{"id":243821,"date":"2022-05-05T09:45:52","date_gmt":"2022-05-05T09:45:52","guid":{"rendered":"https:\/\/nursingstudy.org\/management-information-systems-computers-making-decisions-2"},"modified":"2023-08-09T08:47:13","modified_gmt":"2023-08-09T08:47:13","slug":"computer-making-decisions-discussion-essay","status":"publish","type":"post","link":"https:\/\/nursingstudy.org\/examples\/computer-making-decisions-discussion-essay\/","title":{"rendered":"Management Information Systems- Computers Making Decisions"},"content":{"rendered":"

Need help with my Management question – I\u2019m studying for my class.<\/p>\n

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Your initial post should be 75-150 words in length<\/strong>.<\/p>\n

Computer Making Decisions Discussion Essay<\/h2>\n

Computers Making Decisions<\/strong><\/p>\n

Imagine that you are a shirt sales person and you just heard from your boss that a computer program is going to start telling you how many red, green and yellow (or whatever colors) shirts you are supposed to sell each week.
\nWhat are your thoughts?
\nNow that you know how computers are used to make decisions, how do you think a program could make these decisions for you?<\/p>\n

Please provide original work. No plagiarizing.<\/strong><\/p>\n

Instructions<\/h2>\n

When responding to an academic discussion post, it’s important to maintain a respectful and thoughtful tone while contributing to the conversation. Here’s a step-by-step guide on how to craft a well-structured and engaging response:<\/p>\n

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  1. Read Carefully:<\/strong> Before you start writing your response, make sure you have thoroughly read and understood the original discussion post. This will help you provide relevant and insightful feedback.<\/li>\n
  2. Address the Author:<\/strong> Begin your response by addressing the original author by name or username. This personal touch helps establish a sense of connection and engagement.<\/li>\n
  3. Acknowledge their Points:<\/strong> Start by acknowledging the key points or arguments the author made in their post. This shows that you’ve paid attention to their contribution.<\/li>\n
  4. Add Value:<\/strong> Offer your own perspective, insights, or counterarguments related to the topic. Your response should contribute meaningfully to the discussion by expanding on the points made in the original post.<\/li>\n
  5. Provide Evidence:<\/strong> Back up your response with relevant evidence, examples, or references from credible sources. This adds depth and credibility to your contribution.<\/li>\n
  6. Engage with Others:<\/strong> If other students have also responded to the original post, you can engage with their comments as well. Agree, disagree, or build upon their ideas in a constructive manner.<\/li>\n
  7. Ask Questions:<\/strong> Pose thoughtful questions that encourage further exploration of the topic. This can stimulate more in-depth discussion and showcase your genuine interest in the subject.<\/li>\n
  8. Maintain Politeness:<\/strong> Use respectful and professional language throughout your response. Even if you disagree with someone, do so in a courteous manner.<\/li>\n
  9. Be Concise and Clear:<\/strong> Present your thoughts in a clear and concise manner. Avoid jargon or overly complex language that could confuse others.(Computer Making Decisions Discussion Essay)<\/li>\n
  10. Proofread:<\/strong> Before posting your response, take a moment to proofread it for grammatical errors, typos, and clarity. A well-structured and error-free response reflects positively on your engagement.<\/li>\n
  11. Stay On-Topic:<\/strong> While it’s okay to provide additional insights, make sure your response remains focused on the main topic of the discussion. Tangential or unrelated points can derail the conversation.<\/li>\n
  12. Conclude Thoughtfully:<\/strong> Wrap up your response with a thoughtful conclusion. You can summarize your main points or reiterate your agreement with the original author’s perspective.<\/li>\n
  13. Cite Sources (if applicable):<\/strong> If you’re referencing specific research, studies, or sources, make sure to provide proper citations. This demonstrates your commitment to academic integrity.(Computer Making Decisions Discussion Essay)<\/li>\n
  14. Submit in a Timely Manner:<\/strong> Post your response within the established timeframe for the discussion. This ensures that the conversation flows smoothly and remains engaging.(Computer Making Decisions Discussion Essay)<\/li>\n<\/ol>\n

    Remember, the goal of academic discussions is to foster a collaborative learning environment. By following these steps, you’ll be able to contribute meaningfully and engage in a productive exchange of ideas<\/p>\n

    Computer Making Decisions Discussion Essay: Solution<\/h2>\n
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    As a shirt salesperson, hearing that a computer program will determine the number of shirts I need to sell in different colors each week might bring up a mix of feelings and thoughts. Here’s how I might react and how I think the program could make these decisions:(Computer Making Decisions Discussion Essay)<\/p>\n

    Initial Thoughts<\/strong><\/h3>\n
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    1. Concerns about Accuracy:<\/strong> I might worry about the program’s accuracy in predicting the right quantities for each color. What if it miscalculates and we end up with excess or insufficient stock?(Computer Making Decisions Discussion Essay)<\/li>\n
    2. Human Judgment vs. Data-Driven Decisions:<\/strong> I could wonder whether the program will consider factors beyond just historical sales data, such as current fashion trends or seasonal variations, which might not be captured in the data.<\/li>\n
    3. Adaptability:<\/strong> I might question the program’s ability to adapt quickly to unexpected changes or new market trends. Human intuition and flexibility could be hard to replicate.(Computer Making Decisions Discussion Essay)<\/li>\n
    4. Interaction:<\/strong> I could wonder how much input or override capability I have in this process. Will I be able to adjust quantities if I notice something the program might miss?<\/li>\n<\/ol>\n

      Program’s Decision-Making Process<\/strong><\/h3>\n
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      1. Data Analysis:<\/strong> The program would likely analyze historical sales data, considering factors like seasonality, color popularity, and trends over time. It could use statistical methods to identify patterns and correlations.<\/li>\n
      2. Market Trends:<\/strong> It might gather data from external sources like fashion magazines, social media, and industry reports to detect emerging trends or color preferences.(Computer Making Decisions Discussion Essay)<\/li>\n
      3. Demand Forecasting:<\/strong> By using predictive modeling, the program could forecast demand for each color based on factors like upcoming events, holidays, and past buying patterns.<\/li>\n
      4. Inventory Management:<\/strong> The program might be linked to the inventory system to monitor stock levels in real-time. It would adjust the sales targets based on the current inventory status to prevent overstock or shortages.(Computer Making Decisions Discussion Essay)<\/li>\n
      5. Feedback Loop:<\/strong> Regular feedback from salespeople could be incorporated to refine the program’s predictions. If the program consistently underestimates red shirt sales, for instance, this feedback could lead to adjustments.<\/li>\n
      6. Machine Learning:<\/strong> Over time, the program might use machine learning algorithms to improve its accuracy by learning from its own predictions and actual outcomes.(Computer Making Decisions Discussion Essay)<\/li>\n
      7. Human Override:<\/strong> There could be a mechanism for salespeople to intervene in exceptional cases. For example, if a sudden event causes a spike in demand for a particular color, the program could allow manual adjustments.(Computer Making Decisions Discussion Essay)<\/li>\n<\/ol>\n

        While the program could offer many benefits, such as reducing overstock and ensuring popular colors are available, there are challenges. It might struggle to capture the nuanced decisions a human salesperson could make based on personal interactions and gut feeling. Striking the right balance between data-driven decisions and human intuition would likely be key to success.(Computer Making Decisions Discussion Essay)<\/p>\n

        Reference<\/h2>\n

        https:\/\/www.ncbi.nlm.nih.gov\/<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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