Feral Systems

Information Systems for Complex Problems

Feral Systems Wolf

When formal IT systems fail to meet real-world needs, people create their own solutions. We leverage Nudge Theory and Generative AI to help organizations understand, optimize, and guide these naturally emerging systems toward better outcomes.

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Understanding Emergent Systems

Feral information systems emerge when formal IT fails. We help you work with them, not against them.

What Are Feral Information Systems?

Feral information systems are unofficial solutions developed by individuals and groups to support their day-to-day work when formal IT systems fall short. Like wolves adapting to their environment, these systems emerge naturally to fill gaps in organizational technology.

Also known as "Shadow IT" or "Workaround Systems"
These systems circumvent existing IT infrastructure or work around key system architecture to solve real problems.

Our Philosophy

We don't see feral systems as problems to eliminateβ€”we see them as valuable insights into what your organization actually needs. Using behavioral science and AI, we help you understand, integrate, and optimize these naturally occurring solutions.

Adaptive Information Systems

Our Methodology

Combining behavioral science with artificial intelligence to solve complex organizational challenges.

🧠 Nudge Theory

We apply behavioral economics principles to understand why people create workaround systems and how to guide them toward better choices without restricting their freedom.

Choice Architecture: We design systems and processes that make the right choices easier and more intuitive, reducing the need for feral solutions.

By understanding cognitive biases, social influences, and decision-making patterns, we help organizations create environments where formal systems naturally align with user behavior.

πŸ€– Generative AI

We harness the power of AI to analyze complex system interactions, predict emergent behaviors, and generate innovative solutions for organizational challenges.

AI-Powered Analysis: Machine learning models help us identify patterns in feral system emergence and predict where new workarounds might develop.

Our AI tools can simulate different organizational scenarios, generate policy recommendations, and create personalized nudges that guide users toward optimal system usage.

Choice Architecture for Feral Systems

Designing decision environments that naturally guide organizations toward better inclusion and optimization of emergent systems.

The Challenge: Organizations typically respond to feral information systems with elimination rather than integration. We design choice architectures that make inclusion the natural, preferred option.

Strategic Approaches

πŸ”„ Default Integration Pathways

Instead of forcing users to abandon their feral systems, we create default options that naturally incorporate them:

  • API Bridges: Make connecting feral spreadsheets/databases easier than recreating data
  • Import Wizards: Default templates that preserve feral system logic while adding governance
  • Gradual Migration: Staged integration where feral systems become "training wheels" for formal adoption

πŸ‘₯ Social Proof and Visibility

Leverage the social influence aspects of nudge theory:

  • Success Stories Dashboard: Highlight teams that successfully integrated their feral solutions
  • Peer Recognition: Make feral system creators visible as "innovation pioneers" rather than "rule breakers"
  • Community Sharing: Platforms where teams can share and improve each other's feral solutions

⚑ Effort Reduction Architecture

Make inclusion easier than exclusion:

  • One-Click Documentation: Auto-generate compliance documentation for existing feral systems
  • Reverse Engineering Tools: AI that understands feral system logic and suggests formal equivalents
  • Grandfathering Policies: Automatic approval pathways for feral systems that meet basic criteria

🎯 Reframing the Choice Environment

Change how decisions about feral systems are presented:

❌ "Shut down unauthorized system" vs "Keep breaking rules" βœ… "Enhance your innovation" vs "Start from scratch"
❌ "Compliance violation" βœ… "Optimization opportunity"

⏰ Timing and Context Nudges

Strategic when and where choices are presented:

  • Integration Prompts: During system upgrades, offer feral system integration as default option
  • Budget Cycle Alignment: Present feral system formalization during planning periods
  • Crisis Response: When formal systems fail, immediately offer feral system integration rather than patches

🎨 Personalized Choice Architecture

Based on individual differences and user types:

  • Role-Based Defaults: Different integration pathways for analysts, managers, and IT staff
  • Risk Tolerance Matching: Conservative users get gradual integration; innovators get rapid formalization
  • Skill-Based Onboarding: Technical users see API options first; business users see GUI options

Implementation Framework

Phase 1: Discovery Architecture

Make finding feral systems rewarding rather than punitive

  • Create "amnesty periods" for voluntary disclosure
  • Reward system discovery with recognition and resources
  • Position discovery as innovation identification

Phase 2: Evaluation Architecture

Default assumption: feral systems solve real problems

  • Burden of proof on formal systems to demonstrate superiority
  • Evaluation criteria that value innovation and user satisfaction
  • Integration-first assessment protocols

Phase 3: Integration Architecture

Make integration the path of least resistance

  • Provide more support for integration than for elimination
  • Automated integration tools and workflows
  • Success metrics that reward integration outcomes
Transformation Goal: Convert feral information systems from "problems to be solved" into "innovations to be scaled" through careful design of the organizational decision environment.

Research Collaboration

Advancing the state of the art in emergent information systems through collaborative research and real-world application.

πŸ” Behavioral System Research

Collaborative research into user behavior patterns and system interactions using AI-powered tools. We partner with organizations to study how feral systems emerge and contribute findings to the academic community.

🎯 Nudge Theory Applications

Joint exploration of choice architectures and behavioral interventions in information systems. We work together to develop and test new approaches that advance both theory and practice.

πŸ€– AI-Powered Innovation

Collaborative development of generative AI solutions for system optimization. We partner to create novel approaches that push the boundaries of what's possible in emergent system management.

πŸ”„ Integration Methodologies

Research partnerships focused on developing new methodologies for integrating valuable feral systems into formal IT architecture using behavioral insights and AI-driven analysis.

πŸ“Š Predictive Modeling Research

Collaborative development of AI models that predict emergent system formation. We work together to advance the science of proactive intervention and system improvement.

πŸŽ“ Knowledge Sharing

Joint research into behavioral change programs and knowledge transfer. We collaborate to develop and share new insights that benefit the entire field of information systems.

Speaking & Presentations

Sharing insights on behavioral science applications in security, emergent information systems, and AI-driven organizational transformation at leading industry conferences.

About the Speaker

Logan Browne is Senior Manager for Amazon Global Media and Entertainment Security, specializing in the intersection of behavioral science, information systems, and organizational transformation. With over 20 years of experience in cybersecurity, technical leadership, and protecting critical systems from sophisticated adversaries, he brings a unique perspective to understanding how emergent systems develop in complex organizations.

His work combines expertise in cyber security management, threat management fusion, security operations, and technical team leadership with practical experience building and scaling security engineering teams at Amazon, DXC Technology, and Hewlett Packard Enterprise. He holds an MBA from UC Davis with a concentration in Management of Organizations, a Bachelor's in Computer Science from Hiram College (Cum Laude with Departmental Honors), and is a Certified Information Systems Security Professional (CISSP).

Through research and consulting, Logan helps organizations understand why informal systems emerge and how to leverage behavioral science and AI to optimize rather than eliminate these valuable adaptations. His extensive background includes building multiple "two pizza teams" at Amazon, leading global incident response during major security events, and developing innovative security solutions that have protected intellectual property and systems for some of the world's largest technology companies.

🎀 AWS re:Inforce 2025

Transforming Security Compliance with Nudge Theory

Traditional security approaches often create friction between security teams and builders, increasing costs while reducing innovation. This presentation explores how nudge theory - a Nobel Prize-winning behavioral science framework - can transform security compliance at scale.

"Learn how subtle changes in choice architecture, default settings, and communication methods dramatically improve security outcomes while reducing engineering burden."

Through real-world case studies, discover how organizations achieve higher compliance rates and faster remediation without additional headcount, while fostering a positive security culture.

🎯 Industry Expertise & Speaking Topics

Security in Media & Entertainment: Protecting sensitive content, managing 3rd party supply chains, and securing customer data across global streaming platforms and digital content delivery systems.

Behavioral Security at Scale: Applying nudge theory and behavioral science to improve security compliance, reduce friction for developers, and build positive security cultures in large organizations.

Building High-Performance Security Teams: Creating and scaling "two pizza teams," managing global incident response, and developing technical leadership in complex enterprise environments.

Drawing from 20+ years protecting critical systems at Amazon, HPE, and DXC Technology, including experience with state-sponsored threats and major security incidents.

🎯 Speaking Opportunities

Available for keynotes, panels, and workshops on emergent information systems, behavioral science applications, and the future of AI in organizational contexts.

Contact us to discuss speaking opportunities at your next event or conference.

Ready to Advance the Field?

Join us in pioneering research on emergent information systems. Together, we can develop new methodologies and advance our understanding of how behavioral science and AI can transform complex organizational challenges.

πŸ“§ Research Collaboration

research@ferasys.com

Interested in collaborative research on emergent systems? Let's advance the field together.

🧠 Partnership Opportunities

Join us in exploring how Nudge Theory and Generative AI can transform our understanding of emergent information systems through collaborative research.

Start Collaborating