Real-Time Inventory Visibility

I build dashboards backwards. And they work 3x better than the "right" way. Last year, a retail client asked for a "comprehensive analytics dashboard." They had a 47-page requirements doc. Every metric you could imagine. I threw it in the trash. Instead, I asked one question: "What decision do you make every Monday morning?" "Whether to restock our top 10 SKUs," the CEO said. That's it. That became the entire dashboard. One number: Days of inventory remaining. One visual: Red/yellow/green by SKU. One button: Generate purchase order. The data team was horrified. "Where's the YoY comparison? The regional breakdowns? The predictive models?" Here's what happened: **Traditional approach (their previous dashboard):** • 6 weeks to build • 23 different views • Used 4 times in 3 months • Zero decisions changed **My backwards approach:** • 3 days to build • 1 view • Used 5 times per week • Prevented 2 stockouts in first month alone The difference? I started with the decision, not the data. Most dashboards fail because we build what's possible, not what's needed. We show off our technical skills instead of solving business problems. My backwards process: 1. Identify the decision (not the data) 2. Find the minimum viable metric 3. Make the action obvious 4. Stop. Just stop adding things. That retail client? They saved $50K in lost sales from stockouts in Q1. Not because of fancy analytics. Because someone could actually use the damn thing. The best dashboard isn't the one with the most features. It's the one that gets opened every morning. What's the one metric that actually drives your business decisions? #DataVisualization #DashboardDesign #BusinessIntelligence #DataStrategy #PowerBI

In retail, speed is no longer a competitive advantage—it’s the price of admission. The difference between leaders and laggards comes down to one thing: real-time data. You either see the moment as it unfolds, or you react after the market has already moved on.   When I sit down with retail leaders, I often talk about what I call the low-hanging fruits—not because they’re easy, but because they deliver disproportionate impact, fast.   - First, ERP integration. When buyers and suppliers operate on the same live version of truth, friction disappears. Decisions get sharper. Trust goes up. - Second, intelligent agents. Not dashboards that explain yesterday, but systems that think in the moment—forecasting demand, monitoring inventory, and optimizing logistics as conditions change. - Third, next-generation VMI. Inventory that manages itself—cutting stockouts without tying up capital in excess stock.   These aren’t moonshots. They’re practical, achievable today, and they build momentum quickly.   Recently, we partnered with a leading luxury retailer to bring this vision to life. Their reality was familiar: no real-time visibility, an overwhelming flood of OMS events, legacy infrastructure that couldn’t scale, and legitimate concerns about protecting sensitive data. We re-architected the foundation. A serverless AWS platform capable of processing millions of OMS events in real time. A secure, centralized data lake. AI and ML models embedded into the flow of operations. And live dashboards that put insight directly into the hands of business leaders.   The outcomes spoke for themselves: - Real-time and historical visibility across the enterprise - A scalable, cost-efficient technology backbone - A future-ready platform for advanced analytics and faster decision-making   This isn’t about operational efficiency alone. This is about competitive advantage.   The next wave of retail disruption is already here. The winners will be the ones who master real-time analytics and AI—not as experiments, but as core capabilities embedded into how they run the business. #AIinRetail

𝓦𝓱𝓮𝓷 𝓹𝓪𝓷𝓲𝓬-𝓫𝓾𝔂𝓲𝓷𝓰 𝓼𝔀𝓮𝓹𝓽 𝓪𝓬𝓻𝓸𝓼𝓼 𝓽𝓱𝓮 𝓰𝓵𝓸𝓫𝓮 𝓲𝓷 𝓮𝓪𝓻𝓵𝔂 2020, 𝓻𝓮𝓽𝓪𝓲𝓵𝓮𝓻𝓼 𝔀𝓮𝓻𝓮 𝓫𝓵𝓲𝓷𝓭𝓼𝓲𝓭𝓮𝓭 𝓫𝔂 𝓮𝓶𝓹𝓽𝔂 𝓼𝓱𝓮𝓵𝓿𝓮𝓼 𝓪𝓷𝓭 𝓫𝓻𝓸𝓴𝓮𝓷 𝓼𝓾𝓹𝓹𝓵𝔂 𝓬𝓱𝓪𝓲𝓷𝓼. 𝓦𝓪𝓵𝓶𝓪𝓻𝓽? 𝓣𝓱𝓮𝔂 𝓱𝓪𝓭 𝓪 𝓷𝓸𝓽-𝓼𝓸-𝓼𝓮𝓬𝓻𝓮𝓽 𝓮𝓭𝓰𝓮: 𝓭𝓪𝓽𝓪 𝓪𝓷𝓪𝓵𝔂𝓽𝓲𝓬𝓼. Walmart’s Data-Led Response to Pandemic Panic 🔍 Real-Time Inventory Intelligence By leveraging predictive models, Walmart tracked SKU-level movement across thousands of stores—restocking in real time, right where it mattered most. 🔍 Agile Supplier Collaboration Data helped forecast supply-side disruptions, enabling Walmart to reroute shipments, adjust SKUs, and keep shelves stocked. 🔍 Empowered Local Decision-Making Instead of waiting for top-down instructions, store managers used localized data to act fast—serving real needs in real time. The result? While others ran out, Walmart stepped up—ensuring availability, reducing chaos, and reinforcing customer loyalty. 📌 Takeaway: In a crisis, data isn't just a strategy tool—it’s an execution engine. 💬 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒓𝒆𝒂𝒍-𝒕𝒊𝒎𝒆 𝒅𝒂𝒔𝒉𝒃𝒐𝒂𝒓𝒅𝒔 𝒐𝒓 𝒅𝒂𝒕𝒂-𝒍𝒆𝒅 𝒐𝒑𝒔 𝒊𝒏 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔? 𝑯𝒐𝒘 𝒉𝒂𝒗𝒆 𝒕𝒉𝒆𝒚 𝒉𝒆𝒍𝒑𝒆𝒅 𝒚𝒐𝒖 𝒏𝒂𝒗𝒊𝒈𝒂𝒕𝒆 𝒖𝒏𝒄𝒆𝒓𝒕𝒂𝒊𝒏𝒕𝒚? #WalmartCaseStudy #CrisisResponse #SupplyChainAnalytics #DataDrivenDecisionMaking

I'm excited to share my latest data analytics project: a comprehensive Retail Performance Analysis Dashboard. Problem: The retail company struggled with a lack of clear insights, making it difficult to track overall performance, understand customer behavior, and manage inventory efficiently. Solution: I developed and deployed an interactive, end-to-end Power BI dashboard. By connecting directly to SQL databases, the solution provides a real-time, holistic view of the business, analyzing key KPIs like sales, profit margins, customer segmentation, supplier performance, and stock health. 📊 Tools Used: Power BI | SQL | Excel | DAX | Data Modeling 💡 Key Insights & Highlights: • Total Sales: ₹5.34M • Profit Margin: 28.77% • YoY Sales Growth: 23.48% • Top Performers: The North Region (₹1.52M) and the supplier "Boat" (₹1.1M) were the primary drivers of sales. • Operational Health: Maintained a 65% delivery rate against a 9.17% return rate. • Actionable Inventory: Identified 3 critical products as "Low Stock" (Stock = Reorder Level), flagging them for immediate re-purchasing. Dashboard Link: https://lnkd.in/gHTPaTce #PowerBI #SQL #DataAnalytics #BusinessIntelligence #Dashboard #DataVisualization #RetailAnalytics #DataInsights

What to Measure on an Inventory Dashboard and Why It Matters A good inventory dashboard isn’t about colors or design. It’s about clarity, accuracy, and how quickly it helps you make a decision. Over time, I’ve realized the best dashboards focus on metrics that actually drive action, not just display numbers. 1. Core Inventory Metrics • On-Hand Units – gives the real picture of availability • Safety Stock Coverage (Days) – shows how long the buffer will last • Days of Supply (DOS) – helps align inventory with forecast demand • Open Purchase Orders with ETA – connects inbound supply to future availability 2. Inventory Health Indicators • Critical, Watchlist, Healthy – simple tags that create instant visibility • Deviation vs Forecast – shows where plans are off track • Out of Production date and post-OOP coverage – highlights where risk starts building 3. Channel-Level Visibility Being able to filter by channel or customer (Amazon, Walmart, Top 40, etc.) changes everything. It tells you where the real pressure exists instead of showing one blended view. 4. Operational KPIs • Inventory Turns – how efficiently stock is moving • Aged Inventory % – where cash is stuck • Fill Rate / Service Level – how well we’re meeting demand The goal isn’t to make dashboards more complicated. It’s to make them more useful. When teams see the same data, decisions become faster and conversations become clearer. A strong inventory dashboard doesn’t just show data. It gives direction. #SupplyChain #InventoryPlanning #DashboardDesign #OperationsExcellence #DataDrivenPlanning

🚀 Power BI Widget Tryout Excited to share my first attempt at exploring a widget concept within Power BI! Inspired by the amazing work of Nicholas Lea-Trengrouse, I've tried to pack maximum information into a clean, simple visual design. The goal was to move beyond standard dashboard elements and create a dynamic, single-view snapshot using native visuals (Card, Line Chart) and some creative implementations with HTML & SVG. Key Features & Concepts Explored: ✨ Comprehensive Inventory Snapshot: The widget provides instant visibility into core metrics for the product categories (selectable via a dropdown parameter): 📊 Total Products 📈 Total Sales Qty 📦 On-hand Stock ♻️ Stock Utilization Rate: A clean donut chart highlights the percentage of Stock Utilization, offering a quick gauge of efficiency. ✍️ Dynamic Goal Oriented Text: The summary text changes dynamically to reflect current status, e.g., "Up to Sep, Stock Sales Qty has reached 15400. Highest month sales of Electronics highlighted below." ⛰️ Maximum Value Highlighting: The Line Chart effectively plots monthly sales, & clearly highlight maximum product sales during the period. 🔔 Exploring the Notification Concept (HTML & SVG): A major focus was testing a custom Notification Bell Icon behavior to improve user engagement without cluttering the UI: Active Notifications: If there are notifications, the bell icon animates and displays the count, keeping the focus on the two most recent to maintain layout consistency. No Notifications: The bell would be static, displaying no count. This initial tryout using Native Card visuals, Line Charts, and HTML/SVG for custom elements shows the huge potential for creating highly informative, aesthetically pleasing, and functional single-view dashboards in Power BI. What are your thoughts on this approach? Let's discuss! 👇 #PowerBI #DataVisualization #DashboardDesign #BusinessIntelligence #InventoryManagement #DataAnalytics #WidgetConcept

$500k in spoiled vaccines vs. $50k in preventive tech. The difference? Not just technology—it’s proactive ownership. Some companies: - Depend on manual checks - React after the damage is done - Accept losses as "the cost of business" But the smarter ones? They’re preventing loss before it happens—by embedding real-time monitoring into their cold chain logistics. Here’s how leading providers are doing it with Azure: 1️⃣ IoT sensors are installed in transport containers to monitor temperature and humidity, feeding data directly into Azure IoT Hub. This integration allows logistics companies to access real-time data in their systems without disrupting operations. 2️⃣ Data flows seamlessly into Azure IoT Hub, where pre-configured modules handle the heavy lifting. The configuration syncs easily with ERP and tracking software, so companies avoid a complete tech rebuild while gaining real-time visibility. 3️⃣ Instead of piecing together data from multiple sources, Azure Data Lake acts as a secure, scalable repository. It integrates effortlessly with existing storage, reducing workflow complexity and giving logistics teams a single source of truth. 4️⃣ Then, Azure Databricks processes this data live, with built-in anomaly detection directly aligned with the current machine learning framework. This avoids the need for new workflows, keeping the system efficient and user-friendly. 5️⃣ If a temperature anomaly occurs, Azure Managed Endpoints immediately trigger alerts. Dashboards and mobile apps send notifications through the company’s existing alert systems, ensuring immediate action is taken. The bottom line? If healthcare companies want to reduce risk truly, proactive monitoring with real-time Azure insights is the answer. In a field where every minute matters, this setup safeguards patient health and reputations. Now, how would real-time monitoring fit into your logistics strategy? Share your thoughts below! 👇 #Healthcare #IoT #Azure #Simform #Logistics ==== PS.  Visit my profile, @Hiren, & subscribe to my weekly newsletter: - Get product engineering insights. - Discover proven development strategies. - Catch up on the latest Azure & Gen AI trends.

Series 3: Inside the Planner’s Toolbox – Tactics I’d Bring to Your Team Title: The stockout dashboard that actually changes planner behavior A good dashboard doesn’t just look good — it changes what planners do on Monday morning. I’ve seen plenty of dashboards with beautiful charts but little impact. The visuals were great… the behavior didn’t change. The best dashboards drive action — not admiration. If I were building a stockout visibility view, here’s exactly what I’d include 👇 1️⃣ Days on Hand (DOH): Current inventory ÷ average daily demand over a set time window. Gives immediate visibility into coverage. 2️⃣ Alert thresholds: Conditional formatting when DOH dips below target coverage — say <7 days or <3 days — to flag urgency at a glance. 3️⃣ Days until next receipt: Tie it to open POs. Items with low DOH and long wait times rise straight to the top. 4️⃣ Sortable list: Let planners filter by product family, customer, or priority so focus goes where the risk truly is. Then, the key step — turn it into a ritual: 🔹 Start each day or week reviewing the “red items.” 🔹 Decide: expedite, reallocate, or adjust forecast/safety stock. In past work, this approach cut stockouts meaningfully — not because the data changed, but because it turned information into a clear action list. Dashboards don’t solve problems. People do — when the data makes what matters visible. What’s one dashboard view or habit that’s changed planner behavior for you? #PowerBI #Stockouts #SupplyChainAnalytics #DOH #DemandPlanning

If you're still polling your database every 5 minutes to check for changes, you're doing it wrong. I just published a complete walkthrough on building a MySQL Change Data Capture pipeline in Mage Pro. Now your data pipelines can stream database changes the moment they happen. Stop batch processing when you need real-time data, and start capturing changes as they occur. Here's what you'll learn: ↳ How to configure MySQL for CDC streaming ↳ Setting up the CDC data loader in Mage Pro ↳ Building realistic scenarios for inventory systems ↳ Understanding main configuration parameters Using this approach will: ✅ Eliminate database polling overhead ✅ Reduce latency from minutes to under 1 second ✅ Prevent overselling with instant inventory updates ✅ Enable real-time dashboards for business teams The article includes exact configuration code, explains the main parameters, and shows real-world use cases you can implement today. What's your biggest challenge with real-time data pipelines? 🔔 Follow me for more data engineering tutorials. ♻️ Repost if you think your network will benefit. #dataengineering #sql

A simple 7-step framework to get real-time visibility across your business in 30 days. Growth doesn’t slow down because of bad strategy. It slows down because teams can’t see what’s really happening until it’s too late. When data is delayed, decisions lag. When decisions lag, margins disappear. Here’s how to fix it before the system becomes the bottleneck. Step 1: Map the truth Write out your entire order-to-cash process. Mark every point where data gets re-entered or delayed. Those are your visibility gaps. Step 2: Focus on one critical flow Start small. Choose one high-impact process, like order to shipment, and clean it up first. Quick wins build momentum. Step 3: Standardize your data Define one source of truth for items, customers, pricing, and units. Eliminate duplicate spreadsheets. Make consistency non-negotiable. Step 4: Connect your systems Integrate sales, inventory, purchasing, and finance. Use native connections where possible. Platforms like Acumatica Cloud ERP make this easier than ever. Step 5: Create dashboards that matter Build dashboards that answer real questions. What’s delayed? What’s on target? What needs action today? If a number doesn’t drive a decision, it doesn’t belong on the screen. Step 6: Automate what repeats Repetitive work wastes time. Automate replenishment, report generation, and PO creation directly from sales orders. Step 7: Build daily rhythm Meet for 15 minutes a day to review your live dashboards. Spot issues early. Adjust before problems grow. After 30 days, you’ll see the shift. Fewer manual steps, faster updates, and better decisions backed by real-time data. If you want to go further, I put together a free guide that shows 5 ways to cut your fulfilment time in half using practical Acumatica strategies. Each one can help you streamline and improve visibility across your operation. 📌 You can get it here: https://lnkd.in/gM9gxgQe