Intelligence systems methodology: a systemic approach to the organizational intelligence function

Organizational intelligence can be seen as a function of the viable structure of an organization. With the integration of the Viable System Model and Soft Systems Methodology (systemic approaches of organizational management) focused on the role of the intelligence function, it is possible to elaborate a model of action with a structured methodology to prospect, select, treat and distribute information to the entire organization that improves the efficacy and efficiency of all processes. This combination of methodologies is called Intelligence Systems Methodology (ISM) whose assumptions and dynamics are delimited in this paper. The ISM is composed of two simultaneous activities: the Active Environmental Mapping and the Stimulated Action Cycle. The elaboration of the formal ISM description opens opportunities for applications of the methodology on real situations, offering a new path for this specific issue of systems thinking: the intelligence systems. Knowledge Management Research & Practice (2012) 10, 141-152. doi:10.1057/kmrp.2011.44

Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

Applying model-driven engineering to the development of Rich Internet Applications for Business Intelligence

Business Intelligence (BI) applications have been gradually ported to the Web in search of a global platform for the consumption and publication of data and services. On the Internet, apart from techniques for data/knowledge management, BI Web applications need interfaces with a high level of interoperability (similar to the traditional desktop interfaces) for the visualisation of data/knowledge. In some cases, this has been provided by Rich Internet Applications (RIA). The development of these BI RIAs is a process traditionally performed manually and, given the complexity of the final application, it is a process which might be prone to errors. The application of model-driven engineering techniques can reduce the cost of development and maintenance (in terms of time and resources) of these applications, as they demonstrated by other types of Web applications. In the light of these issues, the paper introduces the Sm4RIA-B methodology, i.e., a model-driven methodology for the development of RIA as BI Web applications. In order to overcome the limitations of RIA regarding knowledge management from the Web, this paper also presents a new RIA platform for BI, called RI@BI, which extends the functionalities of traditional RIAs by means of Semantic Web technologies and B2B techniques. Finally, we evaluate the whole approach on a case study—the development of a social network site for an enterprise project manager.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

Systemological Bases of Business Intelligence

Sustainable development support, balanced scorecard development and business process modeling are viewed from the position of systemology. Extensional, intentional and potential properties of a system are considered as necessary to satisfy functional requirements of a meta-system. The correspondence between extensional, intentional and potential properties of a system and sustainable, unsustainable, crisis and catastrophic states of a system is determined. The inaccessibility cause of the system mission is uncovered. The correspondence between extensional, intentional and potential properties of a system and balanced scorecard perspectives is showed. The IDEF0 function modeling method is checked against balanced scorecard perspectives. The correspondence between balanced scorecard perspectives and IDEF0 notations is considered.

Using business intelligence to support the process of organizational sensemaking

Making sense of an organization overwhelmed with data becomes a problem for decision makers at all levels of business planning and operation. Although scholars have suggested several technological solutions such as business intelligence as being useful in helping busy executives to make decisions, we still know little about assisting business stakeholders in the process of understanding their organizational complexity before such decisions could even be formulated. In this paper, we investigate the opportunities in using BI technologies to make sense of a business environment. We analyze the views and opinions of developers, analysts, consultants, and users of business intelligence, who are experienced in using the technology beyond decision making to support organizational sensemaking. Our results highlight the need for creating and maintaining individual; and organizational identity and enacting this identity on the business and its environment.

Using business intelligence to support the process of organizational sensemaking.

Morteza’s thesis investigated the opportunities in using BI technologies to make sense of a business environment. The results of his research highlighted the need for creating and maintaining an identity for Business Intelligence at both individual and organizational level and enacting this identity on the business and its environment.

Business intelligence em sistemas de apoio à gestão de frotas: Análise de Tecnologias e metodologias

O objecto de estudo desta tese de mestrado surgiu da necessidade de dar resposta a uma proposta para uma solução de business intelligence a pedido de um cliente da empresa onde até à data me encontro a desempenhar funções de analista programador júnior. O projecto consistiu na realização de um sistema de monitorização de eventos e análise de operações, portanto um sistema integrado de gestão de frotas com módulo de business intelligence. Durante o decurso deste projecto foi necessário analisar metodologias de desenvolvimento, aprender novas linguagens, ferramentas, como C#, JasperReport, visual studio, Microsoft SQL Server entre outros. ABSTRACT: Business Intelligence applied to fleet management systems - Technologies and Methodologies Analysis. The object of study of this master's thesis was the necessity of responding to a proposal for a business intelligence solution at the request of a client company where so far I find the duties of junior programmer. The project consisted of a system event monitoring and analysis of operations, so an integrated fleet management with integrated business intelligence. During the course of this project was necessary to analyze development methodologies, learn new languages, tools such as C #, JasperReports, visual studio, Microsoft Sql Server and others.

An open source service oriented Mobile Business Intelligence Tool (MBIT)

Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.

Software como un Servicio: Solución Business Intelligence

El propóosito del proyecto aquíı descrito radica en, por una parte, sentar una base de un sistema de Business Inteligence adaptable a diversos casos de negocio, y por otra, diseñar e implementar una solución completa para una empresa especíıfica fácilmente adaptable a otro caso, incluyendo desde los procesos de Extracción, Transformación y Carga, pasando por el data warehouse hasta el Business Analysis y la Minería de Datos.

Business Intelligence and Multi-market Competition

We consider a multi-market framework where a set of firms compete on two oligopolistic markets. The cost of production of each firm allows for spillovers across markets, ensuring that output decisions for both markets have to be made jointly. Prior to competing in these markets, firms can establish links gathering business intelligence about other firms. A link formed by a firm generates two types of externalities for competitors and consumers. We characterize the business intelligence equilibrium networks and networks that maximize social welfare. By contrast with single market competition, we show that in multi-market competition there exist situations where intelligence gathering activities are underdeveloped with regard to social welfare and should be tolerated, if not encouraged, by public authorities.