Quantitative forecasting uses historical sales data and statistical models to predict future demand, while qualitative forecasting relies on expert judgment, market research, or sales team input, and is especially useful for new products without historical data. The 'bullwhip effect' describes how small fluctuations in customer demand get amplified into much larger swings in orders as they move upstream through distributors, manufacturers, and raw material suppliers, often because each link in the chain adds its own buffer or over-reacts to short-term changes. This amplification can cause manufacturers to overproduce based on exaggerated upstream signals, leading to wasted inventory, or underproduce and cause stockouts when demand signals are misread. Reducing the bullwhip effect typically requires better information sharing across the supply chain, so that every link can see actual customer demand rather than reacting only to the orders from the link directly next to them.