The Failing War on Drugs Network Model of Drug Flow from Mexico to the U.S.

1. The Failing War on DrugsNetwork Model of Drug Flow from Mexico to the U.S. LCDR Ben Cipperley CPT Kevin Larrabee 11 JUN 2012

2. Agenda • Problem Statement • Drug War Background • Modeling • Producer/ Consumer Model • Demand Flow Model • Conclusions • Questions

3. Problem Statement • 65% of narcotics in the U.S. flow from Mexico • $45 billion annually in producer/distributor profits • 99% of all flow from Mexico is overland (U.S. DOJ) • Understand the overland flow of drugs network from Mexico into the U.S. • How do narcotics flow across the border? • What motivates flow? • How to best attack the network • Attack Demand • Attack Distribution • Attack Supply

4. War on Drugs • U.S. War on Drugs • Roots formed during Prohibition (1920’s) • DEA created (1973) • CIA and military involvement (1982) • Demand topped $60 billion in 2012 • $15 billion on drug enforcement in 2010 • ~$500 per second • Interdiction budget $3.9 billion

5. Front Lines • U.S. Customs and Border Patrol • 21,444 Agents • 18,506 on the SW border (86.3%) • Apprehensions • 96% of all CBP apprehensions occur on the southwest US Border • Military Planning Model • Info and Intel driven response

6. A Typical Border Crossing • Different capacities by location • San Ysidro, CA = 24 lanes • Laredo, TX = 20 lanes • Naco, AZ = 2 lanes • 2.7 million loaded container trucks entered the U.S. through the SW border in 2009 • An estimated 30% of all narcotics shipments are seized at the border

7. De La Vega Background • Don Diego de la Vega is the new drug lord of the Zetas Cartel and is focused on pushing cocaine into the U.S. • Zetas cartel struck new deal to combine resources with Sinaloa Federation and the Cartel PacificoSur • Cocaine Manufacturing facilities emerge in 8 Mexican cities

8. Real Life ScenarioThe Drug Lord- Don Diego De La Vega

9. Objectives • Understand how to best attack the network by measuring the amount of profit gained • Red Team (De La Vega) • Maximize profit through minimum cost flow • Maximize narcotics flow into the U.S. • Blue Team (U.S. Border Patrol) • Maximize the cost of production/distribution • Reduce the amount of narcotics flow • Improve interdiction capability

10. Model

11. Model

12. Model with Network Overlay

13. END Ciudad Victoria START

14. Modeling the Network • Assumptions • Omniscient and omnipotent Drug Lord • Shipments occur overland using legal U.S. border crossings • Both the U.S. and de la Vega act optimally • Flow starts from Mexico (no domestic production) • Simultaneous attacks • Limitations • Only modeled legal border crossings • No political effects considered • Blue Force interdiction cost not calculated

15. Model Evolution • Shortest Path • How does cocaine flow across the border? • Producer/Consumer • Basic supply/demand model • Interdiction lowers capacity to zero • Not accurate for how drugs move (NOT Wal-mart!) • Demand Flow • Profit motivates flow • Every crossing evaluated for “efficiency” • Interdiction lowers efficiency to zero • Demand vs. Supply Interdiction • Reduction in efficiency through training

16. Producer/ Consumer

17. Producer/Consumer • Supply of 9,500 kilos produced across nine facilities in Mexico • Demand of 9,500 kilos in the U.S. • Costs to use a road are based upon price of fuel per gallon and distance to destination • Costs to move flow through a border crossing are bribe amounts as a function of number of arrests • Interdictions reduce the flow capacity to zero by making the cost equal infinity

18. Producer/ Consumer Model • Supply is a function of projected production facilities • Demand is a function of population percentage of the Southwest

19. Additional Parameters

20. Operator Resilience Curves Bribes Constant Bribes vary by location At three interdictions, cannot move through NM At ten, lost of $2 Million in profits • Same results as shortest path • At ten interdictions, only decrease profit by $6000 Cannot use NM Cannot use San Diego

21. Bribes Vary by Location cc

22. Compound Strategy • Find a way to increase production cost and increase distribution cost • Seize product • Force higher labor costs • Force him to develop innovative hiding and storage • Decrease of $20 Million Dollars in Profit

23. Demand Flow Model

24. Demand Flow Model • Profit motivates flow • Realistic price-driven distribution • Delivery limited by capacity • Efficiency • Demand profit per kilo • $19,000 (Austin)-$29,000(Dallas) • Production cost per kilo • $10,000(Ciudad Obregon) - $15,500 (Saltillo) • De la Vega limits flow through a border to 1000 kilos • Interdictions reduce flow on an arc to zero

25. END MIDDLE Ciudad Victoria START

26. Demand vs. Supply Interdiction Stop Production in Saltillo Essentially no effect! Reduce Production in Monterrey MAXIMUM EFFECTS!

27. Border Interdictions

28. Supply Interdiction

29. What We Can Do? IMPROVE CAPABILITY TO REDUCE EFFICIENCY! • Account for randomness in the model • 20 model runs to find the expected value • Influence De La Vega to forgo 2800 kilos in production capacity • Reduce amount delivered by 2700 kilos • Reduce profits by more than $15,000,000 with no additional resources applied

30. Conclusion

31. Conclusions • Understand the network • How do narcotics flow across the border? • Through every possible avenue by means of lowest cost • What motivates flow? • Profit! • How to best attack the network • Attack Demand • Education, deterrence • Attack Distribution • Best non-kinetic solution • Training (any improvement shows effect) • Improve border interdiction capability • Attack Supply • Best kinetic solution • Cut the head off the snake

32. Further Analysis • Consider Blue Force costs • Incorporate open desert crossing • Consider political/economic consequences

33. QUESTIONS?