Techniques for Better Decision Making

You're not born a natural problem-solver. It's a skill that needs developing with time: Especially if you want to build a successful digital business.  Most people don't realise it,  But a founder's job is mostly just problem solving on repeat...    Day in and day out.  Over the last few years, I’ve used different problem-solving models Depending on what needed my attention:  💸 Keeping revenue consistent and predictable. 🔧 Setting a strategy that’s clear and actionable. ⭐️ Building a culture people actually want to be part of.  ⚙️ Running smooth operations, even when I’m not in the room. As you can imagine, each one requires a completely different approach. These are the four models that I return to most often 👇 🔍 First Principles Thinking ↳ Strip everything back and start from zero. 1. What do I know for sure about this problem? 2. What’s just a habit or assumption — not a fact? 3. If I had to build a solution from zero, what would it look like? 4. What if I forgot how this is “usually done”? 5. What’s the simplest possible version of solving this? 🔄 Second-Order Thinking ↳ Zoom out and see the bigger picture. 1. If this works... what else does it trigger? 2. What does this look like in 6 months? 2 years? 3. Am I solving a short-term pain or creating a long-term problem? 4. What unintended consequences could show up later? 5. What would someone smarter than me worry about here? 🧠 Root Cause Analysis ↳ Fix an entire system, not just a symptom. 1. What exactly went wrong — and when? 2. What’s the first thing that caused this to break down? 3. If I asked “why?” five times… where would I end up? 4. Where have we solved this badly before? 5. What keeps making this problem reappear? ⚡️ The OODA Loop ↳ When you just need to take the leap. 1. What’s actually happening right now — no bias, just facts? 2. What do I need to unlearn before I can move forward? 3. Based on what I know, what’s the smartest next decision? 4. What small test can I run immediately? 5. What would I change if I had to act in the next 10 minutes? It's easy to panic when an issue arises,  But it will do nothing to actually solve the problem. To problem solve like the top 1%,  You need to stop reacting emotionally... And start responding strategically. If you want to stay sharp under pressure,  My weekly newsletter will help you solve real business problems. Join Step by Step and get actionable insights every Sunday.👇 https://lnkd.in/eXSNaDiu I have other important lessons and 30+ free learning resources for you. What major problem did you solve recently, and how? Share your story in the comments. ⬇️ ♻️ Repost to help your network become better problem-solvers.  And follow Chris Donnelly for more. 

Stop wasting meetings! Too many meetings leave people unheard, disengaged, or overwhelmed. The best teams know that inclusion isn’t accidental—it’s designed. 🔹 Here are 6 simple but powerful practices to transform your meetings: 💡 Silent Brainstorm Before discussion begins, have participants write down their ideas privately (on sticky notes, a shared document, or an online board). This prevents groupthink, ensures introverted team members have space to contribute, and brings out more original ideas. 💡 Perspective Swap Assign participants a different stakeholder’s viewpoint (e.g., a customer, a frontline employee, or an opposing team). Challenge them to argue from that perspective, helping teams step outside their biases and build empathy-driven solutions. 💡 Pause and Reflect Instead of jumping into responses, introduce intentional pauses in the discussion. Give people 30-60 seconds of silence before answering a question or making a decision. This allows for deeper thinking, more thoughtful contributions, and space for those who need time to process. 💡 Step Up/Step Back Before starting, set an expectation: those who usually talk a lot should "step back," and quieter voices should "step up." You can track participation or invite people directly, helping create a more balanced conversation. 💡 What’s Missing? At the end of the discussion, ask: "Whose perspective have we not considered?" This simple question challenges blind spots, uncovers overlooked insights, and reinforces the importance of diverse viewpoints in decision-making. 💡 Constructive Dissent Voting Instead of just asking for agreement, give participants colored cards or digital indicators to show their stance: 🟢 Green – I fully agree 🟡 Yellow – I have concerns/questions 🔴 Red – I disagree Focus discussion on yellow and red responses, ensuring that dissenting voices are explored rather than silenced. This builds a culture where challenging ideas is seen as valuable, not risky. Which one would you like to try in your next meeting?  Let me know in the comments! 🔔 Follow me to learn more about building inclusive, high-performing teams. __________________________ 🌟 Hi there! I’m Susanna, an accredited Fearless Organization Scan Practitioner with 10+ years of experience in workplace inclusion. I help companies build inclusive cultures where diverse, high-performing teams thrive with psychological safety. Let’s unlock your team’s full potential together!

Do you rely on one large generalist model to power multiple use cases, or do you build a suite of specialized models fine-tuned for specific tasks? Large Language Models (LLMs) act as the generalists. One model can handle many functions across financial services: -Fraud Detection -Automated Investing -Customer Service Chatbots -Personalized Banking -Consumer Loan Underwriting -This flexibility makes them ideal for exploration, rapid prototyping, and -scenarios where breadth of understanding matters more than hyper-optimization. Small Language Models (SLMs) act as the specialists. Each is optimized for a single task, such as: -Loan Qualification -Consumer Loan Underwriting -Fraud Detection -The benefit? Efficiency, accuracy, and cost control. By narrowing the scope, SLMs can outperform generalist models in production environments where precision is non-negotiable. The Hybrid Future The reality isn’t LLM or SLM — it’s both. LLMs will serve as the reasoning engines, orchestrating complex workflows and bridging gaps across domains. SLMs will deliver deep expertise in critical tasks, ensuring enterprise-grade performance. This hybrid approach mirrors how organizations operate: broad leadership supported by domain experts. As AI adoption accelerates, companies that can strike the right balance between generalist adaptability and specialist efficiency will set the standard for the next wave of digital transformation. Question for you: In your industry, are you leaning more toward the power of generalist LLMs, the precision of SLMs, or a blended strategy?

If you’re an AI engineer trying to understand how reasoning actually works inside LLMs, this will help you connect the dots. Most large language models can generate. But reasoning models can decide. Traditional LLMs followed a straight line: Input → Predict → Output. No self-checking, no branching, no exploration. Reasoning models introduced structure, a way for models to explore multiple paths, score their own reasoning, and refine their answers. We started with Chain-of-Thought (CoT) reasoning, then extended to Tree-of-Thought (ToT) for branching, and now to Graph-based reasoning, where models connect, merge, or revisit partial thoughts before concluding. This evolution changes how LLMs solve problems. Instead of guessing the next token, they learn to search the reasoning space- exploring alternatives, evaluating confidence, and adapting dynamically. Different reasoning topologies serve different goals: • Chains for simple sequential reasoning • Trees for exploring multiple hypotheses • Graphs for revising and merging partial solutions Modern architectures (like OpenAI’s o-series reasoning models, Anthropic’s Claude reasoning stack, DeepSeek R series and DeepMind’s AlphaReasoning experiments) use this idea under the hood. They don’t just generate answers, they navigate reasoning trajectories, using adaptive depth-first or breadth-first exploration, depending on task uncertainty. Why this matters? • It reduces hallucinations by verifying intermediate steps • It improves interpretability since we can visualize reasoning paths • It boosts reliability for complex tasks like planning, coding, or tool orchestration The next phase of LLM development won’t be about more parameters, it’ll be about better reasoning architectures: topologies that can branch, score, and self-correct. I’ll be doing a deep dive on reasoning models soon on my Substack- exploring architectures, training approaches, and practical applications for engineers. If you haven’t subscribed yet, make sure you do: https://lnkd.in/dpBNr6Jg ♻️ Share this with your network 🔔 Follow along for more data science & AI insights

Bad decisions aren't usually about intelligence or experience⁣. ⁣ They're about making choices without a clear process⁣. ⁣ The best leaders don't have perfect judgment. ⁣ They have reliable systems that guide them toward better choices consistently⁣. ⁣ Here are 8 frameworks that turn decision-making from guesswork into strategy:⁣ ⁣ 1: The Reverse Advocate Protocol⁣ ↳ Assign someone to argue against your choice before finalizing any major decision.⁣ ↳ Challenging your own bias reveals blind spots and strengthens your final choice.⁣ ⁣ 2: The Energy Drain Audit⁣ ↳ Evaluate how much mental and emotional energy each option will require ongoing.⁣ ↳ High maintenance decisions often fail because they exhaust you before creating results.⁣ ⁣ 3: The Up/Down Impact Chain⁣ ↳ Trace how your decision will influence decisions that come before and after it.⁣ ↳ Single decisions create cascading effects that multiply their importance beyond immediate outcomes.⁣ ⁣ 4: The Constraint Liberation Test⁣ ↳ What would become possible if this decision removes your biggest current obstacle.⁣ ↳ The best decisions don't just solve problems they unlock entirely new opportunities.⁣ ⁣ 5: The Identity Alignment Filter⁣ ↳ Consider which option moves you closer to who you want to become as a leader.⁣ ↳ Decisions shape identity over time, and identity shapes all future decisions.⁣ ⁣ 6: The Network Effect Multiplier⁣ ↳ Evaluate how each choice affects your access to people, information, and opportunities.⁣ ↳ Great decisions don't just create direct value, they position you for better future decisions.⁣ ⁣ 7: The Teaching Test Framework⁣ ↳ Ask which decision you'd be most comfortable explaining and defending to your team.⁣ ↳ Choices you can't teach or justify usually indicate unclear thinking or misaligned values.⁣ ⁣ 8: The Pattern Break Analysis⁣ ↳ Identify whether this decision continues existing patterns or creates new ones.⁣ ↳ Sometimes the best choice is the one that breaks you out of cycles that aren't serving you.⁣ ⁣ What's one framework you use?⁣⁣ ⁣⁣⁣⁣ 💚 Follow Hetali Mehta, MPH for more.⁣⁣⁣⁣ 📌 Share this with your network.⁣⁣⁣⁣⁣⁣⁣⁣⁣ 👇Subscribe to my newsletter: https://lnkd.in/eFPeE4gQ

Researchers at UC San Diego and Tsinghua just solved a major challenge in making LLMs reliable for scientific tasks: knowing when to use tools versus solving problems directly. Their method, called Adapting While Learning (AWL), achieves this through a novel two-component training approach: (1) World knowledge distillation - the model learns to solve problems directly by studying tool-generated solutions (2) Tool usage adaptation - the model learns to intelligently switch to tools only for complex problems it can't solve reliably The results are impressive: * 28% improvement in answer accuracy across scientific domains * 14% increase in tool usage precision * Strong performance even with 80% noisy training data * Outperforms GPT-4 and Claude on custom scientific datasets Current approaches either make LLMs over-reliant on tools or prone to hallucinations when solving complex problems. This method mimics how human experts work - first assessing if they can solve a problem directly before deciding to use specialized tools. Paper https://lnkd.in/g37EK3-m — Join thousands of world-class researchers and engineers from Google, Stanford, OpenAI, and Meta staying ahead on AI http://aitidbits.ai

I'd like to share with you a powerful method that's been instrumental in our journey towards making more nuanced and balanced decisions. The Six Hat Solution, developed by Edward de Bono, is a powerful tool for teams and leaders. It's designed to help people explore different perspectives towards a complex situation or challenge, making our decision-making process more structured and comprehensive. 1. Emotional Viewpoint: Reflecting on our emotions offers initial insights. How does this situation make us feel? Personally, the prospect of our upcoming project invokes a mix of excitement and apprehension. Acknowledging our feelings can highlight potential concerns or areas of strong motivation. 2. Factual Analysis: Grounding our discussion in facts ensures a solid foundation. What are the undeniable truths of our current situation? With our project, the realities include our deadlines, budget constraints, and the resources at our disposal. These facts help clarify the scope of our challenge. 3. Optimistic Outlook: Focusing on the positives, we identify which aspects are most likely to succeed. In our scenario, the creativity and resilience of our team stand out as invaluable assets. This positivity is crucial for maintaining momentum. 4. Critical Perspective: Conversely, acknowledging what might not work allows us to anticipate and address potential issues. For us, the constraints of time and the untested nature of some technologies are concerns that need strategic planning. 5. Creative Exploration: By thinking creatively, we open the door to innovative solutions. Could adjusting our approach or incorporating new methodologies enhance our outcome? This phase pushes us beyond our initial assumptions. 6. Synthesised Solution: Finally, integrating all perspectives, we determine the most viable path forward. A phased project implementation, leveraging both proven and new technologies in stages, appears to be our best strategy. What complex decisions are you facing that could benefit from this multi-perspective approach? #leadership #mindset #culture #growth #success #problemsolving

Edward de Bono’s 6 Thinking Hats is a great way to stimulate coming up with effective decisions. Too often, teams default to one style of thinking, usually logical analysis or gut instinct. The 6 Hats force you to step outside that comfort zone and approach a challenge from multiple angles. Here’s your refresher, plus examples of questions that make each hat work: White Hat = Facts & Information Focus on data, not opinion. 𝘞𝘩𝘢𝘵 𝘥𝘰 𝘸𝘦 𝘬𝘯𝘰𝘸 𝘧𝘰𝘳 𝘤𝘦𝘳𝘵𝘢𝘪𝘯? 𝘞𝘩𝘢𝘵’𝘴 𝘮𝘪𝘴𝘴𝘪𝘯𝘨, 𝘢𝘯𝘥 𝘸𝘩𝘦𝘳𝘦 𝘥𝘰 𝘸𝘦 𝘨𝘦𝘵 𝘪𝘵? 𝘞𝘩𝘢𝘵’𝘴 𝘧𝘢𝘤𝘵 𝘷𝘦𝘳𝘴𝘶𝘴 𝘢𝘴𝘴𝘶𝘮𝘱𝘵𝘪𝘰𝘯 𝘥𝘪𝘴𝘨𝘶𝘪𝘴𝘦𝘥 𝘢𝘴 𝘧𝘢𝘤𝘵? Red Hat = Feelings & Intuition Bring emotions and instincts into the open. 𝘞𝘩𝘢𝘵’𝘴 𝘮𝘺 𝘨𝘶𝘵 𝘵𝘦𝘭𝘭𝘪𝘯𝘨 𝘮𝘦 𝘣𝘦𝘧𝘰𝘳𝘦 𝘐 𝘳𝘢𝘵𝘪𝘰𝘯𝘢𝘭𝘪𝘴𝘦 𝘪𝘵 𝘢𝘸𝘢𝘺? 𝘞𝘩𝘢𝘵 𝘧𝘦𝘦𝘭𝘪𝘯𝘨𝘴 𝘢𝘳𝘦 𝘰𝘵𝘩𝘦𝘳𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘳𝘰𝘰𝘮 𝘯𝘰𝘵 𝘷𝘰𝘪𝘤𝘪𝘯𝘨? 𝘞𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘶𝘯𝘴𝘱𝘰𝘬𝘦𝘯 𝘮𝘰𝘰𝘥 𝘢𝘳𝘰𝘶𝘯𝘥 𝘵𝘩𝘪𝘴 𝘪𝘴𝘴𝘶𝘦? Black Hat = Risks & Caution Stress-test the idea for weaknesses. 𝘞𝘩𝘦𝘳𝘦 𝘤𝘰𝘶𝘭𝘥 𝘵𝘩𝘪𝘴 𝘧𝘢𝘪𝘭 𝘪𝘯 𝘵𝘩𝘦 𝘳𝘦𝘢𝘭 𝘸𝘰𝘳𝘭𝘥? 𝘞𝘩𝘢𝘵 𝘶𝘯𝘪𝘯𝘵𝘦𝘯𝘥𝘦𝘥 𝘤𝘰𝘯𝘴𝘦𝘲𝘶𝘦𝘯𝘤𝘦𝘴 𝘤𝘰𝘶𝘭𝘥 𝘸𝘦 𝘵𝘳𝘪𝘨𝘨𝘦𝘳? 𝘞𝘩𝘢𝘵 𝘸𝘰𝘶𝘭𝘥 𝘰𝘶𝘳 𝘩𝘢𝘳𝘴𝘩𝘦𝘴𝘵 𝘤𝘳𝘪𝘵𝘪𝘤 𝘴𝘢𝘺? Yellow Hat = Benefits & Optimism Search deliberately for positives. 𝘞𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘩𝘪𝘥𝘥𝘦𝘯 𝘰𝘱𝘱𝘰𝘳𝘵𝘶𝘯𝘪𝘵𝘺 𝘩𝘦𝘳𝘦? 𝘐𝘧 𝘵𝘩𝘪𝘴 𝘴𝘶𝘤𝘤𝘦𝘦𝘥𝘴, 𝘸𝘩𝘢𝘵 𝘦𝘭𝘴𝘦 𝘮𝘪𝘨𝘩𝘵 𝘪𝘵 𝘶𝘯𝘭𝘰𝘤𝘬? 𝘏𝘰𝘸 𝘤𝘰𝘶𝘭𝘥 𝘵𝘩𝘪𝘴 𝘪𝘮𝘱𝘳𝘰𝘷𝘦 𝘵𝘩𝘪𝘯𝘨𝘴 𝘣𝘦𝘺𝘰𝘯𝘥 𝘰𝘶𝘳 𝘰𝘳𝘪𝘨𝘪𝘯𝘢𝘭 𝘨𝘰𝘢𝘭? Green Hat = Creativity & Alternatives Push for fresh thinking. 𝘞𝘩𝘢𝘵 𝘪𝘥𝘦𝘢𝘴 𝘩𝘢𝘷𝘦𝘯’𝘵 𝘸𝘦 𝘥𝘢𝘳𝘦𝘥 𝘵𝘰 𝘷𝘰𝘪𝘤𝘦 𝘺𝘦𝘵? 𝘞𝘩𝘢𝘵 𝘸𝘰𝘶𝘭𝘥 𝘸𝘦 𝘥𝘰 𝘪𝘧 𝘵𝘩𝘦𝘳𝘦 𝘸𝘦𝘳𝘦 𝘯𝘰 𝘭𝘪𝘮𝘪𝘵𝘴? 𝘞𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 “𝘵𝘩𝘪𝘳𝘥 𝘰𝘱𝘵𝘪𝘰𝘯” 𝘣𝘦𝘺𝘰𝘯𝘥 𝘺𝘦𝘴 𝘰𝘳 𝘯𝘰? 𝐁𝐥𝐮𝐞 𝐇𝐚𝐭 = 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 & 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 Manage the thinking itself. 𝘞𝘩𝘦𝘳𝘦 𝘢𝘳𝘦 𝘸𝘦 𝘴𝘵𝘶𝘤𝘬 𝘪𝘯 𝘰𝘯𝘦 𝘮𝘰𝘥𝘦 𝘰𝘧 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨? 𝘞𝘩𝘢𝘵’𝘴 𝘵𝘩𝘦 𝘣𝘦𝘴𝘵 𝘰𝘳𝘥𝘦𝘳 𝘵𝘰 𝘦𝘹𝘱𝘭𝘰𝘳𝘦 𝘵𝘩𝘦 𝘩𝘢𝘵𝘴 𝘵𝘰𝘥𝘢𝘺? 𝘏𝘰𝘸 𝘸𝘪𝘭𝘭 𝘸𝘦 𝘥𝘦𝘤𝘪𝘥𝘦 𝘸𝘩𝘦𝘯 𝘵𝘩𝘦 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨 𝘱𝘩𝘢𝘴𝘦 𝘪𝘴 𝘥𝘰𝘯𝘦? Used well, the 6 Hats stop you from circling the same answers. They create disciplined diversity of thought and with it, stronger solutions.

We failed terribly at it. We were in a meeting with former colleagues some time back. Our weekly meetings typically involved discussions with the marketing team. This time around, we had secured a client and were tasked with deciding on a campaign strategy. After a lengthy discussion, someone suggested a bold and risky approach. As conventional as it was, not a single soul objected. We all nodded in agreement, though our faces betrayed hesitation. A month later, the campaign failed. During the analysis, it was revealed that no one had genuinely supported the decision in the first place. Each team member admitted that they had gone along with it, assuming that everyone else was in favor. "I didn't want to be the one to hold us back," Eli confessed. "I thought everyone was on board, so I kept quiet," another chimed in. This is a classic example of the Abilene Paradox. It's a situation where a group collectively makes a decision that none of its members actually support. Thinking about it now... We suppressed our opinions to avoid conflict, given the hierarchical nature of the team. However, to avoid falling into this paradox, leaders should: - Use anonymous voting for critical decisions - Ask for specific objections or alternative ideas - Normalize respectful disagreement during discussions - Encourage team members to voice their honest opinions - Create a culture where speaking is rewarded, not penalized - Remind the team that disagreements leads to better outcomes Did you know about the Abilene Paradox?

You don’t grow by avoiding conflict. You grow by learning how to handle it better than most. In high-performing teams, disagreements are normal. But the professionals who move ahead don’t get defensive or emotional—they bring clarity, control, and direction. Dr. Edward de Bono’s Six Thinking Hats is a sharp framework that helps you do just that. Each hat trains your mind to think from a different angle: 🔹 White Hat – Stick to the facts. Leave ego at the door. 🔹 Red Hat – Understand emotions. Yours and others. 🔹 Black Hat – Anticipate the risks. Be the voice of reason. 🔹 Yellow Hat – Look for the positives. Find the hidden opportunity. 🔹 Green Hat – Break patterns. Bring in creative solutions. 🔹 Blue Hat – Lead the process. Keep the conversation focused. Want to be seen as someone who’s ready for the next level? Handle conflict like someone who already belongs there. Because leaders aren’t the loudest in the room. They’re the ones who know how to think through tension, not just survive it.