Operations and Supply Chain Management 9th edition
9th Edition
ISBN: 9781119320975
Author: Roberta S. Russell, Bernard W. Taylor III
Publisher: WILEY
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Chapter 2, Problem 11.1ASC
Summary Introduction
Case summary:
One third of all quality award winners have been from the healthcare category. Undoubtedly this is due to the emphasis by the US government on the provision of quality healthcare. Three recent winners are HCM, SDH and NMHS.
HCM has an 86-bed capacity and has over 800 employees in 10 counties. HCM’s core focus is on – finance and growth, service, quality, and people within its “remarkable always” culture. It is ranked in the top 100 hospitals in the country and has ranked consistently in the top 10 in the country on employee satisfaction.
SDH has a 48-bed capacity with 385 employees and 394 medical staff members. Its core focus areas are – medical surgical and intensive care, birthing, emergency care, and surgical services. Its performance on pneumonia and congestive heart failure puts it in the top 10 in the country. It ranks in the top 10% in employee satisfaction.
NMHS is a community owned health service. It has four hospitals, four nursing homes, 34 clinics, and over 6200 employees. It serves 24 counties and its mission is “to continuously improve the health of the people of our region”. It focuses on five key success factors – people, service, quality, financial, and growth. NMHS too ranks in the top 10% of hospitals in the country.
To determine: Identify and discuss the common quality-motivated characteristics shared by these hospitals.
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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…
Approach
Consider the previous month's forecast to identify which technique is most effective. Use that to forecast the next
month.
Remember to select the forecasting technique that produces the forecast error nearest to zero. For example:
a. Naïve Forecast is 230 and the Forecast Error is -15.
b. 3-Month Moving Forecast is 290 and the Forecast Error is -75.
c. Exponential Smoothing Forecast for .2 is 308 and the Forecast Error is -93.
d. Exponential Smoothing Forecast for .5 is 279 and the Forecast Error is -64.
e. Seasonal Forecast is 297 and the Forecast Error is -82.
The forecast for the next month would be 230 as the Naïve Forecast had the Forecast Error closest to zero with a
-15. This forecasting technique was the best performing technique for that month. You do not need to do any
external analysis-the forecast error for each strategy is already calculated for you in the tables below.
Naïve
Month Period
Actual
Demand
Naïve Forecast
Error
3-
Month
Moving
Forecast
3-
Month
Moving…
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…
Chapter 2 Solutions
Operations and Supply Chain Management 9th edition
Ch. 2 - Prob. 2.1ASCCh. 2 - Prob. 3.1ASCCh. 2 - Prob. 4.1ASCCh. 2 - Prob. 5.1ASCCh. 2 - Prob. 6.1ASCCh. 2 - Prob. 7.1ASCCh. 2 - Prob. 8.1ASCCh. 2 - Prob. 9.1ASCCh. 2 - Prob. 10.1ASCCh. 2 - Prob. 11.1ASC
Ch. 2 - Prob. 13.1ASCCh. 2 - Prob. 1QCh. 2 - Prob. 2QCh. 2 - Prob. 3QCh. 2 - Prob. 4QCh. 2 - Prob. 5QCh. 2 - Prob. 6QCh. 2 - Prob. 8QCh. 2 - Prob. 9QCh. 2 - Prob. 10QCh. 2 - Prob. 12QCh. 2 - Prob. 13QCh. 2 - Prob. 14QCh. 2 - Prob. 15QCh. 2 - Prob. 17QCh. 2 - Prob. 21QCh. 2 - Prob. 22QCh. 2 - Prob. 23QCh. 2 - Prob. 24QCh. 2 - Prob. 25QCh. 2 - Prob. 26QCh. 2 - Prob. 27QCh. 2 - Prob. 28QCh. 2 - Prob. 29QCh. 2 - Prob. 30QCh. 2 - Most students live in a dormitory or apartment...Ch. 2 - Prob. 32QCh. 2 - Describe, in general, how the J.D. Power Circle...Ch. 2 - Select a product that you own (like a cell phone,...Ch. 2 - Prob. 35QCh. 2 - Prob. 36QCh. 2 - Prob. 37QCh. 2 - Prob. 38QCh. 2 - Prob. 39QCh. 2 - Prob. 40QCh. 2 - Prob. 41QCh. 2 - Prob. 42QCh. 2 - Prob. 43QCh. 2 - Prob. 44QCh. 2 - Prob. 45QCh. 2 - Prob. 47QCh. 2 - Prob. 48QCh. 2 - Prob. 49QCh. 2 - Prob. 50QCh. 2 - Prob. 51QCh. 2 - Prob. 55QCh. 2 - Prob. 56QCh. 2 - Prob. 57QCh. 2 - Prob. 60QCh. 2 - Prob. 61QCh. 2 - Prob. 67QCh. 2 - Prob. 68QCh. 2 - Prob. 1PCh. 2 - The Backwoods American company in Problem 2-1...Ch. 2 - Prob. 3PCh. 2 - In Problem 2-3, if the direct manufacturing cost...Ch. 2 - Prob. 5PCh. 2 - The Colonial House Furniture Company manufactures...Ch. 2 - Prob. 8PCh. 2 - Prob. 9PCh. 2 - Prob. 10PCh. 2 - Prob. 11PCh. 2 - Prob. 12PCh. 2 - Prob. 14PCh. 2 - Prob. 1.1CPCh. 2 - Prob. 2.1CPCh. 2 - Prob. 3.1CPCh. 2 - Prob. 3.3CPCh. 2 - Prob. 3.4CPCh. 2 - Prob. 3.5CPCh. 2 - Prob. 3.6CPCh. 2 - Prob. 3.7CPCh. 2 - Prob. 3.8CPCh. 2 - Prob. 4.1CP
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