Decision development in facilitated modelling workshops

While the facilitated modelling literature recognises the importance of the group process within facilitated modelling workshops, published empirical research rarely examines their dynamic nature. In this paper, we address this gap in the literature in two ways. First, we propose to locate facilitated modelling workshops as the main focus of investigation, and adopt decision development as the analytical lens. Second, we provide guidance regarding how to implement a research strategy that is informed by such a focus. We start by mapping the different conceptualisations of decision development that seem embedded within the facilitated modelling tradition, and contrast them with theoretical models from the group communication field. Our analysis identifies a number of potentially useful areas for the study of facilitated modelling workshops from a decision development perspective, and articulates a number tentative research questions and testable propositions amenable to empirical research. Central to our proposal are research methods for the study of dynamic group processes. We thus discuss the steps required to extract group process data from facilitated modelling workshops that are usable and open to analysis. This includes a review of issues regarding research design, coding scheme development, data coding and choice of analytical techniques. Finally, we offer conclusions and briefly discuss some feasibility issues related to the implementation of our proposal.     

Strategy,performance and operational research

This paper explores the nature of operational research and its interactions with performance measurement and strategy. It is argued that operational research (OR) is well fitted to handle strategic issues as the modelling approach of OR facilitates understanding and learning, and the evaluation of strategies prior to action. The development of problem structuring methods is also a key aid to strategy and policy formulation. OR is also beginning to play a role in performance measurement and there is an opportunity for OR to lead in the improvement of performance measurement systems.     

Evaluating Strategy — Its Role Within the Context of Strategic Control

The paper uses a case study to illustrate a number of points in relation to strategy development and strategic control. A group decision support system — ‘Strategic Options Development and Analysis’ (SODA) — was used. The method focuses on the ‘linkages’ between strategic issues rather than on the issues themselves. The paper focuses upon the strategy review process. Three related elements of strategy' are considered as a part of the review: an evaluation of the extent to which the strategy has been implemented and is embedded in the organization; an evaluation of the assumptions underpinning the strategy; and an evaluation of the influence the strategy has on those at the ‘coal-face’.     

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.     

Challenge Versus Exchange in Collective Decision Making: A Comparison of Two Simulation Models Based on Simulated Data

In collective decision making, actors can use different influence strategies to get their way. Differences in influence strategies may, or may not, be connected to differences in collective outcomes. This research studies two influence strategies: the exchange strategy and the challenge strategy. In the existing literature, these strategies are analyzed and compared using simulation models in which actor behavior regarding influence attempts based on one of the strategies is modeled explicitly. Until now, these models have been tested only empirically on limited data sets. However, a theoretical test is necessary to gain more precise insights in the effect of characteristics of collective decision making situations on the collective outcomes. In the present research, computer simulations are used in a structured comparison of two competing models (the iterative exchange model and challenge model). The analyses show that the outcomes of both models are captured for a large part in the actor characteristics on the issues. Besides this, the expected directions of challenges and exchanges play a major part in explaining the outcomes of the models. This research shows that the use of simulated data allows a structured search of the input space, which led to new insights into the iterative exchange model and challenge model, and therefore in the exchange strategy and the challenge strategy.     

Selection of technology acquisition mode using the analytic network process

Selecting the appropriate acquisition mode for a required technology, is one of the critical strategic decisions in formulating a technology strategy. Although a number of factors were found to be influential in the choice of technology acquisition mode, it still remains a void in the literature how to make a strategic decision, based on a huge set of those factors with the help of a systematic approach. This study deals with the selection of technology acquisition mode as a multiple criteria decision making (MCDM) problem. The proposed solution to the problem in this study, is the analytic network process (ANP) approach. Since the ANP is a MCDM method that can accommodate interdependency among decision attributes, it is capable of providing priorities of alternatives with consideration of interrelationships among strategic factors. The 21 influential factors identified from the empirical studies are included as sub-criteria in the ANP model, and they are grouped into five criteria: capability, strategy, technology, market, and environment. The final decision can be made based on the resulting priorities of the alternative acquisition modes. The proposed approach is expected to effectively aid decision making on which mode is adopted for acquisition of required technologies. A case of a software company is presented for the illustration of the proposed approach.     

基于粗集模糊物元的项目组合配置战略贴近度研究

战略导向下的项目组合配置问题是企业进行多项目管理时需要解决的重要问题,对企业战略目标最大化的实现起到关键作用。论文在研究项目与项目关系的视角下,以项目组合配置方案和企业战略关系为出发点,提出了项目组合配置战略贴近度概念,构建了项目组合配置模糊物元模型,并以战略贴近度值的大小为度量标准,对项目组合配置方案与企业战略吻合程度进行分析,为企业项目组合管理提供决策依据。     

Strategic control and interests,its effects on decision outcomes

Application of the model to artificial data shows that actors with strong preferences in the center have more possibilities to realize good outcomes than other actors. On the basis of an empirical application it is shown that a Nash equilibrium does not always arise after a large number of iterations unless actors have learning capabilities or are severely restricted in their strategic behavior.

In political systems and large organizations, ultimate decision makers are usually just a small subset of all actors in the social system. To arrive at acceptable decisions, decision makers have to take into account the preferences of other actors in the system. Typically preferences of more interested and more powerful actors are weighted heavier than those of less interested and powerful actors. This implies that the total leverage of an actor on the decision is determined by the combination of his power (his potential) and his interest (his willingness to mobilize his power). As the exact level of an actor's leverage is difficult to estimate for the other actors in the system, an actor is able to optimize his effects on outcomes of decisions by providing strategic informatioa

In this paper, first an analytic solution is presented for the optimization of strategic leverage in collective decision making by one single actor. In this solution, the actor makes assumptions about the leverage other actors will show in decision making. Subsequently, the actor optimizes the outcomes of decisions by manipulating the distribution of his leverage over a set of issues.

The analytic solution can be theoretically interpreted by decomposing the solution into three terms, the expected external leverage of the other actors on the issue, the evaluation of the deviance of the expected from the preferred outcome of the issue, and the restrictions on the distribution of leverage over the issues. The higher the expectation of the leverages the other actors will allocate to the issue, the less an actor is inclined to allocate leverage to the issue. The higher the evaluation of the deviance, the more an actor is inclined to allocate leverage to the issue. This is restricted, however, by the required distribution of leverages over the issues. The researcher is able to manipulate these restrictions to investigate its consequences for the outcomes.

In the next step, we investigate whether we can find a Nash equilibrium if all actors optimize their leverage simultaneously. Under certain conditions, a Nash equilibrium can be found by an iterative process in which actors update their estimates oh each other's leverages on the basis of what the other actors have shown in previous iterations.     

Supporting strategic conversations: the significance of a quantitative model building process

This paper reports on the use of a quantitative system dynamics simulation model building process that followed on from a ‘soft OR’ strategy making intervention with a top management team. The work was carried out for the Chief Constable and top team of a UK police force. The output of the ‘soft OR’ strategy making process provided the reason for, and so focus of, the simulation model. The focus of the strategic conversation was on exploring the tension between the supply of resources (in this case police officers) and the demands placed on those officers. The project involved a series of strategic conversations with members of the top team that were stimulated through the process of building a system dynamics model. The process was facilitated by two modellers—one focussing on managing the strategic enquiry, while the other considered the implications of the conversation for the construction of the system dynamics model. Through the process of gradually building the system dynamics model, a number of issues and lessons were raised for the development and delivery of effective strategy making and the strategic management of public organisations. In addition there were implications for operational research model building processes, especially when operating at senior levels and within a strategic context.     

An exploration into the influence of psychological profiles upon group decision making

This paper looks at a problem where a group, made up of individuals from a variety of different organisations but with similar technical backgrounds, had the task of producing a forecast for their particular industry. The forecast was to be published by their technical institute and was therefore of general interest in stimulating debate. The group members used a form of judgemental modelling to produce their individual forecasts. After these initial outcomes, the group was split into three sub-groups based upon a method of psychological profiling, with each subgroup repeating the exercise and producing a group-negotiated forecast. The results presented here show how group composition affects the way in which individuals negotiate towards a final outcome. The conclusions reached have implications for decision making aids using decision support systems, both for systems that aim to facilitate and for those that attempt to model the process. Although only a small experiment, the results suggest that there is tremendous potential benefit from this avenue of research when applied to the developing technologies of group decision and negotiation systems.     

Does the Balanced Scorecard make a difference to the strategy development process?

A great number of strategy tools are being taught in strategic management modules. These tools are available to managers for use in facilitating strategic decision making and enhancing the strategy development process in their organisations. A number of studies have been published examining which are the most popular tools; however there is little empirical evidence on how their utilisation influences the strategy process. This paper is based on a large scale international survey on the strategy development process, and seeks to examine the impact of a particular strategy tool, the Balanced Scorecard (BSC), upon the strategy process. Recently, it has been suggested that as a strategy tool, the BSC can influence all elements of the strategy process. The results of this study indicate that although there are significant differences in some elements of the strategy process between the organisations that have implemented the BSC and those that have not, the impact is not comprehensive.     

Choice of modelling technique for evaluating health care interventions

Economic evaluation, such as cost effectiveness analysis, provides a method for comparing healthcare interventions. These evaluations often use modelling techniques such as decision trees, Markov processes and discrete event simulations (DES). With the aid of examples from coronary heart disease, the use of these techniques in different health care situations is discussed. Guidelines for the choice of modelling technique are developed according to the characteristics of the health care intervention.The choice of modelling technique is shown to depend on the acceptance of the modelling technique, model ‘error’, model appropriateness, dimensionality and ease and speed of model development. Generally decision trees are suitable for acute interventions but they cannot model recursion and Markov models are suitable for simple chronic interventions. It is further recommended that population based models be used in order to provide health care outcomes for the likely cost, health benefits and cost effectiveness of the intervention. The population approach will complicate the construction of the model. DES will allow the modeller to construct more complex, dynamic and accurate systems but these may involve a corresponding increase in development time and expense. The modeller will need to make a judgement on the necessary complexity of the model in terms of interaction of individuals and model size and whether queuing for resources, resource constraints or the interactions between individuals are significant issues in the health care system.     

Domain knowledge integration in data mining using decision tables: case studies in churn prediction

Companies' interest in customer relationship modelling and key issues such as customer lifetime value and churn has substantially increased over the years. However, the complexity of building, interpreting and applying these models creates obstacles for their implementation. The main contribution of this paper is to show how domain knowledge can be incorporated in the data mining process for churn prediction, viz. through the evaluation of coefficient signs in a logistic regression model, and secondly, by analysing a decision table (DT) extracted from a decision tree or rule-based classifier. An algorithm to check DTs for violations of monotonicity constraints is presented, which involves the repeated application of condition reordering and table contraction to detect counter-intuitive patterns. Both approaches are applied to two telecom data sets to empirically demonstrate how domain knowledge can be used to ensure the interpretability of the resulting models.     

An agent-based model of organizational ambidexterity decisions and strategies in new product development

Organizational ambidexterity, defined as the pursuit of both exploitation and exploration, has become an important topic in the study of organizations, especially in innovation management theory. Previous literature has not focused on the strategic (game-theoretic) aspects of organizational ambidexterity or on its decision-making aspects. Little is known about how or even whether the decision to adopt ambidexterity is competitively advantageous in the presence of diverse strategies that competitors may adopt. This facet of the subject is inherently game-theoretic; the value of a decision by one firm depends in part on decisions made by other firms. This paper initiates systematic investigation of these strategic aspects, including the overall performance of available strategies. Specifically, this study examines questions of ambidexterity-related strategy performance in the context of new product development. The main contributions are (1) to introduce and make available to the research community an agent-based model and decision support system that captures many of the key aspects and tradeoffs, which have been identified in the literature, of the exploration–exploitation dilemma faced by firms in the new product development process, with a focus on organizations’ product investment decisions and (2) to report on results obtained from the model, calibrated with available data from the literature, augmented by new data collected from interviews with practitioners.     

Inventory management with periodic ordering and minimum order quantities

Periodic review systems are commonly employed by distributors and retailers to replenish their inventories (for example, to co-ordinate in-bound transportation). It is also often the case that vendors specify minimum purchase quantities for physical (for example, packaging) or strategic reasons. When inventory systems recommend order quantities below the prescribed minimum, a decision must be made on whether or not to order. We describe how this environment can be modelled, and employ an extensive factorial experiment involving a simulation to demonstrate situations in which a common simple ‘rounding up’ decision rule performs poorly. In this paper, we discuss financial implications and implementation issues.     

Facilitation practices in decision workshops

Decision workshops, sometimes called decision conferences, help a group of decision makers gain a shared understanding of a decision problem, analyse issues and commit to an action plan under the guidance of an experienced facilitator. This work seeks to identify best practice in the early stages of the facilitation of such workshops when the emphasis is placed on problem structuring and the main issues of a complex decision problem are identified and explored. Four decision workshops, based on the same hypothetical scenario but facilitated by a different person, were organized. Video material of the simulated workshops was analysed to compare and contrast the facilitated meetings including the problem structuring methods used. A framework for studying facilitation practices emerged. The effect of a facilitator on the structuring of the problem, the group decision process and the outcome of the workshop was studied. The results of the work indicate that a facilitator's style and approach to the workshop may have an impact on the action plan devised. Further research is required to generalize the findings of our work.     

An optimization-based decision support system for strategic planning in a process industry: the case of aluminium company in India

We describe how a generic multi-period optimization-based decision support system (DSS) can be used for strategic planning in process industries. The DSS is built on five fundamental elements—materials, facilities, activities, storage areas, and time periods. It requires little direct knowledge of optimization techniques to be used effectively. Results based on real data from an aluminium company in India demonstrate significant potential for improvement in profits. We conclude with a comparison of similar studies in two other process industries.     

Facilitated modelling in operational research

The traditional way of employing operational research in organisational interventions has been the expert mode. In this mode, the problem situation faced by the client is given to the operational research consultant, who then builds a model of the situation, solves the model to arrive at an optimal (or quasi-optimal) solution, and then provides a recommendation to the client based on the obtained solution. An alternative mode of engagement is to conduct the whole intervention together with the client: from structuring and defining the nature of the problem situation of interest, to supporting the evaluation of priorities and development of plans for subsequent implementation. In this latter mode, the operational researcher works throughout the intervention not only as an analyst, but also as a facilitator to the client. This paper discusses this latter mode of engagement with clients, with particular emphasis on the use of facilitated modelling as the intervention tool. Drawing on research scattered across a range of publications and domains, the review presented here provides a formal definition of facilitated modelling, together with a general framework that allows the conceptualisation of a wide variety of facilitated modelling approaches to organisational intervention. Design issues in facilitated modelling and their practical implication are discussed, and directions for future research identified.     

Increasing engineering students' awareness to environment through innovative teaching of mathematical modelling

This article presents the results of two studies on using aninnovative pedagogical strategy in teaching mathematical modellingand applications to engineering students. Both studies are dealingwith introducing non-traditional contexts for engineering studentsin teaching/learning of mathematical modelling and applications:environment and ecology. The aims of using these contexts were:to introduce students to some of the techniques, methodologiesand principles of mathematical modelling for ecological andenvironmental systems; to involve the students in solving real-lifeproblems adjusted to their region emphasizing the aspects ofboth survival (short term) and sustainability (long term); toencourage students to pay attention to environmental issues.On one hand, the contexts are not directly related to engineering.On the other hand, the chances are that many graduates of engineeringwill deal with mathematical modelling of environmental systemsin one way or another in their future work because nearly everyengineering activity has an impact on the environment. The firststudy is a parallel study conducted in New Zealand and Germanysimultaneously with first-year students studying engineeringmathematics. The second study is a case study of the experimentalcourse Mathematical Modelling of Survival and Sustainabilitytaught to a mixture of year 2–5 engineering students inGermany by a visiting lecturer from New Zealand. The modelsused with the students from both studies had several specialfeatures. Analysis of students’ responses to questionnaires,their comments and attitudes towards the innovative approachin teaching are presented in the article.     

Artificial Intelligence and Decision Analysis

Much work has been done on the development of modelling techniques to assist in the process of decision-making. The areas of operational research and statistical analysis are well established, and the speed and memory capacity of computers has facilitated the solution of very large problems using such techniques. Recent developments in artificial intelligence, particularly with regard to expert systems, open up the possibility of modelling the decision-maker rather than the decision situation. This would result in a much more sophisticated decision-support system, but as yet it is an approach which has not been investigated to any significant degree. This paper suggests how AI techniques might be combined with traditional problem-based methodologies to provide a comprehensive decision-analysis support-system framework, modelling the activities of a human decision-maker and providing access to a host of traditional and artificial intelligence tools which can be effectively interfaced.