road. What’s needed now is a critical new skill, something author Andy Molinsky calls global dexterity. In this book Molinsky offers the tools needed to simultaneously adapt behavior to new cultural contexts while staying authentic and grounded in your own natural style. Based on more than a decade of research, teaching, and consulting with managers and executives around the world, this book reveals an approach to adapting while feeling comfortable—an essential skill that enables you to switch behaviors and overcome the emotional and psychological challenges of doing so. From identifying and overcoming challenges to integrating what you learn into your everyday environment, Molinsky provides a guidebook—and mentoring—to raise your confidence and your profile. Practical, engaging, and refreshing, Global Dexterity will help you reach across cultures—and succeed in today’s global business environment. Now readers of the fourth edition will find even more of that practical guidance for negotiating with customers and suppliers around the world. They will also find fresh new cases, additional negotiator profiles and comparisons of Nordic business cultures as well as detailed advice for adapting sales presentations to the culture of the customer. The theme of this new edition of Cross-Cultural Business Behavior is CHANGE. First of all, cultures change. In markets around the world, business behavior is constantly evolving, impelled by generational shifts, improvements in education, and (especially) increasing exposure to the world marketplace. That is why all of the book's 43 'Negotiator Profiles' have been thoroughly updated, with new cases and fresh examples added. In addition to the change in culture, international managers' challenges have changed too. For example, just a few years ago, participants at global management seminars around the world were mainly interested in how to communicate and negotiate with overseas partners. But, they now find that their toughest challenges are how to manage overseas subsidiaries, strategic alliances, and international partnerships. To reflect these new realities, the book's time-tested framework for understanding cross-cultural negotiating behavior has been expanded to include a wide variety of practical pointers on managing in today's global marketplace. This fifth edition is important for everyone involved with global management, whether student or manager, because cultures and business challenges do change. The book is an essential survival guide for doing business in cultures other than one's own. An international business expert helps you understand and navigate cultural differences in this insightful and practical guide, perfect for both your work and personal life. Americans precede anything negative with three nice comments; French, Dutch, Israelis, and Germans get straight to the point; Latin Americans and Asians are steeped in hierarchy; Scandinavians think the best boss is just one of the crowd. It's no surprise that when they try and talk to each other, chaos breaks out. In The Culture Map, INSEAD professor Erin Meyer is your guide through this subtle, sometimes treacherous terrain in which people from starkly different backgrounds are expected to work harmoniously together.

Real time analytics: algorithms and systems

Abstract: Velocity is one of the 4 Vs commonly used to characterize Big Data [5]. In this regard, Forrester remarked the following in Q3 2014 [8]: "The high velocity, white-water flow of data from innumerable real-time data sources such as market data, Internet of Things, mobile, sensors, click-stream, and even transactions remain largely unnavigated by most firms. The opportunity to leverage streaming analytics has never been greater." Example use cases of streaming analytics include, but not limited to: (a) visualization of business metrics in real-time (b) facilitating highly personalized experiences (c) expediting response during emergencies. Streaming analytics is extensively used in a wide variety of domains such as healthcare, e-commerce, financial services, telecommunications, energy and utilities, manufacturing, government and transportation.In this tutorial, we shall present an in-depth overview of streaming analytics -- applications, algorithms and platforms -- landscape. We shall walk through how the field has evolved over the last decade and then discuss the current challenges -- the impact of the other three Vs, viz., Volume, Variety and Veracity, on Big Data streaming analytics. The tutorial is intended for both researchers and practitioners in the industry. We shall also present state-of-the-affairs of streaming analytics at Twitter.

Survey on clinical prediction models for diabetes prediction

Abstract: Predictive analytics has gained a lot of reputation in the emerging technology Big data. Predictive analytics is an advanced form of analytics. Predictive analytics goes beyond data mining. A huge amount of medical data is available today regarding the disease, their symptoms, reasons for illness, and their effects on health. But this data is not analysed properly to predict or to study a disease. The aim of this paper is to give a detailed version of predictive models from base to state-of-art, describing various types of predictive models, steps to develop a predictive model, their applications in health care in a broader way and particularly in diabetes.

Intelligent data analysis approaches to churn as a business problem: a survey

Abstract: Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer's intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.