QUESTIONS
16-1 The American Heritage Dictionary defines quality as: 1. a characteristic or attribute of something; property; a feature. 2. the natural or essential character of something. 3. excellence; superiority.
From a managerial perspective, “quality” can be defined as the degree of conformity between what a customer receives and what a customer is promised. Alternatively, we can conceptualize “quality” as the total level of satisfaction received by the customer.
For purposes of management accounting and control, “quality” can be broken down into two components: design quality and performance quality. The former refers to the extent to which the features (attributes or characteristics) of the product or service are those desired by the customer. The latter refers to the difference between the design specifications of the product and the actual performance of the product. Chapter 16 deals primarily with the management and control of performance quality failures.
16-2 Among factors that might have caused lapses in quality in some firms in the United States were: (1) years of success, (2) lack of competition from foreign companies and (3) absence of information regarding total spending on quality. These and other factors contributed to a lack of awareness that the cost of quality could be substantial and, more often than not, more than the cost of manufacturing. Alternatively, minimizing the total quality-related costs could be the source of competitive advantage for an organization.
16-3 Procter & Gamble defines TQM as “the unyielding and continually improving effort by everyone in an organization to understand, meet, and exceed the expectations of customers.” Typical characteristics of TQM include focusing on satisfying customers, striving for continuous improvement, and involving the entire workforce. TQM is a continual effort and therefore never complete. Global competition, new technologies, and ever-changing customer expectations make TQM a continual effort for a successful firm.
16-4 The Malcolm Baldridge National Quality Award (www.quality.nist.gov) is an annual award created by the U.S. government to recognize U.S. companies in manufacturing, small business, service, education, and healthcare that excel in quality achievement and quality management. ISO 9000 is a set of certification guidelines for quality management and quality standards developed by the International Organization for Standardization in Geneva, Switzerland (www.iso.ch/welcome.html). To be ISO-9000 certified, a firm must document a process to ensure quality related to the design, development, production, final
inspection and testing, installation, and servicing of products, services, and processes. To be certified, an organization has to document its process for controlling quality and must pass a rigorous third-party audit of its manufacturing and customer-service processes.
As quality became a major focus of many businesses throughout the world, being recognized as having high quality, or at least processes in place to ensure quality, opens the door to potential customers, increases the confidence of current customers, raises the morale of employees, and improves operating results. Many European companies and governments purchase products or services only from ISO-9000 certified firms.
16-5 Traditional accounting systems do not attempt to track the total cost of quality. That is, quality-related costs are spread throughout various accounts, including overhead, selling, general, and administrative expenses. As a result, organizations cannot know how much of each sales dollar is consumed by quality costs and, further, for any quality-related investments what the financial return might be. That is, traditional systems are not helpful for managing and controlling quality and quality-related costs.
16-6 Continuous improvement (Kaizen) in total quality management is the belief that quality is not a destination; rather, it is a way of life and firms need to continuously strive for better products with lower costs.
In today's globally competitive environment, where firms are forever trying to outperform the competition and customers present ever-changing expectations, a firm may never reach an ideal quality standard and, as such, needs to continuously improve quality and reduce costs to remain competitive.
16-7 As illustrated in Exhibit 16.3, a comprehensive framework for managing quality consists of a number of elements and characteristics. For example, the driving force behind the framework is the goal of understanding and then satisfying customer expectations. Second, consistent with the principle of TQM, the framework depicts a cyclical (or continuous) process. Third, the framework includes the reporting and analysis of both financial and nonfinancial quality indicators. Fourth, techniques from outside of accounting (e.g., Taguchi loss functions, Six Sigma goals, Pareto charts, cause-and-effect diagrams, etc.) are needed to help identify and then correct quality problems. Finally, the framework depicts a process that involves the entire value-chain of activities (i.e., upstream activities, production activities, and downstream activities).
16-8 The purposes of conducting a periodic quality audit are to identify strengths and weaknesses in quality practices and levels of a firm’s quality and to help the firm identify the target areas for quality improvements.
16-9 Six Sigma is an analytical method designed to achieve near-perfect results in terms of quality. In statistics, the Greek letter sigma stands for standard deviation (i.e., a measure of dispersion around a mean value). On a standard normal bell curve, one sigma above and below the mean covers approximately 68% of the area. The complement of this, 32%, represents the area outside of the mean +/- 1 standard deviation. In absolute terms, a one-sigma quality level represents approximately 320,000 defects per million. A two-sigma quality level represents approximately 4,000 errors per million. By contrast, a Six-Sigma quality level represents approximately 3.4 defects per million!
In terms of implementing Six Sigma, organizations typically use a DMAIC process. In the Define stage, managers identify the underlying quality problem, establish baseline measures and benchmarks (goals for improvement), and agree upon measures of success.
In the Measurement stage, the Six Sigma team studies and evaluates relevant
measurement systems to determine whether they are capable of measuring key inputs and quality attributes (e.g., product dimensions) with the desired level of accuracy.
In the Analysis stage, the team performs graphical and statistical analyses in order to develop preliminary hypotheses for improvement. This involves the identification of “root causes” and the “enablers” of poor performance that need to be corrected.
In the Improve stage, the Six Sigma team designs and conducts experiments to find the optimal conditions needed to operate the process.
In the final stage, Control, the team implements an on-going auditing and control mechanism to help ensure the sustainability of the new process.
16-10 One can think of Six Sigma as a management process. Thus, the basic literature from “change management” may provide useful tips for successfully implementing such programs. Brewer and Eighme, “Using Six Sigma to Improve the Finance Function,” Strategic Finance (May 2005), pp. 27-33, provide the following implementation guidance regarding Six Sigma:
Provide necessary leadership and resources—for Six Sigma to succeed, the CEO and other senior managers must commit to the program. Furthermore, they must provide the necessary resources, such as funding, training, and time. Finally, top management should get key people to buy into the need for Six Sigma; once buy-in is secured by key people, others are likely to follow.
Use top talent—using top talent within the organization provides a strong signal that top management is committed to Six Sigma.
Make training ongoing—avoid one-time-event training by providing refresher courses for all Six-Sigma participants. Such courses not only reinforce prior training, they also introduce new ideas.
Select initial projects carefully (i.e., simple ones with high probability of success)—successful projects build momentum and credibility.
Design projects for short-term wins—short-term wins provide confirmation that efforts are paying off. Recognitions for a “job well done” along the way can help sustain long-term commitment to Six Sigma projects.
Keep people informed—to overcome the fear of change, people must understand the reasons for change. Special efforts should be made to explain to employees why current Six Sigma projects are needed and to keep them informed as to the progress of such projects.
Set up a Website—a dedicated Six-Sigma Web site can help project teams avoid “reinventing the wheel” by providing access to a project library and message board.
16-11 Goalpost conformance is conformance to a quality specification expressed as a specified range (“quality tolerance”) around the target, where the target is the ideal value for the process.
16-12 A goalpost conformance specifies quality as a range around the target (or ideal) value while absolute conformance requires exact meeting of the target value with no variation allowed.
16-13 Taguchi argues that any variation from the exact specifications entails a cost or loss to the firm and that this loss is a quadratic function—that is, the loss grows larger as the variation from target, in either direction, increases.
Deviation from the exact specification increases costs such as rework, loss on disposal, warranty repair or replacement, and hidden quality losses such as customer dissatisfaction and loss of future business and market share. In today’s global competitive environment, these quality costs increase rapidly as customers become ever more demanding for complete satisfaction.
16-14 In general, financial data (such as COQ reports) will be more relevant to managers. These individuals have overall decision-making authority and responsibility for the financial results of operations. Note that such information is prepared only periodically.
On the other hand, nonfinancial quality data are likely to be of greater value to operating personnel. For one thing, such measures are readily understandable by these individuals. For another thing, such information can be used by operating personnel to make process changes/interventions. That is, they direct attention to underlying quality problems in the process. Finally, such measures can be produced on a timely basis—in the extreme, in a “real-time” basis.
16-15 Some examples of costs associated with cost of quality (COQ) categories are:
Prevention Costs: Training costs such as instructors’ fees, purchase of training equipment, tuition for external training, training wages and salaries; salaries for quality planning, cost of preventive equipment, printing and promotion costs for quality programs, application expenses in conjunction with awards for quality; costs incurred to certify suppliers; research on customer needs; quality audits.
Appraisal Costs: Cost of inspecting raw materials, work-in-process, and finished goods inventories; maintenance of test equipment; process control monitoring; inspecting machines; field testing; using statistical process control.
Internal Failure Costs: Net cost of scrap, rework cost, loss due to downgrade of product (opportunity cost), re-inspection costs, and loss due to work interruptions.
External Failure Costs: handling of sales returns; customer complaint resolution; sales allowances due to quality deficiency; warranty claims; product liability lawsuits; service calls; product liability recalls; repair costs in the field; cancelled sales orders due to quality deficiency; loss of sales and market share due to customer ill-will and dissatisfaction.
16-16 Prevention costs rise during the early years of implementing TQM as the firm engages in education to prepare its employees and in the planning and promotion of the quality program. Appraisal costs will also likely rise during the early years of TQM, because the firm needs to ensure that quality is actually being achieved. The increase in appraisal cost, however, is most likely to occur at a slower pace than those of the prevention costs because at the beginning of a TQM program there will be substantial increases in quality training and in promotion to raise awareness on the importance of quality.
The firm may see some decreases in internal and external failure costs in the early years of implementing TQM. However, these two costs most likely will remain at about the same level as before during the first several years of TQM. Many firms may actually see internal failure cost rise, because of the higher standard demanded by the TQM or the higher level of employees’ awareness on the critical importance of perfection in every step of the process. As the firm makes progress in TQM, both internal failure and external failure costs should decrease.
16-17 Costs of conformance are costs incurred to ensure that products or services meet quality standards and include prevention costs and appraisal costs.
Internal and external failure costs are costs of nonconformance. They are costs incurred or opportunity costs because of poor-quality outputs (goods or services).
16-18 Better prevention of poor quality often reduces all other costs of quality. With fewer problems in quality, less appraisal is needed because the products are made right the first time. Fewer defective units also reduce internal and external failure costs as the occasion for repairs, rework, and recall decreases.
Thus, it is generally considered easier to design and build quality in than try to
inspect or repair quality in. Theoretically, if prevention efforts are completely successful, there will be no need to incur appraisal costs and there will be no internal failure or external failure costs. In practice, appraisal costs usually do not decrease, partly because management needs to ensure that quality is there as expected. Nonconformance costs, however, decrease at a much faster pace than prevention costs increase.
16-19 A cost of quality (COQ) report describes quality cost items a firm incurred during the reporting period. A COQ report can help users identify and recognize the effects of their actions on quality costs and to pinpoint areas that need attention.
16-20 Tools for identifying and/or correcting quality problems include:
Control chart—A graph that depicts successive observations taken at a constant interval with the horizontal line representing time intervals, batch number, or production run and the vertical line representing a measure of conformance to the quality specification.
Histogram—A graphical representation of the frequency of events or causes of an indicated (i.e., identified) quality problem.
Pareto diagram (chart)—A histogram of factors contributing to a quality problem, ordered from the most to the least frequent.
Cause-and-effect (“fishbone” or “Ishikawa”) diagram—A graph that consists of spine, ribs, and bones. At the end of the horizontal spine is an indicated (specified) quality problem. The spine itself connects causes to the effect—the quality problem. Each branch or rib pointing into the spine describes a main cause of the problem. Bones pointing to each rib are contributing factors to the cause.
16-21 A “cause-and-effect” diagram is a graphical method to represent a chain of causes and effects used to sort out root causes and identify relationships between causes or between variables. Because of its shape, the diagram also is called a “fishbone diagram.” Cause-and-effect diagrams can be used diagnostically, in conjunction with control charts, to identify the principal causes of an identified quality problem.
16-22 Typical main causes of quality problems in manufacturing operations are: 1) machines, 2) materials, 3) methods, and 4) manpower.
16-23 A Pareto chart (diagram) is a vertical bar chart (graph) displaying the frequency or the number of occurrences of each quality problem, ordered from the most to the least frequent. As such, a Pareto chart can be used diagnostically to identify the primary sources of quality problems and to help managers prioritize quality improvement efforts.
16-24 Customer-response time (CRT) is defined as the amount of time between the time a customer places an order and the time the order is received by the customer. CRT can be broken down into three components: “receipt time” (lapse of time between when a customer places an order and when that order is received by manufacturing); “manufacturing lead time” (the amount of time between when an order is received by manufacturing and when that order is completed—see below); and, “delivery time” (lapse of time between when an order is finished and when the customer receives that order).
Manufacturing lead (manufacturing cycle) time is defined as the lapse of time between when an order is received by manufacturing and when that order is completed. Thus, manufacturing lead time is equal to the sum of waiting time + processing (manufacturing) time.
Cycle time efficiency (also known as throughput time ratio or process cycle efficiency) is the ratio of time spent on value-added activities to the sum of time spent on value-added and non-value-added activities; for example, cycle time efficiency = processing time/(processing time + moving time + storage time + inspection time).
16-25 As indicated by Exhibit 16.3 and the accompanying discussion in the chapter, management accountants are involved extensively in the design and operation of a comprehensive model (framework) for managing and controlling quality. However, the key role played by management accountants, because of their expertise in this regard, is the generation of relevant financial and nonfinancial measures of quality. In terms of the former, accounting provides relevant cost (and revenue) data that decision-makers can use to evaluate the desirability of spending and investments in quality. (This role is compatible with the discussion in Chapter 9 of the text.) As well, management accountants play a key role in helping a cross-disciplinary team develop a COQ reporting system—that is, a comprehensive model, with subcategories, for capturing quality costs across the value chain.
Also noted in Exhibit 16.3 is the use of nonfinancial quality indicators, both internal and external (customer satisfaction measures). The management accountant would typically be involved in the design of systems or processes that would capture and report this information.
Finally, the management accountant can help in the design of two internal audit functions associated with the comprehensive framework: one, the development of “quality audits” (designed to ensure quality); two, the Control stage of Six Sigma (where processes are put in place to monitor progress and to sustain the gains associated with process improvements).
16-26 To be relevant for decision-making, financial information (i.e., costs and revenues) must meet the dual test of being: (a) a future item, that (b) differs between decision alternatives. Relevant costs can also be defined as “avoidable” costs, or as the sum of “opportunity costs” plus “out-of-pocket costs.”
In terms of quality-related spending and investments, firms can anticipate the following financial benefits: reduction in scrap/waste costs; reductions in rework and re-inspection costs; reduction in inventory-holding costs; reduction in inventory recordkeeping costs; reduction in inventory financing costs; and, increases in sales due to improvements in quality (e.g., reduction in production cycle times).
16-27 From a design standpoint, the following are likely desirable qualities (attributes) of a COQ reporting system:
The system collects costs across the entire value chain, both internal and external (so, for example, costs related to gathering consumer-preference data and costs associated with certifying external suppliers would be captured as part of the total cost of quality).
The system focuses on costing of activities (i.e., uses data obtained from an ABC system).
The system includes both out-of-pocket and opportunity costs (the latter occur within the performance failure category, i.e., either as an internal failure or an external failure cost).
The system provides a breakdown of total quality-related costs according to logical categories (such as prevention, appraisal, internal failure, and external failure).
The system reports data in a time-series fashion (this would allow managers to assess the financial effects of spending and investments in quality; it would also allow managers to assess trade-offs between COQ categories over time). The system includes some baseline or appropriate benchmark (e.g., quality
costs could be reported as a percentage of sales or as a percentage of total operating costs; benchmarks could include “best-in-class” performance, either on an internal or an external basis).
16-28 In most cases, external failure costs (of the four categories) would be most damaging to the organization. Some costs within this category (e.g., product-liability lawsuits) can be huge in terms of out-of-pocket terms. Other costs in this category relate to loss of reputation or market share associated with customer dissatisfaction or ill-will. These costs are referred to as “opportunity costs” and can also be huge in dollar terms.
16-29 As shown in Exhibit 16.1, investments in quality can lead to improved business processes, which in turn result in improved quality of outputs (goods and services). Improvement in quality of outputs reduces external failure costs (e.g., warranty expenses), reduces the amount of inventory, can lower total manufacturing costs (e.g., inspection, rework, and inventory control costs). On the revenue side, improvements in quality can result in an improved product image of the company in the mind of consumers and faster throughput times. These, in turn, can lead in the mind of the consumer to higher perceived value of the organization’s output, the financial consequence of which is higher selling prices and increased market share. The combination of reduced costs and increased revenues provides an increase in financial performance (e.g., ROI, earnings per share, etc.).
16-30 High degree of process variation from target usually leads to variation in product attributes, which are important contributors to the quality of a product. Significant variation in process activities usually implies that there is an increased chance that product attributes are below customer expectations. For this reason, the Taguchi Loss Function is represented by a quadratic function—the more the departure from the target, the greater the assumed quality loss.
BRIEF EXERCISES
16-31 Total customer response time (CRT) = order receipt time + order wait time + production processing (manufacturing) time + order delivery time = 10 days + 15 days + 20 days + 10 days = 55 days.
16-32 Manufacturing cycle efficiency is defined as the ratio of value-added time to the sum of value-added time + non-value-added time. In this case, PCE = 4/(4 + 4 + 3 + 2) = 4/13 = 31% (approximately). That is, actual processing time is approximately 31% of total cycle time for a typical order. Note that manufacturing cycle efficiency is also referred to as process cycle efficiency (PCE).
16-33 Manufacturing cycle efficiency = ratio of actual processing (manufacturing) time to total cycle time (processing time + moving time + storage time + inspection time) = 8/(8 + 2 + 5 + 1) = 8/16 = 50%. That is, for a typical order, actual manufacturing (processing) time is 50% of total cycle time.
16-34 The estimated cost coefficient, k, in the Taguchi loss function is calculated as follows:
L(x) = k (x – T)2
$500 = k (5)2
∴ k = $20
16-35 The estimated total quality loss (cost) using the Taguchi loss function is calculated as follows:
L(78) = $20 (78 – 75)2
L(78) = $20 x 9 = $180
16-36 Average cost per unit, based on the Taguchi loss function, is: EL(x) = k (Φ2 + D2) = $20 (22 + 02) = $80
16-37 Total prevention cost = equipment maintenance = $1,154; total appraisal cost = product testing = $786. Total prevention + appraisal costs = $1,940.
16-38 Customer Response Time (CRT) = elapsed time between when a customer places an order (September 1, 2008) and when the customer receives the order (December 1, 2008). Thus, for this example, the CRT = 3 months.
Receipt time can be defined as the elapsed time between the date an order is placed (September 1, 2008) and the date Manufacturing receives the order (September 15, 2008). In this case, receipt time = 2 weeks.
Manufacturing lead time (cycle time) is the elapsed time between when Manufacturing Department receives an order (September 15, 2008) and when actual manufacturing is completed (November 15, 2008). In this case, manufacturing lead time is 2 months (8 weeks).
Manufacturing lead time (8 weeks) can be broken down into waiting time and processing (manufacturing) time, as follows:
Manufacturing wait time = time between when manufacturing receives an order (September 15, 2008) and when manufacturing on the order actually begins (October 15, 2008). In this case, wait time = 4 weeks
Manufacturing (processing) time = time between when manufacturing commences (October 15, 2008) and when the job is completed (November 15, 2008). In this case, processing time = 4 weeks.
Delivery time = time lapse between when an order is finished (November 15, 2008) and when the order is received by the customer (December 1, 2008). Here, delivery time = 2 weeks.
16-39 Correct answer is “a” (an increase in conformance costs resulted in a higher-quality product, and therefore a decrease in nonconformance costs). Conformance costs include prevention and appraisal costs; nonconformance costs include failure costs (internal and external). In the present case, conformance costs in total increased by 50% in total while total failure costs decreased by $655 (i.e., $1,390 – $735).
16-40 Each TV set contains 100 components; thus, if each component is produced according to a 3-sigma quality level, then the probability that a given unit will be
defect-free is: 0.997100 = 0.740484. Therefore, the probability that a unit has one or more defective modules is: 1 – 0.740484 = 0.259516. In practical terms, this means that, on average, for each 100 sets produced only 74 will be defect-free.
EXERCISES
16-41 Cost of Quality (COQ) Reporting—Multiple-Choice (15 minutes)
1. d 5. b
2. c 6. d
3. b 7. b
16-42 Interpretation of Six-Sigma quality expectations (ppm) (30 minutes)
Sigma One-Tailed Two-Tailed Errors (Defects)
Level Area1 Area Per Million
1 0.158655254 0.317310508 317,310.51 2 0.022750132 0.045500264 45,500.26 3 0.001349898 0.002699796 2,699.80 4 3.16712E-05 6.33425E-05 63.34 5 2.86652E-07 5.73303E-07 0.57 6 9.86588E-10 1.97318E-09 0.00
1Excel formula: = 1 - NORMSDIST(n), where n = sigma level (1, 2,...)
The preceding data indicate suggest a common misconception regarding the quality level assumed under Six Sigma. Only when a defect is defined as any deviation from the targeted level of the attribute (i.e., only when the “tolerance” is zero) will the above approach represent the maximum number of defects per million opportunities for error. Note, for example, that the expected number of errors (defects) under Six Sigma is approximately 2 per billion (when any deviation from target is considered a defect). In actual practice, based on initial experience by Motorola, the application of Six Sigma allows some variation (drift) around the target value. That is, there is an assumption that no process can be maintained in perfect control (i.e., no “drift” at all). Thus, in practice, a drift of 1.5 standard deviations around the target value is “allowed.” Any deviation beyond this allowable “drift” would be considered a defect or out-of-control process.
What this means is that a revised formula is needed to calculate the defects per million as the Six Sigma methodology is applied in practice. According to Pyxdek (http://www.qualitydigest.com/may01/html/ sixsigma.html) the Excel formula (under the assumption of an allowable drift of 1.5 sigma) is: 1000000*(1-NORMSDIST(Z-1.5)), where 1.5 = allowable drift (in standard deviations) and Z = Sigma level. For Z = 6.0, the Excel formula returns: 3.398, the defect-per-million figure commonly, but perhaps mistakenly, reported in the literature. (Also see, J. R. Evans and W. M. Lindsay, The Management and Control of Quality, 6th ed. (South-Western, 2005), Chapter 10.
16-43 Quality Ratings—Graduate Business Programs(30 Minutes)
As indicated in the exercise, the various ranking sources to some extent use different quality-related criteria. We provide an example response below, that is, an overview of the ranking criteria used by U.S. News & World Report in their annual ranking of graduate schools of business. U.S. News & World Report bases 40% of its judgment on opinions of business school deans, program directors, and corporate recruiters. Placement success accounts for 35% of the ranking, while the remaining 25% is based on “student selectivity.” The intent of this question is not to develop a definitive listing of quality criteria. Rather, the intent is to provide a nonmanufacturing example of quality rankings that would likely be of interest to many students.
In the 2005 survey, all 399 master's programs in business accredited by AACSB International were surveyed by U.S. News & World Report (347 responded, of which 240 provided the data needed to calculate rankings based on a weighted average of the quality indicators described below).
Quality Assessment (weight = 40%):
Peer Assessment Score (25%)—In the fall of 2005, business school deans and directors of accredited master's programs in business were asked to rate programs on a scale from "marginal" (1) to "outstanding" (5). Those individuals who did not know enough about a school to evaluate it fairly were asked to mark "don't know." A school's score is the average of all the respondents who rated it. Responses of "don't know" counted neither for nor against a school. About 50 percent of those surveyed responded.
Recruiter Assessment Score (15%)—In the fall of 2005, corporate recruiters and company contacts who hire from previously ranked programs were asked to rate programs on a scale from "marginal" (1) to "outstanding" (5). Those individuals who did not know enough about a school to evaluate it fairly were asked to mark "don't know." A school's score is the average of all the respondents who rated it. Responses of "don't know" counted neither for nor against a school. About 31 percent of those surveyed responded.
Placement Success (weight = 35%):
Mean Starting Salary and Bonus (14%)—The average starting salary and bonus of 2005 graduates of a full-time master's program in business. Salary figures are based on the number of graduates that reported data. The mean signing bonus is weighted by the proportion of those graduates that reported a bonus, since not everyone who reported a base salary figure reported a signing bonus.
Employment Rates for Full-time Master's Program in Business Graduates (11%)—The employment rate for 2005 graduates of a full-time master's program in business. Those not seeking jobs or for whom no job-seeking information is
16-43 (Continued)
available are excluded. If the proportions of graduates for whom no job-seeking information is available and who are not seeking jobs are high, then the information is not used in calculating the rankings. Employment rates at graduation (0.07) and three months after graduation (0.14) are used in the ranking model.
Student Selectivity (weight = 25%):
Mean GMAT Scores (16.25%)—The average Graduate Management Admission Test score of students entering the full-time program in fall 2005. Scores on the test range from 200 to 800.
Mean Undergraduate GPA (7.5%)—The average undergraduate grade-point average of those students entering the full-time program in Fall 2005.
Acceptance Rate (1.25%)—The percent of applicants to the full-time program in fall 2005 who were accepted.
Overall Program Rank: Data were standardized about their means, and standardized scores were weighted, totaled, and rescaled so that the top school received a score of 100; others received their percentage of the top score.
Source:U.S. News & World Report, April 10, 2006 (or, http://www.usnews.com/usnews/ edu/grad/rankings/about/07biz_meth_brief.php, accessed on April 4, 2006).
16-44 Spotting Quality in Business Programs (30 Minutes)
The purpose of this exercise is to provide an example of nonfinancial quality measures in a context likely to be of interest to most students, not to provide a definitive list. The instructor might point out that, depending on the mission of the institution and its competitive strategy, items listed below could be of greater or lesser importance (i.e., could be assigned different weights in evaluating the overall quality of a business school).
Bulletin Boards: take a look at what is posted on the bulletin boards of the business school. Will you find a cluttering of cheap magazine offers and offers for temporary employment, or do you observe notices of distinguished visiting speakers, upcoming chamber music series, meeting news from discipline-based student clubs, and fliers for study-abroad opportunities and graduate education? (This is an example of what is considered an unobtrusive indicator of educational quality.)
Intellectual capital represented in the Faculty: Are the faculty active in the profession? Do they conduct research and publish in areas that support the educational mission of the school?
Educational Content of the Curricula: Are the curricula offered in the business school up to date? Are there specified educational objectives associated with each degree program? Is there a comprehensive, program-level assessment plan to provide assurances of learning?
Resources Devoted to Education: Does the program have adequate resources (human and financial) to accomplish its specified mission? Is the institution financially stable? Is there adequate spending on technology?
Student-Faculty Interactions: Are the faculty involved in significant out-of-classroom activities related to the educational process? Is there ample opportunity for independent studies and joint faculty-student research? Are there sufficient study-abroad opportunities in which business school faculty participate?
Mission Statement/Vision Statement: What is the societal role fulfilled by the business school? That is, “how is the world different because this business school exists?” Is the mission of the school adequately communicated to stakeholders, both internal and external?
Assurances of Learning: Does the institution have in place a process for determining “value added”? That is, is there a formal process for determining learning outcomes vis-à-vis stated learning goals?
16-44 (Continued)
Diversity: Is there diversity of faculty background? To what extent does a diverse student body exist?
Placement: What firms and organizations regularly recruit graduates of the business school?
Alumni: How active are alumni in terms of providing financial support and placement opportunities (i.e., internships and full-time jobs) for graduates? Does the school have an active business advisory board/council? In what other ways are alumni involved in the business school?
Characteristics of Entering Students: What are the average SAT scores and high school ranks of the most recent entering class of freshmen?
Faculty Qualifications: From what institutions did faculty earn their terminal degrees? What proportion of faculty is considered full-time? What percentage of faculty have recent relevant professional experience? To what extent are faculty actively engaged in the profession?
Source: The preceding listing of quality criteria is drawn from M. R. Blood, “Spotting Quality,” Decision Line, Vol. 36, No. 4 (July 2005), pp. 14–20.
16-45 Management Accounting’s Role in Six Sigma (20-30 Minutes)
At the most general level, the management accountant (because of expertise in the
measurement process) should be included as a member of the cross-functional Six
-Sigma project team whose responsibility it is to focus on a particular business process, improve that process, and then move on to another project. The role of the management accountant on the project team can perhaps best be described within the
context of the five phases of the DMAIC approach to process improvement: Define,
Measure, Analyze, Improve, and Control.
In the define phase, management accountants, because they are in the best position
to observe and document waste and excessive costs, can help identify opportunities
that warrant Six
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Sigma-type projects. As a follow-up, management accountants canhelp in the project selection process by providing reliable data regarding estimated costs (e.g., required resources degree of difficulty, chance of success) and benefits (e.g., cost savings, customer impact, expected time for project completion) associated with alternative projects under review. In other words, they can play a key role in making sure that the organization does not assume projects where the expected savings won’t justify the investment of Six
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Sigma resources.In the measurement phase, the management accountant would work with other
members of the project team to determine whether the current measurement system is able to collect accurate and timely data for both process inputs (e.g., temperatures, speeds, pressures) and process outputs (e.g., product dimensions or product performance). Furthermore, the management accountant in this phase of the project helps define and measure the factors that have the most influence on process performance.
In the analysis phase, the management accountant participates in the development of process maps, development of hypotheses regarding potential root causes of quality-related problems, and collection of data that either confirm or refute the hypothesized root causes. Finally, the management accountant would help in the determination of the most important root causes.
In the improvement phase, the project team chooses the most useful and feasible
solutions to the root causes identified in the preceding step. Here, the management accountant can help verify and document that planned or anticipated improvement actually occur.
Finally, in the control phase, the management accountant can help in the development of control tools such as audits and check sheets that can be used to ensure sustainability of the process improvements implemented in the preceding stage.
Source: F. Rudisill and D. Clary, “The Management Accountant’s Role in Six Sigma,”
16-46 Applying Six-Sigma Principles to the Accounting Function (30 Minutes)
Perhaps the most fundamental step in the project is selection of an appropriate cross-functional team, including a project champion (in this case, it was the CFO of the organization) and a project leader (usually either a Green Belt or Black Belt). One framework for the project management process is DMAIC (Design, Measure, Analyze,
Improve, and Control). In the present example, the DMAIC phases consisted of the
following stages:
The Define Stage—the project team developed a statement of the problem (“Too many hours are being spent preparing quarter-end financial statements.”) and a goals statement (“Reduce direct hours worked for 18 schedules from over 100 hours to 26 hours.”). The latter was determined in consultation with the primary customer of these quarterly financial statements: the controller of the parent company. This stage also included the development of a graphical representation of the quarterly closing process, from the recording of journal entries to the electronic transmission (E-trans submission) of 18 end-of-quarter schedules to the parent company.
The Measure Stage—the project team assessed the current cycle time of the quarterly closing process and then developed a cycle-time goal for the process (in hours). The current process consumed approximately 109 hours, as follows: preparation of eight balance sheet schedules, 65 hours; preparation of eight income statement schedules, 16 hours; and, preparation of two inter/intracompany schedules, 28 hours. Thus, the overall cycle-time reduction goal was approximately 84 hours!
The Analyze Stage—in this stage, the team created a “fish-bone” (i.e., “cause-and-effect”) diagram to identify possible root causes of the excessive cycle time for quarterly closings. Four primary causes were identified: (1) a high number of hours were spent on the balance sheet schedules, (2) the E-Trans submissions were started late in the day; (3) one-time items were a surprise; and (4) there was a lack of valid references. After completing the fish-bone diagram, the project team hypothesized that three critical root causes were responsible for a large portion of the excess cycle time: (1) lack of ongoing review of balance sheet and inter/intracompany schedules; (2) insufficient automation in generating data; and (3) lack of communication in financial reporting. For each of these three primary root causes, the team identified one or more “failure modes,” that is, ways in which a process could fail and what could be done to prevent or minimize such failures.
The Improve Stage—for each “failure mode” identified in the preceding stage, the team calculated a “risk priority number” (RPN), which was defined as the product of three characteristics of the failure mode: severity of the potential failure mode, frequency of occurrence, and detectability. After all RPNs were calculated, the team compiled a list of actions that addressed the causes of the potential failure modes. Implementing these actions resulted in substantial process improvements: in the first quarter alone, the total cycle time of the process was reduced to 32 hours, slightly above the 26-hour goal.
16-46 (Continued)
The Control Stage—in a sense, the most important control-related decision occurred at the beginning of the project: selection of the CFO as the project champion (“process owner”). After the project had been completed, the team kept its measurement system in place so schedule-preparation times could be monitored on an on-going basis. The team also documented for future staff members new process procedures.
Source: P. C. Brewer and J. E. Eighme, “Using Six Sigma to Improve the Finance Function,” Strategic Finance (May 2005), pp. 27–33.
16-47 Cost of Quality Reporting for Environmental Performance (20–30 Minutes)
The purpose of this exercise is to get students to think strategically as to how COQ reporting might be used as part of a comprehensive approach to the management and control of environmental costs.
1. As global natural resources become more scarce, and therefore subject to increasing demand, society may demand greater accountability as to the environmental performance of businesses. One recognition of this is the ISO 14000 family of standards that relate to the processes organizations have in place to ensure environmental quality. Other firms simply feel that, as with the case of business ethics, good environmental performance can lead to sustainable competitive advantage.
2. There is no set answer to this part of the assignment, but student samples might include some of the following elements:
Prevention Costs:
Process design/redesign (to produce environmentally friendly outputs) Product design/redesign (to consume fewer natural resources, emit fewer
by-products and pollutants, etc.)
Supplier evaluation/certification costs (for example, do preferred suppliers have ISO 14000 certification?)
Product recycling costs ISO 14000 application costs
Appraisal/Detection Costs:
Product or process inspection Contamination testing
Verifying supplier environmental performance
Development of environmental performance standards
Internal Failure Costs:
Treating/Disposing of Toxic Materials Maintaining Pollution-Control Equipment
Licensing of facilities for producing contaminants Using materials and energy inefficiently
External Failure Costs:
Government-imposed fines Restoring land to natural state Cleaning up contaminated soil Cleaning up a polluted lake Loss of reputation
16-47 (Continued)
3. There are likely opposing points of view. Companies that are included in portfolios of high performance in the environmental (or social) area are certainly likely to favor such disclosures. Stockholders (and potential investors) may favor such disclosures, particularly since the external failure costs that some companies face can have devastating effects on the ability of an organization to be a going concern. That is, investors may value the disclosure of environmental performance data as part of their risk-management objectives. As well, companies that are performing well in terms of environmental performance are likely to favor such disclosures to the investing public.
On the negative side, there is a likely bias: unless all companies would be required to disclose such information, it might be difficult to benchmark environmental performance. Also, it may be difficult (or even impossible) to achieve standardization, which may reduce the “informativeness” of such disclosures. Finally, some companies may oppose the disclosure of this information for competitive reasons (that is, the disclosure of such information might be used strategically by the company’s competitors).
16-48 Cost of Environmental Quality Report (30 Minutes)
1. Sample Cost of Environmental Quality Report:
% of Total Operating Amounts Subtotals Cost Prevention Costs: Employee training $100,000 Product design $140,000 Supplier certification $40,000 $280,000 2.8% Detection Costs: Process inspection $320,000 3.2%
Internal Failure Costs: Depreciation—pollution-
control equipment $400,000
Maintaining pollution-
control equipment $200,000 $600,000 6.0%
External Failure Costs:
Lake clean-up $500,000
Land restoration $700,000
Property-damage claim $600,000 $1,800,000 18.0%
Totals $3,000,000 30.0%
2. With only a single year of data, it is difficult to draw any meaningful conclusions. However, a tentative conclusion is that the company may be spending far too little in the conformance quality area (i.e., Prevention and Detection Costs) and, as a consequence, is incurring significant failure costs in the environmental area. 3. Some qualities (attributes) of an effective (“good”) environmental quality cost
system:
Collect environmental quality-cost data from across the value chain (i.e., the scope of data collection should be broad).
If possible, utilize activity-based cost (ABC) data, which could be used to motivate (a) the elimination of non-value-added activities, and (b) improved efficiency in the conduct of value-added activities.
Baseline data: environmental cost data should be compared to one or more relevant benchmarks (sales, best-in-class performance, etc.).
Time-series results (data from a single time period are not likely to be very informative and, in fact, can be misleading; the provision of time-series data will inform management as to the success in reducing total spending in the environmental cost area and trade-offs between categories).
16-49 Nonfinancial (operational) Control Measures: Environmental Performance (15–20 Minutes)
The purpose of this exercise is to get students to think about the process of developing nonfinancial quality indicators, based on specified Environmental Objectives (five in the present case). The purpose of these indicators is to gauge progress in accomplishing the specified Environmental Objectives and, as such, to motivate improved quality in environmental performance. The following answers are suggestive only:
Minimize Hazardous Materials:
Types and quantities of hazardous materials produced (in total, and per unit of output)
Hazardous materials as a percentage of total materials cost “Productivity” measures (ratio of hazardous outputs to inputs) Minimize Raw Materials Usage:
Types and quantities of virgin (i.e., non-recycled) materials used (in total, and per unit of output)
Productivity measures (e.g., ratio of outputs to virgin/raw materials consumed)
Minimize Energy Requirements:
Types and quantities of energy consumed
Productivity measures (energy consumption per unit produced, etc.) Minimize Release of Residues into the Environment:
Pounds of toxic waste produced Cubic metric tons of effluents
Tons of “greenhouse” gases produced
Percent reduction in materials used for packing product Maximize Opportunities to Recycle:
Pounds (or tons) of material recycled
Percentage of units of output that had to be remanufactured Power (energy) produced from incineration
16-49 (Continued-1)
The instructor might want to use some of the following example disclosures from First Energy Corporation (www.firstenergycorp.com/environment) for illustrative purposes:
Environmental Characteristics Associated with Various Sources of Power Generation
Biomass Power Air Emissions & Solid Waste
Coal Power Air Emissions & Solid Waste
Hydro Power Wildlife Impacts
Natural Gas Power Air Emissions & Solid Waste
Nuclear Power Radioactive Wastes
Oil Power Air Emissions & Solid Waste
Other Sources Unknown Impacts
Solar Power No Significant Impacts
Unknown Purchased Resources Unknown Impacts
Wind Power Wildlife Impacts
Air Emission Disclosure: First Quarter 2005 First Energy Corp: Air Emissions--Projected vs. Actual,
Compared to Regional Average (2005)
0 5 10 15 20 25 30 Carbon Dioxide
Sulfur Dioxide Nitrogen Oxides Regional Average Emissions To ns Projected Actual
16-49 (Continued-2)
Radioactive Waste Produced: Projected vs. Actual, 2004 & 2005
2004 2005
Projected
Quantity QuantityActual Projected Quantity QuantityActual Measure High-Level Radioactive Waste 0.0036 0.0018 0.0040 0.0018 Lbs./1,000 kWh Low-Level Radioactive Waste 0.0001 <0.0001 0.0001 <0.0001 Ft3/1,000 kWh Source: www.firstengergycorp.com/environment
16-50 Graphical Depiction: Is there an Optimal Level of Spending on Quality, or, Is Quality “Free”? (30-40 Minutes)
“Quality is Free” Representation
Interpretation: Under this conceptualization, profit maximization occurs under only when “total” (i.e., maximum) quality-levels are achieved for the organization’s outputs. This view is based on a premise that customers seek the highest-quality products and services and are willing to pay for this level of quality, even if at a premium price. Thus, there is an underlying assumption that increases in spending on quality are more than offset by increases in revenues; in short, “quality is free.” Individuals who subscribe to this point of view maintain that increases in product and service quality lead to increased customer satisfaction which, in turn, is a leading indicator of improved financial performance. Quality Revenues/ Costs Revenues Costs
Maximum quality level (e.g., zero defects)
Maximum Profit Level
16-50 (Continued-1)
Diminishing-Returns Conceptualization
Interpretation: This conceptualization for spending on quality assumes a trade-off between the costs and financial benefits of improving quality. As compared to the previous graph, the one above suggests that optimum profits are obtained at a quality level below maximum quality. In other words, at some point, there are decreasing financial returns on additional spending on quality. Beyond a point, the financial returns (benefits) from additional spending on quality are less than the costs incurred to improve quality. This point is illustrated in the graph below.
Quality Level
Zero
Quality Maximum Quality
Failure Costs Prevention & Appraisal Costs Total Cost of Quality Optimum Quality Level Cost of Quality
16-50 (Continued-2)
Diminishing Returns Conceptualization: Trading Off Costs and Benefits for Spending on Quality
Basically, the above representation assumes that after a point, increases in quality spending do not generate commensurate financial benefits (marginal revenues). The “quality is free” argument would hold that marginal revenues always exceed marginal costs. The “diminishing-returns” representation, however, assumes that, as is the case with other economic activities, at some point the marginal cost of increasing quality will exceed the marginal revenues from doing so.
Quality Level Revenues & Costs Optimum Quality Level Total Costs Total Revenue s Maximum Profit Page: 1 Same as above
16-51 Pareto Diagram (15 min)
(1) (2) (3) (4) (5) (6)
(1) Personal emergency (32) (4) Unexpected visitor (11) (2) A child’s illness (26) (5) Overslept (9)
(3) Personal illness (12) (6) Car broke down (8)
Pareto Charts (Diagrams) can be used for diagnostic control purposes, that is, to identify the primary causes of an identified quality problem (such as “absenteeism”) and, as such, to identify possible solutions to the problem. These charts are named after the Italian economist Wilfredo Pareto; they provide a prioritization of causes of an indicated quality problem, based on frequency of occurrence. Thus, they focus attention on causes that could offer the greatest potential for improving quality. A loose interpretation of the information contained in Pareto charts is that a relatively small number (e.g., 20%) of causes represent a majority (e.g., 80%) of reasons for the quality failure (here, absenteeism).
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16-52 COQ Histogram (30 min)
1. COQ Histogram
Genova Company: Cost of Quality as % of Cost of
Goods Sold, 2007 - 2009
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% Preventioncosts Appraisal costs Internal failurecosts External failurecosts Total cost ofquality
16-52 (continued)
2. Cost of Quality (COQ) as Percentage of Costs of Goods Sold (CGS):
2009 2008 2007
Prevention Costs 2.0% 4.0% 1.0%
Appraisal Costs 1.5% 2.5% 3.0%
Internal Failure Costs 14.0% 23.0% 27.0%
External Failure Costs 12.0% 18.0% 31.0%
Total Cost of Quality 29.5% 47.5% 62.0%
Prevention costs increased, then decreased, over the past three years. Appraisal costs decreased steadily over the years.
Total failure costs, as well as internal and external components, decreased over the years.
Total COQ as a percentage of CGS decreased from 62.0 percent to 29.5 percent. 3. The company can probably expect its total cost of quality to continue declining
provided it maintains adequate level of quality training and other efforts to prevent poor quality from occurring and to continue emphasis on the importance of quality. The company was able to see the results within one year of increased efforts in prevention. The company increased its spending on prevention costs fourfold from 2007 to 2008 and both internal and external failure costs decreased in the same year and continued into 2009. However, the company reduced its spending on prevention costs in 2009 to only half of the level the year before; therefore, it may need to monitor closely the internal failure and external failure costs in 2010. It will be a good investment to increase prevention costs if the failure costs start to climb in 2010.
16-53 Quality Cost Classification (5-10 min)
1. Internal failure cost 2. Internal failure cost 3. Appraisal cost 4. Prevention cost 5. Prevention cost 6. Prevention cost 7. External failure cost
16-54 Quality Cost Classification (10 min)
1. External failure cost 2. Internal failure cost 3. Appraisal cost 4. Internal failure cost 5. Appraisal cost 6. Prevention cost 7. Prevention cost 8. Prevention cost 9. External failure cost 10. External failure cost
16-55 Cost of Quality Improvement—Relevant Cost Analysis (20-30 Minutes)
1. Relevant cost analysis (short-term impact on annual operating profit): Annual Cost of Lighting:
Cost of a new lighting system: $100,000 ÷ 5 years = $20,000
Additional operating cost per year 5,000
Incremental cost per year $25,000
Annual Cost Savings:
Current cost of scrapped components:
50,000 units x 5% x $30/unit = $75,000
Cost of scrapped units with adequate lighting:
50,000 units x 3% x $30/unit = 45,000
Net annual cost savings 30,000
Net Annual Cost ($5,000)
2. Some additional factors that might bear on this decision:
Time-value-of money (this type of problem is an example of a capital budgeting decision; as such, the time-value-of-money should be taken into consideration). The reduction in waste/scrapped products produced effectively increases the
capacity of the manufacturing facility—are there any viable uses for this freed-up capacity?
What effect might the improvement in quality have on the reputation of the company and hence sales and market share?
The financial return from reducing scrap is limited (above) to the manufacturing cost of units that must be discarded. Are there any additional cost savings that might be realized because of the reduction in scrap costs?
3. As indicated in Exhibit 16.3 and the accompanying text discussion, the management accountant plays a pervasive role in a comprehensive quality management and control system. Fundamentally, the management accountant is involved in generating relevant financial and nonfinancial quality-related data. Such data are used by managers for decision-making purposes (as in this exercise) and for controlling quality-related costs.
16-56 Cost of Quality Improvements (5–10 Minutes)
Cost of auditors $80,000 x 3 = $240,000
Office space and equipment 100,000
Total cost $340,000
Savings from reduced errors = $600,000 x 90% = 540,000
16-57 Taguchi Loss Function Analysis (Appendix) (30–40 Minutes) 1. Value of k, the cost coefficient, in the Taguchi Loss Function:
k = $20/0.00022
= $20/0.00000004 = $500,000,000
2. Expected Loss Using Taguchi Function:
X Quality Loss L(x) Probability f(x) Expected Loss
0.1996 80 0.02 1.60 0.1997 45 0.05 2.25 0.1998 20 0.12 2.40 0.1999 5 0.11 0.55 0.2000 0 0.45 0.00 0.2001 5 0.10 0.50 0.2002 20 0.08 1.60 0.2003 45 0.05 2.25 0.2004 80 0.02 1.60 $12.75
3. Expected Loss Using Variance Data (see table below), per Albrecht and Roth, “The Measurement of Quality Costs: An Alternative Paradigm,” Accounting Horizons (June 1992), pp. 15–27:
a. D2 = (0.199991 – 0.2)2, where 0.20 = target value and 0.199991 = x (bar)
= mean value of the quality characteristic
= 0.000000000081
b. Expected loss = k (σ2 + D2)
= $500,000,000 x (0.000000025419 + 0.000000000081)
16-57 (Continued) X Probability, f(x) x*f(x) (x – 0.199991)2f(x) 0.1996 0.02 0.003992 0.00000000305762 0.1997 0.05 0.009985 0.00000000423405 0.1998 0.12 0.023976 0.00000000437772 0.1999 0.11 0.021989 0.00000000091091 0.2000 0.45 0.090000 0.00000000003645 0.2001 0.10 0.020010 0.00000000118810 0.2002 0.08 0.016016 0.00000000349448 0.2003 0.05 0.010015 0.00000000477405 0.2004 0.02 0.004008 0.00000000334562 x (bar) = 0.199991 0.00000002541900
16-58 Using Taguchi Function to Determine Tolerance (10 Minutes)
Total quality cost = k * (Tolerance),2 where k = cost coefficient and Tolerance = quality tolerance allowed
$40.00 = k * (0.0001)2 k = $4,000,000,000 The loss function, L(x), is therefore
$1.60 = $4,000,000,000 (x – 0.2)2
So that tolerance = 0.00002, which provides the following specification:
16-59 Relevant Cost Analysis—Conversion to JIT(20 Minutes)
Current After
Income Statement Items Situation JIT ∆
Sales $1,350,000 $1,650,000 $300,000
Less: Costs
Direct materials 405,000 330,000 (75,000)
Direct labor 297,000 247,500 (49,500)
Variable overhead 378,000 165,000 (213,000)
Product-level support costs 162,000 82,500 (79,500)
Inventory carrying costs 18,000 3,000 (15,000)
Operating profit $90,000 $822,000 $732,000
Note to Instructor: An Excel spreadsheet solution file for this exercise is embedded in this document. You can open the spreadsheet “object” that follows by doing the following:
1. Right click anywhere in the worksheet area below. 2. Select “worksheet object” and then select “Open.”
3. To return to the Word document, select “File” and then “Close and return to...” while you are in the spreadsheet mode. The screen should then return you to the Word document.
16-59: Relevant Cost Analysis--Conversion to JIT Manufacturing Data Input
Current After
Item Situation JIT
Manufacturing Costs as a Percentage of Sales:
16-60 Relevant Cost Analysis—Quality Improvements (20 Minutes)
Estimated cost savings resulting from the recently enacted quality program come from two sources:
1. Manufacturing cost savings associated with the reduction in rework costs:
(reduction in reject rate) x (annual volume of output) x (total rework cost per unit) x annual volume
= (0.05 – 0.035) x 15,000 units x [($480 – 70 – 200) + ($362 – 80) + ($80 – 40)]/unit
= (0.015) x 15,000 units/year x $532/unit = $119,700
2. Financing cost savings associated with the reduction in inventory holdings:
Reduction in Inventory Holdings = $400,000 – $250,000 = $150,000
Estimated inventory carry cost rate, per annum x 0.12
Estimated annual savings due to reduction in inventories = $18,000
3. Total estimated savings due to quality improvement program
= rework cost savings + inventory financing cost savings
16-61 Control Chart (30–40 Minutes)
1. Control Chart—Manufacturing Cycle Times (Weekly Data)
Control Chart: Destin Company
10 12 14 16 18 20 22 24 26 Wee k # 1 2 3 4 5 6 7 8 9 10 11 12 Week # M an uf ac tu ri ng C yc le T im e (W ee kl y A ve ra ge ) Average
2. The target cycle time is 14.0 minutes; the lower control limit is 12.0 minutes and the upper control limit is 16.0 minutes. As indicated in the accompanying Excel file, the mean of the 12 weekly observations is 15.2, while the sample standard deviation is 3.6 minutes (which seems high).
Note: An Excel spreadsheet solution file for this exercise is embedded in this document. You can open the spreadsheet “object” that follows by doing the following: 1. Right click anywhere in the worksheet area below.
2. Select “worksheet object” and then select “Open.”
3. To return to the Word document, select “File” and then “Close and return to...” while you are in the spreadsheet mode. The screen should then return you to the Word document. 16-61: Control Chart Data Input Average Week # Cycle Time
1 12.5 Target Value = 14.0
16-61 (Continued)
3. As indicated in part (2), the mean of the sample observations (15.2) is not that far from the target value (14.0). However, inspection of the control chart suggests wide variability in the process, which is confirmed by the sample standard deviation of the 12 observations around the mean value of the dataset. As well, we note that six of the 12 observations lie outside of the control limits (4 exceed the upper control limit, while 2 are below the lower control limit). The control of process variability is one of the key goals of quality improvement. It may be the case that the underlying process in this case needs to be investigated in order to determine why there seems to be so much variability in weekly cycle times. Perhaps some type of intervention/correction is warranted.
4. Management can determine the upper and lower control limits on their control charts through experience (e.g., trial and error) or through the use of statistical procedures. When these control limits are determined statistically (based on process variability, measured either by standard deviations or on the range of observations over time), the control chart is referred to as a statistical control chart. Thus, the principal difference between the two types of charts is the method used to construct the control limits.
16-62 Quality Cost Classification (10 Minutes)
1.
Prevention Appraisal Internal Failure External Failure a. Materials for repair of goods under
warranty x
b. Inspection of goods repaired under
warranty x
c. Processing customer returns x
d. Canceled sales orders due to unsatisfactory products previously
delivered to its customers x
e. Maintenance costs for testing
equipment x
f. Inspecting finished goods x
g. Time spent to determine courses
needed for quality training x
h. Debugging production software
before production begins x
i. Technical help to resolve a
customer’s production problems that may have been caused by bugs in the software shipped with the company’s
product x
j. Supervision of testing personnel x
2. Conformance costs include prevention and appraisal costs. Nonconformance costs
16-63 Quality Cost Classification (10 Minutes)
Prevention Appraisal Internal Failure External Failure
a.
Warranty repairs xb.
Scrap (net) xc.
Sales allowance granted dueto blemish
x
d.
Contribution margin of lost salesx
e.
Tuition for quality management coursesx
f. Raw materials inspections x
g. Work-in-process inspection x
h. Shipping cost for product
replacements x
i. Recalls—processing costs x
j.
Attorney’s fee for handlingenvironmental litigation x
k.
Inspection of reworked productsx
l.
Overtime premium caused byrework
x
m. Machine maintenance x
