Assignment task:
Instructions:
Select one of the two scenarios provided below: Healthcare Operations or Business Logistics. In this summative assignment, you will analyze time-series data in Excel, apply forecasting models, assess model accuracy, and make data-informed recommendations for operational planning. Your work should demonstrate your understanding of forecasting principles and your ability to communicate your analysis clearly and professionally. Need Assignment Help?
Scenario 1: Healthcare - Emergency Department Staffing
Context:
You are a healthcare operations analyst at RiverView Medical Center. Hospital leadership is reviewing weekend staffing patterns for the Emergency Department (ED). You have been provided with historical Saturday patient visit data and are tasked with forecasting visit volumes for the next four Saturdays. Your analysis will help determine appropriate staffing levels and improve patient care outcomes.
Data Provided (past 12 Saturdays - number of patient arrivals):
92, 88, 95, 100, 104, 98, 91, 87, 90, 102, 106, 99
Scenario 2: Business Operations - Logistics Delivery Forecasting
Context:
You are a logistics planner for a national supply chain firm. Warehouse managers have reported inconsistent Monday delivery volumes, which has led to staffing inefficiencies and delayed outbound shipping. You have been given delivery volume data for the past 12 Mondays and are tasked with forecasting the number of deliveries expected in the next four weeks. Your forecast will inform labor scheduling and logistics resource planning.
Data Provided (past 12 Mondays - number of delivery orders):
145, 148, 152, 150, 157, 160, 162, 158, 165, 170, 172, 175
Tasks:
1. Analyze Data Patterns (CLO5):
- Enter the weekly data into Excel and create a time-series plot.
- Describe any observed trends, cycles, or irregularities in the data.
- Explain whether the data appears appropriate for short-term forecasting and justify your reasoning.
2. Apply Forecasting Models (CLO5):
- Apply two forecasting methods (e.g., 3-period moving average, exponential smoothing, linear trend line) to the historical data.
- Generate forecasts for the next four periods using both methods.
- Include Excel calculations or screenshots showing your models and forecast outputs.
3. Evaluate Forecast Accuracy (CLO5):
- Choose an accuracy metric such as Mean Absolute Deviation (MAD) or Mean Squared Error (MSE).
- Compare the two forecasting models using your selected accuracy metric.
- Identify which model provides the most reliable forecast and explain why.
4. Recommend and Interpret (CLO2, CLO5):
- Based on your analysis, recommend which forecast should be used for operational planning.
- Clearly explain the practical implications of your forecast in the selected scenario (e.g., adjusting staff schedules, reallocating logistics resources).
- Acknowledge any limitations in the data or model and discuss how decision-makers should account for uncertainty.
Submission Requirements:
- Your written report should be 500-750 words in length, submitted as a Word document.
- Include your Excel file with the time-series data, forecasting models, and accuracy calculations.
- Use clear, concise, and professional language appropriate for executive or operational decision-makers.
- Clearly label each section of your submission in accordance with the four tasks above.