Problem-Solving Skills Analysis

🎯 Why Most Business Problems Remain Unsolved (And How to Fix That) Last week, I had the privilege of facilitating a Problem Solving & Business Acumen workshop for our teams at L'Oréal Indonesia. 💡 The Problem We All Face (But Rarely Talk About) Here's an uncomfortable truth: we're wired to jump to solutions. In business, this looks like: ✔️ Launching promotions without understanding why sales declined ✔️ Hiring more people without diagnosing process inefficiencies ✔️ Copying competitor tactics without validating if they fit our context The cost? Wasted resources, frustrated teams, and recurring problems that never truly go away. According to the World Economic Forum's Future of Jobs Report 2023, analytical and critical thinking are the #1 and #2 most important skills for workers. Yet, most of us were never formally taught how to think critically or solve problems systematically. 🛠️ The Problem-Solving Process: A Step-by-Step Guide Step 1: Define the Problem (Don't Jump to Judgment!) 📝 Craft a Problem Statement with 6 components: "How can [responsible party] improve/reduce [reality] to meet [expectation] within [timeline] without [anti-goals], in order to fulfill [reason]?" Example: "How can the product team launch a new product on time in Q4 2024 without sacrificing key processes, in order to meet the sales target?" Step 2: Find Alternatives (Issue Tree + MECE) Once the problem is clear, break it down using an Issue Tree. For instance, if mascara sales dropped -14% YoY: 📦 Placement → Gondola compliance, visibility, signage 🎁 Promotion → BOGO mechanics, POS materials 💰 Price → Elasticity, perceived value 🎨 Product Claims → Content freshness, reviews 🔥 Competition → Share of voice, endcap presence ✅ Ensure hypotheses are MECE (Mutually Exclusive, Collectively Exhaustive)—no overlaps, no gaps. Step 3: Test Your Hypotheses Don't fall in love with your first idea. Run quick tests: 📊 For a skincare serum declining in pharmacies, we tested: ✔️ Hypothesis A: Reduced pharmacist advocacy is the issue → Micro-detailing pilot in 10 stores ✔️ Hypothesis B: Cold chain OOS drives lost sales → Warehouse SOP audit + temperature logs ✔️ Hypothesis C: Execution gaps suppress promo ROI → Endcap compliance audit Each hypothesis had clear KPIs and timelines—no guessing, just data. Step 4: Make the Decision (Impact vs. Effort Matrix) Not all solutions are equal. Prioritize: 🟩 Quick wins—do this! 🟦 Strategic bets 🟨 Fill-ins 🟥 Avoid Focus on low effort, high impact moves first. Build momentum, then tackle the big bets. 🚨 What Happens When We Skip These Steps? A mascara brand saw sales drop -14% YoY. The reaction? "Let's run a BOGO promo!" The result? Sales stayed flat. Why? Because the real issues were: ❌ Poor gondola compliance (only 68% correct facings) ❌ Weak influencer share of voice ❌ Competitor secured prime endcap space The lesson: Solutions applied to the wrong problem = wasted budget and missed targets.

Signs of a business problem solving data analyst The best data analysts don't just crunch numbers. They transform business problems into actionable insights. Most focus on technical skills, but exceptional analysts exhibit subtle behaviors that set them apart. Here are signs you're working with a true business problem solver 👇 They start with the business question, not the data ↳ "What decision needs to be made?" comes before "What data do we have?" They translate technical findings into business language ↳ Replace "p-values" with "here's what this means for our strategy" They know which metrics drive outcomes ↳ Focus on the 2-3 metrics that directly connect to business goals They define success before starting the analysis ↳ Establish clear measurement criteria before opening any tools They present insights, not just information ↳ Convert data points into actionable recommendations They tell compelling data stories ↳ Structure findings with a clear beginning, middle, and end They focus on the quality of data, not just quantity ↳ Validate sources before diving into complex analysis They know when accuracy matters vs. when speed does ↳ Match precision to the business need and timeline They identify the "so what" behind every insight ↳ Connect every finding to a specific business impact They map the analysis to specific decision points ↳ Align deliverables to upcoming business decisions They simplify complex concepts without oversimplifying ↳ Use analogies that business leaders understand They know which problems don't need more data ↳ Recognize when a business constraint, not data, is the blocker They connect data silos across departments ↳ Build insights that cross organizational boundaries They focus on the highest-value problems first ↳ Prioritize work that directly impacts revenue or costs They're transparent about data limitations ↳ Clearly state what the analysis can and cannot tell us They build repeatable analytical processes ↳ Design solutions that scale beyond one-time questions The difference between a data technician and a business partner isn't technical skill. It's the ability to turn information into impact. Which of these signs do you see in yourself or your team? ♻️ Repost to help your network identify true analytical talent 🔔 Follow for more insights on data-driven decision making

Brutal truth: Most organizations think they’re doing problem-solving… …but they’re really just treating symptoms. And that’s why most “continuous improvement” efforts quietly fail within 6 months. Here’s the pattern: ↓ A problem emerges ↓ Teams jump into action ↓ They brainstorm fixes ↓ Something sort of works ↓ Everyone gets busy ↳ The problem returns—sometimes worse What’s missing? A disciplined system for understanding what's really going on. that's where Root Cause Analysis comes in. Without true Root Cause Analysis (RCA), all improvement becomes guesswork. RCA is the operating system of real improvement Effective problem-solving is not a single method. It’s a system of thinking supported by tools that reveal what's going on beneath the surface. here are 3 RCA tools: 1/ Fishbone Diagram Purpose: Organize possible causes into categories so patterns emerge. The Fishbone works because it forces teams to externalize assumptions. Instead of blaming individuals or latching onto the first explanation, it broadens the search. 2/ The 5 Whys Purpose: Drill down from surface symptoms to deeper causes through structured questioning. This is the simplest and most used RCA tool. When done well: You follow a single causal chain You validate each “why” with evidence You avoid speculation You keep going until the answer becomes systemic (not human error) When done poorly, it becomes a rapid-fire guessing exercise that leads nowhere. 3/ Fault Tree Analysis (FTA) Purpose: Map how multiple causes combine into failures. FTA is a branching model that shows how different conditions must align for a failure to occur. It is the most rigerous of the RCA tools and my personal favorite. FTA exposes: ➡��conditions for failure ➡️hidden interdependencies ➡️missing safeguards In high-performing organizations, RCA is embedded into: + Total Quality Management + Standardized Work + Just-In-Time and Flow Design + Policy Deployment + Daily Management & Suggestion Systems Organizations don’t fail because problems are too complex. They fail because they don’t build a system for revealing and understanding causes. So start simple: Pick one tool Use it consistently Train people on the thinking behind it Validate causes with data Improve the surrounding systems that make RCA possible Then connect that tool to others—just like Kaizen. Sustainable improvement isn’t an event. It’s a capability. Built patiently. Strengthened daily. Powered by clarity about why things happen. And that starts with Root Cause Analysis.

Problems aren't roadblocks. They're invitations. An invitation to innovate. To rethink. To leap. The difference between stuck and unstoppable? It's not the challenge. It's you. Your lens. Your toolkit. Your willingness to dance with the difficulty. As a tech leader, your ability to solve complex issues can make or break your career. I've led teams across continents, industries, and crises. Here's what I've learned: 𝟭. 𝗥𝗼𝗼𝘁 𝗖𝗮𝘂𝘀𝗲 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Peel back the layers. Ask "Why?" repeatedly. You're not fixing a leak; you're redesigning the plumbing. 𝟮. 𝗦𝗪𝗢𝗧 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Map your battlefield. Know your strengths, weaknesses, opportunities, and threats. Sun Tzu would approve. 𝟯. 𝗠𝗶𝗻𝗱 𝗠𝗮𝗽𝗽𝗶𝗻𝗴 Visualize the chaos. Connect the dots. Your brain on paper, minus the mess. 𝟰. 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 Prepare for multiple futures. Be the chess player who sees ten moves ahead. 𝟱. 𝗦𝗶𝘅 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗛𝗮𝘁𝘀 Wear different perspectives. Be the critic, the optimist, the data analyst, the artist, the operator. Your mind is pliable; use it. 𝙒𝙝𝙮 𝙩𝙝𝙞𝙨 𝙢𝙖𝙩𝙩𝙚𝙧𝙨: - 76% of IT leaders rank problem-solving as the top soft skill (Global Knowledge) - Strong problem-solvers are 3.5x more likely to hit strategic goals (Harvard Business Review) - 70% of problem-solving pros drive more innovation (PwC) These aren't just methods. They're mindsets. Tools to reshape your thinking. I've used these to navigate multi-million-dollar projects and multinational teams. They work. Period. But the real differentiator: consistency. Use these daily. Make them habits. Your problem-solving muscle grows with every rep. Start now. Pick one method. Apply it to a current challenge. Share your results. The best tech leaders aren't born. They're forged in the fires of solving complex problems. What will you solve today?

Most people chase quick fixes. Here's how experts actually solve problems. The blueprint for solving problems effectively: 1. IDEAL Framework ↳ Identify the problem ↳ Define the context ↳ Explore possible strategies ↳ Act on the best strategy ↳ Look back and learn 2. 5 Whys Technique ↳ Ask "Why?" repeatedly ↳ Dig deeper beyond surface symptoms ↳ Find root causes of problems 3. Design Thinking ↳ Empathise with user needs ↳ Define the problem clearly ↳ Ideate creative solutions ↳ Prototype low-fidelity versions ↳ Test and refine with feedback Expert frameworks for structured problem-solving: PDCA Cycle ↳ Plan: Identify and analyse ↳ Do: Implement solutions ↳ Check: Evaluate results ↳ Act: Standardize or restart OODA Loop ↳ Observe: Collect information ↳ Orient: Analyse and synthesise ↳ Decide: Choose action ↳ Act: Follow through Kepner-Tregoe Method ↳ Situation Appraisal ↳ Problem Analysis ↳ Decision Analysis ↳ Potential Problem Analysis The biggest mistake isn't trying to solve problems. It's not using a systematic approach when needed. ♻️ Reshare to help others solve problems better. 🔔 Follow Luke Tobin for more problem-solving insights.

To become a top data analyst you need to be a strong problem solver! Follow this structure to find the real reasons behind business problems: 1. 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: Start by clearly stating the issue. For example, “We’ve observed a significant decrease in sales in the UK over the last few days.”   2. 𝗚𝗮𝘁𝗵𝗲𝗿 𝗗𝗮𝘁𝗮: Collect relevant information such as order processing times, customer service interactions, inventory levels, and active marketing campaigns.   3. 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮: Use tools like SQL, Python, or Excel to analyze the data. Look for patterns, trends, and anomalies that could point to the root cause.   4. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗖𝗮𝘂𝘀𝗲𝘀: Brainstorm all possible reasons for the issue. Use methods like the 5 Whys technique to investigate each potential cause more deeply.   5. 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗛𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗲𝘀: Test your hypotheses against the data to see if they are supported. If not, refine your hypotheses and test again.   6. 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: Once you’ve identified the root cause, support the business by showing possible solutions to address it. Monitor the results to ensure the issue is resolved. 𝗔 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗲𝘅𝗮𝗺𝗽𝗹𝗲 𝗳𝗿𝗼𝗺 𝗺𝘆 𝗽𝗮𝘀𝘁: We notice an increase in customer lead time and here’s how we tackle it. 1. 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺: “Customer lead time has increased by 20% in the last three months.”     2. 𝗚𝗮𝘁𝗵𝗲𝗿 𝗗𝗮𝘁𝗮: We collected data on order processing, sales forecast deviation, and shipping times.     3. 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮: We found that the actual sales were in line with the forecast, and shipping times had remained constant. However, order processing times had increased significantly.     4. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗣𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝗖𝗮𝘂𝘀𝗲𝘀: We checked factors such as outages in warehouses, staffing issues due to high sickness rates, and process inefficiencies resulting from operating close to maximum capacity.     5. 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲 𝗛𝘆𝗽𝗼𝘁𝗵𝗲𝘀𝗲𝘀: Data revealed that a spike in the sickness rate had reduced the available workforce.     6. 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: We proposed to increase capacity buffers by 5% to 10% during the winter and hiring additional temporary workers to address the situation in the short term.   Following this approach for your root-cause analysis, you will become a valued problem-solving partner for your stakeholders. How do you ensure you’re addressing the root cause of an issue and not just the symptoms? ---------------- ♻️ 𝗦𝗵𝗮𝗿𝗲 if you find this post useful. ➕ 𝗙𝗼𝗹𝗹𝗼𝘄 for more daily insights on how to grow your career in the data field. #dataanalytics #datascience #rootcauseanalysis #problemsolving #careergrowth

Problem-Solving Approach A systematic problem-solving approach involves understanding the issue, analyzing it thoroughly, and devising an effective solution. Begin by defining the problem clearly to identify its root cause. Gather relevant data and evaluate possible solutions by considering their feasibility and potential outcomes. Next, select the most suitable solution and implement it with a clear plan. Continuously monitor the results to ensure the problem is resolved effectively. If needed, adjust the approach based on feedback and outcomes. This methodical process fosters clarity, reduces errors, and ensures efficient resolution of challenges, whether personal, professional, or academic.

#PDCA (Plan-Do-Check-Act) 1. Plan: Identify a problem or opportunity for improvement and plan a solution. 2. Do: Implement the planned solution. 3. Check: Monitor and evaluate the effectiveness of the solution. 4. Act: Take corrective action to sustain the improvement. Importance: PDCA is a fundamental framework for continuous improvement, encouraging a cyclical approach to problem-solving and improvement. RCA (Root Cause Analysis) 1. Identify the problem: Clearly define the problem or issue. 2. Gather data: Collect relevant data to understand the problem. 3. Analyze data: Analyze the data to identify the root cause. 4. Implement corrective action: Implement corrective action to address the root cause. Importance: RCA is a methodical approach to identifying and addressing the underlying causes of problems, reducing the likelihood of recurrence. Fishbone (Ishikawa Diagram) 1. Identify the problem: Clearly define the problem or issue. 2. Brainstorm causes: Use a fishbone diagram to brainstorm potential causes, categorized into six areas: - Machines (equipment) - Methods (processes) - Materials (raw materials) - Man (human factors) - Measurement (data collection) - Environment (external factors) Importance: The Fishbone diagram is a visual tool for brainstorming and organizing potential causes of a problem, facilitating a structured approach to problem-solving. Five Why 1. Ask "why" five times: Ask "why" five times to drill down to the root cause of a problem. Importance: The Five Why method is a simple yet effective technique for identifying the root cause of a problem, encouraging critical thinking and persistence. Corrective Action 1. Identify the problem: Clearly define the problem or issue. 2. Analyze the problem: Analyze the problem to identify the root cause. 3. Develop corrective action: Develop and implement corrective action to address the root cause. 4. Verify effectiveness: Verify the effectiveness of the corrective action. Importance: Corrective action is a proactive approach to addressing problems, reducing the likelihood of recurrence, and improving overall quality and efficiency. In summary, these tools and techniques are essential in Quality Control and Continuous Improvement, as they: 1. Encourage a structured approach to problem-solving 2. Facilitate the identification of root causes 3. Promote critical thinking and persistence 4. Support the development and implementation of corrective action 5. Foster a culture of continuous improvement By applying these tools and techniques, organizations can improve quality, reduce waste, and enhance customer satisfaction. #QA,#QC,#PDCA,#FishBone,#5Why,#ContiniousImprovement

Problem Solving Tools Part 3 : 5Why (or Why-Why) Explained Developed by Sakichi Toyoda, the founder of Toyota, as part of the Toyota Production System; the 5 Why method is a powerful problem-solving technique. The basic concept involves asking "Why?" five times to uncover the root cause of a problem. How to Perform a 5 Why Analysis 1️⃣ Assemble a team: Bring together relevant experts to ensure a comprehensive analysis that the problem is looked from different aspects and expertise/angles. 2️⃣ Define the problem: Clearly state the issue you want to investigate. 3️⃣ Ask "Why?": Begin the chain of questioning, with each answer becoming the basis for the next "Why?". The "5" in 5 Why is not a strict rule. You may need fewer or more "Why?" questions to reach the root cause. But usually less than 3 Why's wont enable you to go deep into root cause. 4️⃣ Use Branching : Problems often have more than one root cause. In these cases, you can use branching to cover different causes your team identifies. So one why may have multiple branches, and branch also may have multiple branches like a tree. Branching allows for a more thorough exploration of problem and ensures clarity within the team. 5️⃣ Continue until root cause is found: This may take more or fewer than five "Why?" questions. Check each assumption in Gemba and dont ask further whys if Gemba verification fails. 6️⃣ Develop and implement solutions: Address the identified root cause, prepare a clearly worded action plan with responsible and dedline. Example Problem: Late delivery of repaired parts to customers ❓ Why is the delivery late? ➡️ Branch A: The repair process is stopped midway ➡️ Branch B: Shipping delays ❓ Why is the repair process stopped midway? ➡️ Because the data clerk has entered wrong information into the system ❓ Why has the clerk entered wrong information into the system ? ➡️ Because the labeling on the received packages was not fully unreadable ❓ Why was the labeling unreadable ? ➡️ Because labeling ink got smeared during handling ❓ Why labeling ink got smeared during handling ➡️ Because the label and ink quality is not good enough to prevent smear Benefits of 5 Why Analysis ✅ Comprehensive Problem-Solving: Addresses multiple facets of complex issues. ✅ Improved Root Cause Identification : Helps uncover multiple root causes that might be missed in a linear approach. ✅ Team Engagement : Promotes broader participation and diverse perspectives in problem-solving. ✅ Visualization : Can be represented as a tree diagram, making it easier to understand and communicate the analysis . By using the 5 Why method, teams can conduct a more thorough analysis of complex problems, leading to more effective solutions and continuous improvement in processes.

Problem-solving is not brainstorming. HERE is what it really is Everyone puts “problem-solving” on their CV. Every interview tests for it. Every firm claims to do it. But very few actually understand what it means and why it sets consultants apart. Let’s start with what it’s not: ❌ It’s not a brainstorming session with Post-its on the wall. ❌ It’s not running numbers just to look smart. ❌ It’s not debating opinions until the loudest voice wins. That is not problem-solving. So what is problem-solving in consulting? It’s a method. A way of bringing order when addressing business challenges. Here’s how it really works 👇 1. Frame the problem This doesn’t mean “start throwing ideas.” It means: What are we actually trying to solve? What is the precise question? And is everyone aligned? If you skip this step, the team runs in different directions and wastes time. 👉 The most underrated part of problem solving is not the answer: it’s getting 5 smart people to agree on the question. 2. Build hypotheses Jumping straight to analysis is a rookie mistake. You don’t open Excel and start crunching blindly. You ask: “What hypotheses are we testing? What would need to be true for A to work? Or for B to fail?” 👉 Without this, analysis is just grind. With it, you know exactly what you’re proving or disproving. 3. Test with data Numbers are a filter, a compass: prove it, kill it, or move on. Sometimes it’s one benchmark, sometimes a quick triangulation, sometimes a client interview. 👉 You don’t need a PhD model. You need enough to know if you’re on the right track. 4. Debate with clarity Problem-solving is a team sport. The goal isn’t endless argument; it’s structured debate. Attack the problem, never the person. Pressure-test the logic. Bring facts, not ego. 👉 The best teams don’t avoid debate; they make it sharper, faster, and more respectful. 5. Translate into action Problem-solving that ends in a 50-page deck is useless. It has to land in clear next steps: “Here’s what we do on Monday.” 👉 Problem-solving needs to create impact, turning logic into decisions and action. That’s the superpower. Not IQ. Not endless Excel models. Just the ability to bring order, test reality, and move forward with clarity. And here’s the uncomfortable truth: most people think they’re problem-solving… but they’re not. They brainstorm. They analyze without purpose. They argue opinions with no data.