Initial commit

skills/environmental-scanning-foresight/resources/methodology.md

@@ -0,0 +1,427 @@
+# Environmental Scanning & Foresight Methodology
+
+Advanced techniques for weak signal detection, cross-impact analysis, scenario construction, and horizon scanning.
+
+## Workflow
+
+```
+Environmental Scanning Progress:
+- [ ] Step 1: Define scope and focus areas
+- [ ] Step 2: Scan PESTLE forces and trends
+- [ ] Step 3: Detect and validate weak signals
+- [ ] Step 4: Assess cross-impacts and interactions
+- [ ] Step 5: Develop scenarios for plausible futures
+- [ ] Step 6: Set signposts and adaptive triggers
+```
+
+**Step 1: Define scope and focus areas**
+
+Set scanning boundaries and critical uncertainties to focus research using scoping frameworks.
+
+**Step 2: Scan PESTLE forces and trends**
+
+Systematically collect trends using [1. Horizon Scanning Approaches](#1-horizon-scanning-approaches) and source diversity principles.
+
+**Step 3: Detect and validate weak signals**
+
+Apply [2. Weak Signal Detection](#2-weak-signal-detection) techniques to identify early indicators and validate using credibility criteria.
+
+**Step 4: Assess cross-impacts and interactions**
+
+Map interactions using [3. Cross-Impact Analysis](#3-cross-impact-analysis) to distinguish critical uncertainties from predetermined elements.
+
+**Step 5: Develop scenarios for plausible futures**
+
+Construct scenarios using [4. Scenario Construction Methods](#4-scenario-construction-methods) (axes, narratives, consistency testing).
+
+**Step 6: Set signposts and adaptive triggers**
+
+Design signposts using [5. Signpost and Trigger Design](#5-signpost-and-trigger-design) with leading indicators and thresholds.
+
+---
+
+## 1. Horizon Scanning Approaches
+
+Systematic methods for identifying emerging trends and discontinuities.
+
+### Scanning Sources by Type
+
+**Primary Sources** (firsthand data, high credibility):
+- Government data: Census, economic statistics, climate data, regulatory filings
+- Research publications: Peer-reviewed journals, working papers, conference proceedings
+- Corporate filings: Annual reports, 10-K disclosures, patent applications, M&A announcements
+- Direct observation: Site visits, trade shows, customer interviews
+
+**Secondary Sources** (analysis and synthesis):
+- Think tank reports: Policy analysis, scenario studies, technology assessments
+- Industry research: Gartner, McKinsey, BCG analyses, sector forecasts
+- News aggregation: Specialized newsletters, trade publications, curated feeds
+- Expert commentary: Academic blogs, practitioner insights, conference talks
+
+**Edge Sources** (weak signals, lower credibility but high novelty):
+- Startup activity: VC funding rounds, accelerator cohorts, product launches
+- Social media: Reddit communities, Twitter trends, influencer content
+- Fringe publications: Contrarian blogs, niche forums, subculture media
+- Crowdsourcing platforms: Prediction markets, crowd forecasts, citizen science
+
+### Source Diversity Principles
+
+**Avoid echo chambers**: Deliberately seek sources with opposing views, different geographies, alternate paradigms. If all sources agree, expand search.
+
+**Balance credibility vs novelty**: High-credibility sources (government, peer-reviewed) lag but are reliable. Low-credibility sources (social media, fringe) lead but require validation. Use both.
+
+**Geographic breadth**: Trends often emerge in lead markets (Silicon Valley for tech, Scandinavia for policy innovation, China for manufacturing). Scan globally.
+
+**Temporal depth**: Review historical patterns (past 10-20 years) to identify cycles, precedents, and recurrence vs genuine novelty.
+
+### Scanning Cadence
+
+**Daily**: Breaking news, market movements, crisis events (filter for signal vs noise)
+**Weekly**: Industry news, startup activity, technology developments
+**Monthly**: Government data releases, research publications, trend synthesis
+**Quarterly**: Comprehensive PESTLE review, weak signal validation, scenario updates
+**Annually**: Deep horizon scan, strategic reassessment, long-term trend analysis
+
+---
+
+## 2. Weak Signal Detection
+
+Techniques for identifying early indicators of change before they become mainstream.
+
+### Identification Techniques
+
+**Anomaly detection**: Look for deviations from expected patterns. Methods:
+- **Statistical outliers**: Data points that diverge >2 standard deviations from trend
+- **Broken patterns**: Historical regularities that suddenly change (e.g., customer behavior shift)
+- **Unexpected correlations**: Variables that start moving together when they shouldn't
+- **Missing dogs that didn't bark**: Expected events that fail to occur
+
+**Edge scanning**: Monitor periphery of systems where innovation emerges. Scan:
+- **Geographic edges**: Emerging markets, frontier regions, lead adopter cities
+- **Demographic edges**: Youth culture, early adopters, subcultures, extreme users
+- **Technological edges**: Research labs, patents in adjacent fields, open-source experiments
+- **Organizational edges**: Startups, non-profits, activist groups, fringe movements
+
+**Wildcard brainstorming**: Imagine low-probability, high-impact events. Categories:
+- **Technological breakthroughs**: Fusion power, AGI, quantum computing at scale
+- **Geopolitical shocks**: War, regime change, alliance collapse, resource conflict
+- **Natural disasters**: Pandemic, earthquake, climate tipping point
+- **Social tipping points**: Value shifts, trust collapse, mass movement
+
+### Validation Framework
+
+Not every anomaly is a weak signal. Validate using four criteria:
+
+**1. Source credibility** (Is source knowledgeable and trustworthy?):
+- High: Peer-reviewed research, government data, established expert
+- Medium: Industry analyst, credible journalist, experienced practitioner
+- Low: Anonymous blog, unverified social media, promotional content
+
+**2. Supporting evidence** (Are there multiple independent confirmations?):
+- Strong: 3+ independent sources, different geographies/sectors, replication studies
+- Moderate: 2 sources, same sector, corroborating anecdotes
+- Weak: Single source, no corroboration, isolated incident
+
+**3. Plausibility** (Is amplification mechanism realistic?):
+- High: Clear causal path, precedent exists, enabling conditions present
+- Medium: Plausible path but uncertain, some barriers remain
+- Low: Requires multiple unlikely events, contradicts established theory
+
+**4. Impact if scaled** (Would this matter significantly?):
+- High: Affects core business model, large market, strategic threat/opportunity
+- Medium: Affects segment or capability, moderate market, tactical response needed
+- Low: Niche impact, small market, interesting but not actionable
+
+**Decision rule**: Weak signal validated if credibility ≥ Medium AND (evidence ≥ Moderate OR plausibility + impact both ≥ High).
+
+### Signal Amplification Assessment
+
+Once validated, assess how signal could scale:
+
+**Reinforcing mechanisms** (positive feedback that accelerates):
+- Network effects (value increases with adoption)
+- Economies of scale (cost decreases with volume)
+- Social proof (adoption begets adoption)
+- Policy tailwinds (regulation favors signal)
+
+**Barriers to amplification** (what could prevent scaling?):
+- Technical barriers (physics, engineering, materials)
+- Economic barriers (cost, capital requirements, market size)
+- Social barriers (values, culture, trust, resistance)
+- Regulatory barriers (legal constraints, compliance costs)
+
+**Tipping point indicators** (what would signal transition from weak to mainstream?):
+- Adoption thresholds (>10% market penetration often triggers acceleration)
+- Infrastructure readiness (charging stations for EVs, 5G for IoT)
+- Incumbent response (when major players adopt, legitimizes trend)
+- Media coverage shift (from niche to mainstream publications)
+
+---
+
+## 3. Cross-Impact Analysis
+
+Mapping how trends interact to identify system dynamics and critical uncertainties.
+
+### Interaction Types
+
+**Reinforcing (+)**: Trend A accelerates Trend B
+- Example: AI capability (**+**) remote work adoption (AI tools enable distributed teams)
+- System effect: Positive feedback loop, exponential growth potential, virtuous/vicious cycles
+
+**Offsetting (-)**: Trend A inhibits Trend B
+- Example: Privacy regulation (**-**) personalization (GDPR limits data collection for targeting)
+- System effect: Tension, tradeoffs, oscillation between competing forces
+
+**Cascading (→)**: Trend A triggers Trend B
+- Example: Pandemic (**→**) remote work (**→**) office demand collapse (**→**) urban exodus
+- System effect: Sequential causation, time lags, amplification chains
+
+**Independent (0)**: Trends do not significantly interact
+- Example: Arctic ice melt (0) cryptocurrency adoption (unrelated domains)
+- System effect: Additive, not multiplicative
+
+### Mapping Process
+
+**Step 1**: List 5-10 key trends from PESTLE scan (prioritize high impact)
+
+**Step 2**: Create interaction matrix (trend pairs in rows/columns)
+
+**Step 3**: For each cell, assess: Does Trend A affect Trend B? How (reinforce/offset/cascade)?
+
+**Step 4**: Identify feedback loops (A→B→C→A) that create acceleration or stabilization
+
+**Step 5**: Classify trends by impact and uncertainty into four quadrants:
+
+| Quadrant | Impact | Uncertainty | Implication |
+|----------|--------|-------------|-------------|
+| **Critical Uncertainties** | High | High | Build scenarios around these |
+| **Predetermined Elements** | High | Low | Plan for these, they will happen |
+| **Wild Cards** | High | Very Low (but non-zero) | Monitor, prepare contingency |
+| **Context** | Low | Any | Note but don't scenario around |
+
+### System Dynamics Patterns
+
+**Exponential growth** (reinforcing loop unchecked):
+- Example: Social media network effects → more users → more value → more users
+- Risk: Overshoot, resource depletion, regulatory backlash
+- Management: Look for saturation points, shifting limits
+
+**Goal-seeking** (balancing loop stabilizes):
+- Example: Price increase → demand falls → supply glut → price decrease
+- Risk: Oscillation, delayed response, policy resistance
+- Management: Identify equilibrium, reduce delays, smooth adjustments
+
+**Shifting dominance** (reinforcing dominates, then balancing kicks in):
+- Example: Technology hype cycle (enthusiasm → investment → growth → saturation → disillusionment)
+- Risk: Boom-bust cycles, stranded assets
+- Management: Recognize phases, adjust strategy as loops shift
+
+---
+
+## 4. Scenario Construction Methods
+
+Creating multiple plausible futures that span range of outcomes.
+
+### 2x2 Matrix Method (Most Common)
+
+**Step 1: Select two critical uncertainties** (high impact + high uncertainty from cross-impact analysis)
+- Criteria: Independent (not correlated), span broad range, relevant to strategic questions
+- Example Axes:
+  - Climate policy stringency (Low to High)
+  - Technology breakthrough speed (Slow to Fast)
+
+**Step 2: Define endpoints** for each axis
+- Climate policy: Low = Voluntary pledges, High = Binding global carbon price
+- Tech breakthrough: Slow = Incremental innovation, Fast = Fusion/battery paradigm shift
+
+**Step 3: Create four scenario quadrants**
+- Scenario A: High policy + Fast tech = "Green Acceleration"
+- Scenario B: High policy + Slow tech = "Costly Transition"
+- Scenario C: Low policy + Fast tech = "Innovation Without Mandate"
+- Scenario D: Low policy + Slow tech = "Muddling Through"
+
+**Step 4: Develop narratives** for each scenario (2-3 paragraphs)
+- Opening: What tipping point or series of events leads to this future?
+- Body: How do PESTLE forces play out? What does 2030 look like?
+- Implications: Winners, losers, strategic imperatives
+
+**Step 5: Test consistency**
+- Does narrative logic hold? (no contradictions)
+- Are all predetermined elements included? (high impact + low uncertainty trends must appear in all scenarios)
+- Is scenario distinct from others? (avoid convergence)
+
+### Incremental/Disruptive Axis Method
+
+Alternative to 2x2 when primary uncertainty is pace/magnitude of change:
+
+**Incremental scenario**: Current trends continue, gradual evolution, adaptation within existing paradigm
+**Disruptive scenario**: Discontinuity occurs, rapid shift, new paradigm emerges
+
+Develop 3 scenarios along spectrum:
+- **Optimistic disruption**: Breakthrough enables rapid positive transformation
+- **Baseline incremental**: Current trajectory, mix of progress and setbacks
+- **Pessimistic disruption**: Crisis triggers collapse or regression
+
+### Scenario Narrative Structure
+
+**Opening hook**: Event or trend that sets scenario in motion (e.g., "In 2026, three major economies implement carbon border adjustments...")
+
+**Causal chain**: How initial conditions cascade through system (policy → investment → innovation → adoption → market shift)
+
+**Signposts along the way**: Observable milestones that would indicate this scenario unfolding (useful for Step 6)
+
+**Endpoint description**: Vivid portrait of 2030 or target year (what does business/society/technology look like?)
+
+**Stakeholder perspectives**: Winners (who benefits?), Losers (who struggles?), Adapters (who pivots?)
+
+**Strategic implications**: What capabilities, partnerships, positioning would succeed in this scenario?
+
+### Wild Cards Integration
+
+Wild cards (low probability, high impact) don't fit neatly into scenarios but should be acknowledged:
+
+**Approach 1**: Create 3 core scenarios + 1 wild card scenario to explore extreme
+**Approach 2**: List wild cards separately with triggers and contingency responses
+**Approach 3**: Use wild cards to stress-test strategies ("Would our plan survive pandemic + war?")
+
+---
+
+## 5. Signpost and Trigger Design
+
+Designing early warning systems that prompt adaptive action.
+
+### Leading vs Lagging Indicators
+
+**Lagging indicators** (confirm trend but arrive too late for proactive response):
+- GDP growth (economy already shifted)
+- Market share change (competition already won/lost)
+- Regulation enacted (policy battle already decided)
+
+**Leading indicators** (precede outcome, enable early action):
+- Building permits (predict housing prices by 6-12 months)
+- VC investment (signals technology readiness 2-3 years ahead of commercialization)
+- Legislative proposals (indicate regulatory direction before enactment)
+- Job postings (show hiring intent before headcount data)
+
+**Rule**: Signposts must be leading. Ask: "How far ahead of the outcome does this indicator move?"
+
+### Threshold Setting
+
+Thresholds trigger action when crossed. Must be:
+
+**Specific** (quantitative when possible):
+- Good: "EV market share >20% in major markets"
+- Bad: "Significant EV adoption"
+
+**Observable** (data exists and is measurable):
+- Good: "US unemployment rate falls below 4%"
+- Bad: "Consumer sentiment improves" (subjective unless tied to specific survey)
+
+**Actionable** (crossing threshold has clear decision implication):
+- Good: "If battery cost <$80/kWh → green-light full EV platform investment"
+- Bad: "If battery cost declines → monitor" (what action?)
+
+**Calibrated to lead time** (threshold allows time to respond):
+- If building factory takes 3 years, threshold must trigger 3+ years before market shift
+
+### Multi-Level Triggers
+
+Use graduated thresholds for phased response:
+
+**Yellow alert** (early warning, intensify monitoring):
+- Example: "2 countries delay ICE ban announcements"
+- Response: Increase scanning frequency, run contingency analysis
+
+**Orange alert** (prepare to act, mobilize resources):
+- Example: "3 countries delay + oil prices fall below $60/bbl for 6 months"
+- Response: Halt EV R&D expansion, preserve ICE capability
+
+**Red alert** (execute adaptation, commit resources):
+- Example: "5 countries delay + major automaker cancels EV platform"
+- Response: Pivot to hybrid strategy, exit pure-EV bets
+
+### Monitoring Cadence
+
+Match monitoring frequency to indicator velocity:
+
+**Real-time** (dashboards, alerts): Financial markets, breaking news, crisis events
+**Daily**: Social media sentiment, competitive moves, policy announcements
+**Weekly**: Industry data, technology developments, startup funding
+**Monthly**: Economic indicators, research publications, market share
+**Quarterly**: PESTLE review, scenario validation, signpost assessment
+**Annually**: Comprehensive horizon scan, scenario refresh, strategy adaptation
+
+### Feedback Loops
+
+Signpost systems must feed back into strategy:
+
+**Decision triggers**: Pre-commit to actions when thresholds crossed (remove bias, speed response)
+**Scenario validation**: Track which scenario is unfolding based on signpost patterns
+**Scan refinement**: Add new signposts as weak signals emerge, retire irrelevant indicators
+**Strategy adjustment**: Quarterly reviews assess if signposts require strategic pivot
+
+---
+
+## 6. Advanced Techniques
+
+### Delphi Method (Expert Panel Forecasting)
+
+**Purpose**: Synthesize expert judgment on uncertain futures through iterative anonymous surveying
+
+**Process**:
+1. Recruit 10-20 domain experts (diversity of views, high credibility)
+2. Round 1: Ask experts to forecast key uncertainties (e.g., "When will EV cost parity occur?")
+3. Aggregate responses, share distribution (median, quartiles) anonymously with panel
+4. Round 2: Experts revise forecasts after seeing peer responses, justify outlier positions
+5. Round 3: Final forecasts converge (or persistent disagreement highlights critical uncertainty)
+
+**Strengths**: Reduces groupthink, surfaces reasoning, quantifies uncertainty
+**Limitations**: Time-intensive, expert availability, potential for false consensus
+
+### Backcasting (Futures to Present)
+
+**Purpose**: Work backward from desired future to identify pathway and necessary actions
+
+**Process**:
+1. Define aspirational future state (e.g., "Carbon-neutral economy by 2040")
+2. Identify milestones working backward (2035, 2030, 2025)
+3. Determine required actions, policies, technologies for each milestone
+4. Assess feasibility and barriers
+5. Create roadmap from present to future
+
+**Strengths**: Goal-oriented, reveals dependencies, identifies gaps
+**Limitations**: Assumes future is achievable, may ignore obstacles or alternate paths
+
+### Morphological Analysis (Configuration Exploration)
+
+**Purpose**: Systematically explore combinations of variables to identify novel scenarios
+
+**Process**:
+1. Identify key dimensions (e.g., Energy source, Transportation mode, Governance model)
+2. List options for each (Energy: Fossil, Nuclear, Renewable, Fusion)
+3. Create configuration matrix (all possible combinations)
+4. Assess consistency (which combinations are plausible?)
+5. Develop scenarios for interesting/high-impact configurations
+
+**Strengths**: Comprehensive, reveals overlooked combinations, creative
+**Limitations**: Combinatorial explosion (5 dimensions × 4 options = 1024 configs), requires filtering
+
+---
+
+## 7. Common Pitfalls
+
+**Confirmation bias in scanning**: Collecting evidence that supports existing beliefs while ignoring disconfirming data. **Fix**: Actively seek sources with opposing views, assign devil's advocate role.
+
+**Linear extrapolation**: Assuming trends continue unchanged without inflection points or reversals. **Fix**: Look for saturation limits, feedback loops, historical precedents of reversal.
+
+**Treating scenarios as predictions**: Assigning probabilities or betting on one scenario. **Fix**: Use scenarios to test strategy robustness, not to forecast the future.
+
+**Too many scenarios**: Creating 5+ scenarios that overwhelm decision-makers. **Fix**: Limit to 3-4 distinct scenarios; use wild cards separately.
+
+**Weak signals inflation**: Calling every anomaly a weak signal without validation. **Fix**: Apply credibility + evidence + plausibility + impact criteria rigorously.
+
+**Lagging signposts**: Monitoring indicators that confirm trends after they've materialized. **Fix**: Identify leading indicators with 6-12+ month lead time.
+
+**Stale scans**: Conducting one-time scan without updates as environment changes. **Fix**: Establish scanning cadence (quarterly PESTLE, monthly weak signals, annual scenarios).
+
+**Analysis paralysis**: Over-researching without synthesizing into decisions. **Fix**: Set deadlines, use "good enough" threshold, prioritize actionability over comprehensiveness.