04 demand forecasting
- 2. Decisions that Need Forecasts Which markets to pursue? What products to produce? How many people to hire? How many units to purchase? How many units to produce? And so on……
- 3. Common Characteristics of Forecasting Forecasts are rarely perfect Forecasts are more accurate for aggregated data than for individual items Forecast are more accurate for shorter than longer time periods
- 4. Forecasting Steps What needs to be forecast? Level of detail, units of analysis & time horizon required What data is available to evaluate? Identify needed data & whether it’s available Select and test the forecasting model Cost, ease of use & accuracy Generate the forecast Monitor forecast accuracy over time
- 5. Types of Forecasting Models Qualitative (technological) methods: Forecasts generated subjectively by the forecaster Quantitative (statistical) methods: Forecasts generated through mathematical modeling
- 6. Qualitative Methods Type Characteristics Strengths Weaknesses Executive opinion A group of managers meet & come up with a forecast Good for strategic or new-product forecasting One person's opinion can dominate the forecast Market research Uses surveys & interviews to identify customer preferences Good determinant of customer preferences It can be difficult to develop a good questionnaire Delphi method Seeks to develop a consensus among a group of experts Excellent for forecasting long-term product demand, technological changes, and scientific advances Time consuming to develop
- 7. Quantitative Methods Time Series Models: Assumes the future will follow same patterns as the past Causal Models: Explores cause-and-effect relationships Uses leading indicators to predict the future E.g. Stationery Products for students
- 8. Exponential Smoothing Include all past observations Weight recent observations much more heavily than very old observations: weight today Decreasing weight given to older observations