Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Queue System Analysis at Starbucks Stores Farah Rahmatika and Jasmine Shafa Khairunnisa Faculty of Engineering, Industrial Engineering Pembangunan Nasional Veteran Jakarta University Jalan RS Fatmawati, Pondok Labu, South Jakarta farahrhmtk27@gmail.com & jasmine.shafa27@gmail.com Akhmad Nidhom Nurzaman Lecturer of Industrial Engineering Faculty of Engineering Pembangunan Nasional Veteran Jakarta University Indonesia, South Jakarta akhmadnidhomuzzaman@upnvj.ac.id Fitra Lestari Asosciate Professor, Department of Industrial Engineering Head of Department of Industrial Engineering Member, IEOM Indonesia Chapter Sultan Syarif Kasim State Islamic Unversity, Riau, Indonesia fitra.lestari@uin-suska.ac.id Abstract This case study taken from the Starbucks queue occurred because there was a long queue because there was only one cashier on duty who also made drinks for one customer. Therefore, the purpose of this study is to examine and how to reduce long queues by using the FIFO (First In First Out) method so that the expected results can reduce the number of queues and can streamline time with improvements made to parallel tasks for baristas and cashiers. With the Proposed System, it is proven to be able to reduce the idle time of queues at Starbucks outlets with an average reduced time of 1.95 minutes and a maximum waiting time of 5.3 minutes. System Simulation, Starbucks, Improvement, Proposed System and Queues Fitra Lestari is an Associate Professor and Head of the Industrial Engineering Department at Sultan Syarif Kasim State Islamic University, Indonesia. He finished his PhD project with major area in Supply Chain Management at Universiti Teknologi Malaysia. He is currently a member of IEOM and has published a number of articles in international journals about Supply Chain Management, Logistics and Performance Measurement. Akhmad Nidhom Nurzaman is a Lecturer at Universitas Pembangunan Nasional Veteran Jakarta. He teaches System Simulation, System Modelling, and so on. Farah Rahmatika A determined 3rd year industrial engineering student who has passion in Supply Chain Management and Manufacturing. Has a strong communication and interpersonal skills, as a result from my previous © IEOM Society International 1919 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 experiences both in academical and non-academical activities. I also have design skill that I mostly use to support my works. She currently studying system simulation and data science in leisure time. Jasmine Shafa Khairunnisa. A determined 3rd year industrial engineering student who has passion in Human Resources Management. Has a strong communication and interpersonal skills, as a result from my previous experiences both in academical and non-academical activities. I also have design skill that I mostly use to support my works. She currently studying system simulation and data science in leisure time. © IEOM Society International 1920 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Preliminary a. Situation Analysis Queuing activities often occur in everyday life when you want to wait for service, both in the industrial or service sectors. Queuing occurs when the number of customer arrivals is not balanced with the available service capacity so that customers cannot be served directly. Every manufacturing or service company is required to always be able to provide fast service to its customers so that there is no long waiting time. In line with the rapid changes in the business environment and technology, organizations are also required to make changes for the better. The development of the food and beverage industry at this time has grown very rapidly. The food and beverage industry is still the mainstay for Indonesia's economic growth and was able to grow by 8.41% in 2018. Starbucks Corporation is an American coffee shop chain headquartered in Seattle, Washington. Starbucks is the world's largest premium coffee roaster-retail company with 22,519 stores in 67 countries. Starbucks sells hot and cold drinks (espresso, frappucino, smoothies, tea), merchandise (glasses, tumblers, coffee beans), and food (sandwiches, salads, cakes). Since its founding in 1971 in Seattle, Starbucks has expanded rapidly. Starbucks entered Indonesia for the first time in 2002 and was operated by PT. Sari Coffee Indonesia which is a subsidiary of PT. Mitra Adi Perkasa Tbk, as the sole right holder to introduce and market Starbucks in Indonesia. Based on data from CNN Indonesia (2014), Starbucks has 188 outlets throughout Indonesia.In providing services, the main problem that often occurs is queuing activities that cannot be avoided, the length of time queuing and the length of the queue make customers uncomfortable and bored because they feel that time is wasted just to buy this drink so that it can result in losing customers The average number of queues that occur every day ranges from 8-10 people. The object of this research is the Starbucks SuperMall Karawaci outlet, Tangerang. b. System Problem customers come customer in queue ordering Making order Order complete Figure 1. Problem in actual system One of the main issues observed in relation to queues at Starbucks outlets is the accumulation of queues at the ordering section. It is necessary to look at the level of performance and service of Starbucks outlets with indicators such as the average service time in the system and the percentage of use of port facilities to the demand for loading and unloading of goods over a certain period of time. c. Simulation Goal The purpose of this research is to find out the queuing system and the level of service facilities at Starbuks outlets through a queuing model approach with simulation completion. Meanwhile, the purpose of this study can be described or described as follows: i. Simulating the level of facility performance at Starbucks outlets through a queuing model approach with simulation completion. These indicators are arrival rate, service level, waiting time or delay, idle or idle time, and system time. © IEOM Society International 1921 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 ii. Identify the need for additional facilities at Starbucks outlets. d. Limitations and Assumptions In the process of queuing at Starbucks outlets, the input to be served is orders from customers by operator1 (cashier-barista) from the ordering process to the finished order output. If there are 2 baristas and both of them are in the process of making/preparing food or drinks, then the cashier will be idle and the queue will be long. In the simulation process this time requires several variables, due to time constraints and situations we use secondary data so that we use the assumption that in a day per shift there are only 2 baristas. The service system under study is only focused on the queues that occur and their outputs. © IEOM Society International 1922 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 System Modeling a. Entity= An entity has a unique and distinct existence, although not necessarily in a physical form. Abstraction, for example, is usually considered as an entity. In system development, entities are used as models that describe internal communications and processing, such as distinguishing documents from order processing. i. Description of Interacting Entities In the line in store the interacting entities are Buyers Come - Buyers Queued - Buyer Service - Service by baristas - Order Complete. b. Activities/Relationship A relation is a rule that pairs the members of one set to another. We can find relations in mathematics lessons, such as relations from set A to set B. The relation in question is the installation or correspondence of members of set A to set B. i. Relationship Diagram Figure 2. Relationship Diagram Starbucks System © IEOM Society International 1923 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 c. Resources The resources in this outlet are divided into 2. The first source is the resource where this Starbucks outlet employs waiters, baristas, store managers. At the same time, the second source is the ingredients for making food or drinks taken from factories or agricultural fields i. Server/Service Unit Description The service unit at Starbucks outlets is a cashier who doubles as a barista, each customer has one waiter who serves from the beginning to the delivery of products to customers. d. Entity Flow Diagrams (EFD) Entity Flow Diagram is a diagram that connects between entities, this EFD is one type of structural diagram that is commonly used and utilized in the design of a database or business plan. COME 0 ORDER MAKE 0 0 COMPLETE 0 e. Activity Cycle Diagram (ACD) Customer Come Customer In Queue Making Order Serving Customer Idle Service © IEOM Society International 1924 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Data collection a. Data source i. Data Structure Interview Actual Data Live research Operational Data Store Data Warehouse Improvement Proposal Indirect research Figure 3. Data Structure at Starbucks ii. Operational Data Starbucks Outlet Drive Thru In Store Sales data in a day Sales data in a day Transaction data in a day Transaction data in a day Average queue time Average queue time Figure 4. Optional Data at Starbucks © IEOM Society International 1925 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 iii. Numerical Data Table 1. Time of Service and Service Provider Number of Customers 1 Service Provider 1 2 1 245 3 1 345 4 1 435 5 1 454 6 1 212 7 1 334 8 1 333 9 1 321 10 1 333 11 1 432 12 1 332 13 1 132 14 1 332 15 1 333 16 1 232 17 1 432 18 1 421 19 1 312 20 1 363 21 1 394 22 1 367 23 1 365 24 1 309 25 1 356 26 1 351 27 1 378 Service Time (Second) Average 234 336.5555556 b. Method of collecting data i. Interview Interviews were conducted directly with workers at Starbucks outlets, the questions we asked were as follows: • What is the average number of customers coming in one week? • What is the average amount of service time? © IEOM Society International 1926 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 • How do managers assess service performance? c. Data analysis Data analysis was carried out for making simulations in the form of models using Arena software. The first stage is the buyer arrives. After the buyer arrives, then proceed with queuing first if there is a queue, followed by ordering according to the desired menu to the cashier or waiter at the Starbucks outlet. After the service is complete and the payment has been made, the customer must wait because the waiter is processing the order, and if the order has been processed, the order is ready to be taken by the customer. © IEOM Society International 1927 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Input and Output Analysis a. Model Translation in ARENA i. Before Reconstruction Figure 5. Table When Buyers Come to Starbucks Buyers come to Starbucks outlets to carry out the process directly. Figure 6. Customer make the order Then the customer makes the order process at the cashier. © IEOM Society International 1928 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Figure 7. Ordering Process After the ordering process is done, the operator can continue with the ordering process. Figure 8. Order Complete If the purchase is complete and the order is complete, the order is complete. © IEOM Society International 1929 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 ii. After Reconstruction Figure 9. Buyers come to Starbucks outlet Buyers come to Starbucks outlets and queue according to the order. Figure 10. Buyer Place An Order After the buyer queues, the buyer can place an order and the barista can make an order according to the buyer's request. © IEOM Society International 1930 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Figure 11. Purchase Transaction Complete After the purchase and manufacture process is complete, the purchase transaction is complete. b. Verification Figure 12. No Error Verification © IEOM Society International 1931 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 c. Validation i. Determination of Performance Matrix Figure 13. Key Performance Indicators © IEOM Society International 1932 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Experimentation a. Actual System Before reconstructions are made, queuing is carried out and then continuing with the customer ordering the desired food or drink. After ordering, the operator (barista) makes an order that the customer has ordered. If it is finished, the customer can take the order; this causes the waiting time in the queue to increase because there is no operator in the ordering section if both operators are preparing orders. Before repairing, the conditions in the queue at Starbucks outlets can be quite long because the longest waiting time for ordering occurs in 13.3 minutes, with an average waiting time of 2.88 minutes. b. Proposed System After reconstructions are made, the process is carried out by queuing and then continuing to order. However, the operator in ordering and manufacturing is different, so there is no queue buildup in ordering. After improving the conditions that occur in the queue at Starbucks outlets, the number of customers during the replication time is 313 customers per day, and the longest waiting time is 8 minutes with an average of 0.93 minutes. c. Comparison of Actual and Proposed system Figure 14. Comparison of Actual and Proposed System © IEOM Society International 1933 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Conclusion Starbucks outlets have an inefficient service system which results in long queues so that they have a long idle time. And the Proposed System by queuing and then proceeding to order, but the operator in the order and in the manufacture is different. This results in reduced idle time and the Proposed System can be said to be proven to reduce idle time in the queue. © IEOM Society International 1934 Proceedings of the Second Asia Pacific International Conference on Industrial Engineering and Operations Management Surakarta, Indonesia, September 14-16, 2021 Bibliography Tupkar, Sagar Vinaykumar. 2016. Simulation Modeling Project Starbucks Coffee Centre. United States of America, Ohio. University of Cincinnati. Jianfei, Xia. 2014. Analysis of Starbucks Employees Operating Philosophy. Songjiang District, China. Shanghai University of Engineering. Lares, Bethany Linn. 2020. Long Lines: Looking at The Starbucks On Campus from A Business Process Management Perspective. United States of America, Phoenix. Arizona State University. Vardanyan, Artur P. Sahakyan, Vladimir G. 2019. The Queue Distribution in Multiprocessor Systems with the Waiting Time Restriction. Armenia. National Academy of Sciences of the Republic of Armenia. Tang, Yanli. Guo, Pengfei. Wang, Yulan. 2018. Equilibrium Queueing Strategies Of Two Types Of Customers In A Two-Server Queue. Hong Kong. The Hong Kong Polytechnic University. Haijian, Li. Na Chen, Lingqiao Qin. Limin, Jia. Jian, Rong. 2017. Queue Length Estimation At Signalized Intersections Based On Magnetic Sensors By Different Layout Strategies. Beijing, China. University of Wisconsin Maddison. Yiannis, Dimitrakopoulos. Antonis, Economou. Stefanos, Leonardos. 2020. Strategic Customer Behavior In A Queueing System With Alternating Information Structure. Singapore. Singapore University of Technology and Design. © IEOM Society International 1935
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