This assignment is intended to help you build a supply chain plan/diagram for a new business by analyzing factors that affect sourcing, logistics, metrics, suppliers, and risk.
Create a diagram of the supply chain plan using one of the following tools:
Excel
PowerPoint
Visio
PictoGram
Other faculty-approved platform
Write an 875-word analysis of the supply chain. Include the following:
Value chain and flow of structure
Inputs
Outputs, including customer service structure
Inventory points and forecasting
Sourcing activities
Risks
Locations
Logistics
Cite references to support your assignment.
Format your citations according to APA guidelines.
Company’s is starbucks
Requirements: 875 words
1Service System ApplicationsAllison FranklinUniversity of PhoenixOPS/571Tim Tietjen08/21/2023
2Service System ApplicationsIn the realm of service industries, the effectiveness of different service systems can influence customer experiences and the institution in several ways. In this case, our primary focus will be Starbucks; this is one of the most prominent global coffeehouse chains and is widely recognized for its diverse service offerings. By analyzing how Starbucks uses its counter service, drive-thru service, and online order service, we can gain a deeper understanding of the benefits and drawbacks of each system, in addition to the potential for making comparisons across industries. This analysis not only gives light on the customer service strategy that Starbucks takes, but it also lays the framework for the upcoming exploration of the dynamics of Starbucks’ supply chain, which will be covered in the subsequent assignment.Drive-Thru and Online Order ServiceOne common thing with this franchise is its adoption of the drive-thru service system in several locations. This service is mainly meant for customers looking for a quick and convenient way to order and receive their beverages without leaving the comfort of their vehicles. The strengths of this system are based on its efficiency and speed, making it attractive to customers who are in a hurry (Bulatovic et al., 2021). However, this system is flawed because it might lack the personal interaction and customization option counter service provides. Also, maintaining accuracy during high-traffic periods might be an issue. Starbucks has embraced digitization by offering online ordering services to its customers through its mobile app. Most clients are allowed to order and pay through the app and then pick up what they had ordered at designated locations within the store. This service is essential to clients who prefer minimal physical contact and waiting times. The ease of use and the capacity to coordinate the ordering process more
3efficiently are two of this system’s most vital points. Nevertheless, difficulties may be associated with technical problems, order correctness, and ensuring that beverages are still freshly produced when customers arrive.Counter ServiceMost of their clients can physically visit the stores at any given time and approach the counter and be able to place their order with the barista and then wait for it to be prepared. This allows for personalized interactions between baristas and customers (Lee & Lee, 2020). This provides an opportunity for building customer service. This system’s strengths include the capacity to offer customization, make recommendations, and address client preferences in real time. Other strengths include making recommendations (Bulatovic et al., 2021). However, a possible flaw could be more excellent wait times during peak hours, resulting in dissatisfied customers. This could be a source of potential weakness.ConclusionRegarding industry comparisons, Starbucks often faces competition from national chains and local coffee shops. Some competitors might have a more focused approach to specific service systems, which makes them excel areas. An excellent example of this is a small local coffee shop might excel in customer relationships and personalization due to its small customer base (Ren et al., 2023). On the other hand, a larger chain might emphasize efficiency and speed in its drive-thru service. In conclusion, Starbucks has implemented multiple service systems to cater to customer needs and preferences. Each system has weaknesses and strengths, and the company’s success often lies in effectively managing these aspects to deliver positive customer service.
4ReferencesBulatovic, I., Alnuaimi, M., Alshehhi, M., & Alzaabi, M. (2021). MEASUREMENT OF SERVICE QUALITY IN HOSPITALITY IN TIMES OF COVID-19 PANDEMIC–CASE: STARBUCKS UAE. Economic and Social Development: Book of Proceedings, pp. 97–106. Lee, S. M., & Lee, D. (2020). “Untact”: a new customer service strategy in the digital age. Service Business, 14(1), 1-22. Ren, Y., Choe, Y., & Song, H. (2023). Antecedents and consequences of brand equity: Evidence from Starbucks coffee brand. International Journal of Hospitality Management, 108, 103351.
1Operational Decision-Making using Forecasting (Starbucks)Allison FranklinUniversity of PhoenixOPS/571Tim Tietjen09/04/2023
2Operational Decision-Making using Forecasting (Starbucks)Many coffeehouse chains like Starbucks offer various methods of service to their customers such as Drive-Thru, Online Order, and Dine-in. Each of the methods of service tends to have its own mix of advantages and disadvantages. The key metrics that connect the different service types are the Sales Quantity and the customer service time. Using the monthly data for the Total Sales Quantity and the average Customer service time for the product of ‘Caffè mocha’ from the past eight months (Jan-2023 to August-2023) from a local Starbucks outlet, we will be using the Simple Exponential Smoothing method (alpha =0.2) to forecast for the upcoming month (Sep-2023). This forecasting method is utilized here as it produces a smooth forecast even if any trends or data irregularities are present (Gardner, 2006). Using the results of the forecast, we can make decisions on which customer service method would be profitable for Starbucks in the long run.Forecast of Total Quantity Sold using Exponential SmoothingThe monthly data for the Total Quantity Sold for the ‘Caffè mocha’ was utilized for performing the forecast of the Total Quantity Sold of the ‘Caffè mocha’ product for the month of September 2023. Observation NoMonth/2023Total Quantity SoldSimple Exponential Smoothing forecast (Total Quantity Sold)Absolute ErrorSquared ErrorAbsolute % Error1January23912391.000.000.000.00%2February23542391.0037.001369.001.57%3March23982383.6014.40207.360.60%4April23002386.4886.487478.793.76%5May23302369.1839.181535.391.68%6June21042361.35257.3566227.5812.23%7July23962309.8886.127417.043.59%8August26152327.10287.9082885.1411.01%September 2384.68
3The simple exponential smoothing method provided a forecast of 2384.68 (≈ 2385 quantities sold) for the Total Quantity Sold for September 2023 and the forecast errors were evaluated using metrics such as MAD, MSE, and MAPE. The MAD, MSE, and Mean Absolute Percentage error obtained using the simple exponential smoothing forecast method were 101.05, 20890.04, and 4.31 %. As the MAPE is less than 5 %, we can conclude that the forecast method is significant and does not provide much deviation from the actual quantity sold.Mean Absolute Deviation (MAD) =101.05Mean Squared Error (MSE) =20890.04Mean Absolute percentage error (MAPE) =4.31%The monthly data for the Average service time for the ‘Caffè mocha’ product was utilized for performing the forecast of the Average service time of the ‘Caffè mocha’ product for the month of September 2023. The simple exponential smoothing method provided a forecast of 3.25 minutes for the average service time expected for ‘Caffè mocha’ in September 2023. The MAD, MSE, and Mean Absolute Percentage error obtained using the simple exponential smoothing forecast method were 0.09, 0.03, and 2.55 %. As the MAPE is less than 5 %, we can conclude that the forecast method is significant and does not provide much deviation from the actual average service time for ‘Caffè mocha’ at Starbucks.Observation NoMonth/2023Average Service Time (minutes)Simple Exponential Smoothing forecast (Average Service Time)Absolute ErrorSquared ErrorAbsolute % Error1January3.143.140.000.000.00%2February3.113.140.030.001.09%3March3.133.140.000.000.01%4April3.113.140.030.000.91%5May3.133.130.000.000.04%6June3.123.130.010.000.40%
47July3.353.130.220.056.54%8August3.583.170.410.1711.45%September 3.25Mean Absolute Deviation (MAD) =0.09Mean Squared Error (MSE) =0.03Mean Absolute percentage error (MAPE) =2.55%ConclusionThe forecasting method (exponential smoothing) provided a forecast of 2385 quantities sold and 3.25 minutes of average service time for ‘Caffè mocha’ at Starbucks. As the expected error of the forecast is low and the forecast demand is found to be moderate, it is recommended that Starbucks choose the Dine-in option for customer service as it would reduce the uncertainties expected in other methods of service (Chua et al., 2020).
5ReferencesGardner, E. S. (2006). Exponential smoothing: The state of the art—Part II. International Journal of Forecasting, 22(4), 637–666. https://doi.org/10.1016/j.ijforecast.2006.03.005Chua, B., Karim, S. A., Lee, S., & Han, H. (2020). Customer Restaurant Choice: An Empirical Analysis of Restaurant Types and Eating-Out Occasions. International Journal of Environmental Research and Public Health, 17(17), 6276. https://doi.org/10.3390/ijerph17176276