Using Quality Tools in Decision-Making Issues and Organizational Examples Term Paper

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Quality Tools in Decision Making:

Issues and Organizational Examples

In the competitive atmosphere of the business world today, it is not simply enough to have a good idea of what the present may hold for one's company or one's own personal investments. It is also important to develop organizational strategies and production goals with an eye upon the future. Critical to creating a proper decision-making strategy is the use of proper quality control tools to improve the strategy-creating process. Indeed, as noted by the authors Katherine Manley and S. Sytsma, the quality-control processes of histograms, cause and effect diagrams, and check sheets can and are frequently used to aid in any kind of process, but particularly in regards to organizational quality control in the corporate world. (Manely & Sytsma, 1999) These quality control procedures are particularly useful in business, when properly deployed because they can help managers to 'crunch' incomprehensibly varied or difficult data more understandable and deploy such data when creating a linear, forward-thinking strategy for their organization.

First Quality Control Tool

Histograms

According to Manley and Systma's The Quality Tools Cookbook. (1999, retrieved on 19 January 2004, from the world wide web at (http://www.sytsma.com/tqmtools/tqmtoolmenu.html) a histogram is used to display data distributed by categories in bar graph format. Such graphs are the preferred method for graphing grouped interval data. Histograms depict the number or proportion of data points falling into any particular given class. For example, a histogram would be appropriate for depicting the number of people in different age group samples whom enjoyed a particular product. These graphs always depict continuous classes of data rather than the discrete categories found in other bar charts, giving a bell curve appearance and broadly clarifying trends rather than focusing on isolate groups. However, although they are easily understood by the naked eye of laypeople, histograms can also very easily manipulated to yield false impressions because of their seductively seamless appearance.

When considering the current low-carbohydrate craze, for example, a potential investor in the Atkins industry or a manager in the food and restaurant industry might note that sixty-six percent of recently polled consumers noted that they were "definitely" cutting carbohydrates from their diet, while nineteen percent said 'a little' and only 14% said not at all. Examining the age ranges of those who avowed that they were following a low-carbohydrate diet, and determining it was within the company's target audience, a company might decide to create a low-carbohydrate line of foods.

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However, the continuity given by such graph, either graphed according to desire to cut carbohydrates or according to age, does not necessarily reveal how much potential disposable income all of the polled consumers have to pay for the often more costly low-carbohydrate options, nor their personal definition of what constitutes cutting carbohydrates "a lot," which could be deceptively uniform. ("Big Business of Low Carbs," 2004, retrieved from Personal Finance at Aol.com on 19 January 2004). At best, the histogram identifies a trend, rather than a discrete and quantifiable source of data, and more polling would be needed before a definite decision could be reached.

Second Quality Control Tool

Cause and Effect Diagrams

According to Manley and Systma's The Quality Tools Cookbook. (1999, retrieved on 19 January 2004, from the world wide web: (http://www.sytsma.com/tqmtools/tqmtoolmenu.html) cause and effect diagrams are an analysis tool used to display possible causes of a specific problem or condition. They can be used to explore all the potential or real causes (or inputs) that result in a single effect (or output) and are useful for identifying potential causes of a problem or issue in an orderly way, summarizing major causes, or ranking potential causes according to levels of importance or detail. The usefulness of the categories, of course, determines the usefulness of the diagram.

For instance, according to Bill Powell's article recent "Primary Colors," from Fortune….....

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