Faster the delivery, higher is the throughput. Q: How can you reduce demand variability? A: Demand variability can be addressed by: 1. Promoting demand in the off peak hours using Happy Hours. Another way is to alter policies for seating during the off peak hours — like in the simulation, we have an option of letting them sit on a table when there are more than 4 people in a group- this leads to flexibility and reduces the waiting time for the customers.
Reservation Systems and Overbooking- so that we know when how many people are expected. This is very difficult to implement, because there are many cancellations and we can over book by using the newspaper boy problem. Continuously evaluate response buffer strategies to ensure they are aligned with customer segmentation and associated demand variability.
For example, in configurable product industries, forecasts can be significantly improved through postponement strategies in which end item forecasting is replaced with pooled component forecasting.
Q: What do you think is the best strategy for maximizing profitability Vs maximizing throughput? Are there any correlations between these variables? Home Benihana Assignment Group Benihana Assignment Group What do you mean by ticket simulation? What do you understand by simulation teaching? What do you think are the advantages and disadvantages of studying in a gurukul?
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Question :. This browser does not support the video element. Given an input, a coding machine generates pass-codes for six batches every day as follows. Inpur The shopkeeper offered discount to customers. Pass code for Batch I customer the shopkeeper offered discount to Batch II customer discount the shopkeeper offered to Batch III Customer discount offered the shopkeeper to and so on until the arrangement is completed.
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Sadia Rafique. Kelli Frazier. Show More. Views Total views. Actions Shares. No notes for slide. Benihana Simulation 1. Benihana had the options of sending the guests in batches or placing them in the groups in which they arrived.
This becomes clear from the following example: - Batching would mean clubbing two groups of guests of 5 and 3 members each. They would then occupy one table instead of two. This results in better utilisation of the capacity of the restaurant.
Profits are directly dependant on the number of customers served which is again dependant on the utilisation of the restaurant capacity.
Batching helps in serving more customers and reducing the number of lost customers. This results in the increase of profits. Through put can be defined as the number of customers served per staff. Batching helped in increasing through put by getting more customers served by the same staff. Taking the example ahead, the two groups of guests would need two people to serve if no batching was there. But due to batching, they can now be served by only one staff.
They are ready to pay a premium if given private tables. This strategy causes loss of such customers. The optimal results were obtained in changing the dining time as per the peak duration.
The challenge in this case was to analyze the change in dining time that would result in optimum profit for the hotel. After running all possibilities, it was found that increasing advertising budget by 2x for happy hour at 5 PM will result in the optimal profit.
Yes, it is a good idea to use different types of batching methods at a different time. This will result in maximum nightly profit and also increase in the total revenue maximum with this strategy. This is shown in the below table. In this case the challenge was see the use of different batching type that would result in maximum profit for the hotel.
Yes, this strategy resulted in the optimum results. This is because at different times with different batching strategy resulted in the great profit, brand name of the hotel and customer satisfaction. We were able to control the batching type over the time, advertising decisions, and dining time decisions. This affected to get the maximum customers to serve to maximize the profits. Yes, the decisions improve the result.
For example the batching of 8 during the peak time helped in serving more customers and also reducing the dining time. In case of non-peak hours, the service enhanced helped in building the brand and loyalty. No, the decisions did not make the results worse. This is because all decisions were taken to optimize the profit based on best possible scenarios.
The best strategy is batching, incentives, and changing the dining time to optimize the profitability. The best strategies for optimizing the profit are the best strategies for optimizing throughput too. From these challenges I learnt to understand to design, decide and take action on the best possible ways to optimize the profits and proving the best experiences to the customer. The overall experience with each challenge was to take decisions on individual activities that helped in understanding how individual factor impact the decision to great extent.
In Challenge 6, the individual challenges experience helped to combined few decisions and to reach to the best decision without impacting on the results. In this simulation we learnt that using various decisions the best possible solution or decision can be taken which is not that affective in terms of individual factor. This simulation is a real example of the situations that happens in real life in the retail management. This is ideal situation for any hotel and the important part is to manage it effectively and so this strategic simulation directly relates to retail management.
This simulation taught me that if I own a business, i need to look for various factors in terms of optimizing the revenue or profits without impacting the customer services and quality of the product.
The brand of the company or product matters a lot in the service company. Challenge 1: Does the batching strategy affect throughput and if so, by how much? What are the potential disadvantages of batching?
There are various disadvantages of batching as following: There are many customers who do not like sharing the table. These customers are ready to pay premium if given private table. This strategy leads to loss such customers. This strategy works best in the case where demand highly exceeds the supply. Demand smoothing is solved through reservations and forward orders.
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