Modeling e-Livestock Indonesia.

Area of Science:

• Agricultural Economics
• Information Systems
• Public Policy

Background:

• Indonesia's increasing beef demand outstrips national supply, leading to significant imports.
• Current lack of robust identification, registration, and traceability systems hinders accurate livestock data and effective policymaking.
• Inaccurate data compromises the livestock sector's development and the nation's goal of beef self-sufficiency.

Purpose of the Study:

• To develop e-Livestock business process models for Indonesia using established definitions and success factors.
• To generate actionable recommendations for implementing a comprehensive e-Livestock system.
• To provide a validated framework for improving beef traceability and data accuracy in Indonesia's livestock sector.

Main Methods:

• Soft Systems Methodology (SSM) for understanding complex systems.
• Hermeneutics and Focus Group Discussions (FGD) for in-depth analysis and consensus building.
• Validation of developed business process models and complexity assessment.

Main Results:

• Creation of validated business process models for e-Livestock, demonstrating ease of understanding.
• Generation of recommendations covering functional requirements, identification tools, location numbering, ownership documentation, socialization, institutional aspects, regulations, and infrastructure.
• Quantification of the complexity of the business process models.

Conclusions:

• The developed e-Livestock business process models and recommendations offer a practical guide for government implementation.
• Successful implementation of e-Livestock can significantly improve data accuracy, reduce import reliance, and support beef self-sufficiency.
• The research provides a foundational framework for modernizing Indonesia's livestock management through digital solutions.