Visual-interactive decision modeling (VIDEMO) in policy management: Bridging the gap between analytic and conceptual decision modeling

Policy decision making is a process, rather than a means to an end, stretching over a long time span in a dynamic environment. The advent of easily accessible modeling paradigms promotes the use of sophisticated tools to support policy decision making. It is argued, however, that to be successful in practice, the analytic approaches must be flexible and their role in the problem solving process transparent. In this paper we discuss the concept of visual interactive decision modeling (VIDEMO) in policy management. After positioning decision modeling in the context of problem solving, a generic modeling environment is proposed. It provides the necessary flexibility at the structural level coupled with the required transparency at the formal and resolution levels. The system is based on the premise that policy decision makers can only benefit from the power of analytic modeling if they are supported where and how they want to be supported, without having the analytic tool posing a frame to problem perception, problem analysis, and decision making. In its final version, the proposed VIDEMO approach bridges the gap between analytic and conceptual decision modeling.     

User-model interaction in decision support systems for risk management

This paper describes and evaluates three different approaches to building decision support systems: the Operations Research/Management Science approach, the Decision Analysis/Multiattribute Utility approach, and the Artificial Intelligence/Expert Systems approach. It evaluates the usefulness of the three approaches for risk management. In particular, it defines evaluation objectives of risk analysts, risk managers, and laypeople and provides a subjective assessment how the three approaches stack up against their objectives. The paper concludes that for most risk management applications a combination of the three approaches would be most desirable.This paper was written under contract No. 2709-85-05 ED ISP D of the European Atomic Energy Community, Commission of the European Communities, Joint Research Centre, Ispra Establishment, Ispra, Italy to the Gemeinschaft für Entscheidungs- und Risikoanalyse, Berlin, West Germany. It was prepared for presentation at the Conference on Operations Research and Multiattribute Decision Analysis held in Passau, April 20–26, 1986. The views and opinions expressed in this paper are solely those of the author.     

Multicriteria decision analysis in a decision tree

The outcomes at the tips of a decision tree cannot always be represented by a single numerical value on a one-dimensional axis. In many decision problems they are multidimensional, and their performance is expressed in a mixture of verbal statements and physical or monetary values. We propose to use the scores of cardinal methods for multicriteria decision analysis in order to represent the relative performance of the outcomes. Thereafter, we evaluate the chance forks in the tree via the corresponding aggregation procedure: in the Multiplicative AHP via weighted geometric means of the scores and in SMART via weighted arithmetic means. The procedure is based on the idea that the numerical values of verbal quantifiers like somewhat more, more, … do not depend on what we compare, whether it is relative importance or relative likelihood.     

Patient risk in anesthesia: Probabilistic risk analysis and management improvements

In this paper, we present a pilot study in which we use probabilistic risk analysis (PRA) to assess patient risk in anesthesia and its human factor component. We then identify and evaluate the benefits of several risk reduction policies. We focus on healthy patients, in modern hospitals, and on cases where the anesthetist is a trained medical doctor. When an accident occurs for such patients, it is often because an error was made by the anesthesiologist, either triggering the event that initiated the accident sequence, or failing to take timely corrective measures. We present first a dynamic PRA model of anesthesia accidents. Our data include published results of the Australian Incident Monitoring Study as well as expert opinions. We link the probabilities of the different types of accidents to the state of the anesthesiologist characterized both in terms of alertness and competence. We consider different management factors that affect the state of the anesthesiologist, we identify several risk reduction policies, and we compute the corresponding risk reduction benefits based on the PRA model. We conclude that periodic recertification of all anesthesiologists, the use of anesthesia simulators in training, and closer supervision of residents could reduce substantially the patient risk.     

Error detection and gap filling in cubes of data

We consider the family ZET of algorithms for detecting gross errors and filling the gaps in data tables (object-attribute) and data cubes (object-attribute-time). To work with each element of a table we take the information only from its competent subtable rather than from the whole table. We consider some methods for choosing the “competent” subtable that include tools for avoiding local extrema. An example is presented of the use of a ZET algorithm to solve an applied problem.     

Behavioural decision theory for multi-criteria decision analysis: a guided tour

Multi-criteria decision analysis (MCDA) involves asking decision makers difficult questions, and can leave them thinking that their judgements are not as coherent as they might have thought. This experience can be distressing and may even lead to rejection of the analysis. The psychology of preference sheds light both on how people naturally make choices without decision analytic assistance, and on how people think about the MCDA elicitation questions. As such, it can help the analyst to respond helpfully to difficulties which decision makers may face. In this paper, we review research from Behavioural Decision Theory relevant to MCDA. Our review follows the MCDA process, discussing research relevant to the structuring, value elicitation, and weighting phases of the analysis, outlining relevant and important findings, and open questions for research and practice.     

Enterprise risk management: coping with model risk in a large bank

Enterprise risk management (ERM) has become an important topic in today's more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical sources. Banks especially face financial risks, as the news makes ever more apparent in 2008. This paper demonstrates support to risk management through validation of predictive scorecards for a large bank. The bank developed a model to assess account creditworthiness. The model is validated and compared to credit bureau scores. Alternative methods of risk measurement are compared.     

Signed graphs for portfolio analysis in risk management

We introduce the notion of structural balance for signed graphsin the context of portfolio analysis. A portfolio of securitiescan be represented as a signed graph with the nodes denotingthe securities and the edges representing the correlation betweenthe securities. With signed graphs, the characteristics of aportfolio from a risk management perspective can be uncoveredfor analysis purposes. It is shown that a portfolio characterizedby a signed graph of positive and negative edges that is structurallybalanced is characteristically more predictable. Investors whoundertake a portfolio position with all positively correlatedsecurities do so with the intention to speculate on the upside(or downside). If the portfolio consists of negative edges andis balanced, then it is likely that the position has a hedgingdisposition within it. On the other hand, an unbalanced signedgraph is representative of an investment portfolio which ischaracteristically unpredictable.     

On a risk management analysis of oil spill risk using maritime transportation system simulation

Is it safer for New Orleans river gambling boats to be underway than to be dockside? Is oil transportation risk reduced by lowering wind restrictions from 45 to 35 knots at Hinchinbrook Entrance for laden oil tankers departing Valdez, Alaska? Should the International Safety Management (ISM) code be implemented fleet-wide for the Washington State Ferries in Seattle, or does it make more sense to invest in additional life craft? Can ferry service in San Francisco Bay be expanded in a safe manner to relieve high way congestion? These risk management questions were raised in a series of projects spanning a time frame of more than 10 years. They were addressed using a risk management analysis methodology developed over these years by a consortium of universities. In this paper we shall briefly review this methodology which integrates simulation of Maritime Transportation Systems (MTS) with incident/accident data collection, expert judgment elicitation and a consequence model. We shall describe recent advances with respect to this methodology in more detail. These improvements were made in the context of a two-year oil transportation risk study conducted from 2006?C2008 in the Puget Sound and surrounding waters. An application of this methodology shall be presented comparing the risk reduction effectiveness analysis of a one-way zone, an escorting and a double hull requirement in the same context.     

Multicriteria decision aid in financial management

The financial decisions of an organization are usually included in the context of optimization. Concerning a long-term period, there are decisions related to the optimal allocation of funds, and decisions related to the optimal financial structure. In the short-term case, the decisions are related to the optimization of stocks, cash, accounts receivable, current liabilities, etc. The financial theory analyzes these decisions, mainly from an optimal point of view. The optimal character of such decisions has led researchers to propose operations research techniques to solve the problems that are inherent in such decisions. This paper examines the contribution of multicriteria analysis in solving financial decision problems in a realistic context. The paper also includes an extensive bibliography on the subject.     

The development of computer software for risk analysis: A decision support system development case study

Over the past eight years the Projects Department of BP's Group Engineering and Technical Centre has evolved a risk analysis methodology which is applied during the project appraisal phase to all major engineering construction projects. The computational methods in current use are based on the Common Interval and Memory (CIM) approach, which allows the direct enumeration of distribution combinations rather than the more common Monte Carlo simulation approach. Computer software has been developed in-house to apply these techniques. The programs are written in Fortran and are designed to be used interactively. This paper reviews the general framework of risk analysis applications on BP projects and the lessons learned in developing the first generation of computer software, used until 1985. Some of these lessons may be relevant to decision support system development by others. The development of a new generation of software, now implemented, is also discussed briefly.     

Urban stormwater drainage management: The development of a multicriteria decision aid approach for best management practices

Multicriteria analysis methods have been used over the past decade for resolving environmental issues. This paper deals with the application of a multicriteria analysis (MCA) approach to urban stormwater drainage management. Stormwater source control has become a popular alternative solution for managing stormwater in urban areas. Source control constitutes one variant of best management practices (BMPs) that can be evaluated with respect to various criteria, including: hydraulic efficiency, pollution retention, environmental impact, operation and maintenance, economic investment, and social and sustainable urban living. A French survey was undertaken to assess the performance of different BMPs at the national scale; results highlight the main reasons justifying the use of BMPs. These reasons are primarily related to flood prevention, which far outweighs the economic incentives. Moreover, hydraulic and technical aspects are most frequently noted by users, whereas operation and maintenance aspects are often seen as obstacles to application of these techniques. The survey results, completed by a literature review and expert statements, have been used to establish a matrix of alternatives for multicriteria analysis. The MCA results obtained allow ranking the various alternatives from best to worst, taking into account the different strategies adopted by the decision-makers involved. The development of a multicriteria approach could, in the future, serve as a supporting decision-aid tool, whose purpose would be to guide users in their choice of stormwater source solution.     

Yield management in UK hotels: a systems analysis

A yield management (YM) system is one of the most recent examples of systems development in the hotel industry. YM systems interact with global distribution systems, property management systems and front office systems. However, despite the prevalence of the term ‘systems’, little operational research or systems analysis has been conducted in the hotel sector. In hospitality research journals, yield management is the most researched aspect of hotel operations, but such research is largely conceptual, with limited examples of empirical or systems analysis. This study was designed to undertake, for the first time, a soft systems analysis of yield management in hotels and to develop a systems model. Research was conducted in a number of hotels implementing yield management. One of the case studies is presented to illustrate this. Using this conceptual model, YM theory is critiqued, YM practice is discussed, and subsequently a number of YM issues are identified.     

Generalized evaluation in decision analysis

The paper presents a discussion on evaluation methods in decision analysis. The presentation begins with the discussion of the expected value rule for selection amongst a number of available courses of action. Then a number of other evaluation rules to either replace or supplement the expected value are presented. They are discussed from a choice rather than preference view. To improve the expected value rule (or any other similar rule), it is suggested that it should be supplemented with other, qualitative rules rather than engaging in further modifications in pursuit of the perfect rule. A characteristic of qualitative rules is that they do not rely on multiplying probabilities and values but treat them as separate numeric entities. Once a rule has been agreed upon, it can be applied to all the alternatives, provided there is a computational procedure for evaluating the alternatives under that rule. Delta dominance is introduced as a unifying concept for many of the dominance rules in current use. Dominance and threshold methods are discussed and the kinship between them is pointed out.     

Fifty years of probabilistic decision analysis: a view from the UK

In 1959, LJ Savage attended a statistics seminar held in his honour at the University of London, confronting those present with a radically different approach to reasoning about uncertainty. Britain was well placed to respond to Savage, as very similar ideas had been laid out in Britain a full generation earlier, and in the next few decades, British and British-based practitioners and researchers championed a collection of techniques for thinking quantitatively about uncertainty (which we call ‘Probabilistic Decision Analysis’), developing practice, and contributing to theoretic knowledge about the underlying psychology and mathematics. This effectively turned a collection of purely theoretical ideas into a practical modelling technology. In the first decade of the 21st century, some 50 years on, these ideas have made a noticeable influence on practice and thinking in various domains, but numerous challenges still remain.     

Capturing decision maker preference: Experimental comparison of decision analysis and MCDM techniques

This paper describes the results of a laboratory study which investigates preference in decision making under certainty with multiple, conflicting objectives and continuous decision variables. Techniques for solving such problems are taken from the fields of decision analysis and optimization: the SMART technique for the former and both the NAIVE and Zionts-Wallenius techniques for the latter. The purpose of the experiment is to determine the ability of each technique to correctly capture decision maker preference. In addition, the relative preference of the decision maker for each technique was obtained. The experiment was conducted on a random sample of business school undergraduates and involved a decision with three criteria. The results give insight into the use of several techniques when confronted with decisions with multiple criteria.     

Soft modelling in risk communication and management: examples in handling food risk

Our aim in this paper is to explore the use of soft modelling in an integrated risk communication and management process for managing uncertainties and ‘scares’ in the public domain, particularly in the area of food risk and safety. Much has been written in the past 20 years on the issues relating to the management and communication of food risks and safety issues to the public. Most of this research has been based upon post hoc studies of what went wrong—or, occasionally, right. Here we survey those findings briefly, and draw these into a general framework for risk management and communication. By integrating these into a coherent common framework, we believe that public authorities, food producers and industry may develop more effective strategies for managing and communicating risks which, in turn, will enable the public to make more informed decisions on their diet.     

Raising the bar: strategic multi-criteria decision analysis

This paper discusses the use of multi-criteria decision analysis for supporting strategic decision making in organisations. It begins by exploring the notions of strategic decisions and the strategic decision-making process. We suggest that structuring strategic objectives, dealing with high levels of uncertainty about the future, as well as considering the interconnectedness of strategic options and their long-term consequences are key aspects of strategic decision making support. We then consider the discursive nature of the processes within which strategic decisions are created and negotiated. Our exploration of these concepts leads us to propose a number of adaptations to the standard multi-criteria decision analysis approach, if it were to provide effective strategic decision support, particularly in strategy workshops. We make suggestions on how to implement these proposals, and illustrate their potential with examples drawn from real-world interventions in which we have provided strategic decision support.