Worley Company buys surgical supplies from a variety of manufacturers and then resells and delivers these supplies to hundreds of hospitals. Worley sets its prices for all hospitals by marking up its cost of goods sold to those hospitals by 6%. For example, if a hospital buys supplies from Worley that had cost Worley $100 to buy from manufacturers, Worley would charge the hospital $106 to purchase these supplies. For years, Worley believed that the 6% markup covered its selling and administrative expenses and provided a reasonable profit. However, in the face of declining profits Worley decided to implement an activity-based costing system to help improve its understanding of customer profitability. The company broke its selling and administrative expenses into five activities as shown below: Activity Cost Pool (Activity Measure) Total Cost Total Activity Customer deliveries (Number of deliveries) $ 348,000 4,000 deliveries Manual order processing (Number of manual orders) 380,000 5,000 orders Electronic order processing (Number of electronic orders) 252,000 14,000 orders Line item picking (Number of line items picked) 742,500 450,000 line items Other organization-sustaining costs (None) 630,000 Total selling and administrative expenses $ 2,352,500 Worley gathered the data below for two of the many hospitals that it serves—University and Memorial (both hospitals purchased a total quantity of medical supplies that had cost Worley $35,000 to buy from its manufacturers): Activity Activity Measure University Memorial Number of deliveries 19 29 Number of manual orders 0 41 Number of electronic orders 16 0 Number of line items picked 180 230 Required: 1. Compute the total revenue that Worley would receive from University and Memorial. 2. Compute the activity rate for each activity cost pool. (Round your answers to 2 decimal places.) 3. Compute the total activity costs that would be assigned to University and Memorial. (Round your intermediate calculations and final answers to 2 decimal places.) 4. Compute Worley’s customer margin for University and Memorial. (Hint: Do not overlook the $35,000 cost of goods sold that Worley incurred serving each hospital.) (Loss amount should be indicated with a minus sign. Round your intermediate calculations and final answers to 2 decimal places.)

How did the McCarthy investigations into communist subversion impact the nation as a whole when it came to essential rights of the individual. Who opposed him?

Do not offer solutions! Write about how you might approach the intervention.

1. Research and identify appropriate interventions, strategies for implementation, and methods for evaluation to resolve organizational problems and take advantage of opportunities.

2. Apply management principles to support organizational transformation and change.

Pigs R Us is a second generation, family-owned Richmond-based company with about 400 employees. It slaughters, manufactures, and sells pork food products. Pigs R Us (PRU) is a low-tech, hands-on, “bricks and mortar” type of company with solid brand recognition, an impeccable reputation for high quality and ethical standards. The processes used in manufacturing are with the highest ISO20002 standards, and the plant is maintained immaculately. The personnel are comprised of an older work force (average employee age is late 40s). There is little staff turnover, though lately there have been a diverse group of younger workers joining the company. There has been an impressive record of speedy state and federal new-product approvals, and solid working relationships with their large and small customers.

The company prides itself on the close "southern family," culture of the business. The company logo features a pig with a smile on its face surrounded by small pictures of some of its oldest serving employees. The organization's structure is “old-fashioned”. It is hierarchical with rigid management divisions and reporting policies. Research, manufacturing, and sales and marketing operate in traditional fashion, with employees reporting to supervisors or mid-level managers. By the 1990s, sales and distribution grew from Richmond into a regional market, establishing a competitive advantage throughout the US South. Despite downward economic times in the US and the South, the pork business does well. This is due largely to the fact that Pork is one of the cheaper meat products and there is a variety of ways it can be prepared.

Owned by the Morris family for the last 60 years, Pigs R Us is a key player in the Richmond based food industry. Various Morris family members sit on the board of charities throughout the city and it is not unusual to see the name at society events. Further, the Company sponsors its own Little League Team and has built a recreation center and assisted living facility for the elderly, guaranteeing space for all former 20+ year veteran workers of the company for free. So, it was no surprise, that the whole community was devastated when it was announced by the Morris family that Vance Morris the CEO of Pigs R Us was killed while driving back from a Pigs R US board meeting. The plant closed for a week to show respect and to determine how it would function until the family could make its succession decisions.

Vance Morris was the only son of James and Kathleen Morris. Vance took over the business 10 years before when his father had a heart attack and died. Fresh out of graduate school when his father died. He took over the business that he had known well much to the pleasure and keen eye of the workers. Vance made some marketing changes that allowed for the growth of the company and with the help of the employees brought the plant into its current state. Vance had just gotten married the year before to a young Richmond artist he had met at one of his charity benefits. He had no heirs and no plans for succession as he was in his mid-thirties and had just gotten married. While Vance had cousins in the area they were all professional people who knew nothing about business or pork. The workers could only surmise that the company would be sold, but speculation as to whom it might be did not include someone from out of the city.

Before the deal was announced publicly, John’s widow, Arleen, reported to the workers that a Chinese company, Shanghou (SHU), would be buying Pigs R US. Mrs. Morris assured the workers that the SHU promised not to cut workers' wages and benefits, and to keep the current management team in place. She said that SHU also promised to keep Pork R US headquarters in Richmond. Arleen assured the workers that SHU promised that there would be no changes for the first year and that almost everything would remain the same. From her talks with SHU, Arleen is a bit worried about future changes that SHU may implement.

SHU is a large manufacturer and distributor of food and beverages with, headquarters in Hong Kong. Manufacturing plants operate in mainland China, and the company has additional offices in Europe and Australia. By acquiring the smaller, well-respected Pork R US, SHU aims to diversify and expand its consumer base by including tailor-made pork products globally to meet market projections of a customer upsurge in sustainable, non-beef meats in the next decade. Given SHU’s current availability of telecommunications software and hardware, the deployment of the Pigs R US refrigeration trucks should not be an insurmountable issue.

Many PRU employees, especially the older workers and some of the older managers, are dispirited about the acquisition, and anxious about working for foreigners, downsizing, less face-to-face interaction, language differences, and more electronic systems that are to be put in place. Some of the of the more experienced workers are considering to move or consider an early retirement due to the ongoing rumors about the acquisition. To make matters worse, recent news media have printed stories about tainted food made by other companies in China. Employees fear loss of product quality and damage to PRU’s reputation as well as the loss of the family southern culture that was their pride and joy.

SHU has told PRU workers that for now, most employees will be retained. However, all employees will be evaluated, and reassigned to teams as the new flat structure is put in place. The new CEO is Harvard-educated Daniel Chinn. He supports increasing the company's competitive edge by discovering and developing existing individual potential through group collaboration and team synergy. Ever since his days as a brilliant, hard-driving MBA student; he has been known to be an enthusiastic supporter of job training and career growth. Like many of SHU’s employees, David is in his early thirties. He speaks four languages and is ambitious, self-directed, tech-savvy, accustomed to working remotely, and experienced with a culturally diverse staff. David is eager to make his newest acquisition a success. He wants to move forward on the integration of "Pork R US’ workers into SHU because Chinn believes they are the “greatest asset have a rich knowledge base and experience can be tapped into to bring the company success." Chinn is concerned about the mix of culture and how his ideas of incorporating artificial intelligence and more robotics into the manufacturing processes will be received by management and the workers at the newly acquired plant.

Scenario

The student will use the following situation that has evolved because of the buy out to complete each section of the project. Additional facts will be added to phase two and three of the project to allow students to complete a typical OD process analysis.

Daniel Chinn is anxious to keep the “southern family” culture of Pigs R Us but at the same time wants to use the most modern of manufacturing techniques. He decided that the best way to do this was to start a pilot change operation in the packaging area to demonstrate to the workers the effectiveness of technology. He bought and set up for use 3D printers in the packaging room. The printers were able to create reusable shipping materials and operate in conjunction with the product conveyor for fast and easy. packaging. He brought in two trained 3D printer operators from China to handle the work along with two robots that would move the package material and create shrink-wrapped pallets for loading on to the trucks.

The current packaging department employs 5 workers on day shift and 3 newer workers on the night shift. All day shift workers are in their early fifties and have been working for Pigs R Us all their lives. John Mellon, the lead line man, exemplifies the group. He is 53 years old. He has a family of three children most all are grown. One works in the business with him as the manager of accounting department having gotten a college degree unlike his father. John rarely travels out of state and has never been abroad. He is not terribly familiar with technology. He has a Smart TV but his children have set it up for him to use Netflix.

When the new employees arrived, the packaging staff tried to get to know them but had little in common and found it hard to communicate with them. The new workers ate together at lunch and always with food they brought with them despite offers of food brought in by the older employees to show their “southern roots”. Things are strained between the groups because the older employees thought they were being snubbed and many are uncertain as to the customs and language unable to communicate their real feelings. This all operated to create a schism among the workers which escalated into job performance and employment commitment issues when the six-month results from the 3D/Robot pilot showed the following success in favor of new technology.

The results showed such a marked process improvement with the added benefit of creating materials that were sustainable. The immediate reaction among the older workers was fear for their jobs. The new workers suddenly were the enemy. Chinn was pleased with the new process and indicated that the 3D printing approach would be continued. The word of the decision spread among the families in the company and the “southern family” culture was now closing ranks on the newcomers both in the packaging room and in the other departments thus confirming their fears when news of the buyout surfaced.

An American Company borrowed 1million Canadian dollars to finance the construction of an office building when the Canadian dollar was worth $1 US. At 10% interest, the American Company expected to pay back 1.1 million Canadian dollars which would cost $1.1 million US dollars. However, based on changes in the value of the Canadian dollar, the American Company must pay $1,030,000 million US dollars to satisfy this debt. How will this $70,000 US dollar difference be shown on the American Company’s financial statements under GAAP? How would this have been shown if the American Company used IFRS? Which gives us more relevant information? Explain

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $45 and the estimated standard deviation is about $6.

(a) Consider a random sample of n = 50 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution?

The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $0.85.The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $0.12.    The sampling distribution of x is not normal.The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $6.

Is it necessary to make any assumption about the x distribution? Explain your answer.

It is not necessary to make any assumption about the x distribution because n is large.It is necessary to assume that x has an approximately normal distribution.    It is not necessary to make any assumption about the x distribution because μ is large.It is necessary to assume that x has a large distribution.

(b) What is the probability that x is between $43 and $47? (Round your answer to four decimal places.)


(c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $43 and $47? (Round your answer to four decimal places.)


(d) In part (b), we used x, the average amount spent, computed for 50 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen?

The sample size is smaller for the x distribution than it is for the x distribution.The x distribution is approximately normal while the x distribution is not normal.    The standard deviation is larger for the x distribution than it is for the x distribution.The mean is larger for the x distribution than it is for the x distribution.The standard deviation is smaller for the x distribution than it is for the x distribution.

In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer?

The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.  

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $31 and the estimated standard deviation is about $6.

(a) Consider a random sample of n = 40 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution?

The sampling distribution of x is not normal.The sampling distribution of x is approximately normal with mean μ_x = 31 and standard error σ_x = $0.95.    The sampling distribution of x is approximately normal with mean μ_x = 31 and standard error σ_x = $0.15.The sampling distribution of x is approximately normal with mean μ_x = 31 and standard error σ_x = $6.

Is it necessary to make any assumption about the x distribution? Explain your answer.

It is necessary to assume that x has a large distribution.It is not necessary to make any assumption about the x distribution because n is large.    It is not necessary to make any assumption about the x distribution because μ is large.It is necessary to assume that x has an approximately normal distribution.

(b) What is the probability that x is between $29 and $33? (Round your answer to four decimal places.)


(c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $29 and $33? (Round your answer to four decimal places.)


(d) In part (b), we used x, the average amount spent, computed for 40 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen?

The standard deviation is larger for the x distribution than it is for the x distribution.The mean is larger for the x distribution than it is for the x distribution.    The standard deviation is smaller for the x distribution than it is for the x distribution.The sample size is smaller for the x distribution than it is for the x distribution.The x distribution is approximately normal while the x distribution is not normal.

In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer?

The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.    

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $11 and the estimated standard deviation is about $9.

(a) Consider a random sample of n = 120 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution?

- The sampling distribution of x is not normal

- The sampling distribution of x is approximately normal with mean μ_x = 11 and standard error σ_x = $0.08.

- The sampling distribution of x is approximately normal with mean μ_x = 11 and standard error σ_x = $9.

- The sampling distribution of x is approximately normal with mean μ_x = 11 and standard error σ_x = $0.82.

Is it necessary to make any assumption about the x distribution? Explain your answer.

- It is not necessary to make any assumption about the x distribution because n is large.

- It is not necessary to make any assumption about the x distribution because μ is large.

- It is necessary to assume that x has an approximately normal distribution.

- It is necessary to assume that x has a large distribution.

(b) What is the probability that x is between $9 and $13? (Round your answer to four decimal places.)


(c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $9 and $13? (Round your answer to four decimal places.)


(d) In part (b), we used x, the average amount spent, computed for 120 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen?

- The x distribution is approximately normal while the x distribution is not normal.

- The sample size is smaller for the x distribution than it is for the x distribution.

- The standard deviation is larger for the x distribution than it is for the x distribution.

- The standard deviation is smaller for the x distribution than it is for the x distribution.The mean is larger for the x distribution than it is for the x distribution.

In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer?

- The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.

- The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.

36) Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $32 and the estimated standard deviation is about $7. (a) Consider a random sample of n = 50 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution? The sampling distribution of x is approximately normal with mean μx = 32 and standard error σx = $7. The sampling distribution of x is not normal. The sampling distribution of x is approximately normal with mean μx = 32 and standard error σx = $0.99. The sampling distribution of x is approximately normal with mean μx = 32 and standard error σx = $0.14. Is it necessary to make any assumption about the x distribution? Explain your answer. It is necessary to assume that x has an approximately normal distribution. It is not necessary to make any assumption about the x distribution because μ is large. It is necessary to assume that x has a large distribution. It is not necessary to make any assumption about the x distribution because n is large. (b) What is the probability that x is between $30 and $34? (Round your answer to four decimal places.) (c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $30 and $34? (Round your answer to four decimal places.) (d) In part (b), we used x, the average amount spent, computed for 50 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen? The standard deviation is smaller for the x distribution than it is for the x distribution. The mean is larger for the x distribution than it is for the x distribution. The x distribution is approximately normal while the x distribution is not normal. The sample size is smaller for the x distribution than it is for the x distribution. The standard deviation is larger for the x distribution than it is for the x distribution. In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer? The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer. The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $45 and the estimated standard deviation is about $7.

(a) Consider a random sample of n = 60 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution?

The sampling distribution of x is not normal.The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $7.    The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $0.90.The sampling distribution of x is approximately normal with mean μ_x = 45 and standard error σ_x = $0.12.

Is it necessary to make any assumption about the x distribution? Explain your answer.

It is necessary to assume that x has a large distribution.It is not necessary to make any assumption about the x distribution because n is large.    It is necessary to assume that x has an approximately normal distribution.It is not necessary to make any assumption about the x distribution because μ is large.

(b) What is the probability that x is between $43 and $47? (Round your answer to four decimal places.)


(c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $43 and $47? (Round your answer to four decimal places.)


(d) In part (b), we used x, the average amount spent, computed for 60 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen?

The standard deviation is smaller for the x distribution than it is for the x distribution.The mean is larger for the x distribution than it is for the x distribution.    The x distribution is approximately normal while the x distribution is not normal.The sample size is smaller for the x distribution than it is for the x distribution.The standard deviation is larger for the x distribution than it is for the x distribution.

In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer?

The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.    

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $38 and the estimated standard deviation is about $5.

(a) Consider a random sample of n = 40 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution?

The sampling distribution of x is approximately normal with mean μ_x = 38 and standard error σ_x = $0.79.The sampling distribution of x is approximately normal with mean μ_x = 38 and standard error σ_x = $5.    The sampling distribution of x is approximately normal with mean μ_x = 38 and standard error σ_x = $0.13.The sampling distribution of x is not normal.

Is it necessary to make any assumption about the x distribution? Explain your answer.

It is necessary to assume that x has a large distribution.It is not necessary to make any assumption about the x distribution because μ is large.    It is necessary to assume that x has an approximately normal distribution.It is not necessary to make any assumption about the x distribution because n is large.

(b) What is the probability that x is between $36 and $40? (Round your answer to four decimal places.)


(c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $36 and $40? (Round your answer to four decimal places.)


(d) In part (b), we used x, the average amount spent, computed for 40 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen?

The standard deviation is larger for the x distribution than it is for the x distribution.

The mean is larger for the x distribution than it is for the x distribution.   

The sample size is smaller for the x distribution than it is for the x distribution.

The x distribution is approximately normal while the x distribution is not normal.

The standard deviation is smaller for the x distribution than it is for the x distribution.

In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer?

The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer.

The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.