Posted: November 27th, 2022
The stakeholder presentation serves as the bridge between analytics and business decision making. The presentation provides you with the framework to integrate the course content through a reality-based example.
Imagine for a moment that your team has been recently hired as analytic consultants for a healthcare facility. The organization has requested your team’s help in understanding their personnel data in preparation for a JCAHO audit. You have begun your analysis with a review of their data and have found some inaccuracies and areas of concern (Excel Data Validation Exercise).
Your team has decided that this presentation also offers an excellent opportunity to educate the healthcare organization on the power of analytics to address not only their immediate problem but also in the benefits in using analytics to better position the organization for the future.
Using the provided grading criteria template, analyze the problem and present your findings. You are expected to integrate relevant models and concepts from assigned readings in your analysis, along with using logic and insights/skills from previous classes and personal experiences. Power Point slides are required.
You should provide sufficient information to capture all the components of the Business Analytics Process.
A presentation must include a statement of and background description of the problem;
identification of data sources;
synopsis of data preparation methodologies used and detailed discussion of the data preparation steps taken;
description of and reasoning for the modeling techniques used in analysis;
appropriate and detailed visualization of results;
explanation of conclusions, recommendations,
and predictions drawn from each of the three types of business analytics: descriptive, predictive and prescriptive.
For this presentation, be creative. You may create and use any hypothetical data you deem necessary to formulate or support your recommendation. Just remember, the “data” should be as realistic as possible and free of bias.
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