Sunday, February 22, 2015

Data drivers for Location-Based Analytics

Location-based analytics are important for a number of business issues, such as the definition of sales and service areas, store/warehouse/service area placements, dynamic capacity scheduling and determining quickest delivery routes.

All of these requires a "Drive Time Area (DTA)" model which calculates distance, time and speed on road segments in order to move or reach different locations. In most instances traditional road speed limits are used to calculate this - but by using a real speed profile for different days and time slots provides a significant improvement in answering the above questions. The following picture shows how a road network can be classified into static distance sub-networks to provide an indication of the distance from the center point.

But this still doesn't provide an accurate understanding of the impact of a 10 minute delivery time on a Monday morning to that of a Friday afternoon during weekend traffic.

The following picture shows within a 50 square kilometer radius a 2 minute DTA, 5 minute DTA and 10 minute DTA for the network. It takes into account actual speeds on  different road segments for a particular time period - allowing the business owner to understand which areas can be serviced within which time slot on a daily basis.

Probes such as smartphones, vehicle telematics and navigation devices provide billions of data points which constitute real speed profiles per road segment. Using this as a data driver provides a much clearer understanding and insight into location-based risk and performance than generalized assumptions.

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