Delayed Deliveries

Solution & Explanation

1. Understanding the Context:

• The task is to evaluate the extent of delay in food deliveries that arrive late. This involves analyzing the delivery time data to understand how late the deliveries are compared to the expected delivery time. The data is right-skewed, indicating that while most deliveries are not significantly late, a few are extremely delayed.

2. Choosing the Statistical Measure:

• Mean vs. Median:
  • Mean: Provides the average delay time, including all data points. It is sensitive to outliers, which can skew the results if there are extreme delays.
  • Median: Represents the middle value of the dataset, offering a measure that is not affected by outliers, providing a better sense of the typical delivery delay.
• Recommendation:
  • Given the right-skewed nature of the data, the median is more appropriate for assessing typical delays, as it is less affected by extreme values. However, if the objective is to understand the impact of severe delays, the mean can also be useful to highlight the extent of those outliers.

3. Insights from the Delayed Deliveries:

• Right-Skewed Distribution:
  • Indicates that while most deliveries are close to the expected time, a small number of deliveries are significantly late.
  • Suggests potential operational issues or external factors affecting a minority of deliveries, such as traffic jams, restaurant delays, or driver availability.
• Operational Implications:
  • Median: Provides insights into the typical customer experience, helping to identify systemic issues affecting the majority of deliveries.
  • Mean: Highlights the impact of extreme delays, prompting further investigation into specific cases that deviate significantly from the norm.

4. Additional Considerations:

• Segment Analysis:
  • Consider segmenting the data by time of day, day of the week, or location to identify patterns and potential areas for improvement.
• Outlier Analysis:
  • Investigate the causes of extreme delays to prevent future occurrences, such as operational inefficiencies or unforeseen events.
• Customer Feedback:
  • Analyze customer ratings and feedback to correlate delay times with customer satisfaction, providing a more comprehensive understanding of the impact of delays.

5. Conclusion:

• Prioritizing the median provides a reliable measure of typical delays, while the mean can be used to understand the extent of extreme delays. Combining both measures with additional analysis can offer a holistic view of delivery performance and customer satisfaction, guiding improvements in the delivery process.