Concept:
Safety Stock serves as a protective buffer held in inventory to safeguard against stockouts caused by unpredictable fluctuations in demand rates or replenishment lead times. The statistical formula for safety stock when demand during lead time is normally distributed is:
\[
\text{Safety Stock} = z \times \sigma_L
\]
Where $z$ is the standard normal service factor corresponding to the desired service level, and $\sigma_L$ represents the standard deviation of demand uncertainty during the lead time.
Step 1: Analyzing the relationship between demand uncertainty and safety buffer.
The standard deviation $\sigma_L$ directly quantifies the degree of uncertainty or error present within demand forecasting models. If demand is completely stable and predictable, $\sigma_L = 0$, meaning zero safety stock is required. As market volatility and forecasting uncertainty escalate, $\sigma_L$ grows larger, requiring a larger safety stock buffer to ensure the same service level protection. Thus, a direct proportional dependency exists:
\[
\text{Uncertainty} \uparrow \quad \Rightarrow \quad \text{Safety Stock} \uparrow
\]
This validates Option (3) as a true statement.
Step 2: Disproving the alternative options.
* Option (1) Analysis: If the risk or impact of running out of stock is highly severe, a company must increase its safety stock to reduce that vulnerability, not lower it.
* Option (2) Analysis: Capital opportunity cost represents the financial penalty of tying up funds in stock. A higher opportunity cost creates a stronger incentive to minimize idle assets, prompting a *reduction* in safety stock levels rather than an increase.
Therefore, Option (3) is the only relationship that holds correct.