Scenario Planning Methods

Strategy is all about anticipating and creating a desired future. To prepare for this, it is essential to understand the Futures Cone, outlining five types of future. There is no such thing as “the future.” It all depends on what we mean, how far we look ahead and on whether we are trying to predict or create the future. One of the most helpful tools to understand this is Hancock and Bezolt’s (1994) “Futures Cone.” It describes five different types of future. They are PROJECTED FUTURE The future we tend to get when we simply stick to business as usual and extrapolate the current baseline strategy. It’s more of the same and contains the least uncertainty. PROBABLE FUTURE The future that most likely is going to happen, taking into account trends and developments within and outside the organization. It’s a bit more uncertain, but still quite predictable. PLAUSIBLE FUTURE The future that could happen according to our current knowledge. This is broader than just the probable future and includes futures that we could foresee rather than just expect. POSSIBLE FUTURE The broadest type of future, including everything that might happen. This is the realm of our imagination and extends beyond our current knowledge, tools and technologies. PREFERABLE FUTURE The future that we want to happen. This is different from the four above as it reflects our desires, preferences and intentions rather than what we cognitively can anticipate. As the image illustrates, the Preferable Future often deviates from the Projected Future (business as usual) or Probable Future (following the trends). This means it requires active imagination and bringing in our desires and intentions to imagine a future that is different. At the same time, it also shows that the Preferable Future should mostly reside within the boundaries of the Plausible Future with perhaps a touch of the Possible Future. Otherwise the gap between where you are today and how you want your future to look is too big. This is where the distinction is made between organizations that make smaller, incremental changes, and those that create breakthrough innovations. The further you can stretch your Preferred Future away from the Projected Future towards the Plausible and Possible Futures, the more visionary you need to be, and the more you will be an industry leader. Here’s the question for you: where is your Preferred Future targeted—more of the same (Projected or Probable) or at creating something new (Plausible and Possible)? — For more useful strategy and leadership content, join my Soulful Strategy newsletter: https://lnkd.in/eKjb8Uss #forecast #futureinsight #impactleaders

💡 A Practical Guide to Climate Scenarios! Really pleased to have written the forward to this valuable report on the types and applications of climate scenarios by MSCI Inc. and my former United Nations Environment Programme Finance Initiative (UNEP FI) FI colleagues Looking for a handy summary of the types of scenarios from qualitative to quantitative? Here it is: 1. 𝗙𝘂𝗹𝗹𝘆 𝗡𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀 These scenarios are qualitative descriptions of potential climate futures. ✅ Strengths: - Easily customizable - Useful for high-level strategic discussions - Can capture complex risks that are difficult to quantify ⚠️ Limitations: - Subjective and vulnerable to bias - Lack of numerical outputs makes them hard to integrate into risk models 2. 𝗤𝘂𝗮𝗻𝘁𝗶𝗳𝗶𝗲𝗱 𝗡𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀 This type builds on fully narrative scenarios by adding expert-driven quantitative estimates (macroeconomic forecasts, asset class returns, regional physical risks). ✅ Strengths: - Balances qualitative storytelling with numerical data - Allows for scenario comparisons without requiring sophisticated models - Easier to communicate results with clear quantitative insights ⚠️ Limitations: - Can give a false sense of precision if assumptions are weak - Still dependent on subjective expert input, leading to potential biases 3. 𝗠𝗼𝗱𝗲𝗹-𝗗𝗿𝗶𝘃𝗲𝗻 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀 These scenarios rely on integrated quantitative models to project how climate change and transition risks might evolve under different policy and economic conditions, using macroeconomic models, IAMs, and energy system models. ✅ Strengths: Highly structured and data-driven, reducing subjectivity. Can produce detailed, sector-specific outputs useful for investment decisions. Widely used by regulators and financial institutions for stress testing. ⚠️ Limitations: - Expensive and time-consuming to develop and maintain - “Black box” nature of complex models makes interpretation difficult - Results are only as good as underlying assumptions and data inputs 4. 𝗣𝗿𝗼𝗯𝗮𝗯𝗶𝗹𝗶𝘀𝘁𝗶𝗰 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀 Probabilistic models go beyond single-scenario forecasting by assigning probabilities, variance, and uncertainty estimates to different climate outcomes. ✅ Strengths: - Models uncertainty, improving risk management - Enables sophisticated stress testing for asset prices, portfolios, and corporate exposure - Valuable for insurance, catastrophe modeling, and financial risk assessments ⚠️ Limitations: - Highly complex and computationally demanding - Requires strong assumptions about uncertainty - Limited research on how climate change affects probability distributions #ClimateFinance #ClimateScenarios #SustainableInvesting #RiskManagement #ScenarioAnalysis #Risk #Finance

NEW RESEARCH - WHY THE ENERGY TRANSITION IS DISRUPTIVE & COULD BE MUCH FASTER THAN WE THINK: The clean energy transition isn’t just about swapping out old tech for new—it’s a complex, non-linear process full of feedback loops, tipping points, and unexpected consequences. Our new “Systems Archetypes of the Energy Transition” brief is a must-read for anyone shaping policy, investing, or innovating in this space. Key takeaways: 1) Feedback loops drive change: Reinforcing loops (like learning-by-doing and economies of scale) have made solar, wind, and batteries cheaper and more widespread, often outpacing even the boldest forecasts. 2) Path dependence is real: Early advantages for a technology (think BEVs vs. hydrogen cars) can snowball into market dominance, making policy choices and timing critical. 3) Limits and synergies: As renewables grow, market dynamics like “cannibalisation” can dampen investment—unless we design markets and storage solutions to keep the momentum going. 4) Policy design is everything: Well-intentioned fixes (like price caps or broad subsidies) can backfire, while smart, targeted interventions can unlock positive feedbacks across sectors. 5) Tipping points and decline: The decline of fossil fuels isn’t just a mirror image of clean tech growth—it comes with its own feedbacks, risks, and opportunities for a just transition. The brief also offers practical guidance on using causal loop diagrams and participatory systems mapping—powerful tools for understanding and managing the complexity of the transition. If you’re working on energy, climate, or innovation policy, I highly recommend giving this a read. Let’s move beyond linear thinking and embrace the systems view—because the future will be shaped by those who understand the dynamics beneath the surface. This briefing was led by Simon Sharpe at S-Curve Economics CIC, Max Collett 柯墨, Pete Barbrook-Johnson, me at Environmental Change Institute (ECI), University of Oxford & Oriel College, Oxford & the Regulatory Assistance Project (RAP) and Michael Grubb at UCL Institute for Sustainable Resources.

We hear all about the amazing progress of AI BUT, enterprises are still struggling with AI deployments - latest stats say 78% of AI deployments get stall or canceled - sounds like we’re still buying tools and expect transformation. But those that have succeeded? They don’t just license AI, they redesign work around them. Because adoption isn’t about the tool. It’s about the people who use it. Let’s break this down: 😖 Buying AI tools just adds to your tech stack. Nothing more, nothing less! Stat you can’t ignore: 81% of enterprise AI tools go unused after purchase. (Source: IBM, 2024) 🙌🏼 But adoption, adoption requires new workflows, new roles, and new routines - this means redesigning org charts, updating SOPs, and rethinking “a day in the life.” Why? Because AI should empower decisions—not just automate tasks. It should amplify human strengths—not quietly sideline them. That’s where the 65/35 Rule comes in! 65% of a successful AI deployment is redesigning business processes and preparing the workforce. Only 35% is tools and infrastructure. But most companies still do the reverse. They invest 90% in tech and 10% in training… and wonder why they’re stuck in “perpetual POC purgatory” (my term for things that never make production. It’s like buying a Formula 1 car and expecting your team to win races—without ever learning to drive. Here’s the better way: Step 1: Start with the “day in the life” Map how work actually gets done today. Not hypothetically. Not aspirationally. Just reality. Step 2: Identify friction points Where do delays, errors, or bad decisions happen? Step 3: Redesign with intent Now—and only now—do you introduce AI. Not to replace the human. But to support and strengthen them. Recommendation #1: Design AI solutions with your workforce, not just for them. Co-create roles, rituals, and reviews. Recommendation #2: Adopt the 65/35 Rule as your north star. If your AI strategy doesn’t spend more time on people and process than tools and tech… it’s not ready. ⸻ AI doesn’t fail because it’s flawed. It fails because the org using it is unprepared. #AI #FutureOfWork #DigitalTransformation #Leadership #OrgDesign #HumanInTheLoop #AIAdoption #DataDrivenDecisions #Innovation >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Sol Rashidi was the 1st “Chief AI Officer” for Enterprise (appointed back in 2016). 10 patents. Best-Selling Author of “Your AI Survival Guide”. FORBES “AI Maverick & Visionary of the 21st Century”. 3x TEDx Speaker

The best CEOs plan for 3 different scenarios at once (this transformed my approach to uncertainty): I used to create one "realistic" forecast each year. Then spend 12 months explaining why we missed it. Everything changed when I learned this framework from a mentor who'd scaled multiple companies: Plan 3 scenarios. Execute 1. Adapt quickly. 📊 BASE CASE (95% likely) "What happens if we maintain current performance?" - Focus on core strengths - Maintain spending discipline   - Protect 12+ months runway 🎯 STRETCH CASE (50/50 shot) "What can we achieve with focused execution?" - Expand into 1-2 new areas - Invest in proven ROI initiatives - Keep 6-12 months buffer 🚀 BOLD CASE (25% moonshot) "What's possible if everything goes right?" - Transform multiple areas - Accept lower margins for growth - Operate with 3-6 months runway The magic isn't having 3 spreadsheets. It's what happens when reality unfolds: Q1 tracking to BASE? → You've already planned for efficiency → Team knows exactly what to protect → No panic, just execution Q2 hitting STRETCH markers?  → Green light those strategic hires → Unlock the growth investments → Everyone knows the playbook Q3 approaching BOLD territory? → Time to accelerate aggressively → The plan is already approved → Full speed ahead Instead of surprising your team with pivots, they know all 3 paths from day one. Instead of emergency board meetings, you just point to which scenario you're tracking. Instead of reactive decisions, you make proactive moves based on clear triggers. The result? - Your team trusts the plan - Your investors respect your risk management - You sleep better knowing you're prepared Most importantly: You stop being surprised by reality. And start being ready for it. Every successful scale-up I know uses some version of this. Because uncertainty isn't the enemy. Being unprepared for it is. P.S. Ready to build your 3-scenario plan? Download my framework free:  https://lnkd.in/dhn9y3zq ♻️ Repost to help a leader in your network. Follow Eric Partaker for more planning insights. — 📢 Want to lead like a world-class CEO? Join one of my FREE TRAININGS THIS WEEK: "How to Develop the Mindset Shared by the World's Best CEOs" Wed, July 16th, 12 noon Eastern / 5pm UK time https://lnkd.in/dJRpFXnb "How to Successfully Scale Your Company & Become a World-Class Leader" Fri, July 18th, 12 noon Eastern / 5pm UK time https://lnkd.in/djt83NUz 📌 LAST CHANCE TO APPLY for the CEO Accelerator cohort, starting July 23rd. Learn more here and join 40+ Founders & CEOs: https://lnkd.in/dbE5rkYB

Climate Change Risk Assessments 🌎 Climate-related financial disclosure requirements are expanding across jurisdictions, increasing expectations for companies to assess and report on climate-related risks and opportunities. A structured climate change risk assessment (CCRA) is central to meeting these evolving regulatory demands. CCRAs evaluate both physical risks—such as extreme weather events, water stress, and sea level rise—and transition risks, including policy changes, carbon pricing, and shifts in market or technology landscapes. They also help identify potential opportunities linked to decarbonization, energy efficiency, and new revenue models. Scenario analysis is a core component. It enables companies to test strategic resilience under divergent climate pathways, including high-emissions futures and low-emissions transitions aligned with the Paris Agreement. Most regulatory frameworks now require both perspectives. Benefits of a robust CCRA include improved risk management, reduced exposure to disruptions, and strengthened alignment with investor expectations. Insights from these assessments can be embedded into enterprise risk systems, capital planning, and strategic roadmaps. Key challenges include short-term thinking in risk registers, limited access to forward-looking climate data, and misalignment between climate risk analysis and existing sustainability goals. These gaps can reduce the effectiveness of disclosures and slow organizational response. Recommended approaches include leveraging established scenarios (e.g. IPCC, IEA), integrating outputs into ERM systems, using frameworks like ISSB and TCFD for structure, and applying competitive benchmarking to validate assumptions. Cross-functional engagement improves practical relevance. As regulatory standards converge, CCRAs are becoming a baseline expectation. Those who develop structured, forward-looking assessments will be better positioned to adapt business models, manage uncertainty, and align with capital markets under increasing climate scrutiny. Source: Ramboll #sustainability #sustainable #business #esg #climatechange #risk

Accident Causation Models Accidents rarely occur due to a single failure. They usually result from a chain of weaknesses, missed controls, and hidden system gaps. Here are six widely used accident causation and analysis models every safety professional should know: 🧀 Swiss Cheese Model Shows that multiple safety layers exist in any system, but each layer has weaknesses (“holes”). When these holes align across layers, an accident occurs. Focus: strengthen barriers and reduce latent failures. 🎀 Bow Tie Model Visualizes risk from hazard → top event → consequences. Preventive controls are placed on the left side, and mitigation controls on the right. Focus: barrier management and control effectiveness. 🐟 Fishbone (Ishikawa) Diagram A root cause tool that categorizes contributing factors such as Man, Machine, Method, Material, Environment, and Measurement. Focus: structured brainstorming of causes. ❓ 5 Why Analysis A simple but powerful technique — keep asking “Why?” until the root cause is identified. Focus: digging beyond surface-level causes. 🌳 Fault Tree Analysis (FTA) A top-down logical model that maps how combinations of failures lead to a top event using AND/OR gates. Focus: system failure pathways. 🚦 Event Tree Analysis (ETA) A forward-looking model that starts from an initiating event and maps possible outcome paths depending on success or failure of safeguards. Focus: consequence and scenario analysis. ✅ Strong investigations don’t stop at “what happened” — they uncover why it became possible. #Safety #AccidentInvestigation #RiskManagement #HSE #RootCauseAnalysis #ProcessSafety #EHS #SafetyLeadership

NEW - AI Agent Adoption Guidance from Microsoft's Cloud Adoption Framework Over the past year working with customers, we’ve seen that controlling and standardizing agent development across an organization is top of mind for most leaders. To address this, we created our new AI Agent Adoption Guidance, and it is now publicly available in Microsoft’s Cloud Adoption Framework: Read the guidance here: https://lnkd.in/ehFWdaR5 Why should I use it? This guidance provides an end-to-end framework for AI agent adoption. It helps leaders move from planning to managing all their agents across an organization. It provides best practices at each stage and shows you how Microsoft Foundry and Microsoft Copilot Studio enable those recommendations. The guidance presents a practical sequence through Foundry and Copilot Studio that reflects how teams will naturally use them, mapping best practices to tool usage. It also covers data architecture with Microsoft Fabric, Foundry IQ, and Fabric IQ, as well as SaaS agents in Microsoft 365, GitHub Copilot, Microsoft Fabric, Azure Copilot, Dynamics 365, and Security Copilot agents This approach helps organizations understand how Microsoft supports their journey while enabling them to standardize and govern agent development with confidence. Who is the guidance for? If you are responsible for AI agents across your business, organization, or multiple teams, whether large or small, this guidance is for you. It is designed to help you govern, secure, and measure the success of all your AI agents. What is the process to adopt AI agents? AI agent adoption involves four key steps: 1. Plan for agents: How organizations should identify high-value use cases for AI agents, select the right technology, prepare teams, and ensure data readiness for scaling and governance.   2. Govern and secure agents: How to address governance, security, and observability across an organization, along with baseline policies and tools that support consistent implementation across the organization. 3. Build agents: When to build single-agent or multi-agent systems, plus how Foundry and Copilot Studio fit into the build process to help establish organizational standards. 4. Manage agents: Best practices for integrating agents into operations and managing them over time, including cost optimization, administration, and measuring adoption success. Questions? If you want the guidance to cover other topics, reach out to me on LinkedIn (DM) or on Reddit (MicrosoftCAF) Thank you to my Microsoft colleagues for their insights:  Jason Bouska, Timo Salomäki, Daniel Söderholm, Wandenkolk Tinoco Neto, Sree Lakshmi Adigopula, Piyush Jain, Bilal Amjad, Jorge Garcia Ximenez, Ben Brauer, Pablo Carceller Gonzalez, Philip Fumey, John Lunn, Brian Swiger Thank you to the following Microsoft Most Valuable Professionals (MVPs): Artem Chernevskiy, Edgar McOchieng', Vesa Nopanen [MVP], Sakshi Kokardekar Luke Nyswonger, Martin Ekuan, Hans Yang, Annie Pearl

Thrilled to share that BloombergNEF's 2025 New Energy Outlook is out! We've updated our base case Economic Transition Scenario, which charts out the evolution of the global energy sector based on deployment of cost-competitive technologies and existing policy mechanisms. Despite all of the uncertainty we see around us, NEO 2025 finds that wind, solar and batteries continue to enjoy economic advantages in most markets, and that these will drive their ongoing deployment over the coming decade and beyond. Renewable generation is up 84% by 2030 globally in our new scenario, confounding fears of a slowdown. By 2050, renewables supply more than two-thirds of a much-expanded global power system. We also see data centers driving new power demand, which creates both challenge and opportunity. They represent 4.5% of power demand by 2035, rising to 8.7% by 2050. This is a little less than EVs, but still a significant source of new demand. Importantly, our least-cost modeling shows that data centers are likely to drive consumption of both fossil and renewable power. In the years to 2035, data centers induce more fossil power than clean - in part driven by existing gas and coal generators whose lives are extended by the incremental demand. One exciting finding as that this base-case scenario sees global energy-related emissions (and coal usage) begin their long structural decline from this year onwards. In other words, both may have peaked in 2024. We hope this proves true! Oil on the other hand continues to rise until 2032, and decline thereafter. Gas rises all the way to 2050 and is up 25% by that year. Needless to say, these findings do not align to our Net Zero Scenario. The base case sees emissions drop just 22% to 2050, in line with 2.6 degrees of warming. To get aligned with the Net Zero Scenario (100% reduction by 2050) requires much faster adoption of clean technologies - especially those that are not currently cost-competitive, such as hydrogen, carbon capture, nuclear and sustainable aviation fuels. Whichever scenario you choose to believe (or even if you think the future doesn't quite align with either one), the energy transition continues to hold opportunity! Huge congratulations to the team that pulled off this crucial work, especially (but not only) David Hostert, Matthias Kimmel, Ian Berryman, Rodrigo Quintero, Seohee Song, Kostas Pegios, Anushka Verma and Amar Vasdev. Kudos to each of you. https://lnkd.in/gxvPtjP BNEF clients can find the full report and data set on our web portal and the Terminal, and will also find our deep dive on data centers and power in the US - also published today!

Want to know what's dominating CEO conversations? Here is the most recent data for Q1 2025 by Philipp Wegner with IoT Analytics - Hot off the Press as of March 25th! 𝐊𝐞𝐲 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬: • 𝐓𝐚𝐫𝐢𝐟𝐟𝐬 𝐓𝐚𝐤𝐞 𝐂𝐞𝐧𝐭𝐞𝐫 𝐒𝐭𝐚𝐠𝐞: CEO mentions of tariffs surged by 190%, surpassing previous peaks as companies grapple with new global trade tensions and policies. CEOs are actively exploring strategies to mitigate or even leverage these tariff impacts. • 𝐔𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐒𝐩𝐢𝐤𝐞𝐬: Mentions of uncertainty climbed 49% as geopolitical shifts and trade wars cloud strategic decisions, notably affecting the EMEA region and industrial sector most significantly. • 𝐀𝐈 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐞𝐬 𝐑𝐢𝐬𝐢𝐧𝐠 – 𝐄𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐥𝐲 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈: AI remains a priority, with an impressive 275% spike in discussions about Agentic AI—highlighting a strategic shift towards autonomous decision-making technologies designed to boost efficiency and innovation. • 𝐑𝐞𝐜𝐫𝐮𝐢𝐭𝐢𝐧𝐠 𝐇𝐢𝐭𝐬 𝐚 𝐅𝐫𝐞𝐞𝐳𝐞: Amid economic turbulence, CEOs scaled back conversations on hiring by 8% while hiring freeze mentions soared by 286%, signaling cautious approaches towards workforce expansion. 𝐌𝐲 𝐓𝐚𝐤𝐞: CEOs today face complex, interconnected challenges. They’re shifting from optimistic hiring and growth toward defensive positions amidst economic uncertainty and tariff complexities. At the same time, investments in innovative AI, particularly agentic AI, are viewed as strategic ways to navigate these turbulent waters. 𝟑 𝐏𝐢𝐞𝐜𝐞𝐬 𝐨𝐟 𝐀𝐝𝐯𝐢𝐜𝐞: 𝟏. 𝐑𝐞𝐚𝐬𝐬𝐞𝐬𝐬 𝐒𝐮𝐩𝐩𝐥𝐲 𝐂𝐡𝐚𝐢𝐧 𝐑𝐢𝐬𝐤𝐬: Evaluate your exposure to tariffs immediately. Move swiftly to adjust sourcing and production to maintain competitiveness. 𝟐. 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 𝐢𝐬 𝐂𝐫𝐮𝐜𝐢𝐚𝐥: Strengthen your organization's ability to rapidly respond to geopolitical shifts. Having robust contingency plans can provide stability in uncertain times. 𝟑. 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞 𝐀𝐈 𝐈𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭: Quickly identify and prioritize strategic AI investments—especially autonomous, agentic AI solutions—to drive productivity, agility, and market advantage despite hiring freezes. 𝐅𝐨𝐫 𝐦𝐨𝐫𝐞 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐨𝐧 𝐭𝐡𝐢𝐬 𝐫𝐞𝐩𝐨𝐫𝐭: https://lnkd.in/eWWMt47K ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!