You are the head of analytics at an online retailer that is a competitor of Zappos, selling clothing, footwear and accessories for men, women and children. Your company is facing a difficult situation – the revenue from your major offering is declining. On technical merits, your offering is at least as good, if not better than your competitors’. Your supply chain is able to keep pace with the demand for your offering, but there have been sporadic stock-outs at your major distributors. Your market research suggests that your advertising is less creative and compelling than your competitors’. Furthermore, your major competitor contends that you have violated their patent, and is threatening a patent infringement suit. Your company is likely to go bankrupt if you lose the commercialization rights to its major offering.

You need to diagnose the situation. What are the major trends in the market? Is the market growing, stable or shrinking? What are the trends in your share of the market? You know that your company is losing revenue, but what are the trends in profitability? Are there issues with your supply chain that need to be addressed?

What internal and external data would you need to diagnose the situation? What kinds of analyses would you run? What key performance indicators (KPIs) would you report to your CEO? (20 pts)

You have heard the CMO assert that customers like your competitors’ offering better than your company’s. How would you test this assertion?

What data would you need to diagnose the situation? How would you access these data? What kinds of analyses would you run and what key performance indicators (KPIs) would you report to your CMO? (20 pts)

Your head of HR shows you the results of the latest engagement survey, which clearly shows that there is a risk of losing critical talent from the organization. HR is doing everything that they can to try to address colleague concerns, but that may not be enough.

How would you help the head of HR develop succession plans for the senior roles in the organization? What data would you need to diagnose the situation? Would you need any external data, and if so, what kinds of data? What kinds of analyses would you run and what key performance indicators (KPIs) would you report to the head of HR? (20 pts)

The General Counsel believes that the patent position is strong, but the CEO is concerned about the potential patent suit. He wants the legal team to settle out of court so there is no risk of losing the commercial rights to the offering.

How would you help the CEO and General Counsel understand whether to settle or litigate? How would you help them decide a dollar amount for a settlement if they go that route? (20 pts)

You are being bombarded by issues and questions. You are only a team of one. You must diagnose the situation for the CEO. You have the capacity to focus on only one area… i.e., marketing (customer preference), HR (succession planning for senior roles), or Legal (litigate or settle). Where would you focus, and why? (20 pts)

# Category: Mathematics and Statistics : Analysis

## Part 2: Show your work and explain your process for determining the solution for

Part 2:

Show your work and explain your process for determining the solution for each of these problems on a word document with the solution given below the problem.

If Excel was used, please indicate that as well on the word document.

A word document and/or the Excel Workbook (if used) should be submitted to the Dropbox with labels on the worksheets to indicate which problem is being evaluated.

All answers should be clearly indicated.

Written explanation, reasoning, and rationale should use complete sentences.

A venture capitalist has just given you several million dollars to develop your dream product! Explain in detail what this product is and why people would buy it. (Think Steve Jobs and the iPhone – did people really think we needed “smartphones” back in 2007?)

Now your dream product has gone into production and the manager is asking you, as the statistical expert, to use statistical methods to ensure quality control. See example and CA Starter video in this module’s Livebinder.

Construct a quality control chart and compute upper and lower control limit bounds.

You will generate a random dataset of N samples of defective proportions by completing the following steps:

You will start with a random number by combining the last 2 digits of the year in which you were born plus the day of the month in which you were born. Using the borndate of December 3, 1980, your number would be 80 + 3 = 83. (If your number exceeds 100, subtract 100 from the total.) Call this X and it will seed your random number generation.

Choose a number of samples, N. (N should be between 5 and 10 samples.)

In Excel, type =RAND()*X in a cell. Repeat N times. This will generate the proportion of defective products (out of 100) for your N samples.

Use Excel to create a p-chart for a sample size, 100, and the number of samples, N. See video in Livebinder for creating the p-chart.

What is your Lower Control Limit (LCL) and Upper Control Limit (UCL).

Achieve goals through planning and prioritization.

Is the product in control? If not in control, what sample(s) was outside of the limits, ie below LCL or above UCL?

What measures could be taken now to address the data points that out of control?

What recommendations would you suggest to optimize quality in future production?

## Part 2: Show your work and explain your process for determining the solution for

Part 2:

Show your work and explain your process for determining the solution for each of these problems on a word document with the solution given below the problem.

If Excel was used, please indicate that as well on the word document.

A word document and/or the Excel Workbook (if used) should be submitted to the Dropbox with labels on the worksheets to indicate which problem is being evaluated.

All answers should be clearly indicated.

Written explanation, reasoning, and rationale should use complete sentences.

A venture capitalist has just given you several million dollars to develop your dream product! Explain in detail what this product is and why people would buy it. (Think Steve Jobs and the iPhone – did people really think we needed “smartphones” back in 2007?)

Now your dream product has gone into production and the manager is asking you, as the statistical expert, to use statistical methods to ensure quality control. See example and CA Starter video in this module’s Livebinder.

Construct a quality control chart and compute upper and lower control limit bounds.

You will generate a random dataset of N samples of defective proportions by completing the following steps:

You will start with a random number by combining the last 2 digits of the year in which you were born plus the day of the month in which you were born. Using born date of December 3, 1980, your number would be 80 + 3 = 83. (If your number exceeds 100, subtract 100 from the total.) Call this X and it will seed your random number generation.

Choose a number of samples, N. (N should be between 5 and 10 samples.)

In Excel, type =RAND()*X in a cell. Repeat N times. This will generate the proportion of defective products (out of 100) for your N samples.

Use Excel to create a p-chart for a sample size, 100, and the number of samples, N. See video in Livebinder for creating the p-chart.

What is your Lower Control Limit (LCL) and Upper Control Limit (UCL).

Achieve goals through planning and prioritization.

Is the product in control? If not in control, what sample(s) was outside of the limits, ie below LCL or above UCL?

What measures could be taken now to address the data points that out of control?

What recommendations would you suggest to optimize quality in future production?