Constructing Battlefield Understanding: A Comparison of Experienced and Novice Decision Makers in Different Contexts

Author(s):  
Lawrence G. Shattuck ◽  
Christopher Talcott ◽  
Michael D. Matthews ◽  
Jennifer Clark ◽  
Matthew Swiergosz

Understanding the evolving, complex events on a battlefield requires a decision maker to gather and integrate data from disparate sources. The work described herein is the final in a series of studies that investigates the decision making processes employed by military decision makers. Twenty-one Army officers participated in a simulation of an offensive military operation. The results of this study are compared to the results of three previous studies involving participants with differing levels of expertise (experienced versus novice) and using different types of scenarios (defense versus offense). Results strongly suggest that performance of military decision makers varies based on levels of experience and the data they gather vary according to context. Implications for design of decision support systems are also discussed.

2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.


Author(s):  
Jan Kalina

The COVID-19 pandemic accelerated trends to digitalization and automation, which allow us to acquire massive datasets useful for managerial decision making. The expected increase of available data (including big data) will represent a potential for an increasing deployment of management decision support systems for more general and more complex tasks. Sophisticated decision support systems have been proposed already in the pre-pandemic times either to assist managers in specific decision-making processes or to perform the decision making fully automatically. Decision support systems are presented in this chapter as perspective artificial intelligence tools contributing to a deep transform of everyday management practices. Attention is paid here to their new development in the quickly transforming post-COVID-19 era and to their role under the post-pandemic conditions. As an original contribution, this chapter presents a vision of information-based management, which far exceed the rather limited pre-pandemic visions of evidence-based management focused primarily on critical thinking.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Thais Cristina Sampaio Machado ◽  
Plácido Rogerio Pinheiro ◽  
Isabelle Tamanini

The decision making is present in every activity of the human world, either in simple day-by-day problems or in complex situations inside of an organization. Sometimes emotions and reasons become hard to separate; therefore decision support methods were created to help decision makers to make complex decisions, and Decision Support Systems (DSS) were created to aid the application of such methods. The paper presents the development of a new tool, which reproduces the procedure to apply the Verbal Decision Analysis (VDA) methodology ORCLASS. The tool, called OrclassWeb, is software that supports the process of the mentioned DSS method and the paper provides proof of concepts, that which presents its reliability with ORCLASS.


Author(s):  
Frédéric Adam ◽  
Jean-Charles Pomerol ◽  
Patrick Brézillon

In this article, a newspaper company which has implemented a computerised editorial system is studied in an attempt to understand the impact that groupware systems can have on the decision making processes of an organisation. First, the case study protocol is presented, and the findings of the case are described in detail. Conclusions are then presented which pertain both to this case and to the implementation of decision support systems that have a groupware dimension.


Author(s):  
Udo Richard Averweg

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.


2020 ◽  
Vol 26 (11) ◽  
pp. 631-640
Author(s):  
T. K. Kravchenko ◽  
◽  
S. N. Bruskin ◽  
D. V. Isaev ◽  
E. V. Kuznetsova ◽  
...  

The article focuses on the application of decision support systems for prioritization of product backlog items in IT projects implemented using the Scrum methodology. The study identified the features of prioritization of different types of the product backlog items — user stories, epics and themes. It is justified that high-level product backlog items (epics and themes) require comprehensive prioritization, due to the following reasons. First, high-level product backlog items are particularly important because they determine the planning and implementation of detailed user stories within individual sprints. Second, any high-level item can be considered in terms of different criteria. Third, the implementation of epics and themes takes longer time compared to the implementation of user stories, so it is necessary to take into account possible future states of the project's environment. Fourth, prioritizing epics and themes requires increased objectivity and validity, so group decision making with participation of several experts seems reasonable. Taking into consideration the aforementioned features the conclusion regarding limitations of existing methods of prioritization is made. It is argued that prioritization of high-level product backlog items (epics and themes) may be performed using multi-criteria decision making methods with availability of several problem situations (possible future states of the environment), as well as involvement of several experts. The idea of applying decision support methods and systems is illustrated on the appropriate example. It is also argued that increased consumption of time and resources related with setting and solving decision support tasks may be considered as acceptable for high-level product backlog items.


2020 ◽  
Vol 10 (13) ◽  
pp. 4614
Author(s):  
João Carneiro ◽  
Diogo Martinho ◽  
Patrícia Alves ◽  
Luís Conceição ◽  
Goreti Marreiros ◽  
...  

To support Group Decision-Making processes when participants are dispersed is a complex task. The biggest challenges are related to communication limitations that impede decision-makers to take advantage of the benefits associated with face-to-face Group Decision-Making processes. Several approaches that intend to aid dispersed groups attaining decisions have been applied to Group Decision Support Systems. However, strategies to support decision-makers in reasoning, understanding the reasons behind the different recommendations, and promoting the decision quality are very limited. In this work, we propose a Multiple Criteria Decision Analysis Framework that intends to overcome those limitations through a set of functionalities that can be used to support decision-makers attaining more informed, consistent, and satisfactory decisions. These functionalities are exposed through a microservice, which is part of a Consensus-Based Group Decision Support System and is used by autonomous software agents to support decision-makers according to their specific needs/interests. We concluded that the proposed framework greatly facilitates the definition of important procedures, allowing decision-makers to take advantage of deciding as a group and to understand the reasons behind the different recommendations and proposals.


1991 ◽  
Vol 67 (6) ◽  
pp. 622-628 ◽  
Author(s):  
Dan Bulger ◽  
Harold Hunt

The focus of a decision support system is much different from Management Information Systems (MIS) and data-based "decision support systems". Decision support systems, as defined by the authors, focus on decisions and decision makers, and on information. Technology is treated as a tool and data as the raw material. In many traditional systems the focus is on the technology, and the data is the "information", while decision makers are, to some extent, externalized.The purpose of the Forest Management Decision Support System (FMDSS) project is to develop a set of software tools for creating forest management decision support systems. This set of tools will be used to implement a prototype forest management decision support system for the Plonski forest, near Kirkland Lake, Ontario.There are three critical ingredients in building the FMDSS, these are: (1) knowledge of the decision making process, (2) knowledge of the forest, and (3) the functionality of underlying support technology. The growing maturity of the underlying technology provides a tremendous opportunity to develop decision support tools. However, a significant obstacle to building FMDSS has been the diffuse nature of knowledge about forest management decision making processes, and about the forest ecosystem itself. Often this knowledge is spread widely among foresters, technicians, policy makers, and scientists, or is in a form that is not easily amenable to the decision support process. This has created a heavy burden on the project team to gather and collate the knowledge so that it could be incorporated into the function and design of the system. It will be difficult to gauge the success of this exercise until users obtain the software and begin to experiment with its use.


2021 ◽  
Vol 93 ◽  
pp. 88-102
Author(s):  
A. A. Aparin ◽  

Introduction. The article is devoted to the study of the features of managerial decision-making in complex socio-economic systems in the context of fire and rescue units management. The article deals with the decomposition of the decision-making process into the main elements and provides a thematic analysis of each of them. The author's classification of decision-makers on the fire from among the main positions and non-regular officials of the garrison is presented. The tasks of the research are to analyze the current state of the basic conceptual apparatus of the theory of decision support in the management of fire protection units and to formulate the most general approach to the definition of the decision support process. Methods. The analysis of Russian- and English-language literary, normative and statistical sources of information on the topic under consideration is carried out. The result of the decomposition and synthesis of the analyzed information is tables, figures and diagrams, as well as explanations to them. The author also compares the approaches to decision-making from the Russian-language management theory with the results of empirical studies conducted abroad. Results and discussion. A theoretical review of the basic provisions of the theory of decision support with an appeal to the features inherent in the process of managing fire protection units is carried out. The author presents the results of a retrospective analysis of the development of approaches to the definition of the concepts of "decision support system" and "management support", as well as the definition of the term "support of decision making". Conclusions. Based on the results of the study, a hypothesis is formulated that at the stage of development of specialized decision support systems for decision makers, a synthesis between different approaches will remain. Keywords: decision support systems, management support, decision support, fire department management, complex socio-economic systems


Author(s):  
R. A. Kelly ◽  
W. S. Merritt

Coastal lakes are ecosystems which provide significant environmental, social and economic values. They are a key habitat for many aquatic species, particularly for juvenile fish and aquatic invertebrates. They are a focus for human activity, including recreation, tourism, and many forms of industry and production such as oyster and commercial fisheries. More and more the foreshore areas of lakes are seen as a desirable place to live, with urban development a key pressure on lake systems. However current development, use and management of these systems mean that these values are already under threat. Environmental managers, urban planners and other decision makers need to make complex decisions about patterns of current and future use of these systems which allow for the trade-offs associated with various activities to be effectively taken into account. Decision support systems (DSS) are seen to have a role to play in supporting these activities.When developed properly, DSS can support decision making processes by providing users with a tool that shows the relationships between drivers of a system and outcomes. Environmental outcomes (e.g. estuary health) are controlled by often complex biophysical, ecological, economic and/or social drivers and processes. In this context a DSS should address uncertainty in data, knowledge and predictions, and allow users to explore the sensitivity of outcomes to controllable drivers (e.g. management actions), uncontrollable drivers (e.g. climate variability) and uncertainty. The DSS development and adoption process also needs to be flexible to a changing decision making environment. Ultimately the success of any DSS will depend not only on its technical capacity, including the robustness of any science underlying it, or the ease of use of any interface but also on the circumstances into which it arrives: the time and money allowed for training, capacity building, incorporation of stakeholder comments and development of trust between DSS developers, scientists and the community; the way in which the DSS is embedded in the decision making process; and the ‘politics’ and constantly changing face of the decision making environment.This chapter will discuss issues regarding the development of a DSS under typical planning timeframes where there are limited resources (time and budgetary) and where current and future management issues may not be certain and/or may change over the planning timeframe. The chapter largely draws on experiences gained during the development and application of the CAPER DSS in the Great Lakes, NSW Australia.


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