Chapter 8
Forecast bias
A persistent tendency for a forecast to be over or under the actual value of the data
Time series
A series of observations taken over time.
What is the Exponential Smoothing forecasting method?
A weighted average procedure with weights declining exponentially as data become older
Executive opinion
Forecasting method in which a group of managers collectively develop a forecast
Naïve Method
Forecasting method that assumes next period's forecasting is equal to the current period's actual value
MOST forecasting software packages fall into one of three categories :(1) spreadsheets, (2) statistical packages, and (3) specialty forecasting packages.
True
John's Office Supply Company has the following order history over the last 8 months. __________; April 80 May 75 June 160 July 120 August 80 September 120 October 180 November 90 Compute a 3-month weighted moving average forecast for December, with a weight of 65% for the MOST recent month, 25% for the month preceding the MOST recent month, and 10% for the month preceding that one.
(.65 *90 +.25* 180+.1*120)/3= 115.5
Weighted moving average
A forecasting method in which n of the most recent observations are averaged and past observations may be weighted differently
Which one is the most frequently used forecasting technique?
Exponential smoothing
Quantitative forecasting methods
forecast is based on mathematical modeling
Qualitative forecasting methods
forecast is made subjectively by the forecaster
Simple moving average (SMA)
A forecasting method in which only n of the most recent observations are averaged
Trend-adjusted exponential smoothing
Exponential smoothing model that is suited to data that exhibit a trend
Which of the following is the least useful sales forecasting model to use when sales are increasing?
Simple mean
In exponential smoothing, which of the following values for alpha would generate the most stable forecast where Ft+1= alpha.At + (1-alpha)FT?
0.10
Which of the following forecasting methods would be most accurate if demand were rapidly decreasing?
3- month moving average
A firm has the following order history over the last 6 months. January 120 February 95 March 100 April 75 May 100 June 50 What would the best 4- month simple moving average forecast for July?
81.25 100+75+100+50= 325/4 =
Seasonality
Any pattern that regularly repeats itself and is constant in length
Delphi method
Approach to forecasting in which a forecast is product of a consensus among a group of experts
Market research
Approach to forecasting that relies on surveys and interviews to determine customer preferences
Which of the following is an important factor in forecasting model Selection?
Cost Accuracy Ease of use
Cycles
Data patterns created by economic fluctuations
Which forecasting method seeks to develop a consensus among a group of experts?
Delphi method
Forecast error
Difference between forecast and actual value for a given period
CPFR is at the early stage of development in practice and is being pioneered by a handful of companies.
False
Multiple regression is an extension of linear regression where linear regression is repeated multiple times until forecast is computed.
False
Specialty software packages are the BEST option for forecasting.
False
The first step in CPFR is to generate a joint order forecast.
False
The first step in the forecasting process is to generate a forecast and test accuracy.
False
The forecasting process and accuracy checks need to be once a month.
False
What is the Mean Absolute Deviation (MAD)?
It is a measure of forecast error that computes error as the average of the sim of the absolute errors
What is the Mean Square Error (MSE)?
It is a measure of forecast error that computes error as the average of the squared error
Which of the following is TRUE about the correlation coefficient?
It is a statistic thatmeasures the direction and strength of the linear relationship between two variables
Which is TRUE about the Delphi method?
It seeks to develop a consensus among a group of experts
What is the Simple Average forecasting method?
It uses an average of past data as a forecast
What is the Naïve forecasting method?
It uses last period's actual value as a forecast
Which is an important factor in selecting a forecasting model?
Length of Forecast Horizon Degree of accuracy required Data pattern present Amount and type of data available
Which of the following is a causal forecasting method?
Linear regression
Mean squared error (MSE)
Measure of forecast error that computes error as the average of the squared error
Mean absolute deviation (MAD)
Measure of forecast error that computes error as the average of the sum of the absolute error
Over the long term, which of the following forecasting models will likely require carrying the least amount of data?
Naive
Trend
Pattern in which data exhibit increasing or decreasing values over time
Level or horizontal pattern
Pattern in which data values fluctuate around a constant mean
Seasonal index
Percentage amount by which data for each season are above or below the mean
Forecasting
Predicting future events
Linear regression
Procedure that models a straight-line relationship between two variables
Which are the two categories of forecasting models?
Qualitative and Quantitative models
Correlation coefficient
Statistic that measures the direction and strength of the linear relationship between two variables
What is the Linear Trend Line forecasting method?
Technique uses the least- squares method to fit a straight line to past data over time
Simple mean or average
The average of a set of data
Forecast error is
The difference between the forecast and actual value for a given period
Which is TRUE about causal models?
They are based on the assumption that the variables being forecast is related to other variables in the environment
Which is true about quantitative forecasting models?
They are consistent and objective they are based on statistics and mathematics They are only as good as the data on which they are based
Which is true about qualitative forecasting models?
They can incorporate the latest changes in the environment They are based on human judgement They are often biased
Tracking signal
Tool used to monitor the quality of a forecast
Collaborative Planning, Forecasting, and Replenishment (CPFR) is a collaborative process between two trading partners that establishes formal guidelines for joint forecasting and planning.
True
Predicative analytics uses a variety of techniques- such as statistics, modeling, and data mining- to analyze current and historical facts to make predictions about the future.
True
The simple moving average forecasting method uses fewer periods of data than the simple mean forecasting method does.
True
Random variation
Unexplained variation that cannot be predicted
Exponential smoothing model
Uses a sophisticated weighted average procedure to generate a forecast
Time series models
based on the assumption that a forecast can be generated from the information contained in a time series of data
Causal models
based on the assumption that the variable being forecast is related to other variables in the environment
The BEST model to forecast random variation is
cannot forecast random variation
Economics indicates that the world economy fluctuates over the long term. What types of data pattern would this be?
cycles
Forecast error should be measured monthly with one accuracy measure
false
Which of the following is a principle of forecasting?
forecasts are rarely perfect Forecasts are more accurate for groups or families of items rather than for individual items Forecasts are more accurate for shorter than loner time horizons