Lorex Pharmaceuticals - Essay Example

Quantitative Case Analysis: Lorex Pharmaceuticals Executive Summary Lorex Pharmaceuticals has developed and holds all patent rights to Linatol, a new high blood pressure medicine. Since the pharmaceutical industry operates in a monopolistically competitive atmosphere (where no specific pharmaceutical company dominates the market), the patent-holder of a new product can have considerable market advantage over other companies. Lorex pharmaceutical is therefore seeking solutions to optimize this competitive advantage by balancing cost, productivity, and quality with regards to the production of Linatol. To reach this end, the managers of Lorex Pharmaceuticals must determine and select a target amount to which each of the 10-ounce bottles of the product would be filled. This task takes into consideration two issues: 1) Specifying higher fill targets will lead to higher material cost but fewer seconds, and 2) use of the one-standard-deviation rule can cause production delays. Using tests to determine the optimal fill-line, it has been established that 10.17-ounce mark would result in optimal production and maximum returns. Since probability analysis is only suggestive and the accuracy increases with samples size, it is recommended that more tests be conducted to reach more accurate results. Decision Problem Quality assurance managers of Lorex Pharmaceuticals must determine and select a target amount to which each of the 10 ounce bottles of Linatol, a new high blood pressure medicine, would be filled. Analysis of the Industry and the Company There are currently more than 200 major pharmaceutical companies. As with other industries, specifically in the manufacturing business, economic and financial pressures can force pharmaceutical companies toward greater efficiency. Monopolistic competition is a norm for the pharmaceutical industry, where manufacturers have widely diverse products and services. The structure of the pharmaceutical market has an extensive vertical integration (meaning involvement is most of the steps of production) and horizontal integration (meaning diverse product and service lines). No specific pharmaceutical company dominates the pharmaceutical business; individual pharmaceutical companies have control of only a small portion of the market, where even the largest companies in the industry would control less that ten or even five percent of the market. The pharmaceutical industry is ever changing, as can be seen from the many changes in the structure of markets and organizations that occur over the years. Competition in the industry is intense, which means that mergers, acquisitions, etc. are not uncommon. In the pharmaceutical industry in the U.S., there is an extreme contrast between a specific products market during patent enforcement (where a patent holder may control over 80 percent of the product's market and can charge premium prices) and after the patent expires (where market control is reduced to about 30 percent because of the many sellers and buyers that soon emerge after patent expiration). Lorex Pharmaceuticals has developed Linatol, a new high blood pressure medicine, and the company holds all patents right to it. A company that develops a new drug has the potential to realize very large profits. Decisions in manufacturing budgets and product specifications influence the capacity of a particular product line. These, in turn influence the productivity and actual profit of the company. Thus, manufacturers must take into consideration the cost and quality factors that go into production. It is not unusual for companies to pursue trade-offs in cost, productivity, and efficiency in order to pursue specific markets. This however, can result in poor product quality. This case analysis aims to present some solutions that would help Lorex Pharmaceuticals strike a balance between cost, productivity, and quality. Possible Decision Alternatives Quality assurance managers of Lorex Pharmaceuticals must determine and select a target amount to which each of the 10 ounce bottles of Linatol would be filled, and this problem presents a situation wherein the effective handling of an administrative situation is put to the test. The analysis would require the use of probability, normal distribution fit, and trial and error to determined the fill target that would maximize the contribution of each of the 144 test-fill amounts. The key issues surrounding Lorex' plight can be summed up within the following concepts: 1) Specifying higher fill targets will lead to higher material cost but fewer seconds (seconds, or bottles not filled to the 10-ounce requirement are sold at 80 percent of the wholesale price). 2) Use of the one standard deviation rule can cause production delays. Either way, the goal is to specify the filling target that would maximize expected returns. The management should determine how to pursue the strategy that will yield the greatest profits over a period of time, given the current variables. Qualitative and Quantitative Evaluation of Alternatives In order to determine which target would yield the maximum returns, two variables must be taken into account: cost and the probability distribution of the test amounts. Modification or procurement of a new filling machine has been taken out the question due to issues in economy. Active ingredients make up 74% ($67,662) of the total production cost, while filling materials only make up around 20% ($18,235). Since the active ingredients take up about three-quarters of the total, it is the most relevant cost that is needed to be analyzed. The higher the fill target, the higher costs will be. Given the considerable amount of costs that go into the active ingredients, maximizing profits would necessitate that the fill amount that would yield optimum contribution be specified. In manufacturing, the rule often used for setting fill targets is one standard deviation above the required amount. However one concern with this method is the its considerable potential for causing stoppage in the filling lines. Past experiences state that using the one standard deviation rule can result in the clogging of the storage area for rejected bottles-which suggest that the number of seconds (under-filled bottles) is greater when using the one-standard deviation rule. Since the one-standard deviation rule can potentially be problematic (and the filling target of 10.2 ounces in the filling test was arbitrarily assigned) the task of determining the optimal fill level is yet to be done. The contribution per case for various target fill levels and the identification of the optimal fill level can be determined using probability distribution tests such as the Chi-square test. This test can also show whether or not the one-standard deviation rule can actually yield optimal productivity. For the data distribution, a Chi-square test is performed to see whether or not the observed frequencies are normally distributed. Many processes have a normal probability distribution. This normal distribution approximates various real-life processes, which are drawn form common groups or populations. One central theorem for this concept is that the distribution a large number of independent random variables will approximate a normal distribution. The Chi-square gives an approximation of the probability that sample frequencies are normally distributed in relation to an expected population value. It is useful under the reasonable assumption that calculated quantities can be proven be distributed according to the Chi-square distribution. The following frequency distribution for the data samples in the filling test show that the highest rate of occurrence is in the 10.17-ounce mark: Using data from the filing line test, the Chi-square test shows a relatively small difference between the distribution on the data sets and the normal distribution (37%). This "goodness-of-fit" test establishes whether or not the observed frequency distribution differs for the normal (theoretical) distribution. Since there is a substantial correlation with the data set and the normal distribution curve, it can be inferred that probability distribution of the test statistic can be an accurate gauge (to an extent) of the behavior of larger samples. This means that the relative frequencies in the test statistic can be used to project the probability of the frequency distribution for other samples in the Linatol production line-the current data set can then be used to determine the probability distribution. The Chi-square test supports the notion that the 10.17-ounce mark can yield the highest contribution on the production line. Recommendations Using probability concepts and tests for normal distribution, it has been established that the target amount to which each of the 10 ounce bottles of Linatol should be filled in order to maximize expected returns is 10.17 ounces. However, smaller sample sizes can result to less valid results on the Chi-square test, thus it is recommended that the management conduct more trials to normalize the results and have a bigger data set to work with. The principles previously cited in this report can be applied to the larger data/sample size. Read More