Org MGMT Chapter 4 Flashcards

Questions and Answers

What two numbers are contained in the daily report to the CEO of Walt Disney Parks & Resorts regarding the six Orlando parks?

Yesterday's actual attendance and today's forecasted attendance

Yesterday's actual attendance and last year's actual attendance

Yesterday's forecasted attendance and today's forecasted attendance

Yesterday's forecasted attendance and the year-to-date average daily forecast error

Yesterday's forecasted attendance and yesterday's actual attendance (correct)

As compared to long-range forecasts, short-range forecasts:

Are less accurate

Deal with less comprehensive issues supporting management decisions (correct)

Employ similar methodologies

All of the above

None of the above

One use of short-range forecasts is to determine:

Capital expenditures

Job assignments (correct)

Facility location

Planning for new products

Research and development plans

Forecasts are usually classified by time horizon into which three categories?

Short-range, medium-range, and long-range Signup and view all the answers

A forecast with a time horizon of about 3 months to 3 years is typically called a:

Medium-range forecast Signup and view all the answers

Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a:

Long-range time horizon Signup and view all the answers

The three major types of forecasts used by organisations in planning future operations are:

Economic, technological, and demand Signup and view all the answers

Which of the following most requires long-range forecasting (as opposed to short-range or medium-range forecasting) for its planning purposes?

Capital expenditures Signup and view all the answers

Short-range forecasts tend to ________ longer-range forecasts.

be more accurate than Signup and view all the answers

Which of the following is NOT a step in the forecasting process?

Eliminate any assumptions Signup and view all the answers

The two general approaches to forecasting are:

Qualitative and quantitative Signup and view all the answers

Which of the following uses three types of participants: decision makers, staff personnel, and respondents?

Delphi method Signup and view all the answers

The forecasting technique that pools the opinions of a group of experts or managers is known as:

Jury of executive opinion Signup and view all the answers

Which of the following is NOT a type of qualitative forecasting?

Moving average Signup and view all the answers

Which of the following techniques uses variables such as price and promotional expenditures, which are related to product demand, to predict demand?

Associative models Signup and view all the answers

Which of the following statements about time-series forecasting is true?

It is based on the assumption that the analysis of past demand helps predict future demand. Signup and view all the answers

Time-series data may exhibit which of the following behaviors?

They may exhibit all of the above. Signup and view all the answers

Gradual upward or downward movement of data over time is called:

A trend Signup and view all the answers

Which of the following is not present in a time series?

Operational variations Signup and view all the answers

The fundamental difference between cycles and seasonality is the:

Duration of the repeating patterns Signup and view all the answers

In time series, which of the following cannot be predicted?

Random variations Signup and view all the answers

What is the forecast for May using a four-month moving average?

44 Signup and view all the answers

Which time-series model below assumes that demand in the next period will be equal to the most recent period's demand?

Naive approach Signup and view all the answers

John's House of Pancakes uses a weighted moving average method to forecast pancake sales. It assigns a weight of 5 to the previous month's demand, 3 to demand two months ago, and 1 to demand three months ago. If sales amounted to 1000 pancakes in May, 2200 pancakes in June, and 3000 pancakes in July, what should be the forecast for August?

2511 Signup and view all the answers

A six-month moving average forecast is generally better than a three-month moving average forecast if demand:

Is rather stable Signup and view all the answers

Increasing the number of periods in a moving average will accomplish greater smoothing, but at the expense of:

Sensitivity to real changes in the data Signup and view all the answers

Which of the following statements comparing exponential smoothing to the weighted moving average technique is TRUE?

Exponential smoothing typically requires less record keeping of past data Signup and view all the answers

Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast?

Exponential smoothing Signup and view all the answers

Which of the following is NOT a characteristic of exponential smoothing?

Weights each historical value equally Signup and view all the answers

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

1.0 Signup and view all the answers

Given an actual demand this period of 103, a forecast value for this period of 99, and an alpha of 0.4, what is the exponential smoothing forecast for next period?

100.6 Signup and view all the answers

A forecast based on the previous forecast plus a percentage of the forecast error is a(n):

Exponential smoothing forecast Signup and view all the answers

Given an actual demand this period of 61, a forecast for this period of 58, and an alpha of 0.3, what would the forecast for the next period be using exponential smoothing?

58.9 Signup and view all the answers

Which of the following values of alpha would cause exponential smoothing to respond the SLOWEST to forecast errors?

0.10 Signup and view all the answers

A forecasting method has produced the following over the past five months. What is the mean absolute deviation?

1.2 Signup and view all the answers

The primary purpose of the mean absolute deviation (MAD) in forecasting is to:

Measure forecast accuracy Signup and view all the answers

Given forecast errors of -1, 4, 8, and -3, what is the mean absolute deviation?

4 Signup and view all the answers

Suppose that the last four months of sales were 8, 10, 15, and 9 units, respectively. Suppose further that the last four forecasts were 5, 6, 11, and 12 units, respectively. What is the mean absolute deviation (MAD) of these forecasts?

3.5 Signup and view all the answers

A time-series trend equation is 25.3 + 2.1x. What is your forecast for period 7?

40.0 Signup and view all the answers

For a given product demand, the time-series trend equation is 53 - 4x. The negative sign on the slope of the equation:

Is an indication that product demand is declining Signup and view all the answers

Yamaha manufactures which set of products with complementary demands to address seasonal variations?

Jet skis and snowmobiles Signup and view all the answers

Which of the following is TRUE regarding the two smoothing constants of the Forecast Including Trend (FIT) model?

Their values are determined independently Signup and view all the answers

Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally adjusted sales forecast for January?

1000 units Signup and view all the answers

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 150, and 130. The average demand over all months during the three-year time period was 190. What is the approximate seasonal index for July?

0.684 Signup and view all the answers

Suppose that the demand in period 1 was 7 units and the demand in period 2 was 9 units. Assume that the forecast for period 1 was for 5 units. If the firm uses exponential smoothing with an alpha value of .20, what should be the forecast for period 3? (Round answers to two decimal places.)

6.12 Signup and view all the answers

________ expresses the error as a percent of the actual values.

MAPE Signup and view all the answers

If Brandon Edward were working to develop a forecast using a moving averages approach, but he noticed a detectable trend in the historical data, he should:

Use weights to place more emphasis on recent data Signup and view all the answers

The degree or strength of a relationship between two variables is shown by the:

Coefficient of correlation Signup and view all the answers

If two variables were perfectly correlated, what would the coefficient of correlation r equal?

B or C Signup and view all the answers

The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were 60, 80, 95, and 75 units. These forecasts illustrate:

Bias Signup and view all the answers

The tracking signal is the:

Ratio of cumulative error / MAD Signup and view all the answers

Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of:

Adaptive smoothing Signup and view all the answers

Study Notes

Daily Reports and Forecasts

Walt Disney Parks & Resorts' daily reports to the CEO include yesterday's forecasted attendance and actual attendance.
Long-range forecasts are typically less specific and sometimes less accurate compared to short-range forecasts due to their extensive time frame.

Forecasting Horizons

Forecasts are categorized into short-range, medium-range, and long-range based on the time frame.
Short-range forecasts help with immediate job assignments, whereas medium-range forecasts are used for plans that span 3 months to 3 years.

Uses of Forecasts

Long-range forecasts focus on strategic initiatives like capital expenditures and research and development.
The three major types of forecasts for organizational planning include economic, technological, and demand forecasts.

Characteristics of Time-Series Forecasting

Time-series data can exhibit trends, random variations, seasonality, and cycles.
The fundamental difference between cycles and seasonality lies in the duration of the repeating patterns.

Forecasting Techniques

Two general approaches to forecasting are qualitative and quantitative.
The Delphi method employs a diverse group of participants including decision-makers and respondents to gather insights.

Exponential Smoothing

Exponential smoothing forecasts respond to changes based on past forecasts and actual demand data.
The smoothing constant, or alpha, determines how the forecast adjusts to changes, with higher values leading to faster responses to errors.

Mean Absolute Deviation (MAD)

MAD is a critical measure for evaluating forecast accuracy by assessing the average magnitude of forecast errors without considering their direction.
It can be calculated based on actual and forecasted values to determine the effectiveness of a forecasting model.

Seasonal Adjustments and Trends

Adjustments can be made for seasonality in demand forecasts to arrive at more accurate predictions.
Time-series trend equations help estimate future demand based on historical data.

Coefficients and Correlation

The coefficient of correlation measures the strength of a relationship between two variables, with values ranging from -1 (perfect negative correlation) to 1 (perfect positive correlation).
A tracking signal is utilized to monitor forecast accuracy and indicates when adjustments are necessary.

Application of Forecasting Models

Techniques such as weighted moving averages assign different weights to past demand data, with more emphasis on recent observations to improve accuracy.
If anomalies or trends are detected in data, it’s suggested to adjust the forecasting method used, employing a weighted strategy for more sensitive data sets.

Practical Forecasting Examples

Specific examples, like the four-month moving average prediction for sales, showcase how historical data informs future forecasting.
Products with complementary demands can be forecasted collectively to manage seasonal demand efficiently.

Summary of Key Points

Understanding the various forecasting techniques and their applications is crucial for effective resource planning and decision-making.
Forecast accuracy and adjustments can significantly impact operational efficiency and strategic planning within an organization.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Description

Test your knowledge on organizational management concepts from Chapter 4 with these flashcards. Focus on key metrics and reporting techniques relevant to Walt Disney Parks & Resorts. Perfect for students and professionals looking to enhance their understanding of management practices.