Solution Manual for Quantitative Analysis for Management, 14th edition by Barry Render, Ralph M. Stair Jr, Michael E. Hanna, Trevor S. Hale-Test Bank

SOLUTION MANUAL FOR k j k j




QUANTITATIVE ANALYSIS FOR MANAGEMENT, 14TH EDITION RENDER kj kj kj kj kj kj




CHAPTER 1-15 kj




CHAPTER 1 kj




Introductionto Quantitative Analysis kj kj kj




TEACHING SUGGESTIONS kj




Teaching Suggestion k j k j 1.1: k j Importance of Qualitative Factors. k j k j k j




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 k j Suggestion k j 1.2: k j Discussing k j Other k j Quantitative Analysis k j k j Problems.
Section 1.2 covers an application of the quantitative
k j k j k j k j k j k j k j k j analysis approach. k j



Students can be asked to describe other problems or
k j k j kj k j k j k j k j k j k j k j areas that could k j k j



benefit from quantitative analysis.
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Teaching Suggestion k j k j 1.3: k j Discussing Conflicting Viewpoints. k j k j




Possible problems in the QA approach are presented in this chapter. A discussion
k j k j k j k j k j k j k j k j k j k j k j k j



of conflicting
k j viewpoints
kj within the organization can help students k j k j k j k j k j k j k j



k understand this problem. For example, how many people should staff a
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k registration desk at a university? Students will want more staff to reduce waiting time,
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while university administrators
kj will want
kj less staff to save money. A k j k j k j k j k j k j k j k j k j



discussion of these types of conflicting viewpoints will help students understand some
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of the problems of using quantitative analysis.
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Teaching Suggestion k j k j 1.4: k j Difficulty of k j k j Getting Input k j k j Data.
A major problem in quantitative analysis is getting proper input data. Students
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can be asked to explain how they would get the information they need to
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determine inventory ordering or carrying costs. Role-playing with students assuming the
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parts of the analyst who needs inventory costs and the instructor playing the
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k part j of a veteran inventory manager
k j can be fun and interesting.
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k Students j quickly learn that getting good data can be the
k most j k j k j k j k j k j kj k j k j k j



k difficult part of using quantitative analysis.
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Teaching Suggestion k j k j 1.5: k j Dealing with k j k j Resistance to k j k j Change.

,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
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inventory control or forecasting system.
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SOLUTIONS TO DISCUSSION QUESTIONS AND PROBLEMS kj kj kj kj k j




1-1. Quantitative analysis involves the use of mathematical equations or relationships in
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analyzing
kj a particular problem. In most cases, the results kof j k j k j k j k j k j k j k j k j



k quantitative analysis will be one or more numbers that can be used
j k j k j kj k j k j k j k j k j k j k j k j



k by managers and decision makers in making better decisions. Calculating
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k rates of return, financial ratios from a balance sheet and profit and
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loss statement, determining the number of units that must be produced
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in order to break even, and many similar techniques are examples of quantitative analysis.
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Qualitative analysis involves the investigation of factors in a decision-making problem
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k that cannot be quantified or stated in mathematical terms. The state of the
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economy, current or pending legislation, perceptions about a potential client, and similar
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situations reveal the use of qualitative analysis. In most decision-making
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k problems, both quantitative and qualitative analysis are used. In this book,
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however, 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.
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This type of analysis is a logical and rational approach to making decisions. Emotions,
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guesswork, and whim are not part of the quantitative analysis approach.
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k A number of organizations support the use of the scientific approach: the Institute for
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Operation Research and Management Science (INFORMS), Decision Sciences Institute, and
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Academy of Management.
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1-3. The three categories of business analytics are descriptive, predictive, and prescriptive.
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Descriptive analytics provides an indication of how things were performed in the past.
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Predictive analytics uses past data to forecast what will happen in the future. Prescriptive
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analytics uses optimization and other models to present better ways for a
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company to operate 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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problems using quantitative techniques. The steps of the quantitative analysis process include
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defining
kj the problem, developing a model, acquiring
k input
j data, k j k j k j k j k j k j k j



k developing
j a solution, testing the solution, analyzing the results, and k j kj k j k j k j k j k j k j k j



implementing the results. In every case, the analysis begins with defining the
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problem. The problem could be too many stockouts, too many bad
k j k j debts, k j k j k j k j k j kj k j k j k j k j k j



k or determining
j the products
k to
j produce that will result in the k j k j k j k j k j k j kj k j k j



k maximum profit for the organization. After the problems have been defined, the
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k next step is to develop one or more models. These models could
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k be inventory control models, models that describe the debt situation in the
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organization, and so on. Once the models have been developed, the next step
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is to acquire input data. In the inventory problem, for example, such factors as the
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annual demand, the ordering cost, and the carrying cost would be input data
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that are used by the model developed in the preceding step. In determining
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k the products to produce in order to maximize profits, the input data could
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be such things as the profitability for all the different products, the amount of
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k timej that is available at the various
k j production departments
k j that k j k j k j k j k j k j k j k j

,k j produce the
k j k j products, k j and k j the k j amount k j of k j time k j it k j takes k j for k j each
k j product to
k j

, be k produced
j k j in each production department. The next step
k j k j k j k j k j k j k j is
k j developing k j the solution. This requires
kj k j manipulation of the
kj k j k j model
k j in orderk j to determine the best k j