Topic
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.
Papers published on a yearly basis
Papers
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TL;DR: For those involved in the provision of business information, ultimately it is the question of what to provide at the point of application that is most important when attempting to create business intelligence from online information sources.
Abstract: Organisations seek to use information intelligently and to generate business intelligence for future profitable prospects. Although not regarded as business intelligence per se, there is a role for commercially produced online information sources and internally generated intranet resources in business intelligence activity. For example, the human post-coordination of raw data from a commercial source may direct business decisions; Web pages on intranets serve to unify ‘grey’ internal company information; the company intranet serves as a platform for unifying internal and external sources. However, technological and cultural barriers can inhibit the effectiveness of online information sources held on company networks, and other processes, such as the mining of transactional data, offer alternative means of deriving business intelligence. For those involved in the provision of business information, ultimately it is the question of what to provide at the point of application that is most important when attem...
15 citations
Book•
01 Jan 2014
TL;DR: In this paper, the authors provide an essential framework for becoming a smarter enterprise and show through 31 case studies how IBM has derived value from analytics throughout its business, including creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable
Abstract: How to Transform Your Organization with Analytics: Insider Lessons from IBMs Pioneering Experience Analytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesnt just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation wont happen overnight; however, it is absolutely achievable, and the rewards are immense. This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBMs pioneering analytics practitioners share invaluable real-world perspectives on what does and doesnt work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business. Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics Measuring the immeasurable and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics
15 citations
01 Jan 2013
TL;DR: This chapter gives an introduction to concepts and terms of BI and PM.
Abstract: Globalisation, volatile markets, legal changes and technical progress have an immense impact on business environments in most industries. More and more IT is deployed to manage the complexity. As a result, companies and organisations have to handle growing volumes of data which have become a valuable asset. The ability to benefit from this asset is increasingly essential for business success. Therefore, fast storage, reliable data access, intelligent information retrieval, and new decision-making mechanisms are required. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges. Before important aspects of both topics are analysed from different points of view, this chapter gives an introduction to concepts and terms of BI and PM.
15 citations
Book•
05 Dec 2012
TL;DR: A Framework for Business Anayltics as discussed by the authors is a framework for business anaylutions that includes decision framing, decision modeling, decision execution, and data stewardship, as well as case studies.
Abstract: A Framework for Business Anayltics.- Analytics Domain Context.- Decision Framing: Defining the Decision Need.- Decision Modeling.- Decision Making.- Decision Execution.- Business Intelligence.- Data Stewardship: Can We Use the Data?.- Making Organizations Smarter.- Building the Analytics Capability.- Analytic Methods.- Analytics Case Studies.
15 citations
01 Jan 2011
TL;DR: An organization needs to develop a forecasting system involving several approaches to predicting uncertain events, and it is also important to have strong organizational support for the use of formal forecasting methods if they are to be used successfully.
Abstract: An organization needs to develop a forecasting system involving several approaches to predicting uncertain events. Such forecasting systems require the development of expertise in identifying forecasting problems, applying a range of forecasting methods, selecting appropriate methods for each problem, and evaluating and refining forecasting methods over time. It is also important to have strong organizational support for the use of formal forecasting methods if they are to be used successfully.
15 citations