Question.910 - Review “Bank USA: Forecasting Help Desk Demand by Day” from the end of Chapter 9 in the textbook. Then, please use the information to respond to the following: From the case study, determine the challenges faced by the Help Desk at Bank USA and suggest strategies to mitigate them. Using the data on call volume in the case, select a forecasting model to forecast the short-term demand. Justify why this model was selected over other forecasting models. Support your position. Be sure to respond to at least one of your classmates' posts.
Answer Below:
The challenges faced by the Help Desk at Bank USA may include the following: High call volume: The Help Desk may receive a large number of calls daily, leading to long wait times for customers and increased stress for employees. Seasonal fluctuations: The demand for the Help Desk's services may vary greatly depending on the time of year, such as during tax season or holiday shopping periods. Lack of resources: The Help Desk may have a limited number of staff available to handle customer calls, leading to longer wait times and decreased customer satisfaction. The following strategies may be employed to mitigate these challenges: Increase staffing levels: Hiring additional staff during peak demand periods can help reduce wait times and improve customer satisfaction. Implement call prioritization: Implementing a system that prioritizes customer calls based on urgency can help ensure that the most important issues are addressed first. Utilize self-service options: Offering customers the ability to resolve their issues through self-service options, such as a website or mobile app, can help reduce the number of calls to the Help Desk. Provide staff training: Providing staff with training on how to handle high call volumes, as well as how to handle customer issues efficiently, can help improve customer satisfaction and reduce stress for employees. Utilize technology: Implementing technology such as artificial intelligence, chatbots, or call routing can help improve the efficiency of the Help Desk and reduce wait times for customers. The appropriate forecasting model to use for short-term demand for the Help Desk at Bank USA would likely be a time series model, specifically an ARIMA (Auto Regressive Integrated Moving Average) model. This model would be appropriate because call volume is likely to follow a predictable pattern over time, with past call volume data being a good indicator of future demand. ARIMA models are a popular choice for time series data and can effectively capture trends and seasonality in the data. They also have the ability to handle data that may not be stationary, such as data that has a trend or a strong seasonal component, which is common in demand forecasting. Another model that could be considered is Exponential Smoothing, but ARIMA is a better choice because it can handle a wider range of time series data and provides more control over the modeling process.More Articles From Operation Management
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