Financial Indicators Asset Turnover Finance Essay - Free Essay Example

The graph clearly shows the asset turnover of the four firms Digi Box 0.53x, Little World 1.07x, Blue 0.43x and Mersal 0.24x here the average asset turnover is 0.57x. The asset turnover ratio represents the turnover of assets by dividing sales on total assets (Brigham Houston, 2007). The asset turnover ratio shown in the graph revealed that Little World is the leader when it comes to volume of the business with respect to its total asset investment with asset turnover ratio of 1.07x. Mersal with lowest asset turnover 0.24x is even below the average asset turnover of 0.57x, the firm seriously needs to increase its sales or sell some of the assets or use both strategies to increase asset turnover. Mersal must use either of the strategies to increase its asset turnover. Blue with asset turnover of 0.43x shows the firm also needs to increase its assets turnover by increasing sales or adopting similar strategies. Digi Box has asset turnover of 0.53x the firm could further increase its sales to become the leader in terms of assets turnover. Equity ratio is also termed as debt ratio which specifically measures the long-term debt paying capacity or ability of any firm (Gibson, 2011). This ratio also measures that how well the creditors are protected or covered against risk if the company becomes bankrupt. The graph shows the equity ratio of the four firms Digi Box 83.21%, Little World 70.53%, Blue 95.91% and Mersal 89.37%, here the average for equity ratio is 84.76%. Comparing with the average trade mark equity ratio of 84.76% the Little Worlds equity ratio of 70.53% which is the lowest and shows that Little world is financed more with the help of debt instead of equity, and the ratio is signalling an alarm for the creditors that the firm is losing its capacity to pay its long-term debt. Comparing equity ratio of Little World with Digi Boxs equity ratio of 83.21%, Digi Box is in the red area of near to losing its capacity to pay long-term debts. Mersal with equity ratio of 89.37% and Blue 95.91% shows that these two firms are more financed by banks and therefore threatens the creditors that they are not protected for long-term investments in the firm. Net debt to equity ratio measures the leverage of the firm by dividing long-term debt by stockholders equity and focuses on long-term debts (Megginson Smart, 2009). This ratio is another indication of the level of debt taken by the firm and presents the results by spreading total debt over the shareholders. The net debt to equity ratio in the graph show net debt to equity ratio of Digi Box -52.3%, Little World -12.84%, Blue -64.17% and Mersal -67.16%, here the average will be -49.12%. Mersal with net debt to equity ratio -67.16% shows that the firm is leveraged less with debt and relies heavily on equity and has the least exposure to debt out of the four firms. Blue comes second with -64.17% and Digi Box third at -52.13% of net debt to equity ratio, the negative ratio shows that the firm can take loans from the bank to start new investments as long as the rate of the return of investments is more than the rate of interest. Little World with net debt to equity ratio of -12.84% relies comparatively more on debt with respect to other firms but still the negative values shows that the firm is leveraged through equity and not through debt. Asset Structure Asset Structure shows how much of the firms assets are fixed assets, inventories, receivables and cash equivalents. Firms whose assets are suitable for banks to keep as security and offer loans, use debt more than the firms whose assets are not suitable for security as loan (Brigham Houston, 2007). Asset structure is an important factor in making capital structure decisions. According to the figures shown in the graph Little World has 84.62K receivables which is higher Blue 64.22K, Mersal 59.69K, DigiBox 41.67K and shows that more of little worlds assets are in the form of receivables. Receivables do increase assets but provided they are not liquid assets, hence reducing asset turnover of a firm. Little World also has the most Fixed Assets equal to 901.6K showing the firms long-term investments also the assets which can be kept for security with banks in order to take loans for investments. At the same time the graph shows Little World also has the minimum inventories of 775.52K whi ch is good and low inventories add up to increase asset turnover, and Mersal at 332.77K, DigiBox 1.35M, Little World 775.52K and Blue 1.63M with the highest inventories. Blue held the most cash and cash equivalent of 6.09M showing the liquidity of the firm. Total Asset/Equity The asset structure revealed that team Little World has 84.62K of its assets in the form of receivables hence decreasing the liquidity of the team. Little World has the most Fixed Assets equal to 901.6K, hence firm can seek more investments from banks and Little World also held minimum inventories. The asset turnover ratio also revealed that Little World has the highest asset turnover ratio of 1.07x, more than Digi Box 0.53x, Blue 0.43x and Mersal 0.24x. Therefore according to asset structure and turnover Little World has the highest asset turnover out of all the four teams. Average Logistics Cost per sold product This graph shows the average logistics cost for selling products in Asia and Erurope, Mersal with USD 20.8 the highest average logistics cost per product sold in Asia and Little World with USD 6.6 the lowest average logistic cost per product sold in Asia. Consequently Little World outperforming others with lowest average logistics cost per sold product in Asia. Blue and Mersal have the highest average logistics cost per sold product in Europe i.e. USD 12.6 and DigiBox has the lowest average logistics cost per sold product i.e USD 8.9, consequently in Europe DigiBox outperforms Little World, Mersal and Blue. Selected Line Item Analysis Outsourcing Costs The Tech 1 product costs show the graph for outsourcing production to Asia and it reveals that Digi Box has the lowest cost for outsourcing work to Asia followed by Blue. The Tech 2 production cst graph reveals that Little world has the lowest cost for outsourcing to USA and Asia. Research and Development The figures in profit and loss statement show that Little World spends the highest on Research and Development i.e. USD 330,000 K more than Mersal 251,085 K, Blue 205,000K and DigiBox 55,000K. Research and development is an important part in product development, team Little World spending more on research and development is an important factor in increasing sales consequently increasing total asset turnover. Cash Reserves Mersal has the highest cash and cash equivalent as shown by the figures in Balance Sheet, which shows the liquidity of the firm but also losing investment opportunities due to holding large sums of cash, followed by Blue and DigiBox. Little World on the other hand has lowest cash and cash equivalent showing that the firm is involved more in investing activities. Simulation Learning Outcomes Logistics According to the graph Team Mersal has the highest average logistics cost per sold product in Asia i.e. USD 25.6 and DigiBox with USD 18.7 the lowest average logistics cost per sold product in Asia, therefore team DigiBox has the competitive edge over Little World USD 23.9, Blue USD 20.9 and Mersal. Managing a global organization is a complex challenge to manage logistics in Asia and Europe, here team DigiBox outperforms in Asia whereas in Europe all the teams have almost the same average logistics cost per sold product. Learning This exercise revealed that team Little World has the highest market share of 34.59%, followed by DigiBox 25.94%, Blue 22.84% and Mersal 16.62%. Little world is also offering competitive prices in USA for both Tech 1 and Tech 2. DigiBox is offering lowest prices for Tech 1 in USA. Consequently Little World is the leader in terms of prices in USA, Aisa and Europe. Final Remarks The Simulation exercise has been very useful in managing global operations with the help of financial ratio analysis financial statements. This simulation has helped the team to make decisions based on the information retrieved from financial ratios, consequently providing opportunities for students to learn how to predict financial numbers.