Data Evaluation for Decision Making (100 Points) Successful, fact-based managerial decision-making depends, in part, on identifying sources of relevant information that are suitable for analysis. However, even with the most suitable information, bias can compromise your decision-making process. For this assignment, you will assume the role of a manager and discuss how you would apply the “CRAP Test,” or other respected evaluation technique(s) you will cite, to determine the suitability of data from your IT system for use in making a key decision. In the event you have not had such an experience, assume the role of a big-ticket-item purchaser evaluating Open Data and other public data sources to make your purchase decision. Then consider how you would use the team you manage to assist you in eliminating bias from that key decision. In the event you are evaluating a big-ticket-item purchase, consider how you would use friends, including those from social media, to help you eliminate decision-making bias. Develop a well-written and well-organized paper that includes the following elements: Describe the key decision you must make and the kind of information you would need to perform your evaluation. Discuss how you determined whether the information at hand for decision-making was sufficient, in both quality and quantity. Which tests did you apply and what were the results? Discuss the biases present in your decision-making process. How did your colleagues, subordinates, or friends participate in your bias-elimination quest and what were the results? Discuss the outcome of the evaluation and indicate the decision that you made. You may write in the first person for this assignment, taking the perspective of a manager. Your paper should meet the following requirements: Be 3-4 pages in length Cite at least two academic sources from the CSU-Global Library databases Be formatted according to the CSU-Global Guide to Writing and APA Requirements
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Data Evaluation for Decision Making (100 Points) Successful fact-based managerial decision-making depends in part on identifying sources of relevant information that are suitable for analysis. However even with the most suitable information bias can
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