Benihana Case

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  • Topic: Batch, Periodization, Batch file
  • Pages : 6 (1858 words )
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  • Published : October 11, 2011
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Sales and costs (percentages are relative to gross sales, unless stated otherwise)| Percentages| Dollars/yr| | Typical Restaurant| Typical Benihana Restaurant| Typical Benihana Restaurant| Gross Sales| 100%| 100%| $1,300,000|

Food Sales| 70-80%| 70%| $910,000|
Beverage Sales| 20-30%| 30%| $390,000|
Food cost, % of food sales| 38-48%| 30%| $273,000|
Beverage cost, % of beverage sales| 25-30%| 20%| $78,000| Gross profit| 55-65%| 73%| $949,000|
Labor, benefits| 35-40%| 10%| $130,000|
Advertising| 0.75-2%| 8-10%| $130,000|
Rent| 4.5-9%| 4-7%| $65,000|
Other (supplies, isc., utilities, admin, maint., insurance, royalties)| 10-20%| 10-15% (no royalties)| $150,000| Pre-tax profit (before depreciation)| 3-14%| 36%| $474,000| Depreciation*| 2.5-5%| 2%| $30,000|

Pre-tax profit| 0.5-9%| 34%| $444,000|
Tax (assume 50% tax rate)| 0.25-4.5%| 17%| $222,000|
After tax profit| 0.25-4.5%| 17%| $222,000|
Cash flow (add back the depreciation)| -| -| $252,000|
Payback (years)| -| -| 1.2 years|

2A) Throughput is the number of customers served per night and it increases with batching. The results from the simulation can best be expressed through the following table:

Batching Status| ON| OFF|
Drinks Sold| 202| 436|
Dinners Served| 275| 204|
Lost Customers| 24| 95|
Total Dinner Revenue| $2752| $2038|
Bar Revenue| $403| $871|
Cost| $3025| $3036|
Profit| $121.8| -$202|

As evidenced by the data from this table, batching increases the number of dinners served, decreases the number of lost customers, and overall has a positive impact on the nightly profit of BH. Although because of batching, the number of drinks sold and bar revenue is lower than otherwise (because batching pushes customers from the bar to the restaurant quicker), this loss is offset by the increased revenue from dinners. Under batching, the table utilization rate is 57.11% in comparison to the baseline number of 44.11%, which tells us that batching results in higher throughput ensuring higher profitability and utility from resources. 2B) The following chart displays the data collected from running the simulation on challenge 2. As can be clearly observed, profit is maximized when BH is running a batching system with 79 bar seats and 11 restaurant tables (which can serve up to 11 X 8 = 88 customers at any given time. Figure [ 1 ] : Nightly Profit vs Number of Bar Seats/Number of Dining Tables

2C) After running the simulation Challenge 3, we have determined that the following set is the best dining time targets. Open to 7 pm: 47 minutes; 7-8 pm: 45 minutes; 8-10:30 pm: 75 minutes. Since 7-8 pm is the peak time of customers flowing through the restaurant it would make most sense to minimize the number of time each customer spends on the table in order to maximize table turnover. On the other hand, the later dinner period which is 8-10:30 pm we would want to prolong a customer’s stay for as long as possible as the frequency with which customers enter the restaurant sharply decreases so we want each customer in the later period to spend as much time as possible thus enhancing the possibility of placing a larger order over a longer period of time. The opening hour of Benihana is estimated at roughly 47 minutes dining time per customer as the simulation records highest profits with this number. In addition, in the opening hour of the restaurant there is no bottleneck so it really does not make a significant difference as to how long each dining experience is as long as it fits in well with the average dining time of the next hour 2D) After running simulation challenge number 4, we have discovered that the best advertising and special programs campaign for BH going forward is the following: Increase Advertising Budget 2.1 times; Introduce a happy hour program; Opening the restaurant at 5 pm. Of all the three...
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