A proposed methodology for the design of decision support systems in operations management

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The purpose of this work is to attempt to develop a Decision Support System and a generalised Design Methodology, for the Operational Management of Industrial Organisations. The research subject has been selected as such, because although substantial research has been carried out on the technology of solving a specific problem with quantitative decision support tools such as Operations Research (OR) or Management Science (MS), there is a significant gap on the methodology of developing and implementing these techniques as a direct operational support tool. In recognition of operational managers' increasing needs for decision support tools and in a view of the slow progress and unsatisfactory use of OR/MS techniques, and the inability of Management Information systems to contribute to the operational decision support function, the research is set out to identify the shortcomings of existing practice, and to develop a system in the light of the resulting requirements. A multi-disciplinary approach is adopted for the development of the system and the methodology, which is based on a conceptual framework provided by cybernetics. Theories relating to the communication, regulation and coordination within a system, and to the interactive man-machine problem solving activities provide the basis for the methodology. The end product of the research is a System and a generalised Design Methodology for this system. The primary aims of the system are to co-ordinate the operational decision process throughout the organisation and to increase the effectiveness of the decision-making capacity of the operational managers. It is a microprocessor based modular system which is distributed to the operational decision makers. Functionally, it consists of a 'forward looking' information system which is dedicated to operational decision support, and quantitative decision models including OR/MS methods that are integrated with this system. The modular decision units are connected by this system

Proceedings of the 2004 ONR Decision-Support Workshop Series: Interoperability

In August of 1998 the Collaborative Agent Design Research Center (CADRC) of the California Polytechnic State University in San Luis Obispo (Cal Poly), approached Dr. Phillip Abraham of the Office of Naval Research (ONR) with the proposal for an annual workshop focusing on emerging concepts in decision-support systems for military applications. The proposal was considered timely by the ONR Logistics Program Office for at least two reasons. First, rapid advances in information systems technology over the past decade had produced distributed collaborative computer-assistance capabilities with profound potential for providing meaningful support to military decision makers. Indeed, some systems based on these new capabilities such as the Integrated Marine Multi-Agent Command and Control System (IMMACCS) and the Integrated Computerized Deployment System (ICODES) had already reached the field-testing and final product stages, respectively. Second, over the past two decades the US Navy and Marine Corps had been increasingly challenged by missions demanding the rapid deployment of forces into hostile or devastate dterritories with minimum or non-existent indigenous support capabilities. Under these conditions Marine Corps forces had to rely mostly, if not entirely, on sea-based support and sustainment operations. Particularly today, operational strategies such as Operational Maneuver From The Sea (OMFTS) and Sea To Objective Maneuver (STOM) are very much in need of intelligent, near real-time and adaptive decision-support tools to assist military commanders and their staff under conditions of rapid change and overwhelming data loads. In the light of these developments the Logistics Program Office of ONR considered it timely to provide an annual forum for the interchange of ideas, needs and concepts that would address the decision-support requirements and opportunities in combined Navy and Marine Corps sea-based warfare and humanitarian relief operations. The first ONR Workshop was held April 20-22, 1999 at the Embassy Suites Hotel in San Luis Obispo, California. It focused on advances in technology with particular emphasis on an emerging family of powerful computer-based tools, and concluded that the most able members of this family of tools appear to be computer-based agents that are capable of communicating within a virtual environment of the real world. From 2001 onward the venue of the Workshop moved from the West Coast to Washington, and in 2003 the sponsorship was taken over by ONR’s Littoral Combat/Power Projection (FNC) Program Office (Program Manager: Mr. Barry Blumenthal). Themes and keynote speakers of past Workshops have included: 1999: ‘Collaborative Decision Making Tools’ Vadm Jerry Tuttle (USN Ret.); LtGen Paul Van Riper (USMC Ret.);Radm Leland Kollmorgen (USN Ret.); and, Dr. Gary Klein (KleinAssociates) 2000: ‘The Human-Computer Partnership in Decision-Support’ Dr. Ronald DeMarco (Associate Technical Director, ONR); Radm CharlesMunns; Col Robert Schmidle; and, Col Ray Cole (USMC Ret.) 2001: ‘Continuing the Revolution in Military Affairs’ Mr. Andrew Marshall (Director, Office of Net Assessment, OSD); and,Radm Jay M. Cohen (Chief of Naval Research, ONR) 2002: ‘Transformation ... ’ Vadm Jerry Tuttle (USN Ret.); and, Steve Cooper (CIO, Office ofHomeland Security) 2003: ‘Developing the New Infostructure’ Richard P. Lee (Assistant Deputy Under Secretary, OSD); and, MichaelO’Neil (Boeing) 2004: ‘Interoperability’ MajGen Bradley M. Lott (USMC), Deputy Commanding General, Marine Corps Combat Development Command; Donald Diggs, Director, C2 Policy, OASD (NII

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Evaluating the integration of supply chain information systems: A case study

Supply chain management (SCM) is the integrated management of business links, information flows and people. It is with this frame of reference that information systems integration from both intra- and inter-organisational levels becomes significant. Enterprise application integration (EAI) has emerged as software technologies to address the issue of integrating the portfolio of SCM components both within organisations and through cross-enterprises. EAI is based on a diversity of integration technologies (e.g. message brokers, ebXML) that differ in the type and level of integration they offer. However, none of these technologies claim to be a panacea to overcoming all integration problems but rather, need to be pieced together to support the linking of diverse applications that often exist within supply chains. In exploring the evaluation of supply chain integration, the authors propose a framework for evaluating the portfolio of integration technologies that are used to unify inter-organisational and intra-organisational information systems. The authors define and classify the permutations of information systems available according to their characteristics and integration requirements. These, classifications of system types are then adopted as part of the evaluation framework and empirically tested within a case study

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Towards an integrated perspective on fleet asset management: engineering and governance considerations

The traditional engineering perspective on asset management concentrates on the operational performance the assets. This perspective aims at managing assets through their life-cycle, from technical specification, to acquisition, operation including maintenance, and disposal. However, the engineering perspective often takes for granted organizational-level factors. For example, a focus on performance at the asset level may lead to ignore performance measures at the business unit level. The governance perspective on asset management usually concentrates on organizational factors, and measures performance in financial terms. In doing so, the governance perspective tends to ignore the engineering considerations required for optimal asset performance. These two perspectives often take each other for granted. However experience demonstrates that an exclusive focus on one or the other may lead to sub-optimal performance. For example, the two perspectives have different time frames: engineering considers the long term asset life-cycle whereas the organizational time frame is based on a yearly financial calendar. Asset fleets provide a relevant and important context to investigate the interaction between engineering and governance views on asset management as fleets have distributed system characteristics. In this project we investigate how engineering and governance perspectives can be reconciled and integrated to enable optimal asset and organizational performance in the context of asset fleets

A conceptual model for EAI adoption in an e-government environment

The non-integrated nature of Local Government Authority (LGA) Information Systems (IS) is strongly associated with the inconsistency and duplication of data, reduction in data integrity and quality, and high operational and maintenance cost. The reason is that legacy IS within the LGAs are usually tailored to support particular business processes and functions and are as a consequence usually difficult to integrate. This gives rise to a strong need for an integrated architecture that facilitates reuse of existing applications and flexibly implementing business processes across the functional boundaries within the LGAs. This paper examines a potentially important area of IS integration in the United Kingdom (UK) LGAs through Enterprise Application Integration (EAI) technology. A review of the literature indicates that EAI has been a focal technology for several organisations in solving their integration problems. However, is new in the LGAs; thus research literature around it is limited. Yet the effect of IS integration using EAI technology remains under explored, as little research has been conducted to comprehend the LGAs perception of integration that influences their decisions and actions. The author demonstrates that it is of high importance to investigate this area within LGAs and result in research that contributes towards successful EAI adoption. Therefore, resulting in the development of a conceptual model that may be used to assist the government decision-making process for EAI adoption in an electronic Government (e-Government) environment

An architecture for organisational decision support

The Decision Support (DS) topic of the Network Enabled Capability for Through Life Systems Engineering (NECTISE) project aims to provide organisational through-life decision support for the products and services that BAE Systems deliver. The topic consists of five streams that cover resource capability management, decision management, collaboration, change prediction and integration. A proposed architecture is presented for an Integrated Decision Support Environment (IDSE) that combines the streams to provide a structured approach to addressing a number of issues that have been identified by BAE Systems business units as being relevant to DS: uncertainty and risk, shared situational awareness, types of decision making, decision tempo, triggering of decisions, and support for autonomous decision making. The proposed architecture will identify how either individuals or groups of decision makers (including autonomous agents) would be utilised on the basis of their capability within the requirements of the scenario to collaboratively solve the decision problem. Features of the scenario such as time criticality, required experience level, the need for justification, and conflict management, will be addressed within the architecture to ensure that the most appropriate decision management support (system/naturalistic/hybrid) is provided. In addition to being reliant on a number of human factors issues, the decision making process is also reliant on a number of information issues: overload, consistency, completeness, uncertainty and evolution, which will be discussed within the context of the architecture

Information systems and healthcare XXIV: Factors affecting the EAI adoption in the healthcare sector

Recent developments in the field of integration technologies like Enterprise Application Integration (EAI) have emerged to support organizations towards improving the quality of services and reducing integration costs. Despite the importance of EAI, there is limited empirical research reported on its adoption in the healthcare sector. Khoumbati et al. [2006] developed a model for the evaluation of EAI in healthcare organizations. In doing so, the causal interrelationship of EAI adoption factors was identified by using fuzzy cognitive mapping. This paper is a progression of previous work in the area and seeks to contribute by validating the model through a different case environment. Thus, this paper contributes by deriving and proposing the MAESTRO model for EAI adoption. MAESTRO identifies a set of factors that influence EAI adoption and it is evaluated through a real-life case study. It provides an understanding of the EAI adoption process through its grounding on empirical data. In doing so, the MAESTRO model supports the management of healthcare organizations during the decision-making process for EAI adoption