Moving average forecasting methods are best when demand shows high random variation, as they help to smooth out the noise and capture the underlying level of demand. Moving average methods use the average of the most recent observations as the forecast for the next period. They assign equal weights to all observations in the average, and drop the oldest observation when a new one becomes available. Moving average methods are not suitable for demand patterns that show a clear trend, consistent seasonality, or a cyclical pattern, as they cannot capture these components of demand. For these patterns, more sophisticated methods such as exponential smoothing or regression are needed. References: Forecasting with moving averages, APICS CPIM
8 Planning and Inventory Management | ASCM

Reducing the inventory value by 10% would contribute most to shortening the cash-to-cash cycle time. The cash-to-cash cycle time is calculated as the days of inventory outstanding plus days of sales outstanding minus days of payables outstanding. By reducing the inventory value, the company can decrease the days of inventory outstanding, leading to a shorter cash-to-cash cycle time. This aligns with CPIM's focus on efficient inventory management to optimize the supply chain. References: The concepts are covered in detail in Module 4: Inventory Management