Discussion post

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The group did a phenomenal job. The paper was professional, concise, and comprehensive. The objective for their group was clearly outlined, and they did a good job answering it in a well-thought-out manner. I especially appreciated the effort they put into fully encapturing all the possible limitations and reliability concerns this study could have. Overall, it was a fantastic paper with very few criticisms, but I will discuss my thoughts on some of their graphs below and any minor critiques I may have had.

· Graph 1: Total Sales by CategoryThis graph was a straightforward bar chart used as the foundation for the question this group was trying to answer. The team created this graph by using the "Category" variable in the column section and the "Sales" variable in the row section. Both variables used for the graph had the correct formatting applied to them, and the "Category" variable had a color filter to make the individual variables more distinguishable in the graph. My only problem with the graph is that one significant piece of data was not included, which could have impacted the information provided. This one piece of data is the "Discount" variable. If disproportionate, the amount of discounting applied to specific categories compared to others could have skewed the total amount of sales generated by any category. The conclusion reached may not have changed at all. Still, it would have been prudent for the group to include the "Discount" variable in the graph to determine how much discounting each "Category" variable received and whether there were any outliers amongst them.

· Graph 2: Sales Over Time by CategoryThis graph was very simplistic but effective at what it was attempting to display. The group added the "Order Date" variable to the column and the "Sales" variable to the row to create this line chart, of which both variables were correctly formatted. In addition, they incorporated the "Category" variable as a color filter to break out the sales volume over the years more efficiently and assist themselves with understanding the sales trend for each category from 2014 to 2017. My problem with this graph is not the simplicity of it nor the data used to create it but rather the conclusions reached from it. This graph aimed to illustrate if any "Category" variables performed poorly and should be excluded from future manufacturing operations. After reviewing this graph, the group agreed that no single category should be excluded as they all increased over time, which is true. However, it is essential to note that they are not all increasing at the same rate. Before concluding that they should all be included, I think it would have been in their best interest to investigate the "Furniture" category with more scrutiny. Suppose the stagnation or even the possible future decrease in the trend line for "Furniture" sales cannot be attributed to fluctuations in the market. In that case, it may be best to pursue manufacturing only "Office Supplies" and "Technology," both of which boast faster growth in the rates of sales over time. 

· Additional CommentaryAs mentioned previously, group 5 provided a phenomenal paper, and there are not many critiques I can provide, but I will mention the few I have. First, a few grammatical errors are littered throughout the document that could be cleaned up with a thorough review. Secondly, I appreciate the thought that went into creating the new "Profit Margin" variable, but I have one suggestion. While I know that any layman could quickly figure out the variable by just reviewing the spreadsheet, it would have done your group well to explain how the new variable is calculated. Lastly, unless I misunderstood the question, I believe the prompt for the horizontal and longitudinal scales of data was about any directional variables found in the dataset, such as the "Region," "State," and "City" variables. Aside from these minor critiques, the paper was well put together, and I completely agree with where the group landed regarding its conclusion.