Chapter 4 Flashcards
the art and science of predicting future events
forecasting
the length of time on which a forecast is based
planning horizon
systems that integrate marketing, inventory, sales, operations planning, and financial data to synchronize the supply chain
demand planning software
: planning indications that are valuable in helping organizations prepare medium- to long-range forecasts
economic forecasts
projections of a company’s sales for each time period in the planning horizon
demand forecasts
Forecasts are rarely ______ because of randomness
Forecasts more accurate for groups vs. individuals
Forecast accuracy _______ as time horizon increases
perfect
decreases
: forecasts that incorporate such factors as the decision maker’s intuition, emotions, personal experiences and value system
Qualitative forecasts
a forecasting technique that uses the opinion of high-level managers to form a group estimate of demand
Jury of executive opinion
: a forecasting technique using a group process that allows experts to make forecasts
delphi method
a forecasting technique based on salespersons’ estimates of expected sales
sales force composite
: a forecasting method that solicits input from customers or potential customers regarding future purchasing plans
consumer market survey
: a forecasting technique that uses a series of past data points to make a forecast
Analyze by breaking down into components and projecting them forward – there are four components:
time series
the underlying pattern of growth or decline
trend
regular patterns in a data series that take place over long periods of time
Cyclical patterns
unexplained deviation from a predictable pattern
Random variation (or noise)
repeatable periods of ups and downs over short periods of time
seasonal patterns
: The forecast for any period equals the previous period’s actual value
Naïve forecast
: more recent values in a series are given more weight in computing the forecast
Weighted Moving Average (WMA)
a weighted moving average forecasting technique in which data points are weighted by an exponential function
Exponential Smoothing
is the difference between the observed value of the time series and the forecast, or At – Ft
Forecast error
a straight-line mathematical model to describe the functional relationships between independent and dependent variables
Regression analysis:
A measure of the strength of the linear relationship between independent and dependent variables
Varies between -1.00 and + 1.00
Correlation Coefficient (r):
The percentage of the variation in the dependent variable that results from the independent variable
Varies between 0 and 1
Coefficient of Determination (r2):
