UKCustomPapers | An Overview of Business Intelligence, Analytics, Data Science, and AI

An Overview of Business Intelligence, Analytics, Data Science, and AI

What is sensitivity analysis and how can it help your organization?Links to an external site.
Exploring multiple goals balancing in complex problem solving based on log dataLinks to an external site.
In terms of input data, predictions and assumptions are a distinctive part of model building. According to Delen, Sharda, and Turban (2023), “Sensitivity analysis attempts to assess the impact of a change in the input data parameters on the proposed solution (i.e., via the result variable)” (p.347). Prescriptive analysis relies on sensitivity analysis as it provides flexibility and adaptability to changing conditions. The same holds true for what-if analysis. This system allows the user to input questions associated with “what will happy if.” Inversely, goal seeking is a type of backward analysis in that the use interjects the values needed to achieve a specific intended goal. Finally, decision tables aid the user in organizing data and knowledge into a systemic platform sheet that can be tracked and analyzed to make informed decisions.

In your paper,

Discuss two reasons for implementing sensitivity analysis in the healthcare industry.
Discuss two difficulties that may arise when analyzing multiple goals.
Explain why a healthcare administrator might perform what-if analysis.
Discuss why a healthcare administrator might use goal seeking analysis.
Analyze the difference between decision tables and decision trees.
Explain how decision trees can be used in decision-making processes in a healthcare organization.
Prescriptive Analytics Determining the Impact of Change paper,

Sample Answer

Prescriptive Analytics: Determining the Impact of Change in Healthcare

Sensitivity analysis, what-if analysis, goal seeking, and decision tools like tables and trees are fundamental components of prescriptive analytics. These techniques empower healthcare organizations to move beyond merely understanding past events or predicting future trends, enabling them to actively optimize decisions and respond effectively to dynamic conditions.

What is Sensitivity Analysis and How Can It Help Your Organization?

Sensitivity analysis is a quantitative technique used to determine how different values of an independent variable (input parameter) affect a particular dependent variable (output or solution) under a given set of assumptions. In simpler terms, it answers the question: “How sensitive is our outcome to changes in a specific input?” By systematically varying one or more input parameters and observing the impact on the model’s output, organizations can identify critical drivers of their results and assess the robustness of their proposed solutions.

How it can help an organization:

For any organization, including healthcare, sensitivity analysis provides several key benefits:

Risk Assessment and Management: It helps identify which input variables pose the greatest risk to the desired outcome. For example, in a financial model, it might show that a small change in interest rates has a disproportionately large impact on profitability. This allows the organization to focus its risk mitigation efforts on these high-leverage variables.

Full Answer Section

Improved Decision-Making: By understanding the range of possible outcomes given variations in uncertain inputs, decision-makers can make more informed and robust choices. It helps them prepare for different scenarios and build contingency plans, leading to more resilient strategies.
Resource Allocation: It can guide where resources should be concentrated. If a particular factor is highly sensitive, investing in better data collection or control over that factor might yield significant improvements in outcomes.
Enhanced Model Understanding: It provides deeper insights into the relationships between variables within a model, helping stakeholders understand the underlying drivers of performance and the assumptions upon which decisions are based.

Two Reasons for Implementing Sensitivity Analysis in the Healthcare Industry

In the healthcare industry, where decisions have profound impacts on patient lives, operational efficiency, and financial viability, implementing sensitivity analysis is crucial for:

Optimizing Treatment Protocols and Resource Allocation under Uncertainty: Healthcare outcomes are influenced by numerous variables, many of which are uncertain (e.g., patient response to medication, incidence rates of diseases, resource availability, budget fluctuations). Sensitivity analysis allows healthcare organizations to test how

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