DATA COLLECTION, INFORMATION SHARING &

INTER-AGENCY COOPERATION:EXPERIENCES IN NEPAL

ALEXANDRA ROBINSONUNIVERSITY OF EDINBURGH

TINY HANDS INTERNATIONAL

NEPAL: THE CONTEXT• EXTREME POVERTY• UNEMPLOYMENT• CASTE, GENDER • POLITICAL INSTABILITY • RESOURCE LIMITATIONS (HUMAN, TECHNOLOGICAL, INFORMATION)• LEGAL AMBIGUITY• OPEN BORDER

22

BORDER MONITORING: THE PROBLEM• THE PROBLEM : THI had access to critical information, but lacked tools

and capacity to procure it, and the partnerships and skills to utilize it

• Critical need for victim advocates in order > prosecutions

• Information versus intelligence

• GOAL: to collect data to produce intelligence to:

1) Mobilize investigations and increase prosecutions

2) Map crime networks and help LE break them down

3) Comprehensive threat, trend analysis

4) Track changing strategies > allocate resources

• Maximize LIMITED RESOURCES to achieve MOST IMPACT

33

BORDER MONITORING: CHALLENGES• TOOLS: the wrong questions,

missed opportunities • RESOURCE LIMITATIONS: time,

technology, infrastructure, skills, funds, staff

• LACK OF WILL• LACK OF TRUST: across sectors;

between organizations; information security**

• DUPLICATION & DISSENTION: inter-organizational

44

BORDER MONITORING: SOLUTIONS

• NEW TOOLS: Expanded VIF

• HUMAN RESOURCES: trainings, support staff, specialization, hiring, OVERSIGHT

• TECH RESOURCES• PARTNERSHIPS; MOUs,

protocols

55

THE OUTCOME

• Wealth of data and actionable intelligence

• Mobilization of investigations

• Increased prosecutions

• Effective collaboration; reduction of duplication > better resource management

• “Intelligence-led interventions”

• Resource maximization

• Effective victim services

• Trend Analysis

6 6

RISKS, LIMITATIONS & CONTINUAL CHALLENGES

• HUMAN RESOURCE limitations > OVERSIGHT, monitoring, evaluation: time intensive

• Enforcing policies and procedures

• Staff security

• Political and LE turnover

7 7

TRANSFERABLE? • Universal challenges: limited resources - & we all want

to maximize them

• Between organizations (aggregation analysis, resource allocation & streamlining)

• Between victim services & LE (missed opportunities)

• Information > COOPERATION > Intelligence

8 8

DATA SHARINGTYPES OF INTELLIGENCE (1) Cursory (2) Close Associates (3) Transnational networks • Privacy protocols & MOUs• System integration = difficult,

standardized template = doable

• General reports

9 9

THE IMPACT• Uplift localized anti-trafficking ops, increase

prosecutions• Cross-border/transnational operations• Organized crime (break down networks)• Cross-thematic crime (drugs, money laundering,

etc.) • Border security & response • Improve UK trafficking profile• Social impact: the victim

10 10

QUESTIONS? Email: alexandra.l.robinson@gmail.com

11 11