Structured what if analysis in DSS models

Philippakis, Andreas S.

doi:10.1109/hicss.1988.11929

Cited by 10 publications

(5 citation statements)

References 15 publications

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“…Even within a single model, alternatives can also exist. In the context of model-based business intelligence, analysts vary input model parameters to explore alternative what-if scenarios [11,32]. Similarly, Boukhelifa et al [3] find that alternative analysis scenarios branch out from previous research questions and hypotheses in collaborative model sensemaking.…”

Section: Various Concepts Around Alternativesmentioning

confidence: 99%

Understanding the Role of Alternatives in Data Analysis Practices

Liu

Boukhelifa

Eagan

2019

IEEE Trans. Visual. Comput. Graphics

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Data workers are people who perform data analysis activities as a part of their daily work but do not formally identify as data scientists. They come from various domains and often need to explore diverse sets of hypotheses and theories, a variety of data sources, algorithms, methods, tools, and visual designs. Taken together, we call these alternatives. To better understand and characterize the role of alternatives in their analyses, we conducted semi-structured interviews with 12 data workers with different types of expertise. We conducted four types of analyses to understand 1) why data workers explore alternatives; 2) the different notions of alternatives and how they fit into the sensemaking process; 3) the high-level processes around alternatives; and 4) their strategies to generate, explore, and manage those alternatives. We find that participants' diverse levels of domain and computational expertise, experience with different tools, and collaboration within their broader context play an important role in how they explore these alternatives. These findings call out the need for more attention towards a deeper understanding of alternatives and the need for better tools to facilitate the exploration, interpretation, and management of alternatives. Drawing upon these analyses and findings, we present a framework based on participants' 1) degree of attention, 2) abstraction level, and 3) analytic processes. We show how this framework can help understand how data workers consider such alternatives in their analyses and how tool designers might create tools to better support them.

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Section: Various Concepts Around Alternativesmentioning

confidence: 99%

Understanding the Role of Alternatives in Data Analysis Practices

Liu

Boukhelifa

Eagan

2019

IEEE Trans. Visual. Comput. Graphics

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“…What-if analysis is a method used to understand the outcomes and impacts of changes by systematically varying variables. What-if analysis allows the researcher to measure the effect of changing values of variables on the overall outcome (Philippakis, 1988). A few commercial tools are available that can assist in performing what-if analysis (Matteo, Stefano, & Andrea, 2006 Figure 9 shows that single-and family-ownerships firms use the tool least commonly.…”

Section: What-if Analysismentioning

confidence: 99%

Organizations’ Use of Strategic Planning Tools and Techniques in the Sultanate of Oman

Rajasekar¹,

Raee

2014

IBR

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This study on the use of strategic planning tools and techniques in the Sultanate of Oman aims to contribute to the research on strategic planning processes. Currently, only a few research studies have been conducted on strategic planning in developing countries, especially in the Middle East. Almost no evidence of such research exists to understand the extent of the use of strategic planning tools and techniques in the Sultanate of Oman. The study used a questionnaire to ask about 14 strategic planning tools and techniques. Twenty organizations in Oman that have a written strategic plan comprised the sample population. The data were collected from heads of departments and sections, directors, managers, and advisors directly involved in the strategic planning process. The analysis shows that the most commonly used strategic planning tools employed by organizations in Oman are benchmarking, followed by stakeholders analysis and then strengths, weaknesses, opportunities, and threats (SWOT) analysis, while the Delphi technique, experience curve, Porter's five forces, and what-if analysis techniques were the least commonly used. Considering the segmentation of organizations, one can see that the financial sector and business groups use the tools most frequently whereas the single-and family-ownership groups have limited use of strategic planning tools. On average, almost 30% of the organizations in Oman never or very rarely uses strategic planning tools. This paper provides an understanding of strategic planning in Oman and supplies the missing links in the previous studies conducted on strategic planning.

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“…What-If analysis can be described as a data-intensive simulation that inspects the behavior of a complex system under some given hypothesis (called scenarios) [35]. More pragmatically, What-If analysis measures how changes in a set of independent variables impact a set of dependent variables with reference to a given simulation model [36]. What-If analysis can be used to solve several complicated problems, especially for highly complex research models where the number of variables would make it difficult for general classification models to find patterns [37].…”

Section: Introductionmentioning

confidence: 99%

Predicting Factors Affecting Adolescent Obesity Using General Bayesian Network and What-If Analysis

Kim

Costello

Lee

et al. 2019

IJERPH

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With the remarkable improvement in people’s socioeconomic living standards around the world, adolescent obesity has increasingly become an important public health issue that cannot be ignored. Thus, we have implemented its use in an attempt to explore the viability of scenario-based simulations through the use of a data mining approach. In doing so, we wanted to explore the merits of using a General Bayesian Network (GBN) with What-If analysis while exploring how it can be utilized in other areas of public health. We analyzed data from the 2017 Korean Youth Health Behavior Survey conducted directly by the Korea Centers for Disease Control & Prevention, including 19 attributes and 11,206 individual data points. Our simulations found that by manipulating the amount of pocket money-between $60 and $80-coupled with a low-income background, it has a high potential to increase obesity compared with other simulated factors. Additionally, when we manipulated an increase in studying time with a mediocre academic performance, it was found to potentially increase pressure on adolescents, which subsequently led to an increased obesity outcome. Lastly, we found that when we manipulated an increase in a father’s education level while manipulating a decrease in mother’s education level, this had a large effect on the potential adolescent obesity level. Although obesity was the chosen case, this paper acts more as a proof of concept in analyzing public health through GBN and What-If analysis. Therefore, it aims to guide health professionals into potentially expanding their ability to simulate certain outcomes based on predicted changes in certain factors concerning future public health issues.

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Structured what if analysis in DSS models

Cited by 10 publications

References 15 publications

Understanding the Role of Alternatives in Data Analysis Practices

Understanding the Role of Alternatives in Data Analysis Practices

Organizations’ Use of Strategic Planning Tools and Techniques in the Sultanate of Oman

Predicting Factors Affecting Adolescent Obesity Using General Bayesian Network and What-If Analysis

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