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+---
+name: environmental-scanning-foresight
+description: Use when scanning external trends for strategic planning, monitoring PESTLE forces (Political, Economic, Social, Technological, Legal, Environmental), detecting weak signals (early indicators of change), planning scenarios for multiple futures, setting signposts and indicators for early warning, or when user mentions environmental scanning, horizon scanning, trend analysis, scenario planning, strategic foresight, futures thinking, or emerging issues monitoring.
+---
+# Environmental Scanning & Foresight
+
+## Table of Contents
+- [Purpose](#purpose)
+- [When to Use](#when-to-use)
+- [What Is It?](#what-is-it)
+- [Workflow](#workflow)
+- [Common Patterns](#common-patterns)
+- [Guardrails](#guardrails)
+- [Quick Reference](#quick-reference)
+
+## Purpose
+
+Environmental scanning and foresight helps organizations anticipate change by systematically monitoring external trends, detecting weak signals before they become obvious, and preparing for multiple possible futures. This skill guides you through PESTLE analysis, horizon scanning, scenario development, and early warning systems to inform strategic planning and adaptive decision-making.
+
+## When to Use
+
+Use this skill when:
+
+- **Strategic planning**: Scanning external environment for 3-5 year strategic plans, identifying opportunities and threats
+- **Weak signal detection**: Monitoring early indicators of change that others might miss (regulatory shifts, technology breakthroughs, consumer behavior changes)
+- **Scenario planning**: Developing multiple plausible futures to test strategy robustness across different conditions
+- **Trend analysis**: Tracking PESTLE forces (Political, Economic, Social, Technological, Legal, Environmental) affecting industry or domain
+- **Early warning systems**: Setting signposts and indicators to trigger adaptive responses before trends become crises
+- **Innovation foresight**: Identifying emerging technologies or business models that could disrupt current operations
+- **Risk monitoring**: Tracking geopolitical, climate, or market risks that could impact long-term plans
+- **Regulatory anticipation**: Scanning policy developments and regulatory trends to prepare compliance or advocacy strategies
+
+Trigger phrases: "environmental scan", "horizon scanning", "PESTLE analysis", "weak signals", "scenario planning", "strategic foresight", "futures", "emerging trends", "early warning", "signposts"
+
+## What Is It?
+
+Environmental scanning is the systematic collection and analysis of information about external forces, events, and trends. Foresight extends this by using scanning results to anticipate plausible futures and prepare adaptive strategies.
+
+**Quick example:**
+
+**Scenario**: Electric vehicle manufacturer planning 2025-2030 strategy
+
+**Environmental scan** identifies:
+- **Political**: 15 countries announced ICE vehicle bans (2030-2040)
+- **Economic**: Battery costs declining 15%/year, approaching parity with ICE
+- **Social**: Consumer EV consideration jumped from 20% to 45% (2020-2023)
+- **Technological**: Charging time reduced from 60min to 15min (fast chargers)
+- **Legal**: EPA tightening emissions standards, favoring zero-emission
+- **Environmental**: Climate commitments driving corporate fleet electrification
+
+**Weak signal detected**: Toyota investing $13B in battery production (usually slow to EV). Signal: Major holdout shifting = tipping point approaching.
+
+**Scenario planning**:
+- **Rapid transition** (30% probability): ICE ban enforcement accelerates, charging infrastructure deployed fast → Scale EV production aggressively
+- **Gradual transition** (50% probability): Current trajectory continues, mix of EV/ICE 2030 → Balanced portfolio approach
+- **Reversal** (20% probability): Political backlash, grid capacity limits slow adoption → Maintain ICE capability, hedge bets
+
+**Signposts set**:
+- If EV market share >20% by 2026 → Accelerate (currently 14%)
+- If 3+ countries delay bans → Hedge strategy (currently 0)
+- If battery costs <$80/kWh by 2025 → Full commitment (currently $120/kWh)
+
+**Result**: Strategy prepared for multiple futures, with clear triggers for adaptation.
+
+## Workflow
+
+Copy this checklist and track your progress:
+
+```
+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**
+
+Clarify scanning theme (technology disruption, market evolution, regulatory shift), geographic scope (global, regional, local), time horizon (short 1-2yr, medium 3-5yr, long 5-10yr+), and key uncertainties to explore. See [resources/template.md](resources/template.md#scanning-scope-definition) for scoping framework.
+
+**Step 2: Scan PESTLE forces and trends**
+
+Systematically collect trends across Political, Economic, Social, Technological, Legal, Environmental dimensions. Identify drivers of change (demographics, technology, policy), assess magnitude and direction, and track sources (reports, data, news, expert views). See [resources/template.md](resources/template.md#pestle-scanning-framework) for structured scanning.
+
+**Step 3: Detect and validate weak signals**
+
+Identify early indicators that diverge from mainstream expectations—anomalies, edge cases, emergent behaviors. Validate signal credibility (source quality, supporting evidence, plausibility) and assess potential impact if signal amplifies. See [resources/methodology.md](resources/methodology.md#weak-signal-detection) for detection techniques.
+
+**Step 4: Assess cross-impacts and interactions**
+
+Map how trends interact (reinforcing, offsetting, cascading). Identify critical uncertainties (high impact + high uncertainty) and predetermined elements (high impact + low uncertainty). See [resources/methodology.md](resources/methodology.md#cross-impact-analysis) for interaction mapping.
+
+**Step 5: Develop scenarios for plausible futures**
+
+Create 3-4 distinct, internally consistent scenarios spanning range of outcomes. Build scenarios around critical uncertainties (axes with most impact), develop narrative logic, and test strategies against each scenario. See [resources/template.md](resources/template.md#scenario-development-template) for scenario structure.
+
+**Step 6: Set signposts and adaptive triggers**
+
+Define leading indicators to monitor, set thresholds that trigger strategy adjustment, and establish monitoring cadence (monthly, quarterly, annual). Validate using [resources/evaluators/rubric_environmental_scanning_foresight.json](resources/evaluators/rubric_environmental_scanning_foresight.json). **Minimum standard**: Average score ≥ 3.5.
+
+## Common Patterns
+
+**Pattern 1: Industry Disruption Scanning**
+- **Focus**: Technology shifts, business model innovation, competitive dynamics
+- **PESTLE emphasis**: Technological (new capabilities), Economic (cost curves), Social (adoption patterns)
+- **Weak signals**: Startups with novel approaches, technology breakthroughs in adjacent fields, early adopter behavior
+- **Scenarios**: Disruption speed (rapid vs gradual), winning model (incumbent adaptation vs new entrant dominance)
+- **Example**: Media industry scanning streaming, AI content generation, attention economy shifts
+
+**Pattern 2: Regulatory & Policy Foresight**
+- **Focus**: Government policy, regulatory trends, compliance requirements
+- **PESTLE emphasis**: Political (election outcomes, party positions), Legal (regulatory proposals, court decisions)
+- **Weak signals**: Pilot programs, stakeholder consultations, legislative drafts in one jurisdiction presaging others
+- **Scenarios**: Stringency (light touch vs heavy regulation), speed (gradual vs sudden), scope (sector-specific vs economy-wide)
+- **Example**: Finance sector scanning crypto regulation, data privacy laws, central bank digital currencies
+
+**Pattern 3: Market Evolution & Consumer Trends**
+- **Focus**: Customer behavior, demand patterns, value shifts
+- **PESTLE emphasis**: Social (demographics, values, lifestyle), Economic (income, spending), Technological (enabling platforms)
+- **Weak signals**: Subculture behaviors, Gen Z early adoption, influencer/creator economy patterns
+- **Scenarios**: Value proposition evolution (what customers prioritize), channel dominance (where they buy), price sensitivity
+- **Example**: Retail scanning sustainability values, experiences over ownership, social commerce
+
+**Pattern 4: Geopolitical & Macro Risk Monitoring**
+- **Focus**: Political stability, trade relations, conflict risk, economic conditions
+- **PESTLE emphasis**: Political (elections, tensions), Economic (growth, inflation, debt), Environmental (climate, resources)
+- **Weak signals**: Diplomatic incidents, policy U-turns, capital flows, social unrest indicators
+- **Scenarios**: Geopolitical alignment (cooperation vs fragmentation), economic regime (growth vs stagnation), resource availability
+- **Example**: Multinational scanning supply chain resilience, tariff risks, energy security
+
+**Pattern 5: Climate & Sustainability Foresight**
+- **Focus**: Climate impacts, transition risks, sustainability regulations, stakeholder pressure
+- **PESTLE emphasis**: Environmental (physical risks, biodiversity), Political (climate policy), Social (public opinion), Legal (disclosure rules)
+- **Weak signals**: Extreme weather anomalies, stranded asset warnings, investor divestment, youth climate activism
+- **Scenarios**: Transition speed (orderly vs disorderly), policy stringency (ambitious vs incremental), physical impacts (moderate vs severe)
+- **Example**: Energy company scanning net-zero commitments, carbon pricing, renewable cost curves, grid resilience
+
+## Guardrails
+
+**Critical requirements:**
+
+1. **Scan systematically, not selectively**: Cover all PESTLE dimensions (Political, Economic, Social, Technological, Legal, Environmental) even if some seem less relevant. Selective scanning creates blind spots. Weak signals often appear in unexpected domains.
+
+2. **Distinguish weak signals from noise**: Weak signals are early indicators with potential impact, not every random anomaly. Validate: Does source have credibility? Is there supporting evidence? Is amplification plausible? Is impact significant if it scales? Avoid signal inflation (calling everything a weak signal).
+
+3. **Scenarios must be plausible, not preferred or feared**: Scenarios are not predictions or wish fulfillment. They should span range of outcomes based on critical uncertainties, be internally consistent (logic holds), and challenge current assumptions. Avoid creating only optimistic scenarios or dystopian extremes.
+
+4. **Critical uncertainties have high impact AND high uncertainty**: Not all trends are critical uncertainties for scenario building. Use 2x2 matrix: High impact + low uncertainty = predetermined elements (plan for them). High impact + high uncertainty = critical uncertainties (build scenarios around). Low impact = context (note but don't scenario around).
+
+5. **Cross-impacts matter as much as individual trends**: Trends interact (AI + climate policy + geopolitics). Reinforcing trends accelerate (renewable cost decline + climate policy + corporate commitments). Offsetting trends create tension (privacy vs personalization). Cascading trends trigger others (pandemic → remote work → office demand collapse). Map interactions, don't treat trends in isolation.
+
+6. **Signposts must be observable and leading, not lagging**: Signposts trigger adaptation before full trend materializes. Leading indicators precede outcomes (building permits before housing prices). Lagging indicators confirm but arrive too late (GDP growth rate). Threshold must be specific (">20% market share" not "significant adoption") and monitorable (data exists, update frequency known).
+
+7. **Foresight informs strategy, doesn't dictate it**: Scenarios reveal possibilities and test strategy robustness, but don't automatically prescribe action. Strategy choices depend on risk appetite, resources, values. Use scenarios to stress-test plans ("does our strategy work in scenarios A, B, C?") and identify no-regrets moves (work in all scenarios) vs hedges (work in some).
+
+8. **Update scans regularly, not once**: Environmental conditions change. Set scanning cadence (quarterly PESTLE review, monthly weak signal scan, annual scenario update). Stale scans miss emerging trends. Rigid scenarios ignore new information. Foresight is continuous monitoring, not one-time exercise.
+
+**Common pitfalls:**
+
+- ❌ **Confirmation bias in scanning**: Only collecting evidence supporting existing beliefs. Seek disconfirming evidence, alternate views.
+- ❌ **Extrapolating linearly**: Assuming current trends continue unchanged. Consider inflection points, reversals, discontinuities.
+- ❌ **Treating scenarios as predictions**: Scenarios are not forecasts. No probabilities assigned (or equal probability). They explore "what if" not "what will".
+- ❌ **Too many scenarios (>4)**: Overwhelming decision-makers, diluting focus. Aim for 3-4 distinct scenarios covering key uncertainties.
+- ❌ **Ignoring wild cards**: Low-probability, high-impact events (pandemic, breakthrough, collapse). Acknowledge them even if not primary scenarios.
+- ❌ **Anchoring to recent past**: Recency bias makes recent events (pandemic, financial crisis) loom large. Consider longer historical patterns.
+
+## Quick Reference
+
+**Key resources:**
+
+- **[resources/template.md](resources/template.md)**: PESTLE scanning framework, weak signal template, scenario development template, signpost definition template
+- **[resources/methodology.md](resources/methodology.md)**: Weak signal detection techniques, cross-impact analysis, scenario construction methods, horizon scanning approaches
+- **[resources/evaluators/rubric_environmental_scanning_foresight.json](resources/evaluators/rubric_environmental_scanning_foresight.json)**: Quality criteria for scans, scenarios, and signposts
+
+**PESTLE Dimensions:**
+- **Political**: Elections, policy priorities, geopolitical tensions, governance shifts
+- **Economic**: Growth, inflation, trade, investment, employment, income distribution
+- **Social**: Demographics, values, lifestyle, education, health, inequality
+- **Technological**: Innovation, digitalization, automation, infrastructure, R&D
+- **Legal**: Regulation, standards, liability, IP, compliance requirements
+- **Environmental**: Climate, pollution, resources, biodiversity, circular economy
+
+**Time Horizons:**
+- **Short-term** (1-2 years): Operational planning, current trend extrapolation, tactical adjustments
+- **Medium-term** (3-5 years): Strategic planning, inflection points, scenario planning
+- **Long-term** (5-10+ years): Visioning, transformational change, paradigm shifts, wildcards
+
+**Scenario Archetypes:**
+- **2x2 Matrix**: Two critical uncertainties create four scenarios (common structure, easy to communicate)
+- **Incremental vs Disruptive**: Gradual evolution vs sudden shift
+- **Optimistic vs Pessimistic**: Best case vs worst case (with realistic middle)
+- **Inside-out vs Outside-in**: Organization-driven vs environment-driven change
+
+**Typical workflow time:**
+
+- PESTLE scan (initial): 4-8 hours (comprehensive literature review, data collection)
+- Weak signal detection: 2-4 hours (scanning edge sources, validation)
+- Cross-impact analysis: 2-3 hours (mapping interactions, prioritizing)
+- Scenario development: 4-6 hours (narrative development, consistency checking)
+- Signpost definition: 1-2 hours (indicator selection, threshold setting)
+- **Total initial scan**: 15-25 hours
+- **Ongoing monitoring**: 2-4 hours/month (depends on cadence and scope)
+
+**When to escalate:**
+
+- Quantitative modeling (system dynamics, agent-based models for complex systems)
+- Delphi studies or expert panels (requires facilitation and multi-round synthesis)
+- Large-scale scenario workshops (requires professional facilitation)
+- Econometric forecasting (requires statistical expertise)
+→ Consult professional futurists, scenario planners, or strategic foresight specialists
+
+**Inputs required:**
+
+- **Scanning theme** (what aspect of environment to focus on)
+- **Geographic scope** (global, regional, local)
+- **Time horizon** (short, medium, long-term)
+- **Key uncertainties** (what do we not know that matters most)
+
+**Outputs produced:**
+
+- `environmental-scanning-foresight.md`: PESTLE scan results, weak signals identified, cross-impact analysis, scenarios developed, signposts defined, strategic implications
--- a/skills/environmental-scanning-foresight/resources/evaluators/rubric_environmental_scanning_foresight.json
+++ b/skills/environmental-scanning-foresight/resources/evaluators/rubric_environmental_scanning_foresight.json
@@ -0,0 +1,235 @@
+{
+  "criteria": [
+    {
+      "name": "PESTLE Comprehensiveness",
+      "1": "Scans only 1-2 PESTLE dimensions, significant blind spots, cherry-picks domains",
+      "3": "Covers 4-5 PESTLE dimensions systematically, minor gaps, reasonable source diversity",
+      "5": "Comprehensive scan across all 6 PESTLE dimensions, diverse credible sources, systematic coverage with geographic/temporal breadth"
+    },
+    {
+      "name": "Weak Signal Validation",
+      "1": "Treats all anomalies as weak signals without validation, single sources, unclear amplification path",
+      "3": "Validates signals using credibility + evidence criteria, plausibility assessed, some supporting evidence",
+      "5": "Rigorous validation (source credibility, multiple confirmations, plausible amplification mechanism, significant impact if scaled), clear path from weak to mainstream"
+    },
+    {
+      "name": "Scenario Plausibility",
+      "1": "Scenarios are predictions/wishes rather than plausible futures, inconsistent logic, implausible combinations",
+      "3": "Scenarios are plausible and internally consistent, span reasonable range of outcomes, based on critical uncertainties",
+      "5": "Scenarios are distinct, plausible, internally consistent, span full range of critical uncertainties, include predetermined elements, challenge assumptions, vivid narratives"
+    },
+    {
+      "name": "Cross-Impact Mapping",
+      "1": "Trends treated in isolation, no interaction analysis, misses reinforcing/offsetting dynamics",
+      "3": "Some interaction analysis, identifies key reinforcing or offsetting trends, distinguishes high/low impact",
+      "5": "Comprehensive cross-impact matrix, reinforcing/offsetting/cascading relationships mapped, feedback loops identified, critical uncertainties vs predetermined elements distinguished"
+    },
+    {
+      "name": "Signpost Quality",
+      "1": "Signposts are lagging indicators, vague thresholds, unobservable or unmeasurable",
+      "3": "Signposts are leading indicators with specific thresholds, observable, monitoring plan defined",
+      "5": "Signposts are leading (6-12+ month lead time), specific quantitative thresholds, observable data sources identified, update frequency set, action triggers pre-committed, graduated alerts"
+    },
+    {
+      "name": "Source Credibility",
+      "1": "Relies on single source type or low-credibility sources, no validation, echo chamber",
+      "3": "Mixes primary/secondary sources, includes credible sources (government, research, industry), some diversity",
+      "5": "Source diversity across primary/secondary/edge, balances credibility vs novelty, geographic breadth, temporal depth, actively seeks disconfirming evidence"
+    },
+    {
+      "name": "Strategic Implications",
+      "1": "No connection to decisions, analysis without recommendations, unclear actionability",
+      "3": "Strategic implications identified for key scenarios, connects to business decisions, some actionability",
+      "5": "Clear strategic implications for each scenario, no-regrets moves identified, hedges specified, decision triggers defined, robust across scenarios, actionable recommendations"
+    },
+    {
+      "name": "Uncertainty Management",
+      "1": "Treats uncertainties as predictions, assigns false precision, ignores ranges and confidence",
+      "3": "Distinguishes high/low uncertainty, acknowledges unknowns, uses scenarios to span range",
+      "5": "Explicit uncertainty quantification (high impact + high uncertainty = critical, high impact + low uncertainty = predetermined), wild cards acknowledged, confidence calibrated, avoids false precision"
+    },
+    {
+      "name": "Temporal Scope",
+      "1": "Time horizon mismatched to questions (too short/long), snapshots without trend analysis, recency bias",
+      "3": "Appropriate time horizon (1-2yr, 3-5yr, or 5-10yr based on need), some historical context, trends tracked",
+      "5": "Time horizon matched to strategic planning cycle, historical patterns analyzed (10-20yr lookback), trend trajectories projected, inflection points identified, milestones defined"
+    },
+    {
+      "name": "Update Mechanism",
+      "1": "One-time scan, no monitoring plan, static scenarios, stale data",
+      "3": "Monitoring cadence defined (quarterly/annual), some plan for updates, signposts tracked",
+      "5": "Comprehensive update plan (daily/weekly/monthly/quarterly/annual by indicator type), scenario validation process, scan refinement based on new signals, feedback loop to strategy"
+    }
+  ],
+  "guidance_by_type": {
+    "Industry Disruption Scanning": {
+      "target_score": 4.1,
+      "key_requirements": [
+        "Technology trends (PESTLE-T) comprehensive with patent/startup/VC data",
+        "Weak signals from edge sources (startups, research labs, adjacent fields)",
+        "Scenarios focus on disruption speed (rapid vs gradual) and winning model (incumbent vs entrant)",
+        "Signposts track technology readiness (TRL progression), adoption curves, incumbent response"
+      ],
+      "common_pitfalls": [
+        "Overweighting hype cycles, treating all startups as weak signals",
+        "Ignoring economic/social barriers to adoption",
+        "Linear extrapolation of exponential tech trends"
+      ]
+    },
+    "Regulatory & Policy Foresight": {
+      "target_score": 4.0,
+      "key_requirements": [
+        "Political & Legal dimensions (PESTLE-P,L) prioritized with legislative tracking",
+        "Weak signals from pilot programs, consultations, lead jurisdictions",
+        "Scenarios span stringency (light vs heavy) and speed (gradual vs sudden)",
+        "Signposts track proposals, stakeholder positions, enforcement patterns"
+      ],
+      "common_pitfalls": [
+        "Assuming current policy trajectory continues unchanged",
+        "Missing cross-border regulatory arbitrage opportunities",
+        "Ignoring industry lobbying and capture dynamics"
+      ]
+    },
+    "Market Evolution & Consumer Trends": {
+      "target_score": 4.2,
+      "key_requirements": [
+        "Social & Economic dimensions (PESTLE-S,E) deep, demographics and values shifts",
+        "Weak signals from subcultures, Gen Z behavior, influencer/creator economy",
+        "Scenarios explore value proposition evolution, channel dominance, price sensitivity",
+        "Signposts track early adopter behavior, sentiment, spending patterns"
+      ],
+      "common_pitfalls": [
+        "Overgeneralizing from small samples or vocal minorities",
+        "Confusing stated preferences with revealed behavior",
+        "Anchoring to recent trends (recency bias)"
+      ]
+    },
+    "Geopolitical & Macro Risk": {
+      "target_score": 3.9,
+      "key_requirements": [
+        "Political & Economic dimensions (PESTLE-P,E) comprehensive, global scope",
+        "Weak signals from diplomatic incidents, capital flows, social unrest indicators",
+        "Scenarios span geopolitical alignment (cooperation vs fragmentation), economic regime (growth vs stagnation)",
+        "Signposts track leading indicators (yields, commodity prices, policy shifts)"
+      ],
+      "common_pitfalls": [
+        "Home-country bias in geopolitical analysis",
+        "Treating low-probability tail risks as negligible",
+        "Missing second-order effects and contagion"
+      ]
+    },
+    "Climate & Sustainability Foresight": {
+      "target_score": 4.0,
+      "key_requirements": [
+        "Environmental dimension (PESTLE-E) deep with climate models, plus Political/Legal for policy",
+        "Weak signals from physical anomalies, stranded asset warnings, investor ESG shifts",
+        "Scenarios span transition speed (orderly vs disorderly), policy stringency, physical impacts",
+        "Signposts track carbon pricing, renewable cost curves, extreme weather frequency, commitments"
+      ],
+      "common_pitfalls": [
+        "Underestimating physical risks or transition risks",
+        "Ignoring just transition and social equity dimensions",
+        "Linear climate projections ignoring tipping points"
+      ]
+    }
+  },
+  "guidance_by_complexity": {
+    "Simple/Focused Scan": {
+      "target_score": 3.5,
+      "description": "Single domain or narrow question, limited geographic scope, short time horizon (1-2yr)",
+      "key_requirements": [
+        "3-4 PESTLE dimensions covered (focus on most relevant)",
+        "2-3 validated weak signals from credible sources",
+        "2-3 simple scenarios (baseline, upside, downside)",
+        "3-5 leading signposts with clear thresholds"
+      ],
+      "time_estimate": "8-12 hours"
+    },
+    "Moderate/Strategic Planning": {
+      "target_score": 4.0,
+      "description": "Multi-domain scan, regional/national scope, medium time horizon (3-5yr)",
+      "key_requirements": [
+        "All 6 PESTLE dimensions systematically covered",
+        "5-8 validated weak signals with amplification paths assessed",
+        "3-4 scenarios (2x2 matrix method) with narratives and implications",
+        "8-12 signposts with graduated alerts (yellow/orange/red)",
+        "Cross-impact analysis identifying feedback loops"
+      ],
+      "time_estimate": "20-30 hours initial, 4-6 hours/quarter updates"
+    },
+    "Complex/Comprehensive Foresight": {
+      "target_score": 4.3,
+      "description": "System-level scan, global scope, long time horizon (5-10yr), high stakes",
+      "key_requirements": [
+        "PESTLE comprehensive with geographic breadth and temporal depth (10yr+ lookback)",
+        "10+ validated weak signals from edge sources, expert panels (Delphi)",
+        "4 scenarios with wild cards, advanced methods (backcasting, morphological analysis)",
+        "15+ signposts with real-time monitoring, dashboards, automated alerts",
+        "Cross-impact with system dynamics modeling, sensitivity analysis"
+      ],
+      "time_estimate": "40-60 hours initial, facilitated workshops, 8-12 hours/quarter updates"
+    }
+  },
+  "common_failure_modes": [
+    {
+      "failure": "Confirmation bias scanning",
+      "symptom": "All sources support existing strategy, no disconfirming evidence, echo chamber",
+      "detection": "Check source diversity, political/ideological spectrum, opposing views absent",
+      "fix": "Actively seek contrarian sources, assign devil's advocate, scan opposing geographies/sectors"
+    },
+    {
+      "failure": "Weak signal inflation",
+      "symptom": "Every anomaly labeled weak signal, no validation, dozens of signals without prioritization",
+      "detection": "Weak signals lack credibility assessment, supporting evidence, or plausibility analysis",
+      "fix": "Apply validation framework rigorously (credibility + evidence + plausibility + impact), prioritize top 5-10"
+    },
+    {
+      "failure": "Scenarios as predictions",
+      "symptom": "Probabilities assigned to scenarios, betting on one scenario, scenarios converge",
+      "detection": "Language like 'most likely scenario', resource allocation to single scenario, lack of hedges",
+      "fix": "Frame scenarios as 'what if' not 'what will', test strategy robustness across all, identify no-regrets moves"
+    },
+    {
+      "failure": "Linear extrapolation",
+      "symptom": "Trends projected unchanged, ignores saturation/reversal/inflection, recent past = future",
+      "detection": "Exponential trends extended indefinitely, no consideration of limits or feedback",
+      "fix": "Analyze historical patterns for cycles, identify saturation limits, map feedback loops, consider discontinuities"
+    },
+    {
+      "failure": "Lagging signposts",
+      "symptom": "Signposts are outcome measures (market share, GDP) not leading indicators",
+      "detection": "Indicators move after trend materializes, no advance warning, reactive not proactive",
+      "fix": "Identify indicators with 6-12+ month lead time (permits not prices, proposals not laws, VC not revenue)"
+    },
+    {
+      "failure": "PESTLE cherry-picking",
+      "symptom": "Only 2-3 PESTLE dimensions scanned, missing entire domains, blind spots",
+      "detection": "Environmental or Legal dimensions absent, geographic scope limited to home market",
+      "fix": "Systematically cover all 6 PESTLE, even if some seem less relevant (surprises come from blind spots)"
+    },
+    {
+      "failure": "Stale scenarios",
+      "symptom": "Scenarios created once and never updated, signposts not monitored, strategy unchanged despite shifts",
+      "detection": "Scenario document >2 years old, no monitoring cadence, environmental shifts ignored",
+      "fix": "Quarterly signpost reviews, annual scenario validation, trigger-based updates when thresholds crossed"
+    },
+    {
+      "failure": "Analysis paralysis",
+      "symptom": "Endless scanning without synthesis, hundreds of trends tracked, no strategic implications",
+      "detection": "Reports are data dumps not decision memos, no clear recommendations, 'more research needed'",
+      "fix": "Time-box scanning (80/20 rule), focus on critical uncertainties, prioritize actionability over comprehensiveness"
+    },
+    {
+      "failure": "Missing cross-impacts",
+      "symptom": "Trends analyzed in isolation, interaction effects ignored, surprised by feedback loops",
+      "detection": "No cross-impact matrix, reinforcing/offsetting dynamics not mapped, additive not multiplicative thinking",
+      "fix": "Create interaction matrix, identify feedback loops (A→B→C→A), distinguish critical uncertainties from predetermined"
+    },
+    {
+      "failure": "Ignoring wild cards",
+      "symptom": "Focus only on likely scenarios, low-probability high-impact events dismissed, no contingencies",
+      "detection": "Scenarios all moderate outcomes, no discussion of tail risks or black swans, no resilience planning",
+      "fix": "Explicitly list wild cards (pandemic, breakthrough, collapse), create contingency for high-impact events, stress-test strategy"
+    }
+  ]
+}
--- a/skills/environmental-scanning-foresight/resources/methodology.md
+++ b/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.
--- a/skills/environmental-scanning-foresight/resources/template.md
+++ b/skills/environmental-scanning-foresight/resources/template.md
@@ -0,0 +1,364 @@
+# Environmental Scanning & Foresight Templates
+
+Quick-start templates for PESTLE scanning, weak signal detection, scenario development, and signpost setting.
+
+## 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**
+
+Use [Scanning Scope Definition](#scanning-scope-definition) to clarify scanning theme, geographic scope, time horizon, and key uncertainties.
+
+**Step 2: Scan PESTLE forces and trends**
+
+Systematically collect trends using [PESTLE Scanning Framework](#pestle-scanning-framework) across Political, Economic, Social, Technological, Legal, Environmental dimensions.
+
+**Step 3: Detect and validate weak signals**
+
+Identify early indicators using [Weak Signal Template](#weak-signal-template) with validation criteria for credibility, evidence, and impact potential.
+
+**Step 4: Assess cross-impacts and interactions**
+
+Map trend interactions using [Cross-Impact Analysis](#cross-impact-analysis) to identify reinforcing, offsetting, and cascading effects.
+
+**Step 5: Develop scenarios for plausible futures**
+
+Create 3-4 scenarios using [Scenario Development Template](#scenario-development-template) built around critical uncertainties.
+
+**Step 6: Set signposts and adaptive triggers**
+
+Define leading indicators using [Signpost Definition Template](#signpost-definition-template) with specific thresholds and monitoring cadence.
+
+---
+
+## Scanning Scope Definition
+
+**Scanning Theme**:
+- What aspect of environment? (Technology disruption, market evolution, regulatory shift, competitive dynamics, etc.)
+- What strategic questions? (Should we enter this market? Will our business model remain viable? What capabilities will we need?)
+
+**Geographic Scope**:
+- [ ] Global (worldwide trends)
+- [ ] Regional (continent, trade bloc)
+- [ ] National (country-specific)
+- [ ] Local (city, state, industry cluster)
+
+**Time Horizon**:
+- [ ] Short-term (1-2 years): Operational planning, current trend extrapolation
+- [ ] Medium-term (3-5 years): Strategic planning, inflection points
+- [ ] Long-term (5-10+ years): Visioning, transformational change, paradigm shifts
+
+**Key Uncertainties** (what we don't know that matters most):
+1.
+2.
+3.
+
+**Scanning Objectives** (what decisions will this inform?):
+-
+
+---
+
+## PESTLE Scanning Framework
+
+### Political
+
+**Government & Policy**:
+- Election outcomes and implications:
+- Policy priorities and shifts:
+- Political stability/instability:
+- Geopolitical tensions/alignments:
+
+**Regulation & Governance**:
+- Regulatory proposals in pipeline:
+- Deregulation or liberalization trends:
+- Government intervention patterns:
+- International agreements/treaties:
+
+**Sources**: Government announcements, policy think tanks, political risk indices, diplomatic cables
+
+### Economic
+
+**Macroeconomic Conditions**:
+- GDP growth/contraction forecasts:
+- Inflation and interest rate trends:
+- Employment and labor market:
+- Currency and exchange rates:
+
+**Market & Trade**:
+- Trade policy and tariff changes:
+- Foreign direct investment flows:
+- Supply chain and logistics costs:
+- Capital availability and credit:
+
+**Income & Spending**:
+- Income distribution and inequality:
+- Consumer spending patterns:
+- Savings and debt levels:
+
+**Sources**: Central bank reports, economic forecasts (IMF, World Bank), market data, trade statistics
+
+### Social
+
+**Demographics**:
+- Population growth/decline:
+- Age structure shifts (aging, youth bulge):
+- Migration patterns:
+- Urbanization trends:
+
+**Values & Culture**:
+- Shifting social values (sustainability, equity, individualism):
+- Trust in institutions:
+- Cultural movements and identity politics:
+- Generational attitudes (Gen Z, Millennials):
+
+**Lifestyle & Behavior**:
+- Work-life balance preferences:
+- Health and wellness trends:
+- Education and skill development:
+- Consumption patterns (sharing economy, minimalism):
+
+**Sources**: Census data, survey research (Pew, Gallup), social media trends, cultural commentary
+
+### Technological
+
+**Innovation & R&D**:
+- Breakthrough technologies emerging:
+- R&D investment levels and focus:
+- Patent filings in relevant domains:
+- Technology adoption curves:
+
+**Digital & Automation**:
+- Digitalization of industry:
+- AI and machine learning applications:
+- Robotics and automation:
+- Cybersecurity and data privacy tech:
+
+**Infrastructure**:
+- Broadband and connectivity expansion:
+- Cloud and edge computing:
+- Energy infrastructure and grids:
+- Transportation and logistics tech:
+
+**Sources**: Technology journals, patent databases, VC investment reports, tech conferences, research labs
+
+### Legal
+
+**Regulatory Frameworks**:
+- New laws and regulations:
+- Regulatory enforcement trends:
+- Compliance requirements expanding/contracting:
+- Cross-border regulatory harmonization:
+
+**Standards & Liability**:
+- Industry standards evolving:
+- Liability and litigation trends:
+- Intellectual property regime changes:
+- Data protection and privacy laws:
+
+**Sources**: Legislative trackers, regulatory agency announcements, legal journals, compliance advisories
+
+### Environmental
+
+**Climate & Weather**:
+- Climate change impacts (temperature, precipitation, extremes):
+- Physical risk to assets and operations:
+- Climate policy and carbon pricing:
+- Renewable energy adoption:
+
+**Resources & Pollution**:
+- Natural resource availability (water, minerals, land):
+- Pollution and waste management:
+- Circular economy and recycling:
+- Biodiversity and ecosystem health:
+
+**Sustainability**:
+- Corporate sustainability commitments:
+- Investor ESG pressure:
+- Consumer demand for sustainable products:
+- Supply chain sustainability requirements:
+
+**Sources**: IPCC reports, climate models, environmental agencies, sustainability indices, ESG ratings
+
+---
+
+## Weak Signal Template
+
+**Signal Identified**: [Brief description of anomaly or early indicator]
+
+**Source & Date**:
+- Where detected:
+- When observed:
+- Source credibility (high/medium/low):
+
+**Why This Is a Weak Signal** (not mainstream yet):
+- Diverges from current expectations:
+- Early/emergent (not widely recognized):
+- Edge of system (niche, subculture, fringe):
+
+**Validation Criteria**:
+- [ ] Source credibility: Is source reliable and knowledgeable?
+- [ ] Supporting evidence: Are there multiple independent confirmations?
+- [ ] Plausibility: Is amplification mechanism realistic?
+- [ ] Impact if scaled: Would this matter significantly?
+
+**Potential Amplification Path** (how could this scale?):
+-
+
+**Impact Assessment** (if signal amplifies):
+- Opportunities:
+- Threats:
+- Affected stakeholders:
+
+**Monitoring Plan**:
+- Track indicator:
+- Frequency:
+- Trigger for escalation:
+
+---
+
+## Cross-Impact Analysis
+
+Map how trends interact. Use matrix to identify reinforcing (accelerate), offsetting (tension), and cascading (trigger) relationships.
+
+**Key Trends Identified** (from PESTLE scan):
+1.
+2.
+3.
+4.
+5.
+
+**Interaction Matrix**:
+
+| Trend | 1 | 2 | 3 | 4 | 5 |
+|-------|---|---|---|---|---|
+| **1** | - |   |   |   |   |
+| **2** |   | - |   |   |   |
+| **3** |   |   | - |   |   |
+| **4** |   |   |   | - |   |
+| **5** |   |   |   |   | - |
+
+Legend: **+** = Reinforcing (accelerates), **-** = Offsetting (inhibits), **→** = Cascading (triggers), **0** = Independent
+
+**Critical Uncertainties** (high impact + high uncertainty):
+-
+-
+
+**Predetermined Elements** (high impact + low uncertainty):
+-
+-
+
+**Feedback Loops** (self-reinforcing or self-limiting):
+-
+
+---
+
+## Scenario Development Template
+
+### Scenario Structure (2x2 Matrix)
+
+**Critical Uncertainty 1** (Axis 1): [e.g., "Speed of Technology Adoption"]
+- High:
+- Low:
+
+**Critical Uncertainty 2** (Axis 2): [e.g., "Regulatory Stringency"]
+- High:
+- Low:
+
+**Four Scenarios**:
+
+#### Scenario A: [Name] (High Axis 1 + High Axis 2)
+- **Probability/Plausibility**:
+- **Key Drivers**:
+- **Narrative** (2-3 paragraphs describing this future):
+
+
+- **Strategic Implications**:
+
+
+#### Scenario B: [Name] (High Axis 1 + Low Axis 2)
+- **Probability/Plausibility**:
+- **Key Drivers**:
+- **Narrative**:
+
+
+- **Strategic Implications**:
+
+
+#### Scenario C: [Name] (Low Axis 1 + High Axis 2)
+- **Probability/Plausibility**:
+- **Key Drivers**:
+- **Narrative**:
+
+
+- **Strategic Implications**:
+
+
+#### Scenario D: [Name] (Low Axis 1 + Low Axis 2)
+- **Probability/Plausibility**:
+- **Key Drivers**:
+- **Narrative**:
+
+
+- **Strategic Implications**:
+
+
+**Wild Cards** (low probability, high impact events not captured in scenarios):
+-
+
+**No-Regrets Moves** (strategies that work across all scenarios):
+-
+
+**Hedges** (actions that protect in some scenarios):
+-
+
+---
+
+## Signpost Definition Template
+
+Signposts are leading indicators that trigger adaptive responses before trends fully materialize.
+
+**Signpost 1**:
+- **What to monitor**: [Specific observable indicator]
+- **Current baseline**:
+- **Threshold for action**: [Specific value or condition]
+- **Action triggered**: [What we do when threshold crossed]
+- **Data source**:
+- **Update frequency**:
+- **Lead time** (how far ahead of outcome?):
+
+**Signpost 2**:
+- **What to monitor**:
+- **Current baseline**:
+- **Threshold for action**:
+- **Action triggered**:
+- **Data source**:
+- **Update frequency**:
+- **Lead time**:
+
+**Signpost 3**:
+- **What to monitor**:
+- **Current baseline**:
+- **Threshold for action**:
+- **Action triggered**:
+- **Data source**:
+- **Update frequency**:
+- **Lead time**:
+
+**Monitoring Cadence**:
+- [ ] Weekly (fast-moving indicators)
+- [ ] Monthly (medium-term trends)
+- [ ] Quarterly (strategic review)
+- [ ] Annually (comprehensive environmental scan update)
+
+**Dashboard Location**: [Where are signposts tracked?]
+
+**Review Process**: [Who reviews? What triggers escalation?]