Problem Framing Skills for Freelance Professionals

It's rather easy to get 6-figure advice. 💰 Ask a 6-figure question. 💡 I'm in multiple online communities and often see the question: "How do I get into freelance consulting?" I hate to say it… but that's a terrible question. Think about it. Do you go to a financial advisor with a one-line question and expect a comprehensive strategy for debt, retirement accounts, cash flow, diversification strategies, etc.? What about when you approach mentors, CPAs, therapists? Do you just hit 'em with the one-liner? Of course you don't. If you have an important question with massive implications, you can almost always get a great answer — which most experts are willing to provide — if you simply invest in your question. Frame it as follows: 𝟭) 𝗢𝗻𝗲-𝗹𝗶𝗻𝗲 𝘀𝘂𝗺𝗺𝗮𝗿𝘆 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝟮) 𝗪𝗵𝗮𝘁 𝘆𝗼𝘂'𝗿𝗲 𝘁𝗿𝘆𝗶𝗻𝗴 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝗳𝗼𝗿 — i.e. how you're balancing trade-offs. In the case of freelance consulting: freedom? Work-life balance? Hourly rate? Net revenue? Margin on subcontractors? 𝟯) 𝗟𝗶𝘀𝘁 𝘆𝗼𝘂𝗿 𝗸𝗻𝗼𝘄𝗻𝘀 𝗮𝗻𝗱 𝘆𝗼𝘂𝗿 𝘂𝗻𝗸𝗻𝗼𝘄𝗻𝘀. For unknowns, share your hypotheses and why (sources you’ve read that suggest A, B, or C). Mention books, communities, courses, influencers, etc. that you've read or followed. 𝟰) 𝗟𝗶𝘀𝘁 𝘆𝗼𝘂𝗿 𝗰𝗼𝗻𝘀𝘁𝗿𝗮𝗶𝗻𝘁𝘀. Are you financially constrained? Time constrained? Legally constrained (non-competes)? Constrained by mental or physical health challenges? (You’d be surprised how many entrepreneurs can relate 💬) 𝟱) 𝗦𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗲 𝘁𝗵𝗲 𝗯𝗶𝗴 𝗽𝗶𝗰𝘁𝘂𝗿𝗲 — distill it into the 3 most critical questions. Even better: organize your thoughts clearly, run them past an LLM 🤖, document concisely (bullets, visuals), and invite experts to critique as a linked doc. And if you’re in Discord or Slack… have this discussion in a thread, not the main channel. Your audience will thank you 🙌 — and then they will help you.

McKinsey taught me that brilliant people fail when they answer the wrong question. Don’t just answer questions. Frame them. Because a brilliant answer to the wrong question is still wrong. Ask, “How do we make customer support more efficient?” and everyone races to cut headcount or automate. You might save dollars and bleed trust. Try this instead: “What service approach builds loyalty while balancing cost?” Now you are designing for humans, not just a spreadsheet. How you frame a question shapes what you notice, what you measure and what you ship. Daniel Kahneman and Amos Tversky called this the framing effect. It’s one of the most underrated leadership skills. I learnt the value of spending time on framing the question in my 10 years at McKinsey. At first it felt forced. But projects where we invested serious time up front to define the question led to sharper insights, faster decisions and happier teams & clients. When we didn’t take the time, chaos reigned. Put it into practice this week: 1. Question the question. ↳ What assumptions are baked in? What if you flipped it on its head? 2. Start at the finish line. ↳ Define outcome or experience you want, then trace back the decisions and actions that create it. 3. Make space for the devil’s advocate. ↳ Assign someone to challenge whether you’re even solving the right problem. If you work with data or roll out new tech, your analysis is already shaping outcomes. Make sure you’re shaping the right ones. Have you ever felt like you’ve missed the mark on the question you’re answering? What's one question your team has been wrestling with that might need a reframe? ♻️ Repost to help someone get their question right. 🔔 Follow Clare Kitching for insights on unlocking value with data & AI.

Three skills I wish I had honed before transitioning from #academia to #industry. When I first leaped into #AI and #optimization consulting, I thought it was all about clever math and elegant models. Spoiler: it is—but it’s also so much more. Here are the three complementary skills I wished I had dedicated more time to sharpening while still in school and how to sharpen them. 🖼️ 1. Problem Framing During the #PhD, problems were well-defined, data was clean, the goal was clear, and at times even the solutions were known. Real #business applications on the other hand have error-filled data, ambiguous problem statements, and constantly changing goals. Learning to deal with this ambiguity, in particular identifying the right problem to solve is 80% of the value of industrial projects. How to sharpen: Practice asking why all the time. Build the reflex of questioning your assumptions and actively seek people to poke holes in your logic. Learning what to ask is more important than knowing what to say to correctly frame the problem. 🤝 2. Collaborative building No one builds critical enterprise applications alone. If you can't collaborate with your business partners, stakeholders, engineers and fellow scientists your application will have no business impact. How to sharpen: Explain your research to experts in other fields, to non-technical people, and to young children. Try to make them excited about what you're working on and listen to what parts they struggle to understand to find simpler explanations. Learn to use collaborative #software development tools such as Git and Jira. Learning to write tasks and objectives clearly while learning how to work in parallel without breaking a common codebase will make your team 10x more productive. 📈 3. Quickly iterating No one gets it right the first time. Not because they're not great scientists, but because the beginning of projects are more about discovery than solutions. Where most incoming grads have a hard time is with dealing with the frustration of moving targets. How to sharpen: Practice building models and algorithms that are flexible by thinking of generalizations and extensions beyond immediate use. Try to put yourself in the shoes of the person with the problem and think about the different interactions they'd like to capture. Learn to follow good software development practices that allow easily extending to cover these generalizations. 💡 Final thought: Optimization is a powerful toolkit. But the real art lies in applying it with empathy, clarity, and business awareness. To all the newcomers out there: You’re entering a field that’s both intellectually rewarding and deeply practical. Welcome aboard. Now go make something better. 🌍✨ #DecisionScience #DecisionIntelligence #softskills #Technology #SoftwareEngineering Image Source: Open Art

Clients almost never tell you what they really need. They say: “We’re growing fast.” Translation: We might have supply issues. Or we need a strategy to leverage this growth. They say: “We’ve got a big launch coming up.” Translation: We’re restless, unsure, and need certainty that it won’t flop. This is where freelancers miss the gold. They hear words. But not the signal underneath. Your edge isn’t just doing the work. It’s reading between the lines! 3 ways to practice this skill: 1. Write down the exact phrases clients use. Then translate them into business risks or goals. 2. Ask clarifying questions. “When you say growth, what’s the biggest challenge that creates?” 3. Treat subtext as scope. If they’re hinting at uncertainty, sell them clarity. Freelancers who only solve stated problems get one gig. Freelancers who solve real problems get the client for life. P.S. Follow me for more practical steps to build a strong, sustainable freelance business.

One valuable skill I never learned in a course! I’ve taken more courses than I can count - Python, SQL, data visualization, machine learning. And while all of them have made me sharper in my craft, the skill that’s changed my career the most? It wasn’t listed in any curriculum. I stumbled upon it through trial, error, and more than a few “why didn’t I think of this sooner?” moments. The skill? Learning how to frame the problem before jumping to the solution. In my early days as a data analyst, I used to get so excited about building dashboards or writing complex queries that I’d rush straight into “doing.” But often, halfway through, I’d realize the stakeholder actually wanted something completely different or worse, they weren’t sure themselves. It’s in those first conversations where you listen, ask better questions, and understand the “why” behind the request. The moment you start focusing on defining the problem well, everything else falls into place. You save hours of rework. You avoid misalignment. This skill has helped me earn trust in ways no technical trick ever could. The funny thing? It’s also made my technical skills shine more because they’re being applied in the right direction. If there’s one thing I’ve learned, it’s this: Tools and code are only as valuable as the clarity of the problem they’re solving. So if you’re starting out in your career or even if you’re seasoned, spend more time up front understanding the “why.” Ask better questions. Be curious. #storytelling #datavisualization #data #career #careertips

Two months into my VP of Technology role, I'm on a plane to evaluate a multi-million dollar acquisition. This was my moment to prove myself. I spent three days interviewing their team, analyzing their infrastructure, documenting every technical issue. Walking into my CEO's office, I was confident: "I don't think we should buy this company." I laid out all the technical problems—legacy code, infrastructure gaps, integration nightmares. His response? "Okay, we're going to buy it anyway." Wait, what? The visible factors looked like textbook due diligence: Technical analysis, stakeholder interviews, system evaluation. I thought I was being thorough and strategic. But the invisible factors I was missing were everything: Problem framing, value recognition, asset evaluation paradigms. I was analyzing this as a "technology acquisition" when it was actually a "customer acquisition." My CEO walked me through the real analysis: "You'll never find perfect technology. But look at these customers paying monthly despite those issues. We're buying a customer base, not a tech platform." He was right. We acquired the company, ran their technology for two years, migrated customers to our platform, lost maybe 15% in the transition, but grew revenue enough that it didn't matter. Huge success. Here's what really happened: My problem framing determined what evidence I saw and valued. Frame it as "technology acquisition" and every bug becomes a red flag. Frame it as "revenue asset acquisition" and paying customers become the primary signal. The sequence mattered: You have to get the frame right before you collect evidence, or you'll just gather data that confirms the wrong conclusion. The broader insight? How you frame the problem determines the solution you see. This applies everywhere—hiring decisions, product features, market strategy, team performance issues. To replicate this: First ask "What type of problem am I actually solving?" Then collect evidence. Not the other way around. Most people reverse this sequence and wonder why their thorough analysis leads to poor decisions.