Benihana Case
1)
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 | …show more content…
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 campaigns that were listed as options, the happy hour is by far the most profitable, and the advertising budget seems to produce the maximum profit at a factor of 2.1 times the current budget. Any more or less produces a lower profit. And opening the restaurant at 5 o’ clock is a logical consequence of introducing a happy hour program.
2E) Open to 7 pm: Batches of 8 7 pm to 8pm: Batches of 8 8 pm to Closing: 4 share a Table
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. Also 4 is a factor of 8 so it is the most efficient way of allocating seats for customers because if we went for tables of 4 to 8 we run a higher risk of losing customers per seat in the occasion of having a batch of 6 arrive. By have batches of 4 you can accommodate the largest number of combinations in terms of the number of customers in one party. Differing batching methods during different times impact profitability and operating costs as overhead is allocated across number of customers so the more you can accommodate in a given period of time, the lower your costs and the higher your profits.
f. Based on the simulations that we ran, we have found that the following set of variables achieve the highest level of profit for BH restaurants:
i) Retain the batching system. ii) Maintain a bar size of 79 seats and 11 restaurants. iii) Maintain an optimal dining time of 47 minutes from open to 7 pm, 45 minutes from 7 pm to 8 pm, 75 minutes from 8 pm to 10:30 pm. iv) Establish an advertising budget of 2.1 times the current advertising budget and launch a happy hour program opening the restaurant at 5 pm. v) Modify batching system of 8, 8, and 4 through the three different time frames respectively.
This set of decisions gives us an average nightly profit of $506 according to the simulations.
3A) The utilization results for the two scenarios are as follows:
i) Scenario A: No batching: 15 bar seats: 19 tables: 29.92% ii) Scenario B: Batching: 47 bar seats: 15 tables: 52.21%
3B) We observe from the simulation that between 6 pm and 7 m, demand is light, with 4 minutes between arrivals on average.
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. 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 …show more content…
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. Batching helps push customers to the restaurant from the bar eliminating delayed service times. The profits from Scenario A to Scenario B are $-495.71 and $-226.07 respectively.
4) We are assuming that the floor plan in Exhibit B has 14 tables and 54 bar seats.
If 14 tables clear every hour, then one table clears ever 60/14 = 4.29 minutes. A customer entering the 54-seater bar would be 55th in line, thus just making the 7th batch in line. The 7th batch in line would have to wait approximately 7 X 4.29 = 30 minutes before being seated at a dining table.
5)
The bar: * increases turnover and efficient allocation of seats * facilitates batching and eliminates variability in the batch size which allows for profit maximization * standardizes the variability of customer throughput * It allows for an opportunity to generate additional revenue while customers wait to be seated in the dining room
The chef: * reduces service time by standardizing training and skill set * delivers consistency in product * turnover is faster and higher capacity because the chef force feeds the customer while making the food * Increases price to customers because it adds an entertainment value * reduces customer anxiety because their food is prepared in front of them * customers don't get bored if they are amongst boring company because they get to see their food being prepared in a stylish way * Reduces fixed costs because less kitchen space required and more space can be given to dining room thus allowing higher potential to earn revenues
Limited
Menu: * Cuts cost * Inventory efficiency and control on wastage * Customer knows exactly what to expect and there are no surprises * Cuts order time per customer * Simple menu but covers the essential food categories thus catering to all preferences * reduces variability and service time because cooking times are more consistent so you can gauge your turnover more accurately 7) Since each batch of customers receives the same dining experience, ignoring minor variability between chef and ingredients, and the limited menu offering, BH is not a typical upscale restaurant which operates like a job shop. That said, it’s unique processes and entertainment value provided to customers also ensures it isn’t a downscale McDonald’s like flow shop. We think BH is somewhere in between the two, probably closer to the flow-shop than a job-shop yet not being recognized as such by a customer because of it’s marketing strategy.
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 | …show more content…
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 campaigns that were listed as options, the happy hour is by far the most profitable, and the advertising budget seems to produce the maximum profit at a factor of 2.1 times the current budget. Any more or less produces a lower profit. And opening the restaurant at 5 o’ clock is a logical consequence of introducing a happy hour program.
2E) Open to 7 pm: Batches of 8 7 pm to 8pm: Batches of 8 8 pm to Closing: 4 share a Table
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. Also 4 is a factor of 8 so it is the most efficient way of allocating seats for customers because if we went for tables of 4 to 8 we run a higher risk of losing customers per seat in the occasion of having a batch of 6 arrive. By have batches of 4 you can accommodate the largest number of combinations in terms of the number of customers in one party. Differing batching methods during different times impact profitability and operating costs as overhead is allocated across number of customers so the more you can accommodate in a given period of time, the lower your costs and the higher your profits.
f. Based on the simulations that we ran, we have found that the following set of variables achieve the highest level of profit for BH restaurants:
i) Retain the batching system. ii) Maintain a bar size of 79 seats and 11 restaurants. iii) Maintain an optimal dining time of 47 minutes from open to 7 pm, 45 minutes from 7 pm to 8 pm, 75 minutes from 8 pm to 10:30 pm. iv) Establish an advertising budget of 2.1 times the current advertising budget and launch a happy hour program opening the restaurant at 5 pm. v) Modify batching system of 8, 8, and 4 through the three different time frames respectively.
This set of decisions gives us an average nightly profit of $506 according to the simulations.
3A) The utilization results for the two scenarios are as follows:
i) Scenario A: No batching: 15 bar seats: 19 tables: 29.92% ii) Scenario B: Batching: 47 bar seats: 15 tables: 52.21%
3B) We observe from the simulation that between 6 pm and 7 m, demand is light, with 4 minutes between arrivals on average.
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. 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 …show more content…
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. Batching helps push customers to the restaurant from the bar eliminating delayed service times. The profits from Scenario A to Scenario B are $-495.71 and $-226.07 respectively.
4) We are assuming that the floor plan in Exhibit B has 14 tables and 54 bar seats.
If 14 tables clear every hour, then one table clears ever 60/14 = 4.29 minutes. A customer entering the 54-seater bar would be 55th in line, thus just making the 7th batch in line. The 7th batch in line would have to wait approximately 7 X 4.29 = 30 minutes before being seated at a dining table.
5)
The bar: * increases turnover and efficient allocation of seats * facilitates batching and eliminates variability in the batch size which allows for profit maximization * standardizes the variability of customer throughput * It allows for an opportunity to generate additional revenue while customers wait to be seated in the dining room
The chef: * reduces service time by standardizing training and skill set * delivers consistency in product * turnover is faster and higher capacity because the chef force feeds the customer while making the food * Increases price to customers because it adds an entertainment value * reduces customer anxiety because their food is prepared in front of them * customers don't get bored if they are amongst boring company because they get to see their food being prepared in a stylish way * Reduces fixed costs because less kitchen space required and more space can be given to dining room thus allowing higher potential to earn revenues
Limited
Menu: * Cuts cost * Inventory efficiency and control on wastage * Customer knows exactly what to expect and there are no surprises * Cuts order time per customer * Simple menu but covers the essential food categories thus catering to all preferences * reduces variability and service time because cooking times are more consistent so you can gauge your turnover more accurately 7) Since each batch of customers receives the same dining experience, ignoring minor variability between chef and ingredients, and the limited menu offering, BH is not a typical upscale restaurant which operates like a job shop. That said, it’s unique processes and entertainment value provided to customers also ensures it isn’t a downscale McDonald’s like flow shop. We think BH is somewhere in between the two, probably closer to the flow-shop than a job-shop yet not being recognized as such by a customer because of it’s marketing strategy.