Forecasting Flashcards
What is forecasting ?
• Process of predicting a future event • Underlying basis of business decisions such as • production • inventory • personnel • facilities
What are the time horizons in Forecasting?
- Short range forecasting: up to 1 year generally less than 3 months ( purchasing, job scheduling, production levels, job assignments)
- Medium range Forecast: 3 months to 3 years ( sales production and planning)
- Long range Forecasting: 3 or more years ( new product planning, facility location, research and development)
What kinds of forecasting are there ?
1. Economic forecasts • Address business cycle – inflation rate, money supply, housing starts, etc. 2. Technological forecasts • Predict rate of technological progress • Impacts development of new products 3. Demand forecasts • Predict sales of existing product
What are the 7 steps of forecasting?
• Determine the use of the forecast • Select the items to be forecasted • Determine the time horizon of the forecast • Select the forecasting model(s) • Gather the data • Make the forecast • Validate and implement results
What are the different approaches to forecasting ?
1. Qualitative Methods: Used when situation is vague and little data exist: • new products • new technology Involves intuition, experience • e.g., forecasting sales on Internet 2. Quantitative Methods: Used when situation is ‘stable’ and historical data exist • existing products • current technology Involves mathematical techniques • e.g., forecasting sales of color televisions
What are the Qualitative Methods?
1. Jury of executive opinion •Pool opinions of highlevel executives, sometimes augment by statistical models
- Delphi method
•Panel of experts,
queried iteratively - Costumer Market survey
•Ask the customer
4. Sales Force composite •Estimates from individual salespersons are reviewed for reasonableness, then aggregated
What are the Quantitative Methods?
- Time Series Models:
1. Naive approach
2. Moving averages
3. Exponential
smoothing
4. Trend projection
Associative Model:
5. Linear regression
What are the time series components?
- Trend
- Cyclical
- Seasonal
- Random
Describe the trend component
• Persistent, overall upward or downward pattern
• Changes due to population, technology, age,
culture, etc.
• Typically several years duration
Describe cyclical component
• Repeating up and down movements • Affected by business cycle, political, and economic factors • Multiple years duration • Often causal or associative relationships
Describe the seasonal component
- Regular pattern of up and down fluctuations
- Due to weather, customs, etc.
- Occurs within a single year
Describe the random component
• Erratic, unsystematic, ‘residual’ fluctuations
• Due to random variation or unforeseen events
• Short duration and
non repeating
Describe the Naive Approach method
• Assumes demand in next period is the same as demand in most recent period • e.g., if May sales were 48 units, then June sales will also be 48 units - Sometimes cost effective and efficient
Describe the Moving Average Method
- Moving Average (MA) is a series of arithmetic means
- Used if little or no trend present
- Used often for smoothing
- Provides overall impression of data over time
Formula: MA = (∑ demand in previous n periods)/n
Describe the Weighted Moving Average
It is the same as the Moving average but factors are applied depending on the proximity of the month relative to the month being calculated. The more recent the higher is the weight and the more relevant it is to the calculation. Thus old periods are of less relevance to the calculation.
