Solution Manual For Quantitative Analysis For Management, 14Th Edition By Render All Chapters 1 To 15 Reviewed

QUANTITATIVE ANALYSIS FOR MANAGEMENT
SOLUTION MANUAL for QUANTITATIVE ANALYSIS FOR

MANAGEMENT, 14TH EDITION By RENDER All Chapters 1 to

15 REVIEWED

Bonie314 Stuvia

,SOLUTION MANUAL FOR m m




QUANTITATIVE ANALYSIS FOR MANAGEMENT, 14TH EDITION m m m m m



RENDER
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CHAPTER 1-15 m




CHAPTER 1 m




Introduction to Quantitative Analysis m m m




TEACHING SUGGESTIONS m



Teaching Suggestion 1.1: Importance of Qualitative Factors.
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Section 1.1 gives students an overview of quantitative analysis. In this section, a number of
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qualitative factors, including federal legislation and new technology, are discussed. Students
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can be asked to discuss other qualitative factors that could have an impact on quantitative
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analysis. Waiting lines and project planning can be used as examples.
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Teaching Suggestion 1.2: Discussing Other Quantitative Analysis Problems.
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Section 1.2 covers an application of the quantitative analysis approach. Students can be asked
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to describe other problems or areas that could benefit from quantitative analysis.
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Teaching Suggestion 1.3: Discussing Conflicting Viewpoints.
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Possible problems in the QA approach are presented in this chapter. A discussion of
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conflicting viewpoints within the organization can help students understand this problem. For
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example, how many people should staff a registration desk at a university? Students will
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want more staff to reduce waiting time, while university administrators will want less staff to
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save money. A discussion of these types of conflicting viewpoints will help students
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understand some of the problems of using quantitative analysis.
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Teaching Suggestion 1.4: Difficulty of Getting Input Data.
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A major problem in quantitative analysis is getting proper input data. Students can be asked
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to explain how they would get the information they need to determine inventory ordering or
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carrying costs. Role-playing with students assuming the parts of the analyst who needs
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inventory costs and the instructor playing the part of a veteran inventory manager can be fun
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and interesting. Students quickly learn that getting good data can be the most difficult part of
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using quantitative analysis.
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Teaching Suggestion 1.5: Dealing with Resistance to Change.
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11-1
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,Resistance to change is discussed in this chapter. Students can be asked to explain how they
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would introduce a new system or change within the organization. People resisting new
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approaches can be a major stumbling block to the successful implementation of quantitative
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analysis. Students can be asked why some people may be afraid of a new inventory control
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or forecasting system.
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SOLUTIONS TO DISCUSSION QUESTIONS AND PROBLEMS m m m m m



1-1. Quantitative analysis involves the use of mathematical equations or relationships in
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manalyzing a particular problem. In most cases, the results of quantitative analysis will be one
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mor more numbers that can be used by managers and decision makers in making better
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mdecisions. Calculating rates of return, financial ratios from a balance sheet and profit and loss
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mstatement, determining the number of units that must be produced in order to break even, and
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mmany similar techniques are examples of quantitative analysis. Qualitative analysis involves
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mthe investigation of factors in a decision-making problem that cannot be quantified or stated
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min mathematical terms. The state of the economy, current or pending legislation, perceptions
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mabout a potential client, and similar situations reveal the use of qualitative analysis. In most
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mdecision-making problems, both quantitative and qualitative analysis are used. In this book,
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mhowever, we emphasize the techniques and approaches of quantitative analysis.
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1-2. Quantitative analysis is the scientific approach to managerial decision making. This type
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mof analysis is a logical and rational approach to making decisions. Emotions, guesswork, and
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mwhim are not part of the quantitative analysis approach. A number of organizations support
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mthe use of the scientific approach: the Institute for Operation Research and Management
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mScience (INFORMS), Decision Sciences Institute, and Academy of Management.
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1-3. The three categories of business analytics are descriptive, predictive, and prescriptive.
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mDescriptive analytics provides an indication of how things were performed in the past.
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mPredictive analytics uses past data to forecast what will happen in the future. Prescriptive
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manalytics uses optimization and other models to present better ways for a company to operate
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to reach goals and objectives.
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1-4. Quantitative analysis is a step-by-step process that allows decision makers to investigate
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mproblems using quantitative techniques. The steps of the quantitative analysis process include
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mdefining the problem, developing a model, acquiring input data, developing a solution, testing
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m the solution, analyzing the results, and implementing the results. In every case, the analysis
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mbegins with defining the problem. The problem could be too many stockouts, too many bad
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m debts, or determining the products to produce that will result in the maximum profit for the
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morganization. After the problems have been defined, the next step is to develop one or more
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mmodels. These models could be inventory control models, models that describe the debt
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msituation in the organization, and so on. Once the models have been developed, the next step
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mis to acquire input data. In the inventory problem, for example, such factors as the annual
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mdemand, the ordering cost, and the carrying cost would be input data that are used by the
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mmodel developed in the preceding step. In determining the products to produce in order to
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mmaximize profits, the input data could be such things as the profitability for all the different
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mproducts, the amount of time that is available at the various production departments that
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mproduce the products, and the amount of time it takes for each product to be produced in
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meach production department. The next step is developing the solution. This requires
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11-2
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, m manipulation of the model in order to determine the best
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11-3
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