Benihana Simulation Assignment PDF

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Benihana simulation assignment with possible answer...

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Benihana Simulation Assignment The Benihana simulator is an exercise with the objective of optimizing a restaurant’s operations to maximize average nightly profits. Benihana is has a unique business model, where patrons get to watch a hibachi chef prepare their meal right in front of them. The restaurant is divided into sections, the bar and the dining room. The bar area is essential to Benihana’s business model for two reasons. Firstly, it serves as a profit center for the restaurant, and secondly, due to Benihana’s unique dining experience, the dining room is made up of tables that each sit 8 people around a hibachi tabletop. To maximize utilization, Benihana needs to make sure each table has 8 paying customers per service (there are multiple services per night). The bar area essentially serves as a waiting room for patrons that may come in groups of less than 8, allowing the host to combine small groups into one table. Benihana operates on slim profit margins, with only $10 in revenue per meal served, with a cost of $3.50 and $2 revenue per drink sold, or $1.50 if the happy hour is pursued, with a cost of $1.40 per drink. To best maximize profits and utilization, infinite situations can be tested in the online simulator.

The first adjustable variable in the simulation is a binary choice, either to batch customers or not batch customers. Batching customers would mean combining multiple patrons at one table, and then serving them all at the same time, with one chef cooking for 8 people at the same time. It’s difficult to imagine Benihana’s not using a batch system, but hypothetically it could be a non-structured system where customers walk in and sit wherever they please. Alternatively, a non-batched system could result in chefs

preparing food for smaller parties of guests, a couple of meals at a time. For Benihana’s business model, using a batch system is clearly the superior option, their business would be infeasible if it weren’t implemented.

Once a decision has been made to batch or not batch customers, the next variable is deciding the ratio of bar seats to tables. As previously stated, each table seats 8 people, and the ratio of bar seats to tables is 8 to 1. There are important factors which need to be considered when deciding on the ratio, primarily the revenues from each section of the restaurant and how they impact one another. To decide the best ratio, it is necessary to understand a later decision, the advertising strategy. If a happy hour is implemented, the revenue from drinks drops from $2 to $1.50, leaving a measly 10 cent profit per drink sold. The benefit of pursuing a happy hour is that it attracts customers who will most likely pay for a meal, with a comparatively higher profit margin than drinks. The most profitable simulation I was able to achieve did pursue a happy hour, and the ratio used to achieve this is 71 bar seats and 12 tables.

Benihana is a physical location, meaning there are capacity restraints. They cannot simply add a table when it’s busier than usual, the only way they can increase profits is by maximizing the number of patrons they can serve in a night. The next step in the simulation is to set the average dining time during three segments of the night. The three segments are the early bird diners, from open until 7PM, then peak time, from 7PM to 8PM and lastly the late crowd, from 8PM to 10:30PM. The simulation makes note that the average dining time is 60 minutes, but to best maximize utilization (which

in turn leads to greater profits) it could be possible to cut the time down to 45 minutes. The Benihana dining room is an experience for guests, but at the end of the day patrons are hungry and want to be fed as quickly as possible. As long as the chefs can maintain their showmanship, while still producing high quality food, it would be logical to cut the dinner service down to 45 minutes per seating. Chefs would benefit from more tips, and the restaurant could increase revenues without expanding the capacity. The bar area would suffer from this, as patrons will spend less time waiting for tables, however the profits from meals ($10 revenue, $3.50 cost) far outweighs the 10 cents per drink from the bar during happy hour.

To fill the restaurant each night, Benihana can rely on word of mouth, or they can boost their exposure through an advertisement and or deal. The simulation can test revenues with zero advertising, all the way up to 4 times the normal budget, which is $447 per night. Using the default settings in the simulation, the average nightly profit is $83.64. With no advertising or promotional deals, the average nightly profit is $232.57. If a happy hour is implemented, the restaurant opening time is changed to 5PM, and a 2.1 times normal marketing budget is spent, the nightly revenue jumps to $476.64. It would be advantageous for Benihana to spend more than their norm on an advertising program, in conjunction with a drink deal to drive more patrons into their establishment, which aligns with the objective of maximizing utilization to drive nightly profits up.

After testing dozens of possible combinations in the Benihana simulator, the highest average nightly profit I could achieve is $632.50. In this scenario, almost every

default setting has been augmented. Firstly, batching customers into groups is a key to the feasibility and success of Benihana. The next decision made is to batch the customers in groups of 8, to maximize utilization of Benihana’s fixed capacity. Smaller groups would waste resources, like the chef’s fixed time to prepare meals, regardless of party size. The most profitable restaurant layout, taking into account the other manipulated variables in this configuration of the simulator is 71 bar seats and 12 tables. Cutting down each service from the standard 60 minute duration to a 45 minute duration will increase table turnover. Using the same 12 tables, opening at 5PM and closing at 10:30PM, a 60 minute duration would allow a maximum of 528 meals to be served, whereas a 45 minute duration would push it up to a maximum of 704 customers. The calculation doesn’t take into account the wait time between services, and it is based on maximum possible utilization, but it is still a hypothetical 30% plus increase, even a 15% real world increase would be beneficial. The chefs would feel the additional pressure, but it would increase their tips, and some Benihana locations already offer a monetary incentive for chefs to complete dinner service within 45 minutes. To

keep the fast paced restaurant packed with guests, Benihana should

pursue a happy hour to attract customers and bump up the advertising budget to 2.1 times their normal budget. Opening at 5PM will attract families with young children, senior citizens (most don’t like to eat dinner too late), and the after-work drinks crowd. Patrons can go right from their office to Benihana’s for drinks, and they will be enticed to stick around for dinner, especially because the food is cooked right in the dining room. The other advertising options are to build awareness or discount dinners to $8.50, but neither of these options are as beneficial as a happy hour. Benihana’s was founded in

1964, therefore many people have already heard of it and are familiar with the brand. Discounting dinners to $8.50 eats into the revenue margins substantially, plus at $10, the meal is already relatively cheap, so it doesn’t make much sense. The objective of this plan is to drive customers into the dining room as quickly and efficiently as possible, discounting the meals is in conflict with the overall strategy. With this plan, there is a 59.76% utilization rate, which doesn’t seem that high, but when taking into account the industry in addition to the policy to seat guests only in batches of 8, the utilization rate is justified. The Benihana simulator is simply that, a simulation of reality that doesn’t take into account the infinite factors that can affect a restaurant. There could be a snow storm, a new competitor, or even a broken hibachi table, but implementing some of the strategies recommended based on the simulation in a real life scenario could lead to increased utilization and in turn increase profitability.

Optimal Simulation Data

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