Insights for Problem-Solving from Technology Blogs

Testing with users sharpens decisions when problems are clearly defined. I was inspired by ÌníOlúwa Abíódún’s assertion that framing problem statements is a key ingredient in problem-solving. Too often, teams quickly dive into design work without the specificity to drive meaningful action and results. Check out her insightful post: https://lnkd.in/gwqHmaUS “As you tackle challenges in your work, remember to take the time upfront to precisely articulate/frame the problem you're solving and what success looks like.” I agree. In my Helio conversations, I meet teams looking for testing solutions without clearly understanding why they need to test. This often happens because they need a complete picture of why a feature or flow is necessary in the first place. They're searching for answers, hoping testing will reveal what to focus on. Many teams know what they want to test but must understand how testing will help them make better decisions. While hunches and intuition are fine, a structured feedback process can offer a clear focus. Helio user data provides valuable signals before committing to any concept. Here’s how our service teams help customers think about this problem: Concept ↳ Provides a foundation and focus for the testing process, ensuring that efforts are directed towards a specific idea or issue that needs validation or improvement. Testing ↳ Engages real users to gather authentic feedback and insights, important for understanding how the concept performs in a real-world scenario. Leading Indicators ↳ Leading indicators offer early signals about the concept's potential success or issues, guiding necessary adjustments before full-scale implementation. KPIs ↳ KPIs provide quantifiable measures of performance and impact, allowing for objective assessment and comparison over time. Observation ↳ Direct observation and feedback review help identify unexpected issues and understand the context behind the data, leading to more informed decisions. Decision Making ↳ Ensures that decisions are data-informed and evidence-based, reducing the risk of biases and increasing the likelihood of achieving desired outcomes. When you do this in continuous weekly cycles, the learnings compound, making it easier for teams to zero in on the right problems.   #productdesign #productdiscovery #userresearch #uxresearch

🌿 The more complex the problem, the more intentional I’ve had to become about how I approach it. Not just technically — but mentally. In data science, it’s easy to focus on outputs: pipelines, models, insights, dashboards. But over time — and through experience — I’ve come to realize that the real differentiator isn’t how quickly you build, but how well you define the problem before you build. Some of the most meaningful work I’ve been part of didn’t come from complex algorithms, but from: • Taking time to ask better questions • Re-examining assumptions that seemed obvious • Reframing metrics to reflect what truly matters to the business • Stepping back to map the logic — before opening a single tool 💡 One of the most valuable lessons I’ve learned? Often, the hardest part of data work isn’t the analysis — it’s defining what’s worth analyzing. While many of us can build models or pull data, I’ve found that the real value often lies in the ability to pause, prioritize, and translate a broad or ambiguous ask into a clear, structured, and actionable question. A clean space helps, but clarity of thought matters more. Clarity is a competitive advantage — and it’s something I’m still learning to sharpen every day. If you’re on a similar path, I’d love to hear what shifted your thinking or helped you grow. #DataScience #Analytics #StrategicThinking #ProblemSolving #BusinessImpact #WomenInSTEM #CareerGrowth #InsightsThatMatter

🔍 Are Your Problem-Solving Habits Holding You Back? 🔍 🎯 As we step into November, a season of planning and setting ambitious goals for the next year, it's the perfect time to ponder on this question. I have been reflecting upon common missteps that hinder our problem analysis and solving - the insight I had was that they apply beyond our professional life: 1️⃣ Missing root-cause analysis: It's easy to take surface-level issues at face value without delving deeper into their origins. Just like when we see a dip in productivity in a team, and we assume they need more training, when in reality, the problem might lie in unclear processes. 2️⃣ Correlation bias: We often confuse what's merely connected with what truly causes a change. For example, just because you received a promotion after networking at an event, it doesn't mean the event caused the promotion. 3️⃣ Lacking an 80-20 focus: When dealing with complex problems, it's easy to get lost in the details. Prioritizing the most impactful actions is vital, just as in life, where focusing on a few major life changes often leads to more significant personal growth. 4️⃣ Confusion between 'Information', 'Insight', 'Implication', and 'Action': Gathering information is not the same as deriving meaningful insight, which, in turn, is different from realizing its implications and taking action. Misunderstanding this process can stall progress and lead to outliers of either ‘analysis / paralysis’ or ‘blind execution’ 💡 So, how do we address these biases and have an effective approach to problem solving? I. Problem Framing: Have a well-laid-out value driver tree that can pinpoint both logically and quantitatively the layers of drivers leading to a situation or problem. Investing deeply in problem definition and framing is often dismissed, but it contributes most foundationally to the eventual success. II. Solutioning: Rigorously think through all possibilities with their pros, cons, risks, and implications. This discipline is critical for every major problem or opportunity, however redundant it may seem. Just like the problem framing stage, in most cases the solution is almost never simply the first hypothesis we think of, but a nuanced and multinomial equation. III. Strategy to Execution: Though I'm addressing this separately, it adds to point II above. Engage real-world practitioners who can validate the execution plan deeply. Set up execution parameters grounded in reality, relying on feedback from past experiences. This ensures a realistic approach from strategy to execution, but also mitigates for inertia risks. 🤔 Being able to recognize the strengths and skills needed for effective problem solving across all these 3 steps is seldom found in one individual. Consider distributing these steps among individuals from complementary backgrounds and experiences. So, how do you tackle these biases in your journey to self-improvement? #ProblemSolving #IdentifyingBiases #ChangeStartsFromWithin