Introduction to Hierarchical Production Planning and Demand Forecasting
- Slides: 9
Introduction to Hierarchical Production Planning and (Demand) Forecasting
The role of hierarchical production planning in modern corporations (borrowed from Heizer and Render)
Production Planning through Time-based Decomposition Corporate Strategy Aggregate Unit Demand Aggregate Planning (Plan. Hor. : ½-2 years, Time Unit: 1 month) Capacity and Aggregate Production Plans End Item (SKU) Demand Master Production Scheduling (Plan. Hor. : a few months, Time Unit: 1 week) SKU-level Production Plans Manufacturing and Procurement lead times Part process plans Materials Requirement Planning (Plan. Hor. : a few months, Time Unit: 1 week) Component Production lots and due dates Shop floor-level Production Control (Plan. Hor. : a day or a shift, Time Unit: real-time)
Forecasting • Def: The process of predicting the values of a certain quantity, Q, over a certain time horizon, T, based on past trends and/or a number of relevant factors. • In the context of OM, the most typically forecasted quantity is future demand(s), but the need of forecasting arises also with respect to other issues, like: – equipment and employee availability – technological forecasts – economic forecasts (e. g. , inflation rates, exchange rates, housing starts, etc. ) • The time horizon depends on – the nature of the forecasted quantity – the intended use of the forecast
Forecasting future demand • Product/Service demand: The pattern of order arrivals and order quantities evolving over time. • Demand forecasting is based on: – extrapolating to the future past trends observed in the company sales; – understanding the impact of various factors on the company future sales: • • • market data strategic plans of the company technology trends social/economic/political factors environmental factors etc • Rem: The longer the forecasting horizon, the more crucial the impact of the factors listed above.
Demand Patterns • The observed demand is the cumulative result of: – some systematic variation, resulting from the (previously) identified factors, and – a random component, incorporating all the remaining unaccounted effects. • (Demand) forecasting tries to: – identify and characterize the expected systematic variation, as a set of trends: • seasonal: cyclical patterns related to the calendar (e. g. , holidays, weather) • cyclical: patterns related to changes of the market size, due to, e. g. , economics and politics • business: patterns related to changes in the company market share, due to e. g. , marketing activity and competition • product life cycle: patterns reflecting changes to the product life – characterize the variability in the demand randomness
Forecasting Methods • Qualitative (Subjective): Incorporate factors like the forecaster’s intuition, emotions, personal experience, and value system; these methods include: – – Jury of executive opinion Sales force composites Delphi method Consumer market surveys • Quantitative (Objective): Employ one or more mathematical models that rely on historical data and/or causal/indicator variables to forecast demand; major methods include: – time series methods: – causal models: F(t+1) = f (D(t), D(t-1), …) F(t+1) = f(X 1(t), X 2(t), …)
Selecting a Forecasting Method • It should be based on the following considerations: – Forecasting horizon (validity of extrapolating past data) – Availability and quality of data – Lead Times (time pressures) – Cost of forecasting (understanding the value of forecasting accuracy) – Forecasting flexibility (amenability of the model to revision; quite often, a trade-off between filtering out noise and the ability of the model to respond to abrupt and/or drastic changes)
Applying a Quantitative Forecasting Method Determine Method • Time Series • Causal Model Collect data: <Ind. Vars; Obs. Dem. > Fit an analytical model to the data: F(t+1) = f(X 1, X 2, …) Update Model Parameters Use the model forecasting future demand Monitor error: e(t+1) = D(t+1)-F(t+1) Yes Model Valid? No - Determine functional form - Estimate parameters - Validate
- Methods of demand forecasting in managerial economics
- Demand forecasting introduction
- Module 5 supply and demand introduction and demand
- Proses produksi multimedia
- Demand forecasting introduction
- Demand estimation and forecasting
- Collaborative planning and forecasting
- Demand estimation and forecasting
- Forecasting and demand measurement
- Current market demand