What is A System
A baseline assessment will help you understand how interconnected your commercial process is, figure out your strengths, understand and prioritize the barriers preventing you from success, and then help determine where you’re wasting resources.
System Collapse and Innovation Cycle
A Framework for Understanding Organizational Change
Exploring the cyclical nature of system innovation, operation, and inevitable collapse, with insights into transforming sales and marketing from a revenue-centric to a value-centric model.
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The Cycle of Human Nature and Systems Collapse
Scientific Validation
This cyclical pattern has been confirmed by research in complex adaptive systems theory, institutional economics, and resilience science. As Thomas Kuhn demonstrated in his landmark work "The Structure of Scientific Revolutions," even scientific paradigms themselves follow this pattern of emergence, institutionalization, and eventual replacement when anomalies accumulate that cannot be explained within the existing framework.
"Systems inevitably face critical transitions when they become too rigid to adapt to changing conditions. These state shifts are characterized by sudden reorganization after periods of gradual stress accumulation."
Throughout history, human systems follow a predictable pattern of innovation, operation, and eventual collapse. This cycle aligns with the Panarchy model in resilience theory, which describes how all complex adaptive systems move through phases of growth, conservation, collapse, and renewal.
Innovation Phase
Leaders create new systems in response to changes in the external environment. During this phase, visionaries see possibilities that others miss and develop novel approaches that address emerging needs and challenges.
Panarchy Equivalent: Reorganization (α) phase — The period of renewal where resources are reorganized into new configurations, enabling innovation and setting the stage for a new cycle.
Key characteristics:
- Openness to experimentation and risk-taking
- Focus on first principles rather than established norms
- Rapid iteration and learning from failures
- Questioning of fundamental assumptions
Design Phase
Designers refine the innovation through trial and error, developing mechanisms to extract more value from the system. This phase is characterized by rapid learning and development of best practices.
Panarchy Equivalent: Early Exploitation (r) phase — The period of rapid growth where resources are readily available and the system expands quickly, establishing its fundamental patterns.
Key characteristics:
- Refinement of original ideas into practical applications
- Development of processes and frameworks
- Identification of patterns and optimization opportunities
- Creation of performance metrics and measurement systems
Education Phase
Educators formalize the learnings into structured forms, guides, and training materials. Knowledge becomes codified and transferable, enabling broader adoption of the system.
Panarchy Equivalent: Late Exploitation (r) phase — The system continues growing but begins to establish more rigid structures and standardization to scale its operations efficiently.
Key characteristics:
- Standardization of practices and terminology
- Development of certification programs and formal training
- Creation of scalable onboarding processes
- Simplification of complex concepts for widespread adoption
Expertise Phase
Experts develop deep specialization in established practices, often losing sight of the original principles. The system becomes increasingly rigid as expertise focuses on executing the established playbook rather than adapting to changes.
Panarchy Equivalent: Conservation (K) phase — The system maximizes efficiency but becomes increasingly rigid and interconnected, optimizing existing structures at the cost of adaptability.
Key characteristics:
- Emergence of orthodoxy and resistance to new ideas
- Increasing emphasis on following established processes
- Growth of specialized roles and internal jargon
- Diminishing returns from system optimization
- Focus shifts from adaptation to preservation of the status quo
Collapse Phase
The system fails to adapt to significant changes in the external environment. What once was innovative becomes dogmatic and rigid, ultimately leading to collapse and creating space for new innovation.
Panarchy Equivalent: Release (Ω) phase — The system's accumulated rigidities make it vulnerable to disruption, leading to a rapid release of resources and breakdown of established structures.
Key characteristics:
- Growing disparity between system outputs and environmental needs
- Resistance to fundamental change from stakeholders invested in the status quo
- Increasing resources required to maintain diminishing returns
- Crisis events that expose fundamental flaws in the system
- Emergence of new leaders with fresh perspectives
Historical Examples of System Collapse
These patterns of system evolution and collapse can be observed throughout history, across diverse domains including science, military strategy, business, and education.
Expert Validation: The Science of System Collapse
The cycle described in this framework aligns with established scientific concepts in complex systems theory, organizational science, and resilience theory:
"All human constructs go through similar cycles of growth, conservation, release and reorganization. Understanding these adaptive cycles is crucial for navigating periods of transformation, whether in ecosystems, institutions, or markets."
Scientific Terms for System Collapse and State Shifts
Panarchy
A conceptual model describing how systems cycle through four phases: exploitation (r), conservation (K), release (Ω), and reorganization (α). This model explains why systems eventually become rigid and collapse when they accumulate too much complexity in the conservation phase.
Critical Transitions
Sudden, dramatic shifts between stable states. These often occur after a system has been gradually losing resilience until a tipping point is reached, at which point even small perturbations can trigger a catastrophic shift to an alternative state.
Path Dependency
The way in which the set of decisions available in the present is limited by decisions made in the past, even though past circumstances may no longer be relevant. Explains why systems become locked into suboptimal structures.
Competency Trap
Organizations become so proficient with existing practices that they fail to adapt to environmental changes. Success with established methods paradoxically leads to failure when conditions change.
The Inquisition of Galileo (1633)
Innovate: The Catholic Church initially embraced scientific exploration, with figures like Roger Bacon advocating for the scientific method in the mid-1200s.
Expertise & Dogma: By 1616, the Church had formally declared heliocentrism as heretical, based on strict interpretation of scripture like Psalms 104:5 - "the Lord set the Earth on its foundations; it shall not move."
Collapse: Instead of adapting to new scientific discoveries, the system threatened Galileo with torture to enforce compliance with outdated geocentric models, ultimately placing him under house arrest.
World War I Tactics (1914-1918)
Innovate: Military tactics evolved significantly during the Napoleonic era.
Expertise & Dogma: By WWI, generals on both sides were rigidly trained in century-old doctrine that hadn't adapted to modern weapons and conditions.
Collapse: The result was catastrophic losses, exemplified by the Battle of the Somme where one million soldiers died for just 12 miles of territory. Generals who suggested new tactics risked being fired, while those who continued failing with outdated approaches remained in command.
Commercial System Collapse and Reinvention
Today's commercial systems are exhibiting clear signs of the Conservation (K) phase transitioning to Release (Ω), characterized by rigid dogma, diminishing returns, and an inability to adapt to changing customer expectations.
The Paradigm Shift in Commercial Systems
FROM: Go to Market
Models used to predict market dynamics are correct. Forecasts are close to actuals.
TO: Go to Customer
Models used to predict market dynamics are incorrect. Discover patterns of commercial communities.
The Old 4Ps
The New 4Ps
Signs of Commercial System Collapse
1. Geocentric Business Mindset
Modern commercial systems operate in a "geocentric" model where revenue is the center of the universe and customers are distant objects orbiting around the business. This manifests in terminology and frameworks that place business needs at the center:
- Customers reduced to "buyers" with predefined "journeys"
- Obsession with "Ideal Customer Profiles" and qualifying criteria
- Heavy focus on pipeline stages and conversion metrics
- Organizational silos that fragment the customer experience
2. Dogmatic Practices
The field has developed a complex orthodoxy of jargon, playbooks, and frameworks that are treated as doctrine rather than tools:
- Unchallenged "best practices" with little research validation
- Proliferation of specialized terminology: SQL, MQL, QBR, etc.
- Rigid role definitions (hunter/farmer, SDR/AE, etc.)
- Prescriptive "sales motions" and scripted interactions
- Metrics focus on activity rather than outcomes
3. Diminishing Returns Strategy
As effectiveness declines, the primary response is intensification rather than innovation:
- More products, more assets, more activity
- More data collection and analysis
- More inspection and process enforcement
- More specialized roles and team expansion
- Increasing costs without proportional revenue growth
Comparing Paradigms
Geocentric (Current)
Heliocentric (Future)
Path Forward: Value Communication System
Breaking the cycle requires conscious innovation to create a new commercial system that moves from a "Go to Market" model to a "Go to Customer" approach, focusing on discovering patterns rather than relying on predictable forecasts.
The Commercial System Evolution
Failure of traditional commercial systems based on forecasting and market penetration models
Creation of value-based commercial systems focused on customer patterns and co-creation
The Value Communication System represents a fundamental reimagining of commercial frameworks, shifting from forecasting market penetration to discovering identifiable and emerging patterns with different types of customers.
Key Principles of the Value Communication System
From Product to Possibility
Shift from focusing on product capabilities to helping clients envision what they can do. This transforms the commercial relationship from one of feature comparison to co-creating a vision of success.
From Place to Pattern
Replace defined routes to market with illumination of obstacles to achieving vision. Instead of focusing on distribution channels, identify the patterns that are emerging in different commercial communities.
From Promotion to Path
Move beyond getting the word out about products to plotting practical, realistic courses for success. Create personalized paths that help customers navigate their unique challenges rather than broadcasting generic messages.
From Price to Proof
Transition from hitting the right price point to providing simple before and after examples. Demonstrate tangible results that highlight the transformation customers can expect rather than focusing on cost-based decisions.
From Responding to Co-Creating
The most fundamental shift is from responding to existing demand to co-creating demand with customers. This represents a move from the Conservation (K) phase where systems rigidly follow established patterns to a Reorganization (α) phase where new configurations are created through collaboration.
Implementing the Value Communication System
Creating sustainable change requires a three-phase approach that mirrors the transition through the adaptive cycle:
Phase 1: Release & Awareness (Ω→α)
- Recognize signs of system collapse in current commercial approaches
- Document diminishing returns from traditional methods
- Map customer value perceptions vs. internal value communication
- Identify relationship networks in your customer ecosystem
- Let go of rigid frameworks that no longer serve customer needs
Phase 2: Reorganization & Experimentation (α)
- Create protected innovation spaces outside normal processes
- Develop visual value communication prototypes
- Test new approaches with select customer relationships
- Observe emerging patterns in customer interactions
- Measure impact using both traditional and new metrics
- Document learnings and adapt continuously
Phase 3: New Growth System (r)
- Scale successful experiments across the organization
- Develop training and enablement for the new approach
- Redesign metrics and incentives around value creation
- Implement supporting technology and tools
- Create mechanism for continuous innovation to avoid future system collapse
- Build feedback loops to detect early signs of rigidity
Scientific Evidence for Cyclical System Dynamics
The cycle described in this framework has been validated across multiple scientific disciplines:
Resilience Theory
Demonstrates how systems accumulate rigidities during stability periods, eventually requiring creative destruction for renewal.
Organizational Ecology
Shows how organizational inertia creates vulnerability to environmental shifts, leading to selection events.
Innovation Studies
Describes how dominant designs emerge, stabilize, and eventually collapse when disruptive technologies emerge.
These scientific frameworks affirm that state shifts and system collapses are not anomalies but predictable phases in cyclic processes - essential for long-term adaptation and evolution.