IEEE Trans Vis Comput Graph. 2022 Dec;28(12):4101-4112. doi: 10.1109/TVCG.2021.3074023. Epub 2022 Oct 26.
When an organization chooses one course of action over alternatives, this task typically falls on a decision maker with relevant knowledge, experience, and understanding of context. Decision makers rely on data analysis, which is either delegated to analysts, or done on their own. Often the decision maker combines data, likely uncertain or incomplete, with non-formalized knowledge within a multi-objective problem space, weighing the recommendations of analysts within broader contexts and goals. As most past research in visual analytics has focused on understanding the needs and challenges of data analysts, less is known about the tasks and challenges of organizational decision makers, and how visualization support tools might help. Here we characterize the decision maker as a domain expert, review relevant literature in management theories, and report the results of an empirical survey and interviews with people who make organizational decisions. We identify challenges and opportunities for novel visualization tools, including trade-off overviews, scenario-based analysis, interrogation tools, flexible data input and collaboration support. Our findings stress the need to expand visualization design beyond data analysis into tools for information management.
当一个组织在多个可选方案中选择一个行动方案时，这项任务通常由具有相关知识、经验和对背景了解的决策者来完成。决策者依赖数据分析，这些数据可以委托给分析师，也可以由决策者自己来做。通常，决策者会将数据（可能是不确定或不完整的）与多目标问题空间中的非形式化知识相结合，在更广泛的背景和目标下权衡分析师的建议。由于过去大多数视觉分析研究都集中在了解数据分析师的需求和挑战上，因此对于组织决策者的任务和挑战以及可视化支持工具如何提供帮助的了解较少。在这里，我们将决策者描述为领域专家，回顾管理理论中的相关文献，并报告对做出组织决策的人员进行的实证调查和访谈的结果。我们确定了新颖可视化工具的挑战和机遇，包括权衡概述、基于场景的分析、查询工具、灵活的数据输入和协作支持。我们的研究结果强调了需要将可视化设计从数据分析扩展到信息管理工具。
