ForecastingProcess of predicting a future eventUnderlying basis ofall business decisions Sales will be $200 Production Million! Inventory Personnel Facilities
Types of Forecasts by Time Horizon Short-range forecast Up to 1 year; usually less than 3 months Job scheduling, worker assignments Medium-range forecast 3 months to 3 years Sales & production planning, budgeting Long-range forecast 3+ years New product planning, facility location
Short-term vs. Longer-term Forecasting• Medium/long range forecasts deal with more comprehensive issues and support management decisions regarding planning and products, plants and processes.• Short-term forecasting usually employs different methodologies than longer-term forecasting• Short-term forecasts tend to be more accurate than longer-term forecasts.
Types of Forecasts• Economic forecasts – Address business cycle, e.g., inflation rate, money supply etc.• Technological forecasts – Predict rate of technological progress – Predict acceptance of new product• Demand forecasts – Predict sales of existing product
Seven Steps in 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
Realities of Forecasting• Forecasts are seldom perfect• Most forecasting methods assume that there is some underlying stability in the system• Both product family and aggregated product forecasts are more accurate than individual product forecasts
Forecasting ApproachesQualitative Methods Quantitative Methods Used when situation Used when situation is vague & little data is ‘stable’ & historical exist data exist New products Existing products New technology Current technology Involves intuition, Involves experience mathematical e.g., forecasting sales on techniques Internet e.g., forecasting sales of color televisions
Overview of Qualitative Methods Jury of executive opinion Pool opinions of high-level executives, sometimes augment by statistical models Delphi method Panel of experts, queried iteratively Sales force composite Estimates from individual salespersons are reviewed for reasonableness, then aggregated Consumer Market Survey Ask the customer
Overview of Quantitative Approaches• Naïve approach• Moving averages Time-series Models• Exponential smoothing• Trend projection• Linear regression Associative models
Moving Average Method MA is a series of arithmetic means Used if little or no trend Used often for smoothing Provides overall impression of data over time Equation Demand in Previous n Periods MA n
Weighted Moving Average Method• Used when trend is present – Older data usually less important• Weights based on intuition – Often lay between 0 & 1, & sum to 1.0• Equation Σ(Weight for period n) (Demand in period n) WMA = ΣWeights
• Forecasting• 1. The following gives the number of pints of Type A blood used at Woodlawn Hospital in the past 6 weeks:• Week of Pints Used• Aug 3 360• Sept 7 389• Sept 14 410• Sept 21 381• Sept 28 368• Oct 5 374• a. Forecast the demand for the week of October 12 using a 3 week moving average.• b. Use a 3 week weighted moving average, with weights of 0.1, 0.3 and 0.6 using 0.6 for the most recent week.
Disadvantages of Moving Average Methods• Increasing n makes forecast less sensitive to changes• Do not forecast trend well• Require much historical data
Linear Trend Projection• Used for forecasting linear trend line• Assumes relationship between response variable, Y, and time, X, is a linear function Yi a bX i• Estimated by least squares method – Minimizes sum of squared errors
Linear Regression Equations Equation ˆ Yi a bxi : n x i yi nx y i 1 Slope: b n 2 2 x i nx i 1 Y-Intercept: a y bx