Benihana Case free essay sample

The best method of breaking batching into certain time periods is to start of the first two dinner intervals with batches of 8 as we discovered above it is the most efficient way of allocating your overheads across customers and accommodating the largest number of customers in a given period of time. For the last dining time period we decided to go with the tables of 4 batching because the number of customers that flow through the restaurant decreases so we would have to decrease the number per batch to avoid losing customers due to larger wait times. Between 7 pm and 8 pm, once again on average, we find there to be about 1 minute between arrivals, increasing back to 4 minutes per arrival from 8 pm to 9 pm. If the average party size is 4, then we can sum up these averages to be (60/4*4) + (60/1 * 4) + (60/4 *4) = 360 customers, which is BH’s demand. With 15 tables and batching, BH has a capacity of 15*8= 120 seats at any given time and since the average dining time observed from the simulation is 1 hour, the total capacity within the 3 hour period is 120*3= 360. We will write a custom essay sample on Benihana Case or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Since capacity meets demand, one would think the utilization rate should be 100%, but yet for the 15 table simulation run earlier, we find the number to be at 52. 21%. The reason for this is that there is variability in demand, size of a party, and even in the dining times. Customers don’t always arrive at a steady stream of 8 per table. There is a higher concentration between 7 pm and 8 pm, in comparison to the other timeframes during which demand can’t be met with capacity while during other times, there will be unused capacity. Customers also don’t always arrive in a perfect batch of 8; a batch of 7 might leave one seat unused. And sometimes, customers tend to stay longer than the average one hour, causing a bottleneck in the capacity. Because of this variability, utilization is not 100%. 3C) From the aforementioned simulation run in 3A, we can see that the bar and batching reduces the variability and increases utilization as well as profits. The increased number of bar seats provide for a waiting area for full batches to be formed as well as serving as a revenue generator.