Streamlining Daily Tasks

𝗧𝗼𝗱𝗮𝘆’𝘀 𝘃𝗶𝘀𝗶𝘁 𝘁𝗼 Crumble 𝗿𝗲𝗺𝗶𝗻𝗱𝗲𝗱 𝗺𝗲 𝗼𝗳 𝗺𝘆 foodpanda operations 𝗱𝗮𝘆𝘀… During peak hours at Crumble, the store was jam-packed with customers. It immediately took me back to my Foodpanda experience, where during peak hours we had to process 100–150 orders in just one hour. The interesting part? We didn’t face customer queues inside the store — instead, it was the riders who crowded outside, waiting for their pickups. This kind of chaos taught me some important lessons about 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗵𝗲𝗹𝗽 𝗼𝗳 𝗱𝗮𝘁𝗮. 𝗔𝘁 𝗙𝗼𝗼𝗱𝗽𝗮𝗻𝗱𝗮, 𝘄𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗱 𝗶𝘁 𝘁𝗵𝗿𝗼𝘂𝗴𝗵: – 𝗗𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴: We tracked how long it took a picker to pick, a packer to pack, and a rider to pick up. This helped us benchmark productivity per role. – 𝗦𝗵𝗶𝗳𝘁 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: “Super shifts” during peak demand meant we met order targets without overspending on extra staff during slower hours. – 𝗩𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: We introduced digital order screens showing order numbers for riders — avoiding confusion and wasted time. But still there are on and off days but we have the visibility to track what happens due to all the timestamps and data 𝗪𝗵𝗮𝘁 𝗜 𝗼𝗯𝘀𝗲𝗿𝘃𝗲𝗱 𝗮𝘁 𝗖𝗿𝘂𝗺𝗯𝗹𝗲: – They track orders from the time of placement, but 𝗸𝗲𝘆 𝘁𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀 𝗮𝗿𝗲 𝗺𝗶𝘀𝘀𝗶𝗻𝗴 — like when the order is packed or handed over. – Staff call out orders vocally in a noisy environment, which creates delays. 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗰𝗼𝘂𝗹𝗱 𝘀𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝘂𝗿𝘁𝗵𝗲𝗿: – 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲 𝗼𝗿𝗱𝗲𝗿 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝘁𝗶𝗺𝗲𝘀𝘁𝗮𝗺𝗽𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗰𝘆𝗰𝗹𝗲: from order placed → prepared → packed → handed over. This builds transparency and benchmarking. – Implement 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗼𝗿𝗱𝗲𝗿 𝘃𝗶𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 screens for customers (like KFC or McDonald’s). It reduces dependency on manual announcements. – Use historic order data to forecast peak-hour demand and align staff rosters accordingly — ensuring the right resources at the right time. – Benchmark productivity per role (e.g., average orders packed per hour) to identify training needs and process gaps. – Separate counters line to maintain discipline Final thought: Peak-hour chaos is common in food businesses — but with the right data, benchmarking, and a few small process tweaks, the experience can become smoother for staff, and customers. It was inspiring to see Crumble’s popularity, and I believe with some structured improvements, their customer experience can reach even greater heights.

Dear Stakeholders and Executive Leaders: The easiest way to improve the data and AI team’s productivity is to stop scheduling meetings with them. If technical team members have over 3 internal meetings per week, something’s wrong. That’s not collaboration or communication. It’s overhead. Most meetings can be handled via email or Slack message. We’re moving meetings, emails, and DMs into NotebookLM. Each team member has an “Info I know that you may need to know…” notebook. They drop information into it, thinking, “Vin would want to know about this,” or “This will be important in 3 months.” Each client and project has one with meeting recordings, emails, documents, diagrams, where to find data, and whatever else. We handle most information requests by asking questions there first. Everyone has a status notebook. They add updates at the beginning and end of the day. They can talk it out, write it down, take pictures of a whiteboard…it all works the same. I have a “How to do…” collection. It has processes for invoicing, SOW creation, managing difficult client scenarios, etc. Whenever someone asks me, or I ask them ‘how to,’ it’s recorded for a new notebook. For now, Google’s data-sharing policy works for us. We are evaluating Notebook Llama in case it changes. Get used to doing something once, documenting it in the easiest mode, and adding it to an LLM-supported knowledge base. LLMs can help transform it into a knowledge graph that more efficiently represents the workflows and expertise required to run the business. Businesses will only benefit from AI when they rethink and innovate existing workflows. Start with the ones that add the most overhead, like meetings. #ArtificialIntelligence #GenAI #Productivity

How To Actually Transform Your Life Forget motivation. It's a neurological sugar rush that crashes when you need it most. I built 5 companies (and crashed spectacularly with my first) by learning this hard truth: your brain doesn't care about your goals—it cares about your habits. Habits aren't just behaviors—they're neural pathways hardwired into your brain. They're still running when motivation dies. Want real transformation? Start with these brain hacks: 1. Think microscopically small Your brain's reward system activates on completion, not effort. A 5-minute walk daily rewires your neural circuitry more than an ambitious gym plan you abandon in week two. I once tried transforming my entire routine overnight. I failed catastrophically. Now? I add one tiny habit monthly. My brain can handle that without rebellion. 2. Consistency beats intensity The dopamine rush from intense effort feels productive. It's lying to you. Your hippocampus (memory center) physically reorganizes with consistent repetition, not occasional heroic efforts. What transformed my productivity wasn't working harder—it was showing up at the same time, in the same place, day after day. 3. Layer, don't overhaul Your basal ganglia (habit center) can only process limited change at once. Start with one keystone habit. Once automated, it becomes a platform for the next. I began with a 2-minute morning meditation. Now it's the foundation for my entire morning routine. The paradox of change is powerful: attempting less accomplishes more. Start so small it seems ridiculous. Repeat until it's automatic. Layer gradually. Become someone new through neural repetition. Your future isn't built on motivation spikes—it's built on biological habit loops that run on autopilot. What's one microscopically small habit you'll start tomorrow? Share below 👇 - Follow me Dan Murray-Serter 🧠 🧠 for more on habits and leadership. ♻️ Repost this if you think it can help someone in your network! 🖐️ P.S Join my newsletter The Science Of Success where I break down stories and studies of success to teach you how to turn it from probability to predictability here: https://lnkd.in/ecuRJtrr

Want to know why you can’t stick to the habits you’ve been trying to build? Because you’re waiting for motivation to take action. You WANT to build that new habit - to start networking, to start strength training regularly, to learn a new skill… But the motivation to take action - to send the message, to go to the gym, to practice - is never there when you need it. That’s why you need to take action first. Motivation follows action. And James Clear, one of the world’s leading experts on habit formation and behavior change, told me something on today’s episode of The Mel Robbins Podcast that really stuck with me: A habit is a behavior that you do consistently. But motivation is inconsistent… …so why would you make something you want to do consistently, rely on something that fluctuates? That’s why you have to make the behavior something that’s easy to say yes to - even on the days you’re running low on energy, capacity, or time. James has a simple rule for this: Take whatever habit you’re trying to build, and scale it down to something that takes two minutes or less. Sending DMs to 10 different people in your network, doing an hour-long workout, or practicing something for 30 minutes every day are not realistic goals if you’re exhausted or overwhelmed. Instead, commit to sending just one connection request on LinkedIn, doing just ten pushups, practicing for just two minutes every day. James calls this, “reducing the scope, but sticking to the schedule.” In other words, start by scaling down your habits to the smallest, simplest versions. Then keep showing up. The more you show up, the easier showing up will feel. And when showing up feels easy, that’s when you can start scaling UP your habits. If you’ve been struggling to build good habits or break bad ones, you have to listen to my conversation with James. He explains that if you can’t seem to stick to habits, the problem isn’t you – it’s your systems. He breaks down the proven frameworks behind lasting behavior change, and he explains how tiny, consistent improvements compound into extraordinary results over time. And even if you’ve read his book Atomic Habits (I have several times), there are things in the interview today James says he’s never shared before - including 2 specific tools he wishes he included in the book. I’ll link it in the comments.

As a data analyst, you can deliver more efficient results by applying the principle of Occam’s Razor. The principle stating that the simplest solution is often the best can be a powerful mindset for data analysts seeking clarity in their analytical process. Here’s how you can apply this old wisdom to enhance your work: 1. 𝗠𝗼𝗱𝗲𝗹 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻: When building predictive models, it’s tempting to go with the most complex and hyped ones available. However, simpler models are not only easier to understand but often more robust and generalizable. Apply Occam’s Razor to choose models that achieve the needed accuracy with the lowest complexity possible.     2. 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: A focused and digestible visualization often communicates more effectively than a complex one overloaded with information. Use Occam’s Razor to strip down your dashboards to the essential KPIs and make it easy for your stakeholders to decide based on them.     3. 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: When creating new features from your data, prioritize those that offer significant insights with minimal added complexity. This practice keeps your dataset manageable and your analyses focused.     4. 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝗼𝗹𝘃𝗶𝗻𝗴: Faced with a data problem, start with the simplest hypothesis that could explain the observations. Testing and potentially ruling out simple solutions first can save time and resources, leading to a more efficient path to the root cause.     5. 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗠𝗮𝗸𝗶𝗻𝗴: When analyzing data for decision-making, present findings straightforwardly. Simplify your conclusions to make them actionable and ensure they directly address the business question at hand. By following the principle of Occam’s Razor, data analysts can avoid unnecessary complications, enhancing the efficiency of how they generate insights. Keep it simple, and transform your data into clear, impactful stories that drive decision-making. How has simplifying your analysis improved your results? ---------------- ♻️ Share if you find this post useful ➕ Follow for more daily insights on how to grow your career in the data field #dataanalytics #businessanalytics #datascience #occamsrazor #simplicity

I asked James Clear (his book Atomic Habits has sold 25M+ copies): How do you build habits that last a lifetime. Here’s what he shared: 1. Set habits with the worst day in mind Most people set goals for their best days: “I’ll do 100 push-ups every day.” But the smarter question is: “What can I still stick to on my worst day?” Even one push-up before bed matters. It casts a vote for: I’m the kind of person who doesn’t miss workouts. 2. Forget finish lines Habits don’t “take 21 or 90 days.” The truth is that habits last as long as you keep doing them. The moment you stop, it’s no longer a habit. So design for sustainability, not sprints. 3. Anchor habits to your identity Every action you take is a vote for who you are. Ask yourself: • What habits make me proud of myself? • What do I feel excited about when people notice? That’s your compass. Small actions build into evidence for the story you want to live. 4. Reframe self-control Self-control isn’t about gritting your teeth. It’s about perspective. Switch “I have to” → “I get to.” Example from James: “I have to wake up for my dog at 3am.” Reframe: “I get to spend 5 more minutes with him.” This tiny shift turns obligation into gratitude, and gratitude sustains effort. 5. Expect seasons to change Big life shifts (new job, moving, marriage, kids) reset your rhythms. That’s normal. Plan for it: • Don’t stack deadlines right after a major change • Give yourself learning time to adapt • Seek peers just ahead of you. They’ve solved the problems you’re about to face 6. Teams need environments, not reminders On teams, habits stick when the space encourages them. Examples: • James put Audible on his phone’s home screen = he started reading more • A startup projected its #1 metric (instals) on the wall = kept the team aligned • I cut Slack for my team = productivity jumped because our real flow was in Asana + video calls. Environments shape behavior more than reminders ever will. 7. Master the art of showing up Any new habits should take less than 2 minutes to start. So, instead of aiming for the full outcome right away,  shrink it down to the simplest possible action, something so easy you can’t say no to. Examples: • “Read 30 books a year” → Read 1 page • “Do yoga 4 days a week” → Roll out your yoga mat • “Write every day” → Open your notebook James shared Mitch’s story: he only let himself stay 5 minutes at the gym. Silly? Maybe. Effective? Absolutely because he became the kind of person who shows up. The big takeaway: Habits aren’t about grit. They’re about designing small, sustainable wins that prove your identity through all seasons of life.

In the world of continuous improvement, BAs often focus on optimizing business processes, but what about the process of business analysis itself? A "Lean BA" applies Lean principles to their own work, ruthlessly identifying and eliminating waste. This means less time spent on unnecessary documentation, fewer meetings that lack clear outcomes, and a constant focus on delivering only the information that is absolutely necessary to move the project forward. By streamlining the requirements gathering and documentation process, a Lean BA can accelerate project timelines, reduce rework, and free up valuable time to engage in more strategic, value-added activities. The goal isn't to cut corners; it's to cut waste and maximize value.

Focusing on AI’s hype might cost your company millions… (Here’s what you’re overlooking) Every week, new AI tools grab attention—whether it’s copilot assistants or image generators. While helpful, these often overshadow the true economic driver for most companies: AI automation. AI automation uses LLM-powered solutions to handle tedious, knowledge-rich back-office tasks that drain resources. It may not be as eye-catching as image or video generation, but it’s where real enterprise value will be created in the near term. Consider ChatGPT: at its core, there is a large language model (LLM) like GPT-3 or GPT-4, designed to be a helpful assistant. However, these same models can be fine-tuned to perform a variety of tasks, from translating text to routing emails, extracting data, and more. The key is their versatility. By leveraging custom LLMs for complex automations, you unlock possibilities that weren’t possible before. Tasks like looking up information, routing data, extracting insights, and answering basic questions can all be automated using LLMs, freeing up employees and generating ROI on your GenAI investment. Starting with internal process automation is a smart way to build AI capabilities, resolve issues, and track ROI before external deployment. As infrastructure becomes easier to manage and costs decrease, the potential for AI automation continues to grow. For business leaders, identifying bottlenecks that are tedious for employees and prone to errors is the first step. Then, apply LLMs and AI solutions to streamline these operations. Remember, LLMs go beyond text—they can be used in voice, image recognition, and more. For example, Ushur is using LLMs to extract information from medical documents and feed it into backend systems efficiently—a task that was historically difficult for traditional AI systems. (Link in comments) In closing, while flashy AI demos capture attention, real productivity gains come from automating tedious tasks. This is a straightforward way to see returns on your GenAI investment and justify it to your executive team.

I recently spoke with a sales leader about a common challenge: how overly complex internal processes slow down sales reps. “Our reps are spending more time navigating internal workflows than selling,” they mentioned. This is a widespread issue—when every step of a deal requires approvals or confusing steps, it keeps reps from engaging with prospects effectively. To fix this, simplifying the sales process goes beyond just removing steps; it’s about empowering your team and creating clear, action-oriented pathways. Here’s how: 1. Cut Down Approval Layers: Allow senior reps to make decisions within defined limits, reducing reliance on time-consuming approvals. This speeds up deal cycles and encourages ownership. 2. Use Clear Playbooks: Ambiguity breeds inefficiency. Standardized, easy-to-follow sales playbooks eliminate confusion and help reps move deals forward confidently, knowing what to do at each stage. 3. Automate Admin Tasks: Manual data entry and updating deal stages take up valuable time. Automation tools handle these low-value tasks, allowing reps to spend more time selling and less on busywork. 4. Streamline Communication: Simplify who’s responsible for what. Clear communication lines and fewer meetings reduce delays, ensuring that when reps need answers, they get them fast. 5. Empower Your Reps: Equip your team with the authority to make pricing decisions or offer discounts without having to escalate every time. Giving them the ability to act quickly builds trust and boosts productivity. By making these changes, you’re not just reducing steps—you’re unlocking the full potential of your sales force, enabling them to focus on what matters most: closing deals and building relationships. Simplified processes mean faster, smoother sales cycles and ultimately better results for your team. #SalesOptimization #SalesEfficiency #SalesLeadership #SalesProductivity #SalesProcess #AutomationInSales #SalesTeam #LeadConversion #RevenueGrowth #BusinessEfficiency