Forecast
a statement about the future value of a variable of interest
weather, demand, resource variability
We make forecasts about such things as ________, ________, and ____________.
informed
Forecasts are an important element in making ________ decisions.
Expected level of demand
Accuracy
2 important aspects of forecasts
structural variation
The level of demand may be a function of some ____________ ___________ such as a trend or seasonal variation.
Accuracy
related to the potential size of forecast error
past
Techniques assume some underlying casual system that existed in the _____ will persist into the future.
perfect
Forecasts are not _______.
more
Forecasts for groups of items are more accurate than those for individual items.
decreases, increases
Forecast accuracy _______ as the forecasting horizon _________.
-timely
-accurate
-reliable
-expressed in meaningful units
-in writing
-simple to understand and use
-cost effective
Elements of a good forecast: (7 things)
-Determine the purpose of the forecast
-Establish a time horizon
-Obtain, clean, analyze appropriate data
-Select a forecasting technique
-Make the forecast
-Monitor the forecast
Steps in the Forecasting Process: (6)
minimize
Forecasters want to ________ forecast errors.
impossible
It is nearly _______ to correctly forecast real-world variable values on a regular basis, so, it is important to provide an indication of the extent to which the forecast might deviate from the value of the variable that actually occurs.
accuracy
Forecast _______ should be an important forecasting technique selection criterion.
Error
#NAME?
beyond
If errors fall ______ acceptable bounds, corrective action may be necessary.
MAD
#NAME?
MSE
0
evenly
MAD weights all errors ___________.
squared
MSE weights errors according to their _________ values.
Qualitative Forecasting
these techniques permit the inclusion of soft information such as: human factors, personal opinions, and hunches. These factors are difficult, or impossible, to quantify.
Quantitative Forecasting
these techniques involve either the projection of historical data or the development of associative methods that attempt to use casual variables to make a forecast, and rely on hard data.
Time-series forecasts
uses historical data assuming the future will be like the past
Judgemental forecasts
uses subjective inputs such as opinions from consumer surveys, sales staff, managers, executives, and experts.
Delphi Method
privately gather informants from within the company
Associative forecasts
uses explanatory variables to predict the future
predictor variables
variables that can be used to predict values of the variable of interest
Regression
a technique for fitting a line to a set of data points
Simple Linear Regression
the simplest form of regression that involves a linear relationship between two variables
straight line
The object of simple linear regression is to obtain an equation of a _____ _____ that minimizes the sum of squared vertical deviations from the line.
-Variations around the line are random
-Deviations around the line should be normally distributed
-Predictions are made only within the range of observed values
Simple Linear Regression Assumptions
Least squares line
y=a + bx
Standard error of estimate
a measure of the scatter points around a regression line
small
If the standard error is relatively ______, the predictions using the linear equation will tend to be more accurate than if the standard error is larger.
Correlation
a measure of the strength and direction of relationship between two variables; ranges between -1 and 1
Square of the correlation coefficient
a measure of the percentage of variability in the values of y that is "explained" by the independent variable; ranges between 0 and 1.
MUST
Before a forecasting technique is selected, you _______ understand the underlying pattern of demand for your organization because your selected forecasting technique _____ be able to mimic and predict that pattern of demand.
-Trend
-Seasonality
-Cycles
-Irregular variations
-Random variation
Time-series Behaviors: (5)
Trend
long term (data) upward (growth) or long term downward (decline) movement
Seasonality
short term that repeats itself (greeting cards)
Cycles
long term wave-like variations often based on business cycles; pay close attention to economic indicators (luxury goods)
Irregular variation
due to unusual circumstances, does not repeat typical behavior, unusual circumstances (hurricane)
-not an exact science
-involves error
-assumes past predicts the future
-cant account for unplanned occurrences
-forecast is NOT EQUAL to actual demand
-accuracy decreases as the time period of forecast increases
Accuracy of forecasts:
-smooths fluctuations in time series data
-exhibits less variability than actual demand
-reflects recent values of a time series
-works best for slow, incremental changes
-Types of averaging forecasts: Naive, Moving Averages, Weighted Averages, Exponentia
Forecasting Averaging Techniques
Naive Forecasts
any period's forecast, equals the previous period's actual demand. Good for stable or seasonal demand. Advantages: cheap, quick and easy, no data analysis, easy to understand.
Moving Averages
averages a number of recent actual demand values, updated as new values become available. Advantages: lag actual demand, number of data points in an average determine the sensitivity of each new data point, easy to compute and understand. Disadvantages: a
Weighted Moving Average
assign greater weights to the most recent values in a time series. If Demand is rapid increasing, you want a heavier weight on most recent value.
Exponential Smoothing
each new forecast is based on the previous forecast plus a percentage of the difference between the previous forecast and actual demand from the period.
Next FC= Previous FC + alpha(actual D - Previous FC)
slower
The lower the value of alpha, the ________ the forecast will adjust.
greater
The closer the value of alpha is to 1, the _______ the responsiveness of the forecast.
low
If forecast error is positive, the forecast was too _____.
high
If forecast error is negative, the forecast was too _____.
measured, evaluated
Regardless of the forecasting technique selected, accuracy must be ________ and ________.
-model may be inadequate
-irregular variations may have occurred
-FC technique has been incorrectly applied
-Random variation
Sources of FC errors: (4)
Control charts
useful for identifying the presence of non-random error in forecasts
Tracking signals
can be used to detect forecast bias
-Cost
-Accuracy
-Availability of historical data
-Availability of FC software
-Time needed to gather and analyze date and prepare a FC
-FC horizon
Factors to consider in choosing a FC technique: (6)
Reactive approach
view forecasts as probable future demand; react to meet that demand
Proactive approach
Seeks to actively influence demand; advertising, pricing, product modifications; generally requires either an explanatory model or a subjective assessment of the influence on demand
better
The _______ forecasts are, the more able organizations will be to take advantage of future opportunities and reduce potential risks.
short-term
A worthwhile strategy is to work to improve ______-______ forecasts.
up-to-date
Accurate ____-____-_____ information can have a significant effect on forecast accuracy.
Reduce
_______ the time horizon forecasts have to cover.
supply chain
Sharing forecasts or demand data through the ______ ______ can improve forecast quality.