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

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Organizational culture influence on information quality - use of business intelligence systems relationship: portuguese context

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Farming systems methodology for efficient resource management at the farm level: a review from an Indian perspective

Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

The greater whole: towards a synthesis of system dynamics and soft systems methodology

This paper makes a theoretical case for using these two systems approaches together. The theoretical and methodological assumptions of system dynamics (SD) and soft system methodology (SSM) are briefly described and a partial critique is presented. SSM generates and represents diverse perspectives on a problem situation and addresses the socio-political elements of an intervention. However, it is weak in ensuring `dynamic coherence'. consistency between the intuitive behaviour resulting from proposed changes and behaviour deduced from ideas on causal structure. Conversely, SD examines causal structures and dynamic behaviours. However, whilst emphasising the need for a clear issue focus, it has little theory for generating and representing diverse issues. Also, there is no theory for facilitating sensitivity to socio-political elements. A synthesis of the two called ‘Holon Dynamics' is proposed. After an SSM intervention, a second stage continues the socio-political analysis and also operates within a new perspective which values dynamic coherence of the mental construct - the holon - which is capable of expressing the proposed changes. A model of this holon is constructed using SD and the changes are thus rendered `systemically desirable' in the additional sense that dynamic consistency has been confirmed. The paper closes with reflections on the proposal and the need for theoretical consistency when mixing tools is emphasised.

Diagnóstico sistêmico de uma farmácia de manipulação de Porto Alegre com a utilização da "Soft Systems Methodology"

As empresas e instituições estão num ambiente que oferece oportunidades e ameaças, o que exige um conjunto de informações voltado tanto a processos e decisões táticas, operacionais e estratégicos. No entanto, conseguir informações com rapidez e qualidade não se trata apenas de adquirir pacotes de sistemas de informações ou mesmo desenvolvê-los nas organizações. Infelizmente, isto é o que mais tem ocorrido. Desta forma, a fim de ultrapassar esse amadorismo, faz-se necessário um diagnóstico sistêmico da organização, com objetivo de identificar os requisitos informacionais necessários à construção de um sistema de apoio às decisões. Destarte, este estudo realiza um diagnóstico sistêmico numa farmácia com a utilização da “Soft Systems Methodology”, a qual a partir de ampla interação entre pesquisador e as pessoas envolvidas , identifica e estrutura a situação problemática de forma encadeada, analisando-a sob duas preocupações: uma relacionada ao mundo real e outra ao pensamento sistêmico. Com este processo, desenvolve uma aprendizagem que permite não só a identificação dos requisitos informacionais necessários à construção de um sistema de informações como também reunir e organizar visões muitas vezes divergentes a respeito de uma realidade complexa, a fim de propor um rol de atividades e ações que possam contribuir para o processo de melhoria da situação problemática.

Rumo a um desenho técnico de um sistema de apoio à decisão para uma reconfiguração do soft systems methodology: o caso do planejamento sistêmico

A multidisciplinaridade da tomada de decisão sofre com as peculiaridades de qualquer campo multidisciplinar. A falta de comunicação, muitas vezes, gera problemas e as respostas que podem ser encontradas dentro de outras áreas. Os Métodos de Estruturação de Problemas são respostas para os questionamentos atuais nas escolas de administração e negócios, principalmente o uso multimetodológico destes com outros métodos. Tendo o Soft Systems Metholodogy – SSM – como base, e a incorporação do Strategic Options Development and Analysis – SODA – ao processo do SSM, Georgiou (2012) apresenta o Planejamento Sistêmico em sua configuração mais recente. Visando buscar uma ferramenta computacional que atenda os pressupostos do SSM, e que incorpore as especificações da configuração do Planejamento Sistêmico, definem-se uma notação para o método e uma formalização das para as comunicações existentes entre os elementos, subsistemas, sistema e ambiente e, com isso, torna-se possível controlar o uso do método de forma iterativa. Para demonstrar tal uso, apresenta-se uma análise de um caso real e demonstra as dificuldades encontradas na utilização da Notação e Comunicação definida. Posteriormente, apresenta-se um desenho técnico de uma ferramenta computacional modular e que pode ser usada de forma integrada com outras ferramentas de outros métodos. Como resultado, têm-se o avanço na definição de padrões no uso das ferramentas do SSM, na apresentação dos aspectos sistêmicos do Planejamento Sistêmico, na apresentação de um uso iterativo do método e na apresentação de um desenho técnico para uma ferramenta computacional.

SSM samba: a survey of brazilian approaches to soft systems methodology (1999-2005)

This paper reports the results of a survey intended to discover the manner in which Soft Systems Methodology (SSM) is understood and used in Brazil. The focus is upon SSM papers published in national and international journals, and conferences, incorporating a refereeing procedure. To be included in the survey, publications had to meet at least one of the following criteria: (a) authorship is clearly of Brazilian nationality; or, (b) authorship is affiliated to a Brazilian institution; or (c) application is set in Brazil. Similar surveys reporting on the United Kingdom, Australia and, to a lesser extent, Spain have been published previously in the literature. This paper, therefore, contributes to the growing international understanding and usage of SSM. Ultimately the paper serves as an initial map of the developing context in Brazilian SSM theory and practice.

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

A systems methodology for analysing and simulating manufacturing systems

The Systems Engineering Group (SEG) at De Montfort University are developing the Boardman Soft Systems Methodology (BSSM) which allows complex human systems to be modelled, this work builds upon Checkland's Soft Systems Methodology (1981). The BSSM has been applied to the modelling of the systems engineering process as used in design and manufacturing companies. The BSSM is used to solicit information from a company and this data is then transformed into systemic diagrams (systemigrams). These systemigrams are posited to be accurate and concise representations of the system which has been modelled. This paper describes the collaboration between SEG and a manufacturing company (MC) in Leicester, England. The purpose of this collaboration was twofold. First, it was to create an objective view of the MC's processes, in the form of systemigrams. It was important to get this modelled by a source outside of the company, as it is difficult for people within a system being modelled to be unbiased. Secondly, it allowed a series of systemigrams to be produced which can then be subjected to simulation, for the purpose of aiding risk management decisions and to reduce the project cycle time

Semantic linking through spaces for cyber-physical-socio intelligence:a methodology

Humans consciously and subconsciously establish various links, emerge semantic images and reason in mind, learn linking effect and rules, select linked individuals to interact, and form closed loops through links while co-experiencing in multiple spaces in lifetime. Machines are limited in these abilities although various graph-based models have been used to link resources in the cyber space. The following are fundamental limitations of machine intelligence: (1) machines know few links and rules in the physical space, physiological space, psychological space, socio space and mental space, so it is not realistic to expect machines to discover laws and solve problems in these spaces; and, (2) machines can only process pre-designed algorithms and data structures in the cyber space. They are limited in ability to go beyond the cyber space, to learn linking rules, to know the effect of linking, and to explain computing results according to physical, physiological, psychological and socio laws. Linking various spaces will create a complex space — the Cyber-Physical-Physiological-Psychological-Socio-Mental Environment CP3SME. Diverse spaces will emerge, evolve, compete and cooperate with each other to extend machine intelligence and human intelligence. From multi-disciplinary perspective, this paper reviews previous ideas on various links, introduces the concept of cyber-physical society, proposes the ideal of the CP3SME including its definition, characteristics, and multi-disciplinary revolution, and explores the methodology of linking through spaces for cyber-physical-socio intelligence. The methodology includes new models, principles, mechanisms, scientific issues, and philosophical explanation. The CP3SME aims at an ideal environment for humans to live and work. Exploration will go beyond previous ideals on intelligence and computing.

An analysis of the role of soft systems methodology in the change process and the contribution of the facilitator within this process

This research aims to examine the effectiveness of Soft Systems Methodology (SSM) to enable systemic change within local goverment and local NHS environments and to examine the role of the facilitator within this process. Checkland's Mode 2 variant of Soft Systems Methodology was applied on an experimental basis in two environments, Herefordshire Health Authority and Sand well Health Authority. The Herefordshire application used SSM in the design of an Integrated Care Pathway for stroke patients. In Sandwell, SSM was deployed to assist in the design of an Infonnation Management and Technology (IM&T) Strategy for the boundary-spanning Sandwell Partnership. Both of these environments were experiencing significant organisational change as the experiments unfurled. The explicit objectives of the research were: To examine the evolution and development of SSM and to contribute to its further development. To apply the Soft Systems Methodology to change processes within the NHS. To evaluate the potential role of SSM in this wider process of change. To assess the role of the researcher as a facilitator within this process. To develop a critical framework through which the impact of SSM on change might be understood and assessed. In developing these objectives, it became apparent that there was a gap in knowledge relating to SSM. This gap concerns the evaluation of the role of the approach in the change process. The case studies highlighted issues in stakeholder selection and management; the communicative assumptions in SSM; the ambiguous role of the facilitator; and the impact of highly politicised problem environments on the effectiveness of the methodology in the process of change. An augmented variant on SSM that integrates an appropriate (social constructivist) evaluation method is outlined, together with a series of hypotheses about the operationalisation of this proposed method.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.