This report investigates how the Office of Border Patrol could employ pattern and trend analysis and systematic randomness to increase interdiction rates and mitigate smuggler adaptation. The analysis shows how approaches that combine the techniques yield higher interdiction rates than approaches using either technique alone, and it examines the circumstances in which combined approaches are competitive with perfect surveillance.
Using Pattern Analysis and Systematic Randomness to Allocate U.S. Border Security Resources
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- How can the Office of Border Patrol (OBP) best leverage pattern and trend analysis and systematic randomness to increase its interdiction rate along the U.S. border?
- Under what circumstances (e.g., size and features of the patrol zone, level of threat activity, number of patrols) would OBP stations benefit from using comparable approaches? Under what circumstances would such approaches differ?
- How should OBP start implementing approaches to pattern and trend analysis and systematic randomness?
The U.S. Department of Homeland Security is responsible for protecting U.S. borders against terrorist threats, criminal endeavors, illegal immigration, and contraband. Unfortunately, due to budgetary and other resource constraints, it cannot "see and be" everywhere at once. In response, the Office of Border Patrol (OBP) is investigating how pattern and trend analysis and systematic randomness can be used to position border security personnel and equipment in the places and at the times they will be most effective. A RAND study examined how these techniques affect interdiction rates, incorporating results from a RAND-developed agent-based simulation model of the interaction of border patrol agents and illegal smugglers. The model allowed an exploration of how interdiction rates differ across thousands of scenarios that vary by the number of patrols, the rate of illegal flow, the size of the border, and the approach OBP takes to using pattern and trend analysis and systematic randomness. The analysis shows how approaches that combine these two techniques yield higher interdiction rates than approaches using either technique alone, and it identifies circumstances in which combined approaches are competitive with perfect surveillance.
Resource Allocation Approaches That Combine Pattern and Trend Analysis and Systematic Randomness Yield Higher Interdiction Rates Than Approaches Using Either Strategy Alone
- Appropriate combinations of pattern and trend analysis and systematic randomness can, in some circumstances, yield interdiction rates that are competitive with "perfect surveillance" (perfect hindsight of historical crossings — both successful and unsuccessful).
- The benefits of combining pattern analysis and systematic randomness appear particularly strong when the number of available patrols is high relative to the rate of illegal flow but low relative to the size of the border — the circumstances confronted by many OBP stations.
Regardless of Strategy, Interdiction Rates Are Better Explained by Relative Measures Rather Than by Absolute Measures
- Relative measures, such as coverage and capacity, are more predictive of interdiction rates than absolute measures, such as the number of patrols, the size of the border, or the number of smugglers.
- OBP stations group in counterintuitive ways when compared using relative measures, such as coverage and capacity. For example, some northern and southern border stations appear more similar than when they are compared absolutely by the number of patrols, the number of apprehensions, or the length of the border.
- The Office of Border Patrol (OBP) should catalog all detections of illegal border crossings, even those that do not result in interdiction, and incorporate them into analyses of historical patterns and trends
- OBP should institute a plan to schedule patrols based on daily pattern and trend analysis and systematic randomness. This plan should include a phase of experimentation using randomized control trials.
- OBP should develop a management tool to compare its stations based on relative measures, such as coverage and capacity.
Table of Contents
Resource Allocation, Pattern Analysis, and Systematic Randomness
Simulation Model of OBP Patrol-Smuggler Interaction
Findings from the Analysis of the Simulation Model
Comparison of Border Patrol Stations
Experimental Design for Evaluating the Contributions of Pattern Analysis and Systematic Randomness
Conclusions and Recommendations