Showing papers on "Business analytics published in 2005"

Towards real-time business intelligence

Abstract: Analysing data to predict market trends of products and services and to improve performances of enterprise business systems has always been part of running a competitive business. But it is becoming essential nowadays that not only is the analysis done on real-time data, but also actions in response to analysis results can be performed in real time and instantaneously change parameters of business processes. This paper discusses issues and problems of current business intelligence systems, and then outlines our vision of future real-time business intelligence. We present a list of emerging technologies which could contribute to the realisation of real-time business intelligence and some examples of applying them to improve BT's systems and services.

System and method for designing effective business policies via business rules analysis

Abstract: Methods and systems are provided for analyzing the business rules, business metrics, and decision parameters for a firm or organization, processing a subset of such data to form output, and offering access to selective views of such output including evaluation and comparative data regarding execution of such business rules, information on corresponding business metrics or sets of business metrics, information on corresponding decision parameters or sets of decision parameters or scenarios, and other useful analytic information which can help a firm or organization evaluate and modify business policies based on said rules, metrics, and parameters. In addition to said rules, metrics and/or parameters, the data for the business rule analysis can include conventional historical data or hypothetical data based on simulations which the current system and method provide based on prescribed random and non-random algorithms. The simulated or hypothetical data enables users to conduct rule analysis based on historical data, simulated data, or hybrid models. In this manner, the methods and systems described in this invention provide for both an evaluation of a firm's current policies as well as an evaluation of policy modifications not actually executed but for which hypothetical data can be provided and analyzed.

Enhanced business intelligence - supporting business processes with real-time business analytics

Abstract: In the 21st century, organizations are experiencing environmental changes characterized by indistinct organizational boundaries and fast-paced change. As a result firms need appropriate decision support infrastructures in order to face these challenges. Current data warehousing and business intelligence approaches are widely accepted as a middleware layer for state-of-the-art decision support. However, they do not provide sufficient support in dealing with the upcoming challenges, such as real-time and closed loop decision making. In this paper, we suggest an architecture for enhanced business intelligence that aims to increase the value of business intelligence by reducing action time and interlinking business processes into decision making.

Business management tool

Abstract: The present invention includes a business management tool that is configured to receive and process both first and second data sources for planning, performance and forecasting purposes. The business management tool of the present invention is further configured to utilize essential data including key performance indicators. The foregoing data sets are inputting into an integrated planning, performance and forecasting methodology that integrates historical data and forecasting data to form a closed loop system for managing a business. Lastly, the business management tool of the present invention is adapted to advise managers of those conditions and variables that subject the business to the most risk with regard to revenue planning and forecasting.

Dynamic business model framework for emerging technologies

Abstract: This paper suggests a new framework for business models that takes into account disruptive technologies. It identifies four stages in the development of new technologies. In each of these stages there are factors that should be overcome. Stage 1 emphasises technical issues. In stage 2 environmental factors such as law and adoption should be considered. Developers begin to incorporate traditional business model factors in stage 3. Stage 4 focuses on factors that will sustain the business. The paper also distinguishes between supply and demand business models. The development of the literature on peer to peer networks illustrates these stages.

Measurement of Business Intelligence in a Finnish Telecommunications Company.

Abstract: Business intelligence (BI) is a managerial concept and tool that is used to help organisations to manage business information and to make effective decisions. Measurement of BI is generally considered an important issue but at the same time it is considered difficult to carry out in practice. There is also a lack of research on the topic. The paper describes the current knowledge regarding the measurement of BI and makes a contribution on the currently small amount of empirical knowledge on the topic. The research is implemented by means of a literature review and action

Systems and methods for selective sharing of business performance information

Abstract: An automated system for allowing a submitter business to selectively share business performance information with requestor businesses through a business performance information sharing data center computer system over the Internet. A submitter business uploads a data file including business performance information such as a trial balance report generated by the business' own accounting software program. The uploaded file is converted from the submitter-defined format to a standardized format. Various business performance data analyses are performed on the standardized data including generating standardized business performance reports and analyzing the data in accordance with financial metrics. After the business performance data has been formatted and analyzed, the submitter will specify one or more companies authorized to view the business performance data including specifying a level of business performance detail, from a plurality of levels of detail, and/or a business performance time period for which that company may view business performance information.

System, method and computer program product for evaluating an asset management business using experiential data, and applications thereof

Abstract: A method, system and computer program product for evaluating and quantifying the risk, performance and potential of an asset management business are disclosed. Experiential data generated by the business' processes is extracted and used as source data in evaluating the business. Experiential data includes both qualitative and quantitative information compiled from operating systems, databases, applications, workflows, interviews, paper-based files and financial records. Business processes are measured individually and then collectively to understand the business as a whole. A set of metrics and a series of algorithms are used to measure the risk, performance and potential of the business drawing from the outset on the experiential data collected and a comparison of the business process workflows to quality control checks.

The Evaluation of Business Intelligence: A Case Study in a Major Financial Institution

Abstract: Business intelligence (BI) is the current industry movement that addresses the use of IT to support management decision making. Unlike previous approaches to decision support, BI systems are large-scale information systems. Whereas the development of small-scale personal decision support systems (PDSS) and executive information systems (EIS) may be authorised and funded at an individual executive’s discretion, BI systems require evaluation and approval processes more like those used in large-scale operational IT projects. This paper presents a framework for BI and proposes that Symon’s Context-Content-Process model is useful for understanding BI projects. A pilot case study of BI evaluation in a major bank is described and analysed in terms of the Context-Content-Process model. The findings include the recognition of the importance of nonfinancial intangible factors in BI evaluation, the use of operational justification for strategic BI systems, and the varying perspectives of different stakeholders in BI systems. The framework and case findings provide part of the foundation for a larger project concerning the development of a BI evaluation method.

Business analytics: getting behind the numbers

Abstract: – To identify, discuss and provide a solution for a common problem in the mathematical analyses in business analyses, namely, paralysis by analysis., – The paper first discusses the scale and frequency of the paralysis by analysis problem, before discussing it in more depth before addressing a fundamental problem, which is an important root of the paralysis by analysis problem, the indiscriminate usage of central tendency measures. Finally, it discusses how variance can be turned from being a liability into an asset. The approach is conversational but examples and a case study are provided to substantiate the arguments., – The paper provides some recommendations for avoiding paralysis by analysis., – Basically, the paper shows by argument and example why practitioners and some researchers need to better understand the limitations and promises of mathematical analyses and to some extent how to incorporate this understanding into their work., – There is nothing really new in this paper, but it discusses a problem that for some reason is often ignored by practitioners and some researchers. The true value of the paper therefore lies in making practitioners, in particular, more aware of the limitations as well as the possibilities in the mathematical analyses performed in business analytics so that they can better understand what they are doing and hence get behind the numbers, as it were.

Incorporating Real-Time Financial Data Into Business Curricula

Abstract: The need to incorporate business and economic data into curricula has been a driver of technology adoption in business schools. Webbased resources and professional data services, such as Reuters and Bloomberg, are being increasingly adopted by business programs to meet this need. There are clear trade-offs to adopting either technological approach. In this article, the author presents examples of incorporating real-time data from professional data services into a variety of business topics.

A performance measurement perspective for event-driven process chains

Abstract: Business processes access data warehouse (DWH) information for performance measurement, supporting business decisions. Today, there are no conceptual models available that make the relationship between DWH architectures and business processes transparent. In this paper, we extend the event-driven process chain, a business process modeling language, with an additional perspective to make this relationship explicit in a model.

New trends in Business Intelligence.

Abstract: Today, as DWing reached a high level of efficiency, new opportunities in exploiting information coming from the operational databases are requested by users. Consequently, we believe that in the next future the interests of researchers will be more and more oriented to BI applications while DW will play the role of an on the shelf module within a large set of resources placed at the knowledge workers disposal with the aim of exploiting at best the information encrypted in the operational data. The aim of this paper is to sketch our idea about the deve lop prospects for BI and to report in detail one of the most promising evolution in this direction: Business Performance

Nestlé Improves Its Financial Reporting with Management Science

Abstract: Nestle's executive information system (EIS) department gathers data from the firm's subsidiaries (reporting units) to provide top management with operational, financial, and strategic information. In 1996, the EIS department decided to improve its service by using business analytics tools based on management science (MS) techniques. It wanted to encourage analysts and controllers to make better use of the information supplied. We developed four OR modules: sensitivity analysis, forecasting, simulation, and optimization, and integrated them into a more global modeling scheme for evaluating the economic profitability of Nestle's projects and more generally evaluating the value of the Nestle group and its multifocal businesses. Disseminating this approach within the Nestle group through training and internal consulting has been a long and important process that has increased the number of managers accustomed to quantitative decision making and established new reporting protocols imposing the use of MS models.

A knowledge-based entrepreneurial approach for business intelligence in strategic technologies: Bio-MEMS

Abstract: We propose a knowledge-based entrepreneurial (KBE) approach for business intelligence in strategic technologies at industrial sectors. The KBE approach is at the convergence of business intelligence and knowledge management and is used for advising users in business decisions and potential risks. Our approach comprises both a technology roadmap model as well as a knowledge-based entrepreneurial portal for various technologies. We use the Biological-Micro-Electrical-andMechanical-Systems industry (Bio-MEMS) to illustrate the approach. The technology roadmap model identifies the main actors, defines their roles and specifies the issues to be addressed. It handles information about main products, market trends, companies, research centers, application domains, products, standardization, and intellectual properties issues. The portal provides knowledge about the main actors through automation facilities based on digital libraries, searching and knowledge extraction from databases, data-ware houses and the Web. We explain how the KBE is helping Bio-MEMS users in business analysis.

On teaching business decision-making in complex domains

Abstract: This paper treats teaching decision-making in business as a separate issue from teaching business decision support. We consider business decision-making ability to be a combination of theory and practice (experience) and hence, perceive teaching decision-making an exercise that has to take both, business theory and business experience into consideration; this can be achieved with experiential learning. Complexity in the business environment and different learning environments are discussed. Selected instances of teaching decision-making under complexity are presented for illustration.

Integration of e-learning with business intelligence system

Abstract: A business intelligence system comprises a business intelligence interface system that enables users to interface with a business intelligence system and an electronic learning system that delivers electronic learning related to the business intelligence system. The business intelligence interface system enables one or more portions, such as folders of reports, individual reports, metadata or other business intelligence objects, or a report definition, of the business intelligence system for use by a user based on information related to whether the user has engaged in electronic learning associated with the one or more portions. A user may self-provision access by earning a privilege based on reviewing a lesson, passing a test, and/or other activities relative to the business intelligence object. Upon meeting electronic learning criteria, the electronic learning system updates privileges to enable access to the business intelligence object or class of objects.

Trends in Data Processing for Decision Support

Abstract: The quality of decision-making process is affected by the quality of information used in the process. Trends in data processing for decision support show that business users need analytical applications which incorporate a variety of data analysis techniques incorporating task-specific knowledge, i.e. that are business task-oriented. Such business analytics applications must be vertically connected across the organization, their information is desired to be in a visually acceptable form, even through wireless devices. The analysis functions have to be integrated into the information system, and integrated into the action and result measurements.

VisImpact: business impact visualization

Abstract: Business Intelligence (BI) deals with transforming raw business data into valuable information for making decisions. The goal is to improve the operation and use of large-scale, complex information systems. A number of automated BI techniques are available. These methods, however, have to be supported by user interaction to make successful business decisions. In this paper, we present a new technique for interactive business intelligence based on visualization technology, called VisImpact. The basic idea of the VisImpact technique is to visually display the relationships between the important business operation parameters and the distribution of the process flow. We have applied VisImpact in the areas of business contract analysis, business operation analysis, and fraud analysis, to show the power of the VisImpact technique for finding process flows, patterns, and trends, and for a quick identification of exceptions (outliers). Our interactive VisImpact system provides the means for an instant drilldown to a transaction record level which allows observing the evolution of business dynamics.

Monitoring of contextual correlation of business process events

Abstract: The fast changing business environment today makes high demands on the organizations for deep visibility into business activities at real-time and immediate response capabilities. In this paper we present how to efficiently detect correlated business process events that represent opportunities or problems to the organization and require quick action from the decision-maker.

On architecting business performance management grid for adaptive enterprises

Abstract: A business performance management grid is a grid-based system that supports an adaptive environment in which businesses can make prompt and well-informed business decisions We describe the Business Performance Management Services Architecture, the architecture for grid-based services and an OGSA-based reference implementation for this architecture Then we present a case study involving an implementation of a business performance management system in microelectronic manufacturing and describe its extension to the grid environment

Performance Management with Business Intelligence

Abstract: In today's highly competitive business, the quality and timeliness of business information for an organization is not the choice between profit and loss, it is a question of survival or bankruptcy. No business organization can deny the inevitable benefits of business intelligence. Business intelligence takes the advantage of already developed and installed components of IT technologies to help companies leverage their current IT investments and use valuable data stored in ERP or legacy systems. Business intelligence software can be a transformational asset for organizations. It can eliminate much of the guesswork within organizations, enhance communication and joint planning across functions and lines of business, and enable organizations to respond much more quickly to changes in financial conditions, customer preferences and supply chain operations. Specialists assess the use of business intelligence will become so widespread that every desktop will have a BI icon. Business intelligence will become an integral part of an enterprise's information system and, like word processing software, it will be used by almost all end users. Gartner Dataquest estimates a 2.3 billion dollars global market in 2005 and an 8.2% growing rate for 2005-2007. It is expecting for business intelligence to spread its wings to cover everyone, from small, medium, and to large companies - we will show that the Romanian market is also reactive to this trend.

Preface (BPI 2005)

Abstract: Business process intelligence (BPI) is an emerging area that has been increasing in importance during the last few years as a result of the pressing need for companies to improve the business processes underlying their business operations so as to better meet their business goals. A number of groups in different research areas are working on technologies to support different aspects of BPI, even if they do not call it this.