Foresight Scenarios Toolkit

A complete system for turning strategic uncertainty into better decisions.

🚀 Use this tool live → — No installation required. Try it in your browser.

This isn't just another scenario planning guide. It's an operational toolkit that takes you from "we should think about the future" to "here's what we're doing about it."

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Who This Is For

You Are	Your Problem	How This Helps
Strategy leader	Board wants to see we've thought about uncertainty	Structured scenarios with probability tracking
Risk manager	Current risk register assumes one future	Stress-test against multiple plausible worlds
Policy advocate	Need to argue for different regulatory approaches	Scenario-based framing for stakeholder engagement
Startup founder	Betting the company on assumptions about the future	Identify which assumptions matter most
Foresight practitioner	Scenarios die in slide decks	Operational system that keeps scenarios alive

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What Makes This Different

Most scenario planning produces nice documents that gather dust. This toolkit solves that with:

1. Decision Framework — Explicit methods to translate scenarios into strategic choices
2. Indicator Tracking — Early warning system to detect which scenario is emerging
3. Contingency Playbooks — Pre-developed responses so you can move fast
4. Weekly Operations — 30-minute scanning rhythm that keeps scenarios current
5. Workshop Guides — Step-by-step facilitation for running sessions

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Quick Start

# Clone the repo
git clone https://github.com/delschlangen/foresight-scenarios-toolkit.git
cd foresight-scenarios-toolkit

# Generate outputs from the AI governance example
python scripts/generate_matrix.py
python scripts/generate_indicators.py

# See example weekly scan
cat examples/weekly_scan.md

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What's Included

Framework (framework/)

Document	Purpose
method.md	Four-stage foresight methodology
drivers.md	Example: 12 AI governance drivers analyzed
uncertainties.md	How to select critical uncertainties
scenarios.md	Four complete scenario narratives
indicators.md	10 signals with thresholds and sources
decisions.md	NEW: How to use scenarios in decision-making
contingency.md	NEW: Pre-built response playbooks

Guides (guides/)

Guide	Purpose
adaptation.md	NEW: Step-by-step domain adaptation with worked example
facilitation.md	NEW: How to run scenario workshops

Scripts (scripts/)

Script	Purpose
generate_matrix.py	Creates 2x2 matrix from config
generate_indicators.py	Creates indicator register from config

Examples (examples/)

File	Description
scenario_matrix.md	Generated 2x2 with probabilities
indicator_register.md	Complete monitoring register
weekly_scan.md	Sample horizon scan with 6 signals

Templates (templates/)

Blank templates with [FILL IN] placeholders and instructions for building your own scenarios:

Template	Purpose
drivers_template.md	Driver analysis form with STEEP+T categories
scenario_template.md	Scenario narrative structure with quality checklist
indicator_template.md	Indicator definition with source library
weekly_scan_template.md	Horizon scan log with action tracking

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The Methodology

DRIVERS → UNCERTAINTIES → SCENARIOS → INDICATORS → DECISIONS
   ↓            ↓             ↓            ↓            ↓
 12 forces   2 axes       4 worlds    10 signals   Action
 analyzed    selected     developed   monitored    triggers

Stage 1: Identify Drivers Map 10-15 forces shaping your focal question using STEEP+T framework.

Stage 2: Select Uncertainties Choose 2 high-impact, high-uncertainty drivers as scenario axes.

Stage 3: Build Scenarios Develop 4 narrative futures for each quadrant of the 2x2 matrix.

Stage 4: Define Indicators Create early warning signals for each scenario.

Stage 5: Connect to Decisions Stress-test strategies, find robust moves, build contingency plans.

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Use Cases

Use Case 1: Strategic Planning

Situation: Annual strategy refresh, board wants assurance we've considered multiple futures.

How to Use:

1. Run workshop using guides/facilitation.md
2. Test current strategy against all 4 scenarios
3. Identify robust moves that work across scenarios
4. Build contingency triggers for scenario-specific responses

Deliverable: Strategy document with scenario stress-testing section.

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Use Case 2: Investment Decision

Situation: Major capital allocation decision with 5+ year horizon.

How to Use:

1. Define focal question around the investment decision
2. Build scenarios around key uncertainties
3. Calculate expected value of investment under each scenario
4. Set decision triggers: "If scenario X probability exceeds 40%, we [action]"

Deliverable: Investment memo with scenario-weighted analysis.

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Use Case 3: Policy Advocacy

Situation: Advocating for regulatory approach to emerging technology.

How to Use:

1. Build scenarios showing different regulatory futures
2. Identify which scenario aligns with your preferred policy
3. Develop indicator-based arguments: "Early signs suggest [scenario], which supports [policy]"
4. Prepare responses for alternative scenarios

Deliverable: Policy brief with scenario-based framing.

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Use Case 4: Risk Management

Situation: Enterprise risk register assumes a single future.

How to Use:

1. Map current risks to scenario likelihoods
2. Identify scenario-specific risks not currently tracked
3. Stress-test controls against each scenario
4. Add scenario probability to risk weighting

Deliverable: Enhanced risk register with scenario overlays.

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Use Case 5: Ongoing Horizon Scanning

Situation: Leadership wants regular updates on strategic environment.

How to Use:

1. Set up indicator monitoring per indicators.md
2. Run weekly 30-minute scans
3. Update scenario probabilities monthly
4. Trigger strategic review when thresholds crossed

Deliverable: Weekly scan memo, monthly probability dashboard.

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The AI Governance Example

The included example focuses on AI governance 2024-2030:

Focal Question: How will AI governance evolve, and what does that mean for strategy?

Axes:

• AI Capability: Incremental ↔ Discontinuous
• Regulation: Fragmented ↔ Harmonized

Scenarios:

1. Coordinated Caution — Orderly governance before capabilities leap
2. Emergency Coordination — Crisis forces cooperation
3. Patchwork Progress — Steady advancement, messy governance
4. Fragmented Scramble — Transformative AI with minimal guardrails

This example is fully worked through all stages, including indicators, weekly scans, and decision implications.

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Adapting for Your Domain

The methodology applies to any strategic foresight need. See guides/adaptation.md for step-by-step instructions with a worked example (energy transition).

Domains this works for:

• Geopolitical risk
• Technology adoption/disruption
• Market/competitive dynamics
• Regulatory landscapes
• Climate/sustainability futures
• Supply chain resilience
• Workforce evolution

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Operational Rhythm

Frequency	Activity	Time	Output
Weekly	Indicator scan	30 min	Signal log
Monthly	Probability review	1-2 hrs	Updated probabilities
Quarterly	Deep scenario review	Half day	Narrative updates if needed
Annually	Full reassessment	1-2 days	Refresh drivers and scenarios

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Project Structure

foresight-scenarios-toolkit/
├── framework/
│   ├── method.md           # Core methodology
│   ├── drivers.md          # Driver analysis example
│   ├── uncertainties.md    # Uncertainty selection
│   ├── scenarios.md        # Four scenario narratives
│   ├── indicators.md       # Indicator register
│   ├── decisions.md        # Decision framework
│   └── contingency.md      # Contingency playbooks
├── guides/
│   ├── adaptation.md       # Domain adaptation
│   └── facilitation.md     # Workshop guide
├── templates/
│   ├── drivers_template.md     # Blank driver analysis
│   ├── scenario_template.md    # Blank scenario structure
│   ├── indicator_template.md   # Blank indicator register
│   └── weekly_scan_template.md # Blank scan log
├── scripts/
│   ├── generate_matrix.py
│   ├── generate_indicators.py
│   ├── scenarios_config.json
│   └── indicators_config.json
├── examples/
│   ├── scenario_matrix.md
│   ├── indicator_register.md
│   └── weekly_scan.md
├── README.md
└── LICENSE

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Getting Started

Option A: Learn the methodology

1. Read framework/method.md for the four-stage process
2. Study the AI governance example across framework/*.md
3. Review framework/decisions.md for the action framework

Option B: Run a workshop

1. Start with guides/facilitation.md
2. Adapt the agenda for your context
3. Use guides/adaptation.md for non-AI domains

Option C: Set up ongoing scanning

1. Define your scenarios (or use/adapt the example)
2. Configure indicators in scripts/indicators_config.json
3. Run python scripts/generate_indicators.py
4. Establish weekly scanning rhythm

Option D: Build from templates

1. Copy templates from templates/ to your working directory
2. Fill in [FILL IN] placeholders with your domain content
3. Use hints and instructions embedded in each template
4. Reference framework/ examples for guidance

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Live Demo

Use this tool directly in your browser: https://delschlangen.github.io/foresight-scenarios-toolkit

No installation or dependencies required.

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References

• Schwartz, P. (1991). The Art of the Long View
• Shell Scenarios Team. Scenarios: An Explorer's Guide
• Wilkinson, A. & Kupers, R. (2014). The Essence of Scenarios
• IFTF. Foresight Toolkit

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License

MIT License — See LICENSE

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Built by Del Schlangen | LinkedIn