Final answer:
The best way to measure service level for time-slot delivery involves using Statistical Process Control to analyze customer waiting time data and ensure consistent delivery services. Performance metrics such as average waiting times and delivery time variability, combined with statistical testing at a significance level of 5%, can demonstrate service efficiency and inform improvements.
Step-by-step explanation:
The best way to measure service level for time-slot delivery is through a combination of different analytical methods that capture both efficiency and customer satisfaction. To measure service levels effectively, one should refer to the concept of Statistical Process Control (SPC) and use key performance indicators such as mean delivery times, the standard deviation of delivery times, and the percentage of on-time deliveries.
Applying SPC to time-slot delivery can utilize customer waiting time data to ensure that delivery services are consistent and predictive of future performance. For instance, by utilizing the data provided in Solution 5.11, which indicates one customer arrives every two minutes on average, this metric can be used as a standard to measure real-world performance against. An analysis of the variation among waiting times, as discussed in the conclusion about a single line versus multiple lines, can be performed using an appropriate statistical test, such as a t-test, with a significance level of 5%. This test may validate the claim that a single line causes lower variation among waiting times (shorter waiting times).
Moreover, for Richard's Furniture Company that delivers furniture uniformly between 10 a.m. to 2 p.m., probabilities for delivery time intervals and average times for successive deliveries would also provide insights into service efficiency and customer experience. This can help in assessing service level, as a balance must be struck between minimizing delivery windows and ensuring customer expectations for time-slot delivery are met.