Jenn Kostichis the new department director for emergency services at Northwest General Hospital. One of her responsibilities is to ensure proper staffing in the emergency room (ER) by scheduling nurses to appropriate shifts. This has historically been a problem for the ER. The former director did not base nurse schedules on forecasts, but used the same fixed schedule week after week.Jenn had recently received her degree in operations management. She knew that schedules needed to be based on forecasts of demand. She needed to start by analyzing historical data in order to determine the best forecasting method to use. Jenn’s assistant provided her with information on patient arrivals in the ER by hour and day of the week for the previous month, October. October was considered a typical month for the ER, and Jenn thought it was a good starting point. Jenn reviewed the information (shown in the chart) that she had requested and wondered where to begin.
Questions1. What is your opinion of the level at which the data are being collected? What are some of the advantages of collecting data at this level?
2. Aggregate the original data for October as you see appropriate (e.g., sum up by day of week, time of day, week of the month, etc.). This will give you a new data set to work with. Analyze your data for patterns. Can you find any?
3. Forecast the hourly patient arrivals for November. You must clearly explain and justify your forecasting model.
4. Calculate the forecast accuracy measures FE, MAD, CE, TS, if you were to use your model in question 3to forecast the patient arrivals in October. What can you deduce from these measures?
