Strategic Management Example

Strategic Management Example Strategic Management – Coursework Example STRATEGIC MANAGEMENT Cost Leadership Strategies Cost leadership entails standardization by reducing costs. On the other hand, Strategic management enhances low-cost production for given levels of quality since the low-cost leadership targets broad markets (Peny 2013, p.45). The three primary cost leadership strategies used include competitive advantage strategy, differentiation strategy and focus strategy in the management of businesses and organizations (Hill, Jones & Schilling 2014, p.33). The essay focuses on BHP Billiton strategic report 2014, based the analysis of the three cost leadership strategies in the management of BHP Billiton Company. Consequently, in strategic management of cost leadership, only rare and valuable resources can be sources of competitive advantage (Porter 2010, p.2). In BHP Billiton Company, their ability to profitably transport their petroleum and minerals as valuable resources incorporate their competitive advantage strategy under cost leadership. Besid es, oil and minerals from BHP Billiton Company are rare and precious resources that enable standardization of costs hence incorporating competitive advantage in cost leadership management. Differentiation strategy entails the development of services and products that offer unique attributes (Barney 2001, p.41). The development of services and outputs allows for cost leadership by controlling costs of goods and services. In BHP Billiton Company, development of goods and services is through distribution and selling of products with regulation of financial risks associated with revenue in Market. Therefore, differentiation is a form of cost leadership that assists in the sale of products and services in the market Additionally, focus strategy narrows on a particular segment of cost leadership to achieve cost differentiation and advantage (Hitt, Ireland & Hoskisson 2014, p.22). Furthermore, the needs of a group or company become better by focusing entirely on a particular segment in man aging cost leadership strategy in the management of companies or groups. BHP Billiton Company focuses on improvement of productivity across all aspects of their businesses, hence enabling them to achieve cost advantages and differentiation in the market.BibliographyBarney, J. B 2001, Is The Resource-Based â€Å"View† A Useful Perspective For Strategic Management Research? Yes, Academy Of Management Review, 26, 1, pp.41-56. Hill, C., Jones, G., & Schilling, M 2014, Strategic Management: Theory: An Integrated Approach, Stamford, CT: Cengage Learning. Hitt., M., Ireland, D., R, & Hoskisson., R 2014, Strategic Management: Concepts: Competitiveness And Globalization, Stamford, CT: Cengage Learning.Peny, M 2013, Global Strategy, Stamford, CT: Cengage Learning.Porter, M.,E. 2010, Competitive Strategy: Techniques for Analyzing Industries and Competitors, Quick MBA, Internet Center for Management and Business Administration, Inc.

Unbiased and Biased Estimators

Unbiased and Biased Estimators One of the goals of inferential statistics is to estimate unknown population parameters. This estimation is performed by constructing confidence intervals from statistical samples. One question becomes, â€Å"How good of an estimator do we have?† In other words, â€Å"How accurate is our statistical process, in the long run, of estimating our population parameter. One way to determine the value of an estimator is to consider if it is unbiased. This analysis requires us to find the expected value of our statistic. Parameters and Statistics We start by considering parameters and statistics. We consider random variables from a known type of distribution, but with an unknown parameter in this distribution. This parameter made be part of a population, or it could be part of a probability density function. We also have a function of our random variables, and this is called a statistic. The statistic (X1, X2, . . . , Xn) estimates the parameter T, and so we call it an estimator of T. Unbiased and Biased Estimators We now define unbiased and biased estimators. We want our estimator to match our parameter, in the long run. In more precise language we want the expected value of our statistic to equal the parameter. If this is the case, then we say that our statistic is an unbiased estimator of the parameter. If an estimator is not an unbiased estimator, then it is a biased estimator. Although a biased estimator does not have a good alignment of its expected value with its parameter, there are many practical instances when a biased estimator can be useful. One such case is when a plus four confidence interval is used to construct a confidence interval for a population proportion. Example for Means To see how this idea works, we will examine an example that pertains to the mean. The statistic (X1 X2 . . . Xn)/n is known as the sample mean. We suppose that the random variables are a random sample from the same distribution with mean ÃŽ ¼. This means that the expected value of each random variable is ÃŽ ¼. When we calculate the expected value of our statistic, we see the following: E[(X1 X2 . . . Xn)/n] (E[X1] E[X2] . . . E[Xn])/n (nE[X1])/n E[X1] ÃŽ ¼. Since the expected value of the statistic matches the parameter that it estimated, this means that the sample mean is an unbiased estimator for the population mean.