1. The problem asks why the waiting time might be longer for a young employee. 2. This is a question related to statistics and probability, often analyzed using concepts like the exponential distribution or queueing theory. 3. One common model for waiting times is the exponential distribution, where the waiting time $T$ has probability density function $f_T(t) = \lambda e^{-\lambda t}$, with $\lambda$ being the rate parameter. 4. If young employees have a lower rate $\lambda$ (meaning they complete tasks or get served more slowly), their expected waiting time $E(T) = \frac{1}{\lambda}$ will be longer. 5. Factors influencing longer waiting times for young employees could include less experience, slower decision-making, or less familiarity with processes, effectively reducing their service rate $\lambda$. 6. In queueing theory, the waiting time depends on arrival rates and service rates; if a young employee's service rate is lower, their waiting time increases. 7. Therefore, the longer waiting time for young employees can be explained by their lower effective service rate in the system, leading to higher expected waiting times. This explanation uses basic probability and queueing concepts to understand waiting times.