Which of the following scenarios could benefit from spatial analysis?

• A. Counting employees who missed more than five days of work in the last month from a database of employee timesheets.
• B. Automating the searching and display of prices for flights on a particular route.
• C. Measuring the average response time in a customer support case queue system.
• D. Identify the closest retail location to a customer given their location.

Answer: (D)

Spatial analysis focuses on geographic relationships between locations, such as distance, proximity, and spatial patterns. Identifying the closest retail location to a customer given their location directly uses coordinates for the customer and the stores, and relies on calculating distances or performing a nearest-neighbor or network-distance query to find which store is nearest. This is a quintessential spatial operation, because it depends on the physical arrangement of features in space.

The other scenarios don't hinge on geographic relationships. Counting employees who missed days is a data aggregation task on a table of timesheets, with no need for location context. Automating flight price searches on a route involves attribute data and routing logic, but not proximity between physical features. Measuring average response time in a queue is a temporal performance metric, not a geographic analysis.