Your company is using a plant of size 10,000 sq. ft. that was constructed in 2006 for $300,000. The cost indices that correspond to this size of a plant for 2006 and 2014 are 145 and 186 respectively. If the power-sizing exponent is 0.55, how much would it cost to build a 40,000 sq. ft. warehouse in 2014?

Note: Answer would be $816,026. Please include complete explanation and step-by-step solution.

Hospital chain HCA relied heavily on revenue growth in its effort to take the firm private. On July 24, 2006, management again announced that it would “go private” in a deal valued at $33 billion, including the assumption of $11.7 billion in existing debt. Would you consider a hospital chain a good or bad candidate for an LBO? Explain your answer.

Nike was founded in 1964 by Bill Bowerman and Phil Knight in Beaverton, Oregon. It began as Blue Ribbon Sports (BRS). In 1972, BRS introduced a new brand of athletic footwear called Nike, named for the Greek winged goddess of victory.

The company employs 26,000 staff around the world with revenues in fiscal year 2005 of $13.7 billion. It has facilities in Oregon, Tennessee, North Carolina, and the Netherlands with more than 200 factory stores, a dozen Nike women stores, and more than 100 sales and administrative offices.

Its subsidiaries include Cole Haan Holdings, Inc., Bauer Nike Hockey, Hurley International LLC, Nike IHM, Inc., Converse Inc., and Execter Brands Group LLC. As of May 31, 2004, manufacturing plants included Nike brand, with 137 factories in the Americas (including the United States), 104 in EMEA, 252 in North Asia, and 238 in South Asia, providing more than 650,000 jobs to local communities.

Objective

Nike grew from a sneaker manufacturer in the early 1970s to a global company selling a large number of products throughout the world. Nike’s sneaker supply chain was historically highly centralized. The product designs, factory contracts, and delivery are managed through the headquarters in Beaverton, Oregon. By 1998, there were 27 different and highly customized order management systems that did not talk well to the home office in Beaverton, Oregon. At that time Nike decided to purchase and implement a single-instance ERP system along with supply chain and customer relationship management systems to control the nine-month manufacturing cycle better, with the goal being to cut it down to six months.

Plan

The company developed a business plan to implement the systems over a six-year period, with multiple ERP rollouts over that time. The plan called for the implementation of the demand planning system first while working through the ERP system and supply chain implementation.

Implementation

The demand planning system was implemented first for reasons that made a lot of sense. The total number of users was small in comparison to the ERP system and was thought to be relatively easy to implement; however, this turned out not to be the case. When the system went live, there were a number of problems related to the software, response time, and data. In addition, training was not adequately addressed, causing the relatively small number of end users to use the system ineffectively. The single-instance ERP system and supply chain implementation plan differed from the demand planning system and called instead for a phased rollout over a number of years.

The ERP system implementation went much more smoothly. Nike started in 2000 with the implementation of the Canadian region, a relatively small one, and ended with the Asia-Pacific and Latin America regions in 2006, with the United States and Europe, Middle East, and Africa in 2002. This included implementing a single instance of the system, with the exception of Asia-Pacific, and training more than 6,300 users.

The total cost of the project as of 2006 was at $500 million—about $100 million more than the original project budget.

Conclusion: What was Learned?

The demand planning system interfacing to legacy data from a large number of systems that already did not talk well with each other was a root cause for misinformation and resulted in inadequate supply planning.

The demand planning system was complex, and end users were not trained well enough to use the system effectively.

System testing was not well planned and “real” enough to find issues with legacy system interfaces.

The overall business plan for all the systems and reasons for taking on such a highly complex implementation were well understood throughout the company. Thus, Nike had exceptional “buy-in” for the project and was able to make adjustment in its demand planning system and continue with the implementation. The goal was to ensure business goals were achieved through the implementation, and not so much to get the systems up and running.

Nike exhibited patience in the implementation and learned from mistakes made early in the process.

Training was substantially increased for the ERP implementation. Customer service representatives received 140–180 hours of training from Nike, and users were locked out of the system until they completed the full training course.

Business process reengineering was used effectively to clarify performance-based goals for the implementation.

Case Questions

1. How could OPM3 have helped to identify the problems with implementing the demand planning system?

2. What were the three primary reasons Nike was successful with the ongoing ERP implementation?

3. Why was a phased rollout the correct decision for Nike?

The following are the grades of 27 students in a statistics exam: 20 28 42 51 54 55 56 57 9 61 62 63 64 65 67 68 69 71 74 75 76 77 79 81 84 86 100 a. The number of classes is 5, construct a frequency table. b. Draw a histogram. c. Construct stem and leaf diagram

Please explain these 3 question on NIKE on their sensitive , revenue value quality prestige etc

• How sensitive are your customers to changes in price?
• What revenue do you need to break even and achieve profitability?

• What does the price say about your product in terms of value, quality, prestige, etc.

1. According to a social media​ blog, time spent on a certain social networking website has a mean of 17 minutes per visit. Assume that time spent on the social networking site per visit is normally distributed and that the standard deviation is 7 minutes.
   1. If you select a random sample of 100 sessions, what is the probability that the sample mean is between 16.5 and 17.5 minutes?
2. A global research study found that the majority of​ today's working women would prefer a better​ work-life balance to an increased salary. One of the most important contributors to​ work-life balance identified by the survey was​ "flexibility," with 41​% of women saying that having a flexible work schedule is either very important or extremely important to their career success. Suppose you select a sample of 100 working women.

What is the probability that in the sample between 33​% and 48​% say that having a flexible work schedule is either very important or extremely important to their career​ success?

3. A survey found that 27​% of consumers from a Country A are more likely to buy stock in a company based in Country​ A, or shop at its​ stores, if it is making an effort to publicly talk about how it is becoming more sustainable. Suppose you select a sample of 100 respondents from Country A. Complete parts​ (a) through​ (d) below.

What is the probability that in the​ sample, between 23​% and 31​% are more likely to buy stock in a company based in Country​ A, or shop at its​ stores, if it is making an effort to publicly talk about how it is becoming more​ sustainable?

Consider a closed economy (an autarky). The equilibrium price of computers in this autarky is equal to $1,000. Suppose that the world price of computers is equal to $800.

2. Show the consumer surplus, producer surplus, equilibrium price and quantity traded for the closed economy in part-a in the market for computers.

3. Now suppose this closed economy opens up to international trade. Now show the consumer surplus, producer surplus, equilibrium price and quantity traded. Also make sure to show the exports / imports of the newly opened economy.

4. What happened to consumer surplus, producer surplus, equilibrium price and quantity traded after this economy opened up to international trade?

5. Suppose the policy makers in the newly opened economy are concerned about the welfare of computer producers. Hence, they decide to impose a 30% tariff (a tax on imports) on imported computers. Show the price of computers in the newly opened economy after the tariff is imposed. Show the consumer surplus, producer surplus, equilibrium price and quantity traded after the tariff is imposed. Also make sure to show the government’s tariff revenue.

Could this be answered within excel + handwritten notes and thoroughly explained. Please and thank you

INTRODUCTION TO LINEAR CORRELATION AND REGRESSION ANALYSIS.

An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead). Consumers, of all income and wealth classes, were surveyed. Every year, 1500 consumers were interviewed. The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually. Below is the data shown for the last 24 years.

Date                X                     Y (in thousands of dollars)

1994                79.1                 55.6

1995                79                    54.8

1996                80.2                 55.4

1997                80.5                 55.9

1998                81.2                 56.4

1999                80.8                 57.3

2000                81.2                 57

2001                80.7                 57.5

2002                80.3                 56.9

2003                79.4                 55.8

2004                78.6                 56.1

2005                78.3                 55.7

2006                78.3                 55.7

2007                77.8                 55

2008                77.7                 54.4

2009                77.6                 54

2010                77.6                 56

2011                78.5                 56.7

2012                78.3                 56.3

2013                78.5                 57.2

2014                78.9                 57.8

2015                79.8                 58.7

2016                80.4                 59.3

2017                80.7                 59.9

Questions:

1. Do you think that measuring the level of optimism is a good predictor for trying to forecast future spending on luxury items? Explain why or why not.
2. How would you be able to improve on the model? You must provide a minimum of two specific ways to go about improving the model.
3. If the economist expects that, by year’s end, the average level of consumer confidence will hit 81.5 points, how much will be expected by consumers to spend on luxury items?

Use the data and Excel to answer this question. It contains the United States Census Bureau’s estimates for World Population from 1950 to 2014. You will find a column of dates and a column of data on the World Population for these years. Generate the time variable t. Then run a regression with the Population data as a dependent variable and time as the dependent variable. Have Excel report the residuals.

(a) Based on the ANOVA table and t-statistics, does the regression appear significant?

(b) Calculate the Durbin-Watson Test statistic. Is there a serial correlation problem with the data? Explain.

(d) What affect might your answer in part (b) have on your conclusions in part (a)?

Thanks id advance! Will try to rate the answer ASAP. Please show your process too :)

NOTE THAT

((This should be done by R studio !))

Q: Upload your data as a CSV in R studio, then do any
cleaning or convert needed for example convert the date in your table
from character to date and NA identifiers . After do all these, run a summary statistics

R ONLY !!