Chapter 4 Flashcards
forecasting
process of predicting a future event
short range forecast
- up to 1 year, generally less than 3 months
- purchasing, job scheduling, workforce levels
- tend to be most accurate
medium range forecast
- 3 months to 3 years
- sales and production planning, budgeting
long range forecast
- 3+ years
- new product planning, facility location, research and development
- introduction and growth (product life cycle) require longer forecasts than maturity and decline
types of forecasts (3)
economic, technological, demand
economic forecasts
money supply, inflation rate..
technological forecasts
predict rate of technological progress, impacts development of new products
demand forecasts
predict sales of existing products and services
7 steps in forecasting
- determine the use of the forecast
- select the items to be forecasted
- deterring the time horizon of the forecast
- select the forecasting models
- gather the data
- make the forecast
- validate and implement results
qualitative methods (4)
- Jury of executive opinion
- delphi method
- sales force composite
- market survey
jury of executive opinion
group of high level experts
delphi method
using a group (decision makers, staff and respondents) that allows experts to make forecasts
sales force composite
salespersons estimates of expected sales
market survey
asking the customer
quantitative methods (3)
time series, naive approach, moving average method
time series
uses a series of past data points to make a forecast components:
trend: changes due to population, technology
cyclical: business cycle, political, economical
seasonal: weather, customs
random: natural disasters
naive approach
assumes demand in next period is the same as demand in the most recent period
moving average method
used if little or no trend, provides overall impression of data over time
moving average = (sum of demand in previous n periods) / n
weighted moving average
weights based on experience and intuition
weighted moving average = [(sum of weight for period n) x (demand in period n)] / sum of weights
season index formula
season index = expected annual demand / 12 x index
