Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Planificació Agregada× | Efecte Fuet× | |
|---|---|---|
| Camp | Gestió d'operacions | Gestió d'operacions |
| Família | Machine learning | Machine learning |
| Any d'origen≠ | 1992 | 1961 |
| Autor original≠ | Wallace, T. F. | Jay Forrester |
| Tipus≠ | Demand-supply planning framework | Phenomenon and analysis framework |
| Font seminal≠ | Wallace, T. F. (1992). Sales & Operations Planning: The how-to handbook. Cincinnati: APICS Publications. link ↗ | Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102. link ↗ |
| Àlies | sales and operations planning, production planning | demand amplification, Forrester effect |
| Relacionats | 5 | 5 |
| Resum≠ | Aggregate Planning (or Sales & Operations Planning, S&OP) is a collaborative, iterative process that balances demand and supply at a high level—typically grouping products into families and planning over a 3–18 month horizon. Developed formally by Tom Wallace and popularized through APICS, aggregate planning helps organizations align sales forecasts, production capacity, inventory, and workforce to meet demand efficiently while managing costs. It serves as the bridge between strategic business plans and detailed operational execution. | The Bullwhip Effect is a phenomenon in supply chain management where small fluctuations in end-customer demand cause progressively larger fluctuations in orders as one moves upstream from retail to distributors to manufacturers to suppliers. First formally documented by Jay Forrester in his 1961 system dynamics work, and later popularized by Lee, Padmanabhan, and Whang in 1997, the effect reveals how information delays and ordering strategies amplify demand variability throughout supply chains, leading to excess inventory, inefficient production scheduling, and increased costs. |
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