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CASE STUDY FOR CHAPTER 7 Worker Productivity among Giant U.S. Corporations Traditional measures of firm productivity tend to focus on profit margins, the rate of

CASE STUDY FOR CHAPTER 7 Worker Productivity among Giant U.S. Corporations Traditional measures of firm productivity tend to focus on profit margins, the rate of return on stockholders equity, or related measures like total asset turnover, inventory turnover, or receivables turnover. Profit margin is net income divided by sales and is a useful measure of a companys ability to manufacture and distribute distinctive products. When profit margins are high, it is a good sign that customer purchase decisions are being driven by unique product characteristics or product quality rather than by low prices. When profit margins are high, companies are also able to withstand periods of fluctuating costs or weak product demand without devastating consequences for net income. While high profit margins have the potential to attract new competitors, they also act as credible evidence that a firm offers a hard-to-imitate combination of attractive goods and services. Return on equity (ROE), defined as net income divided by the accounting book value of stockholders equity, is an attractive measure of firm performance because it reflects the effects of both operating and financial leverage. When ROE is high, the company is able to generate an attractive rate of return on the amount of money entrusted to the firm by shareholders in the form of common stock purchases and retained earnings. High profit margins give rise to high ROE, as do rapid turnover in inventory, receivables and total assets. Rapid inventory turnover reduces the risk of profit-sapping product closeouts where slow-moving goods are marked down for quick sale. Rapid receivables turnover eases any concern that investors might have in terms of the firms ability to collect money owed by customers. High total asset turnover, defied as sales divided by total assets, documents the firm=s ability to generate a significant amount of business from its fixed plant and equipment. Despite these obvious advantages, each of these traditional firm performance measures suffers certain shortcomings. Profit margins are strongly influenced by industry-related factors that might obscure superior firm productivity when firms from different industries are compared. For example, the automobile industry is huge and net profit margins for mediocre performers are commonly in the 2.5-3 percent range. Even standout performers, like Toyota, struggle to earn 6 percent on sales. Meanwhile, even mediocre banks commonly report profit margins in the 15-20 percent range. Similarly, and despite obvious advantages, ROE suffers as a performance measure because steep losses can greatly diminish retained earnings, decimate the book value of stockholders equity, and cause ROE to soar. When companies buy back their shares in the open market at prices that greatly exceed accounting book values, the book value of shareholders equity also falls, and can unfairly inflate the ROE measure. For these reasons, some analysts look to the growth in net income as a simple and less easily distorted measure of accounting profit performance. However, the biggest problem with corporate performance measures based upon profit rates tied to sales, stockholders equity or assets has nothing to do with measurement problems tied to irregular profit and loss patterns or corporate restructuring. The biggest problem with traditional corporate profit measures is that they fail to reflect the firms efficient use of human resources. In the services-based economy of the new millennium, the most telling indicator of a companys ability to compete is its ability to attract, train, and motivate a capable workforce. In economics, the term human capital is used to describe the investment made in workers and top management that make them more efficient and more profitable employees. Employee training and education are two of the most reliable tools that companies can use to keep an edge on the competition. However, determining an efficient amount of worker training and education is trickier than it might seem at first. In a competitive labor market, employees can expect to command a wage rate equal to the amount they could compel in their next-best employment opportunity. At least in part, this opportunity cost reflects employee productivity created by better worker training and education. Because dissatisfied workers can be quick to jump ship, employers must be careful to maintain a productive work environment that makes happy employees want to stay and contribute to the firm that paid for their education and training. Employers need capable and well-trained employees, but no employer wants to be guilty of training workers that end up working for the competition! All successful firms are efficient in terms of constantly improving employee productivity, and then motivating satisfied and capable employees to perform. In light of the importance placed upon capable and well-motivated employees, an attractive alternative means for measuring corporate productivity is in terms of profits and revenues per employee. Table 7.5 gives interesting perspective on employee productivity by showing revenue per employee and profits per employee for the 30 giant corporations that together comprise the Dow Jones Industrial Average. Questions A. What firm-specific and industry-specific factors might be used to explain differences among giant corporations in the amount of revenue per employee and profit per employee? B. A multiple regression analysis based upon the data contained in Table 7.6 reveals the following (t statistics in parentheses): Profit/Emp. = $1,269.016 + 0.220 Ind. Profit/Emp. + 0.084 Rev./Emp. + 0.004 Ass./Emp. (0.17) (2.33) (8.22) (1.20) R2 = 89.7 percent, F statistic = 75.48 B.1. Interpret these results. B.2. Is profit per employee more sensitive to industry-specific or firm-specific factors for this sample of giant corporations? B.3. Building the Regression and Linearity Model for this case by using the Excel program? The table on the link below is helpful in building a Regression and Linearity Model https://books.google.co.il/books?id=FGeoCwAAQBAJ&pg=PA275&lpg=PA275&dq=Table+7.5+gives+interesting+perspective+on+employee+productivity+by+showing+revenue+per+employee+and+profits+per+employee+for+the+30+giant+corporations+that+together+comprise+the+Dow+Jones+Industrial+Average.&source=bl&ots=Al7XdX0-1f&sig=mo-Hga_xbkaxdtN9xBgyAPDozRI&hl=en&sa=X&ved=2ahUKEwi63e_Ci9ncAhXRccAKHZVNCfIQ6AEwAXoECAkQAQ#v=onepage&q=Table%207.5%20gives%20interesting%20perspective%20on%20employee%20productivity%20by%20showing%20revenue%20per%20employee%20and%20profits%20per%20employee%20for%20the%2030%20giant%20corporations%20that%20together%20comprise%20the%20Dow%20Jones%20Industrial%20Average.&f=false

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