reply to my classmates Operation Management


NOTE: Reply with Reference include one question.

Note: each reply should be separated** 

** 100 words for each reply**

Reply to my first classmate: ABDULMONEM 

waiting time in restaurants

The conventional measures of system performance in restaurants.

Consumers normally just had to stand in line when purchasing and utilize a selection of products and services. Such queuing events are often unfavorable and have been shown to influence customers' overall satisfaction with the product or service. To efficiently control these queuing events, several businesses have implemented a range of initiatives aimed not just at reducing the length of the wait but also at improving consumers' views of that as well (Kumar, Kalwani, & Dada, 1997). Many businesses are required customers to wait for lines such as hospitals, shopping in supermarkets, hotel check-in, etc. However, the most common one, in my opinion, is waiting in line in resultant. People will not travel every, shop in a supermarket, or go to a hotel every day. That is not the case for a restaurant. People go there regularly, like every day or at least two or three times a week. Students at universities, businessmen, and women might go to a restaurant every day. Personally, I go to a restaurant at least two times a week. Wating in line and how long it takes influence my decision. I do not mind waiting 5 to 10 minutes but not more than that.

Restaurant business has several common system performance measures, and they are considered the best measures of system performance. The income per seat available, table turnover rate, table usage on average are all measures of system performance (Ryan, n.d.). However, they are deeply connected to the average amount of consumers queuing (inline or in the system) and the average length of time consumers need to wait (inline or in the system) variables (Stevenson, 2018, p. 790). Why are connected? The table or seat available will determine the average number of customers to be served and the time required.

Describe why the effectiveness of the measure and develop a strategy to be used

The average amount of consumers queuing and the average length of time consumers need to wait are the most effective ones because they give an idea of the ideal capacity a restaurant should be in. What I mean by capacity is the number of tables, seats, and employees available in the restaurant. For example, if the number of tables and seats are good but the number of employees is not, the restaurant will still make the customers wait for more, which will make them unhappy. At the same time, if the number of employees to serve customers is a lot, but the number of tables is not, the restaurant will lose money by employing extra employees who do nothing. Balancing between the number of customers and their waiting time and the number of employees and tables needed is what these measures will give to the restaurant management.

Many strategies can be used to reduce the length of the queue while keeping costs to a minimum. However, according to a study conducted by Johye Hwang, the best one that can be used is the table assignment policy strategy; this policy strategy has four options:

  • The front-to-back policy is that clients are able to sit far from the rear of a dining room.
  • The out-in policy is that clients could sit close to the front because they could like or appreciate a fantastic outdoors view or sit near a wall or a windowpane to safeguard their privacy.
  • In-out policy, clients choose to be near an exciting or exciting event or activity.
  • A random policy assigns equal chances to each seat in any location.

These strategies are based on the number of clients to be served and the time to rate of arrival. However, for a large number of customers, the best option is the out-in policy (2008).

The calculation to help the business.

A good restaurant will turn over a table every 45 minutes (Lieberman, 2014). We can make a calculation that will help the management know how many customers their restaurant can accommodate. So, if we assume that we have ten tables that accommodate two customers each, the restaurant can serve 20 people. Also, if the shift is eight hours, that will give us (8*60 minutes = 480 minutes). Then, 480 / 45 = 10.66 means that a table can be used ten times each shift. 10 (the turnover) * 10 (the total number of table) * 2 (total number of customers in each table) = 200 customers / eight hours. Now the management know that the capacity of the restaurant is 200 customer, and with the use of out-in policy, the restaurant management will be utilized the full system available


Hwang, J. (2008). Restaurant Table Management to Reduce Customer Waiting Times. (334-351, Ed.) Journal of Foodservice Business Research, 11(4). doi:

Kumar, P., Kalwani, M. U., & Dada, M. (1997). The Impact of Waiting Time Guarantees on Customers' Waiting Experiences. Marketing Science, 16(4), 295-314. doi:

Lieberman, M. (2014, 05 27). Restaurant Etiquette: How Long is Too Long to Linger at a Table? Retrieved 11 08, 2021, from

Ryan, K. (n.d.). KPIs Every Restaurant Manager Should Measure. Retrieved 11 08, 2021, from

Stevenson, W. J. (2018). Operations Management (18 ed.). New York, NY, USA: McGraw-Hill Education. Retrieved 11 08, 2021


Reply to my second classmate: Tariq

Waiting Lines in Businesses

A waiting-line system, or queuing system, is when a person or object spends time waiting in a line to complete a transaction or activity. A waiting line can be measured by its two extreme service points: a low level of service and a high level of service. According to Kostecki (1996), “Waiting lines may imply significant marketing costs and managers should know how to cope with them”. Therefore, we nowadays there are some famous drives through café in Saudi is making longline just for the sake of marketing and they have achieve that. Although, Big business and well stablished organizations are obsessed with waiting queues for some critical reasons. The key factors involve the expense to have waiting area, the potential missed market, the probable loss of consumer satisfaction and the resultant congestion that could interrupt other business processes and/or consumers until they are being served or refused to wait. (Stevenson 2018).

In evaluating the existing or planned service programs, performance managers consider five standard systems performance indicators. These five indicators are primarily consumer and spend based. The first indicator is the average number of clients, either in a queue or online waiting. The second indicator is that consumers must wait in line or in a system with an estimated average time (Stevenson, 2018). Thirdly, a significant indicator is machine use, relating to the percentage of resources used and how occupied rather than idle servers are. The next indicator is the tacit expense of a defined capability level and its corresponding line of waiting. The final indicator is the chance of service delivery.

The impact of queuing during visits to hospitals compared with the time spent in patients on access to care in hospitals is becoming more and more a cause of serious concern to a modern community subjected to substantial strides in technical progress and pace. This problem may lead to loss of work if not fixed and handled appropriately. The study of queuing conditions and issues of concern is usually linked to device efficiency metrics. It involves how long a consumer expects to wait in the line before servicing or how long it takes to wait before the service is finished. Some variables need to be identified and monitored by healthcare personnel to monitor and enhance queue conditions by management to determine alternatives (Ndukwe, Omale, & Opanuga, 2011).

            The remedy method of overcoming waiting lines is that patients divide with pain and without pain into patients in which multi-canals are created instead of all, though their requirements are entirely different. Moreover, it enhances online reservations for appointments in order to be more friendly. Such initiatives will decrease the accumulated patient period and therefore minimize the clinic's overall expense.


Ndukwe, H. C, Omale, S., & Opanuga, O. O (2011). Reducing queues in a Nigerian hospital pharmacy. African Journal of Pharmacy and Pharmacology, 5(8), 1020–1026. Retrieved from

Stevenson, W. (2018). Operations management (13th ed.). New York, NY: McGraw-Hill Irwin.

Kostecki, M. (1996). Waiting lines as a marketing issue. European management journal, 14(3), 295-303.

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