BUS225_Module_Four_Assignment

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Feb 20, 2024

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1 Module Four Assignment Laine Arguelles Southern New Hampshire University BUS 225: Critical Business Skills for Success LaShana Butler January 31, 2024

2 Module Four Assignment Explanation of the Importance of Data Analysis Data analysis is a critical aspect of evaluating the performance of a product. It enables us to detect trends, patterns, and insights that would be difficult to identify otherwise (Amadebai, 2023). Analyzing data allows us to make informed decisions on how to enhance our products and services. This report presents an analysis of the performance of our latest product, and it provides recommendations on how to improve it. The analysis examines various metrics such as sales, percent of monthly profit goals manufacturing cost, overhead, and units produced to give a comprehensive understanding of the product's performance. Our objective is to offer actionable insights that will enable us to improve the product and meet our customers' needs. Description of Findings Our comprehensive analysis of the yearly profit and loss statement for a particular product launch reveals that we failed to meet our company's target of achieving 25% of the Cost of Goods Sold (COGS) at the beginning of the year. However, by the end of December, we succeeded in generating a 75% profit margin for the fourth quarter alone. While this achievement could not compensate for the losses incurred in the first and second quarters, it does indicate a positive trend in the product's performance. Unfortunately, the total profit margin for the year was only 4.18%, which falls short of our goal. This initial loss can be attributed to the high overhead and labor costs incurred at the beginning of the first quarter of the year, as well as the lack of customer sales. We observed that the cost of overhead was directly proportional to our profit margins. In the first quarter, sales only improved in March, but there was no corresponding reduction in overhead or labor costs. Despite a higher volume of products sold in March, we were still unable to emerge from the negative. This suggests that the number of products sold, no matter how high, will not contribute to our percentage goals unless there is a reduction in overhead and labor costs. We noted that the COGS decreased over the year, resulting in a corresponding increase in our profit percentage. In conclusion, our analysis reveals that while we failed to meet our initial target, we made significant progress in the fourth quarter, and there is a positive trend in the product's performance. To achieve our goal in the future, we recommend a reduction in overhead and labor costs to improve profit margins. Summary of Results

3 This bar graph shows product profits over the course of the year. The bars are colored to show red for loss and green for profit growth. The red colors show that it is not profitable and actually incurred a loss. There is a clear label of the month of each profit under each bar part. Colors show in the middle of the year that we began to show slow growth. August and September show a clear turning point where profits finally were in the green. The y axis is labeled in parts of monetary amounts of five-thousand increments, showing above and below the mid horizontal base line of zero growth line. The labels at the bottom show each month and the referring color of each month's profits. As you can see Jan and February had the most loss, but in March growth occurred but there was no stability because April and May plummeted below our horizontal line zero profits yet again. In the next chart I will show you the reasons I believe that are behind the loss we had in the first quarter. Going into the second and third quarter you can see that profit was successful, in yellow ranges and increasing steadily. The last quarter shows stabilization in green and profits above our 25% goals for just that quarter, but that doesn't make up the losses from the beginning of the year.

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4 This is a line graph. On the left y-axis I have the scale in a range of zero to 10,000. The x-axis shows the month of the year. The labels at the bottom are specifically for labor, materials, and overhead to show our (COGS). Throughout the year material does not change with a steady need for the product to be produced the same to show other areas we should make improvement. As our sales of each product is only .25cents we can't save any more money lowering our standard of the way we buy materials. Labor and overhead look to be directly correlated to our profits. As we see Labor and overhead are higher in January to May when you see the drop, and in July it stabilized and remained low as profits increased in the previous bar graph. The purpose of analyzing this data is to inform the company about the success of our product launch in meeting our sales profit goals of 25% for the year. If you only looked at the Excel data sheet, you might conclude that we did not meet the target and only achieved 4.18% in sales. However, when you examine the data in easy-to-read graphs over time, it becomes apparent that profits were steadily increasing. By delving further into the data, we can also understand why the increase happened gradually over time, despite the decrease in labor and overhead costs while keeping material costs steady. In doing the calculations from January's percent of profits of -75% to December's 79%, you will see that the percent increase is actually six times larger in increase range at 194%. Moreover, if you calculate from the time, we were above the horizontal zero profits line in June compared to

5 December, you will see a percent increase of 108%, which proves that the product is now taking off. I have learned that data can easily be misleading if you don't analyze it the right way. Media and visual aids play a critical role in helping us see the big picture the right way by breaking it down into easy to look at points. Visually placing data in clear charts can also help us break down the problems we are looking for and help us problem solve for better success.

6 References Amadebai, E. (2023). The Importance Of Data Analysis In Research . Analytics for Decisions. https://www.analyticsfordecisions.com/importance-of-data-analysis-in-research/ Soomo Learning. (n.d.). https://www.webtexts.com/courses/60915-colegrove/traditional_book/chapters/ 6103901-using-data-to-inform-decisions/pages/61039002.

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