Using Sampling and Statistics to Analyze MillerCoors Distribution Network Performance MillerCoors is a U.S. manufacturer of beer brands including Miller, Coors, Molson, and Blue Moon, operating 10 breweries with a network of over 500 distributors servicing over 700,000 retail accounts, including supermarkets, bars, and restaurants. All U.S. breweries are required by law (emanating from the repeal of prohibition) to use a three-tier distribution system with a wholesaler/distributor layer between the brewery and the retail customer. An advantage of this system is that the distributor has direct local contact with retailers, which can help them develop a locally engaged market strategy. However, the distribution network must also be efficient and cost effective in order to deliver the brewer’s products to retailers fresh, in a timely manner, and damage free. MillerCoors collects data from its distributors for seven attributes, weighted according to business considerations—expired products, processes, product damage, in-house audits, incorrect product staging, quality certifications, and consumer complaints. Data are collected using facility inspections and retail account audits; the latter collected by visiting a sample of 15, 20, or 25 random retailers based on the size of the distributor. This results in over 6000 of the brewer’s national retail accounts being audited each year. These data are used to develop a performance ranking of distributors based on a scaled score of each of the seven quality attributes (computed by using the z value for a normal distribution ). The final rankings are developed by multiplying each distributor’s score by the weighting factors, and adding the seven attribute scores for each distributor, and then “ curving ” (like grades are curved in a class) the summed distributor scores to develop a system-wide comparison based on performance. One direct outcome of the evaluation process was discovering (using a process flow diagram) that there was excessive and inefficient package handling in the distribution system. Identify another company with a national distribution network and discuss how it might use a similar sampling process to evaluate distributor’s performance.

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Answer 1

Textbook Question

Chapter 3, Problem 1.1ASC

Using Sampling and Statistics to Analyze MillerCoors Distribution Network Performance

MillerCoors is a U.S. manufacturer of beer brands including Miller, Coors, Molson, and Blue Moon, operating 10 breweries with a network of over 500 distributors servicing over 700,000 retail accounts, including supermarkets, bars, and restaurants. All U.S. breweries are required by law (emanating from the repeal of prohibition) to use a three-tier distribution system with a wholesaler/distributor layer between the brewery and the retail customer. An advantage of this system is that the distributor has direct local contact with retailers, which can help them develop a locally engaged market strategy. However, the distribution network must also be efficient and cost effective in order to deliver the brewer’s products to retailers fresh, in a timely manner, and damage free.

MillerCoors collects data from its distributors for seven attributes, weighted according to business considerations—expired products, processes, product damage, in-house audits, incorrect product staging, quality certifications, and consumer complaints. Data are collected using facility inspections and retail account audits; the latter collected by visiting a sample of 15, 20, or 25 random retailers based on the size of the distributor. This results in over 6000 of the brewer’s national retail accounts being audited each year. These data are used to develop a performance ranking of distributors based on a scaled score of each of the seven quality attributes (computed by using the z value for a normal distribution). The final rankings are developed by multiplying each distributor’s score by the weighting factors, and adding the seven attribute scores for each distributor, and then “curving” (like grades are curved in a class) the summed distributor scores to develop a system-wide comparison based on performance. One direct outcome of the evaluation process was discovering (using a process flow diagram) that there was excessive and inefficient package handling in the distribution system.

Identify another company with a national distribution network and discuss how it might use a similar sampling process to evaluate distributor’s performance.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

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Scenario You have been given a task to create a demand forecast for the second year of sales of a premium outdoor grill. Accurate forecasts are important for many reasons, including for the company to ensure they have the materials they need to create the products required in a certain period of time. Your objective is to minimize the forecast error, which will be measured using the Mean Absolute Percentage Error (MAPE) with a goal of being below 25%. You have historical monthly sales data for the past year and access to software that provides forecasts based on five different forecasting techniques (Naïve, 3-Month Moving Average, Exponential Smoothing for .2, Exponential Smooth for .5, and Seasonal) to help determine the best forecast for that particular month. Based on the given data, you will identify trends and patterns to create a more accurate forecast. Approach Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next…

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Answer 2

Textbook Question

Chapter 3, Problem 1.1ASC

Using Sampling and Statistics to Analyze MillerCoors Distribution Network Performance

MillerCoors is a U.S. manufacturer of beer brands including Miller, Coors, Molson, and Blue Moon, operating 10 breweries with a network of over 500 distributors servicing over 700,000 retail accounts, including supermarkets, bars, and restaurants. All U.S. breweries are required by law (emanating from the repeal of prohibition) to use a three-tier distribution system with a wholesaler/distributor layer between the brewery and the retail customer. An advantage of this system is that the distributor has direct local contact with retailers, which can help them develop a locally engaged market strategy. However, the distribution network must also be efficient and cost effective in order to deliver the brewer’s products to retailers fresh, in a timely manner, and damage free.

MillerCoors collects data from its distributors for seven attributes, weighted according to business considerations—expired products, processes, product damage, in-house audits, incorrect product staging, quality certifications, and consumer complaints. Data are collected using facility inspections and retail account audits; the latter collected by visiting a sample of 15, 20, or 25 random retailers based on the size of the distributor. This results in over 6000 of the brewer’s national retail accounts being audited each year. These data are used to develop a performance ranking of distributors based on a scaled score of each of the seven quality attributes (computed by using the z value for a normal distribution). The final rankings are developed by multiplying each distributor’s score by the weighting factors, and adding the seven attribute scores for each distributor, and then “curving” (like grades are curved in a class) the summed distributor scores to develop a system-wide comparison based on performance. One direct outcome of the evaluation process was discovering (using a process flow diagram) that there was excessive and inefficient package handling in the distribution system.

Identify another company with a national distribution network and discuss how it might use a similar sampling process to evaluate distributor’s performance.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

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Answer 3

Textbook Question

Chapter 3, Problem 1.1ASC

Using Sampling and Statistics to Analyze MillerCoors Distribution Network Performance

MillerCoors is a U.S. manufacturer of beer brands including Miller, Coors, Molson, and Blue Moon, operating 10 breweries with a network of over 500 distributors servicing over 700,000 retail accounts, including supermarkets, bars, and restaurants. All U.S. breweries are required by law (emanating from the repeal of prohibition) to use a three-tier distribution system with a wholesaler/distributor layer between the brewery and the retail customer. An advantage of this system is that the distributor has direct local contact with retailers, which can help them develop a locally engaged market strategy. However, the distribution network must also be efficient and cost effective in order to deliver the brewer’s products to retailers fresh, in a timely manner, and damage free.

MillerCoors collects data from its distributors for seven attributes, weighted according to business considerations—expired products, processes, product damage, in-house audits, incorrect product staging, quality certifications, and consumer complaints. Data are collected using facility inspections and retail account audits; the latter collected by visiting a sample of 15, 20, or 25 random retailers based on the size of the distributor. This results in over 6000 of the brewer’s national retail accounts being audited each year. These data are used to develop a performance ranking of distributors based on a scaled score of each of the seven quality attributes (computed by using the z value for a normal distribution). The final rankings are developed by multiplying each distributor’s score by the weighting factors, and adding the seven attribute scores for each distributor, and then “curving” (like grades are curved in a class) the summed distributor scores to develop a system-wide comparison based on performance. One direct outcome of the evaluation process was discovering (using a process flow diagram) that there was excessive and inefficient package handling in the distribution system.

Identify another company with a national distribution network and discuss how it might use a similar sampling process to evaluate distributor’s performance.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

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Answer 4

Textbook Question

Chapter 3, Problem 1.1ASC

Using Sampling and Statistics to Analyze MillerCoors Distribution Network Performance

MillerCoors is a U.S. manufacturer of beer brands including Miller, Coors, Molson, and Blue Moon, operating 10 breweries with a network of over 500 distributors servicing over 700,000 retail accounts, including supermarkets, bars, and restaurants. All U.S. breweries are required by law (emanating from the repeal of prohibition) to use a three-tier distribution system with a wholesaler/distributor layer between the brewery and the retail customer. An advantage of this system is that the distributor has direct local contact with retailers, which can help them develop a locally engaged market strategy. However, the distribution network must also be efficient and cost effective in order to deliver the brewer’s products to retailers fresh, in a timely manner, and damage free.

MillerCoors collects data from its distributors for seven attributes, weighted according to business considerations—expired products, processes, product damage, in-house audits, incorrect product staging, quality certifications, and consumer complaints. Data are collected using facility inspections and retail account audits; the latter collected by visiting a sample of 15, 20, or 25 random retailers based on the size of the distributor. This results in over 6000 of the brewer’s national retail accounts being audited each year. These data are used to develop a performance ranking of distributors based on a scaled score of each of the seven quality attributes (computed by using the z value for a normal distribution). The final rankings are developed by multiplying each distributor’s score by the weighting factors, and adding the seven attribute scores for each distributor, and then “curving” (like grades are curved in a class) the summed distributor scores to develop a system-wide comparison based on performance. One direct outcome of the evaluation process was discovering (using a process flow diagram) that there was excessive and inefficient package handling in the distribution system.

Identify another company with a national distribution network and discuss how it might use a similar sampling process to evaluate distributor’s performance.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

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Answer 5

Textbook Question

Answer 6

Textbook Question

Answer 7

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

Answer 8

Expert Solution & Answer

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

Answer 9

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Answer 10

Expert Solution & Answer

Answer 11

Summary Introduction

To determine: Difference between attribute control charts and variable control charts.

Introduction: Control charts are referred as graphs which presents the placing of sample. It determines whether the sample is in its control limit or not. It is established in order to find the control limits of each sample.

Answer 12

Explanation of Solution

Following points highlight the difference between attribute control chart and variable control chart.

Attribute control chart is used for discrete values such as more or less, good or bad, and so on, while variable control chart is used for the variables which are continuous in nature.
In attribute control chart, sample contains non-measurable values such as good or bad, and so on, while in variable chart, variables could be measured such as weight, heights, and so on.
For attribute control chart, two types of charts are used namely, p-chart and c-chart; whereas, for variable chart, mean chart and range chart are used.
Attribute control chart accounts for proportion of defects and then number of defects in a sample; whereas, variable control chart determines whether the sample is in statistical control limits or not.

Answer 13

Ch. 3.S - Prob. 1Q Ch. 3.S - Prob. 2Q Ch. 3.S - Prob. 3Q Ch. 3.S - Prob. 4Q Ch. 3.S - Prob. 5Q Ch. 3.S - Prob. 6Q Ch. 3.S - Prob. 7Q Ch. 3.S - The Great Lakes Company, a grocery store chain,...Ch. 3.S - Prob. 2P Ch. 3.S - Prob. 3P

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