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Running Head: COMPANY B PERFORMANCE REPORT
Company B Performance Report
Name
Institution
Course
Date
1
COMPANY B PERFORMANCE REPORT
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Performance Report of ERPSIM Manufacturing Game
Introduction
This report will give a detailed analysis of Company B's performance in the six rounds of
the ERPSim Extended Manufacturing Game on November 30 and December 7. It evaluates
important performance factors such as total sales, gross margin, net margin, operational
productivity, and marketing and makes recommendations for future improvements. The report
includes visualizations of areas that need to be improved as well as reflections on areas where we
thrive. This report illustrates and describes how the group dramatically boosted sales,
enhanced expenditure control, maintained efficient manufacturing, and applied a smart pricing
plan to raise profitability and total business valuation. The visualization chart shows that the
Company value increased from the first practice game on November 30th to the last evaluated
game on December 7th. The first practice game came to a conclusion with $36.2 million as its
value, and the last game terminated with $126.2 million as the value. The team came second in
both games held on 30th November and 7th December, having recorded a valuation for the
COMPANY B PERFORMANCE REPORT
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company of $111.5 million and $126.2 million, respectively. The results are pleasing, though
there is still room for improvement in all elements of the game to retain our Company's image
and earn a high rating.
KPI Indicators
Total sales
Chart 1: Total Sales per round
Chart 2: Total Sales per round per team
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Chart 3: Total Sales in round 6 with highest sales
Chart 4: Total Sales in round 1 with lowest sales
Different charts give an analysis of the company's performance over the six rounds in the
main performance indicator of total sales. The cumulative total sales from the six rounds are
shown in Chart. It also demonstrates that the company's revenues consistently climbed from
round 1 to round 6. Chart 2 reveals that round 6 was the best-selling round, with pieces sold
totaling $8,675,744.90. The same data displays round 1 as the lowest selling round, with pieces,
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sold totaling $1,295,960.61. However, most units were sold in round 6. This is due to the fact
that the pricing was greater in Round 6, and since Round 6 was the final round contested, the
staff cut prices to clear out the remainder of the inventory. Charts 3 and 4 show the sales byproduct for the best-selling round 6 and worst-selling round 1. The team's product combination
has been quite successful, reaching our greatest ERPSim performance to date. The team chose to
switch after experiencing challenges with the product mix, which has had a big, positive
influence on our sales. In subsequent games, the team will retain the same four items and price
them above the market price throughout the game, then drop our pricing in the last round to
create higher sales and complete the game with a strong round of sales.
Gross margin
Chart 5. Gross Margin per round
Round 3 earned the highest Gross Margin score of 67.65%. As seen in Chart 5, the Gross
Margin rose consistently up to Round 3 and then declined significantly at Round 4 to 67.443%.
In Round 5, $0.74 of every dollar earned from sales was retained, with the remaining $0.26
utilized to cover obligations other than COGS. Because the gross margin is the amount of sales
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income retained by a firm after deducting all expenses associated with product manufacturing, it
can be extrapolated that the higher the sales price of the product, the larger the gross margin, as
illustrated in chart 5. The lower average selling price of each product in round 1 than that
of Round 5 shows that the gross margin rises as prices rise.
The team was among the top three highest performing firms, trailing the best performing
team with less than 2% in each round. The lowest difference between the team and the best team
was 0.323 percent recorded in Round 6, while the greatest difference was 2% recorded in Round
2. One plausible explanation for the best-place team's continued ranking is that its selling prices
are greater than that of this team, meaning the rival firm sells more units than this firm. The rival
firm also spends more on marketing to boost its sales volumes. Because the team aims to rank
first, one feasible change to the approach is to raise the selling prices of the items and spend
more on advertising.
Net Margin
Chart 6. Chart 6: Net margin
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The company's net margin averaged approximately 26.55 percent overall six rounds, with
the greatest percentage coinciding 29.412% in Round 4 and the lowest net margin averaging
23.946% in Round 2, as shown in Chart 6. As seen by the game outcomes, the net margin
average is the greatest of any game outcome. A large net margin indicates that the team
efficiently controlled expenses and delivered items at considerably higher prices than the costs of
goods sold. This was accomplished through a mix of effective management, minimal costs, and a
good pricing approach.
When contrasted with other teams, the team had the highest net margin %, demonstrating
its joint capacity to control expenses while successfully pricing the items for higher sales volume
that results in profitability. The team's focus on efficient manufacturing schedule and cost of
products sold propelled it to rank first in terms of net margin. The team’s objective is to charge a
high enough price for our items that we can make a profit after selling the products. This method,
along with our aggressive pricing strategy, enabled our firm to beat the market and dramatically
boost its valuation. As previously said, one feasible improvement to the plan would be to invest
more in advertisement to sell more numbers every round. This will raise the net margin %,
enhancing the company's profitability and total firm valuation.
Round Productivity
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Chart 7: Round Productivity
The company's production increased steadily from round 1 to round 6 during the game as
shown in chart 7. Excluding the 12.083% decline between Rounds 4 and 6, the company boosted
its production percentage every successive round. The company's overall round productivity
shows that the greater the production %, the closer the company approaches the maximum
achievable productivity of 76.667 every round. Incorporating these three aspects into the
visualization provides a better picture of the changes in productivity percentages with every
round for future improvement.
To dig further into these productivity figures, Charts 7 illustrate the rounds with the
lowest and highest productivity in terms of yield by product and by step (day), respectively. The
lowest productivity was 63.333 in Round 1, and the best productivity was 76.667 percent in
Round 7. The notable variation in output is directly related to the quantity expected. Since the
predicted quantity was smaller in round 1 compared to round 5, the extra days with a setup time
of 8 hours resulted in a lower yield translating into poorer productivity. The prediction in Round
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5 was substantially higher. The bulk of the days in this round was spent in production, resulting
in an increased productivity percentage, though at the expense of reduced setup time.
Based on this study, one can infer that forecasting for a bigger unit increases productivity
due to the reduced setup time. Whereas this strategy may be beneficial in increasing output, it is
possible that we may lose out on generating some of our other items. Because of the enormous
number of units in production, none was made in Round 5. This forecasting approach may have a
beneficial impact on the company's productivity but may have a detrimental impact on the
product mix. Making investments in the manufacturing process is one method that may retain
the high productivity % while also preserving our product mix. The company produces 480,000
units per round at a minimum because it makes no effort to raise the maximum productivity
volume or decrease setup time. Suppose the company invested in either increasing its maximum
capacity or decreasing its setup time. In that case, it could continue producing more units of all
four items in six rounds, thereby keeping the market product mix.
Conclusion
Generally, the team representing this company is pleased with its performance in this
game. The team has developed into a powerful squad by learning from and correcting previous
mistakes to attain the top rank in recent games. Despite modest variations, the company's
valuation improved over time due to the effort by all members that resulted in an improvement in
their individual performance. The team feels that its present product mix is effective after hard
work amid challenges. Henceforth, the team commits to creating the product mix with the
highest productivity, profitability, and high potential to achieve maximum sales capacity.
Focusing on the items ranked as the market's top performers, with consistently strong
sales, will result in better performance in the future. However, it is important for the company to
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improve its forecasting approach so that we can set our pricing correctly to preserve our strong
gross and net margins while increasing sales and valuation. Our production was high in this
game, and we intend to keep it that way. To accomplish so, the company wants to effectively
enhance its productivity % while also keeping sufficient inventory of all items to maintain the
perfect product mix and market offers. In terms of marketing strategy, the
company understands the significance of devoting financial resources to boost the sale
of its products.
The company acknowledges the definite link between its marketing costs and sales,
which indicates a higher sales volume and profitability for every additional dollar spent in
marketing. The company will continue to invest in marketing methods to increase product sales
in future games. The company also wants to stick with decreasing the pri...