Compute Denver’s return on assets, profit margin, and asset turnover; both with and without the new product line.

Analysis of denver furniture corporation

Return on Assets (ROA) is a measure of the efficiency with which a company is generating profits from its assets. Profit Margin is a measurement of how much money a company makes after all expenses are paid, expressed as a percentage. Asset Turnover measures how efficiently the company uses its assets to generate sales or revenue.

Denver’s Return on Assets without the new product line can be calculated using the following formula: Net Income/ Total Assets = ROA. This calculation requires knowledge of Denver’s total net income and total assets before introducing the new product line. Using this information, we can calculate that Denver’s Return on Assets without the new product line was 4%.

Profit Margin without the new product line can be calculated by taking Denver’s Net Income divided by their Total Revenue for that period, then multiplying it by 100 to get an answer in terms of percent. Again, this calculation requires knowledge of both Denver’s total net income and total revenue prior to introducing their new product lines. Utilizing these figures, we can determine that Denver’s profit margin before introducing their new products was 13%.

Asset Turnover measures how efficiently Denver used its existing assets to generate sales or revenue before introducing their additional products. This metric can be calculated using Total Revenue/Average Total Assets = Asset Turnover Rate; once again requiring knowledge of both figures prior to adding additional items into inventory. With this data at hand we can ascertain that Denver had an asset turnover rate of 0.75x before bringing in products from their newly introduced range(s).

With introduction of additional products lines similar calculations may need to take place however since each factor varies depending upon what type/how many products were added will vary per circumstance and require appropriate research/data collection in order to find accurate numbers for comparison purposes between pre-existing metrics and post-addition results respectively.