Performance Improvement Consulting

Introducing Insights in Chrome DevTools Performance panel! Many web developers know the power of the Chrome DevTools Performance panel, but navigating its wealth of data to pinpoint issues can be daunting. While tools like Lighthouse provide great summaries, they often lack the context of when and where issues occur within a full performance trace. On the Chrome team we're bridging this gap with the new "Insights sidebar" directly within the Performance panel. Read all about it: https://lnkd.in/gGd3bkPw This exciting feature integrates Lighthouse-style analysis right into your workflow. After recording a performance trace, the Insights sidebar appears, offering actionable recommendations. Crucially, it doesn't just list potential problems but highlights relevant events and overlays explanations directly on the performance timeline. Hover over an insight like "LCP by phase," "Render blocking requests" or "Layout shift culprits" to visually connect the suggestion to the specific moments in your trace. The sidebar covers key areas like Largest Contentful Paint (LCP) optimization (including phase breakdowns and request discovery), Interaction to Next Paint (INP) analysis (like DOM size impact and forced reflows), Cumulative Layout Shift (CLS) culprits, and general page load issues such as third-party impact and image optimization. It's designed to make performance debugging more intuitive by linking high-level insights to the granular data, helping you improve Core Web Vitals and overall user experience more effectively. Check out the Insights sidebar in the latest Chrome versions (it's been evolving since Chrome 131!). It’s a fantastic step towards making complex performance analysis more accessible. Give it a try on your next performance audit! #softwareengineering #programming #ai

Reporting is NOT delivering insights. Unfortunately, many data & analytics professionals think it is. Reporting dashboards show WHAT's happening and enable basic slicing and dicing, but fail to deliver WHY. Example - "Performance is down 15% WoW" This is just stating the obvious. It's not a real insight. It's not actionable. This leaves many business leaders frustrated. When business stakeholders ask for more dashboards, what they are ultimately trying to achieve is "I need to know what's impacting my key business metrics and what I should do to improve it". Adding 15 more charts/views/slices won't help much to understand what's impacting the key business metrics and which actions should be taken. The key to REAL INSIGHTS that can move the needle? ROOT-CAUSE ANALYSIS to find the WHY (i.e., DIAGNOSTIC analytics) This is the most effective way to drive change with data & analytics. This can make the data & analytics team a TRUSTED ADVISOR and get a seat at the leadership and decision-making table. Insights need to be: 🟢SPEEDY: business stakeholders need quick insights into performance changes to make decisions before it's too late 🟢PROACTIVE: don't wait for business stakeholders to ask. Monitor key metrics and proactively share insights to become that trusted advisor 🟢IMPACT-ORIENTED: focus on the key drivers that drove most of the change and communicate accordingly 🟢EFFECTIVELY COMMUNICATED to drive the right action #data #analytics #impact #diagnosticanalytics

Is this familiar? A complaint lands. An investigation runs. A finding is made. The case is closed. Six months later, the same team is back in HR. This is the cycle most organisations are trapped in — and it's not a failure of process. It's a failure of diagnosis. The real question isn't "did bullying occur?" It's "what organisational conditions made it inevitable?" Workplace bullying is rarely a rogue individual problem. It is almost always a systems problem wearing an individual's face. Are you managing bullying incidents — or diagnosing the conditions that produce them? The answer to that question defines whether your organisation ever breaks the cycle. Regulators in Australia now expect board-level oversight of psychosocial risks under WHS law. This is no longer purely an HR matter — it's a governance matter. HR's role has shifted from reactive investigator to strategic architect. That means owning the data, leading the governance conversation, and diagnosing the organisational conditions — not just managing the individual cases. The cost of inaction is well documented: diminished productivity and performance, rising psychological injury claims, reputational risk, and the attrition of high-performing talent.

Your data problems aren't actually about data—they're X-rays revealing deeper organizational issues. Data struggles are not just broken dashboards or fragmented databases—they're revelations about how teams collaborate, how decisions flow, and how leadership shapes priorities.  👉 If Finance's spreadsheets can't talk to Marketing's dashboards, it's because Finance and Marketing aren't talking enough.  👉 Overengineered analytics pipelines emerge from fear of making bold decisions.  👉 Meaningless KPIs come from avoiding tough alignment conversations. Think of data health as an organizational early warning system—the cultural canary revealing hidden fault lines. When leadership ignores anomalies or fails to invest in proper governance, what looks like neglected data is actually a mirror of neglected organizational health. If you can't measure customer retention, that's not a data gap—it's a priorities crisis. Here's the kicker: This creates a vicious feedback loop. Poor data drives flawed decisions, which reinforces the problems that created the poor data. Take a marketing department working with unreliable lead attribution—they'll inevitably misallocate resources, deepening organizational inefficiencies and eroding trust in decision-making. When no one trusts the numbers, "the data is broken" becomes a convenient excuse for "We'd rather not face our internal misalignments." Teams retreat to gut instincts and outdated heuristics, further distancing themselves from reliable insights. Left unchecked, this pattern breeds a culture where finger-pointing trumps progress. The path forward requires treating data issues as leadership imperatives: 👉 First, create unified goals that demand cross-functional collaboration—shared KPIs that break down territorial walls. 👉 Second, elevate data literacy to the same level as financial fluency across your organization. 👉 Third, and most crucially, simplify. Complexity isn't sophistication—it's a tax on your organization's agility. The organizations that thrive won't be the ones with the most advanced tech stacks or the biggest data teams. They'll be the ones who recognize that data health and organizational health are two sides of the same coin. You can’t fix organizational issues by fixing the data.

Power BI for Sales Performance Analysis Boosting Sales with Power BI: A Real-Life Success Story   Scenario: Challenge: Our sales team struggled with tracking performance metrics across different regions and product lines. The data was scattered across various sources, making it difficult to get a unified view.   Solution: We implemented Power BI to consolidate sales data from CRM, ERP, and other systems into a single, interactive dashboard.   Steps: 1. Data Integration:    Used Power BI's built-in connectors to pull data from multiple sources.   Example Query:     let         SalesData = Sql.Database("ServerName", "DatabaseName", [Query="SELECT * FROM Sales"])     in         SalesData     2. Data Modeling:   Created relationships between tables to allow for comprehensive analysis.   Example: Linked sales data with regional data to analyze performance by region.   3. Interactive Dashboards:   Designed dashboards to track key metrics like total sales, sales growth, and regional performance.   Features: Drill-down capabilities, slicers for filtering by date, product, and region.   Impact: Improved Visibility: Sales managers now have a clear, real-time view of performance metrics. Faster Decisions: Quick access to data enabled faster decision-making and strategy adjustments. Increased Sales: Identified high-performing regions and focused efforts on underperforming areas, resulting in a 15% sales increase.     Include screenshots of the Power BI dashboard, before-and-after performance metrics, and user testimonials. Have you used Power BI to transform your sales performance? Share your story in the comments!   #PowerBI #Sales #DataVisualization #BusinessIntelligence #TechInnovation #DataDriven

📊 Max Speed Exposure Dashboard – built in the Fundamentals of Load Monitoring Course 📊 This visual is one of the key Power BI dashboards featured in our Fundamentals of Load Monitoring course—in collaboration with Jo Clubb for Sport Horizon UK - designed to help practitioners better understand and manage exposure to high-speed running. But beyond the dashboard… here’s a bit of real-life context 👇 When I was working as a sport scientist in elite football, this exact issue—exposure to max speed—was something we faced constantly: ⚽️ At QPR FC, at times we had players not hitting the required high-speed thresholds, especially those on the fringes or returning from injury. It was a challenge to balance rehab, rotation, and tactical work while ensuring the right physical stimulus. 🌍 At Kerala Blasters FC in India, it became even more complex. The climate, fixture congestion, and travel made it difficult to maintain consistent high-speed exposures. Monitoring was critical to managing fatigue, injury risk, and training load. 🟢 With the London Senior Gaelic football team, we faced a different issue—amateur athletes balancing jobs and travel with training. We had to be smarter with the limited time we had, using simple data tools to guide high-intensity exposures. 👴 And now—playing with the London Masters (Over-40s Gaelic football team)—I feel this challenge myself. We train less, we recover slower, and we’re still competitive. Even at this level, exposing the body safely to higher speeds is a real consideration! That’s why I believe dashboards like this one—tracking % of max speed and days since last high-speed effort—are so valuable. They help guide smarter, safer, and more effective decisions for athletes at every level. 📈 This dashboard is just one example from the course—bringing real-world monitoring issues to life through data and design. #Tableau #PowerBI #SportsAnalytics #DataVisualisation #SportHorizon #SportScience #BespokeInsights #PerformanceAnalysis #DataAnalytics #DataAnalysis #Football #Soccer #Excel #AthleteMonitoring #LoadMonitoring

Across industries, clients are sharing with me that something quiet, yet significant, is unfolding in boardrooms: strategic planning is being fundamentally rethought, not just refreshed. Two signals are driving the shift: 1️⃣ Corporate Restructuring Is Accelerating Kraft Heinz’s decision to split into two companies is just one recent example. We're seeing more leadership teams acknowledge that legacy structures built for scale may now be barriers to growth: nimble entities are far more adaptable in uncertain times. In my own practice, I’m currently working with a large-scale healthcare executive client reorganizing around service-line profitability (not geography), and a fintech firm exploring spinouts to unlock value in client-driven capabilities. Clarity is the new currency and leading strategy discussions. Exclusionary growth-oriented strategies are passe. 2️⃣ Capital Markets Are Opening Back Up Another observation is that IPO momentum is returning. Axios recently reported up to 60 IPOs are expected before year-end. Klarna, Gemini, and others are moving forward, and even mid-market firms are reevaluating M&A plans. One client postponed a deal this summer, not because of funding obstacles, but to sharpen their investor story in light of the competition. The most impactful shift? Strategic planning itself is being rebuilt. Traditional planning models are losing trust and relevance. In today’s politicized and noisy environment, many of my clients are curating their own data ecosystems. Some have added “noise filters” to adjust for narrative manipulation. Others are shortening cycles from annual to rolling 6–9 months. Here are 3 practices I’m seeing among forward-looking orgs: ✅ Scenario Loops over Static Models Dynamic updates based on volatile indicators (commodities, regulation, consumer trust) guide real-time adjustments. ✅ Strategy + Structure Are Now Linked One tech firm redesigned its org chart during its strategy retreat, not 6 months later. ✅ Investor Storytelling Is Part of Planning Especially for firms near funding or IPO, strategic planning now includes a messaging track. My O&G CFO client called it their “Investor GPS.” As you prepare for your next planning cycle, ask: ·       Is our structure aligned for where we’re going, not just where we’ve been? ·       If the capital window opens, are we ready? ·       Are we telling a story the market believes? In 2026, strategy is more abut being directionally clear, structurally agile, and ready to move. #ExecutiveLeadership #StrategicPlanning #CapitalMarkets #IPO #CorporateRestructuring #2026Strategy #BoardLeadership

When a Quality Manager join a new company, how he must start his working in professionally and effectively for improvement , step by step.. *Phase 1: Familiarization and Foundation Building 1. Review Company Policies and Procedures 2. Meet with Key Personnel's of all departments 3. Conduct a thorough tour of the facility to understand operations, identify potential quality risks, and get a sense of the company culture. 4. Examine quality records, including audit reports, customer complaints, and corrective actions to understand the company's quality performance. *Phase 2: Assessment and Gap Analysis 1. Evaluate quality processes, such as inspection, testing, and calibration to identify gaps and inefficiencies. 2. Identify potential quality risks, including supply chain risks, equipment risks, and process risks. 3. Analyze quality data, including defect rates, customer satisfaction, and supplier performance to identify trends and areas for improvement. 4. Develop a comprehensive report outlining the gaps and inefficiencies in the quality management system. *Phase 3: Setting Key Performance Indicators (KPIs) and Targets 1. Establish quality objectives, including defect reduction, customer satisfaction improvement, and supplier performance enhancement. 2. Develop KPIs to measure quality performance, including defect rates, customer satisfaction, and supplier performance. 3. Set targets and benchmarks for each KPI based on industry standards, customer requirements, and company goals. 4. Communicate KPIs and targets to relevant stakeholders, including department heads, supervisors, and quality team members. *Phase 4: Quality improvements plan 1. Prioritize areas for improvement based on the gap analysis report and quality data analysis. 2. Develop corrective actions to address gaps and inefficiencies in the quality management system. 3. Establish timelines and responsibilities for implementing corrective actions. 4. Develop a comprehensive quality improvement plan outlining the corrective actions, timelines, and responsibilities. *Phase 5: Implementation and Monitoring 1. Implement corrective actions outlined in the quality improvement plan. 2. Regularly monitor progress against KPIs and targets. 3. Continuously evaluate and improve the quality management system to ensure it remains effective and efficient. 4. Communicate results to relevant stakeholders, including department heads, supervisors, and quality team members. Countermeasures for inefficiencies- 1. Streamline processes to reduce waste and increase efficiency. 2. Implement lean principles to minimize waste and maximize value. 3. Provide training and development opportunities to enhance employee skills and knowledge. 4. Foster open communication across departments and levels to ensure quality issues are identified and addressed promptly. 5. Conduct regular audits to ensure compliance with quality standards and identify areas for improvement.

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗖𝗔𝗣𝗔: A Powerful Tool for Sustainable Quality Improvement In any manufacturing, product quality and consistency are critical. But despite best efforts, issues do occur — a deviation in production, a packaging defect, or a market complaint. This is when 𝗖𝗔𝗣𝗔 becomes more than just a process — it becomes a commitment to continuous improvement. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗖𝗔𝗣𝗔? 𝗖𝗔𝗣𝗔 stands for Corrective and Preventive Action — a systematic method to: • Identify the root cause of a problem • Take actions to fix it • Prevent it from happening again It’s a key component of any robust Quality Management System (𝗤𝗠𝗦) and essential for operational excellence. 𝗪𝗵𝘆 𝗶𝘀 𝗖𝗔𝗣𝗔 𝗖𝗿𝗶𝘁𝗶𝗰𝗮𝗹? • Ensures product quality and consumer safety • Reduces recurring issues and production downtime • Supports regulatory and certification compliance (ISO, BRC, FDA, etc.) • Enhances team accountability and cross-functional learning • Builds long-term trust with consumers and stakeholders 𝗧𝗵𝗲 𝗖𝗔𝗣𝗔 𝗣𝗿𝗼𝗰𝗲𝘀𝘀: 𝗦𝘁𝗲𝗽 𝗯𝘆 𝗦𝘁𝗲𝗽 𝟭. 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 • Receive and log the issue (complaint, audit non-conformance, or deviation). • Understand where, when, and how it was discovered. 𝟮. 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝗼𝗻 (𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗔𝗰𝘁𝗶𝗼𝗻) • Isolate the affected product or batch. • Inform relevant stakeholders and prevent further distribution. 𝟯. 𝗥𝗼𝗼𝘁 𝗖𝗮𝘂𝘀𝗲 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 • Use structured tools: 5 Whys, Fishbone Diagram, Pareto Analysis • Focus on identifying the true systemic issue, not just symptoms. 𝟰. 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝘃𝗲 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 • Implement targeted solutions to eliminate the root cause. • Examples: process change, retraining, equipment upgrade, supplier improvement. 𝟱. 𝗣𝗿𝗲𝘃𝗲𝗻𝘁𝗶𝘃𝗲 𝗔𝗰𝘁𝗶𝗼𝗻𝘀 • Assess risk across related areas. • Strengthen controls, modify SOPs, or introduce new checks to stop similar issues elsewhere. 𝟲. 𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗻𝗲𝘀𝘀 𝗖𝗵𝗲𝗰𝗸 • Track KPIs and monitor trends. • Audit the implemented changes and ensure sustainability of results. 𝟳. 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 • Record all findings, actions, and decisions. • Good documentation ensures traceability and supports future audits or reviews. 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: A detergent pouch was reported leaking in distribution: • Correction: Recalled affected pouches and halted dispatch. • Root Cause Analysis: Identified sealing temperature inconsistency due to worn-out heating elements. • Corrective Action: Replaced machine components and retrained operators. • Preventive Action: Introduced new validation steps before every shift and added an automated sealing sensor. • Verification: No leakage reported in 3 months of follow-up data. #CAPA #QualityManagement #FMCG #Manufacturing #Compliance #RootCauseAnalysis #ContinuousImprovement #OperationalExcellence #QMS #ProblemSolving #AuditReady

📊 Sales Performance & Profitability Dashboard | End-to-End Analysis 🚀 Project Overview Developed an interactive Sales Performance Dashboard using a 53K+ row transactional dataset to analyze revenue growth, profitability, discount impact, regional performance, and product efficiency. The project focuses on transforming raw sales data into actionable business insights for strategic decision-making. 🔑 Key Business Insights • Generated $2.30M in total revenue with $286K profit, achieving a 12.47% profit margin • Strong year-end sales growth, but profit growth lags due to high discounting • West (38%) and East (32%) regions lead profitability, while the South region underperforms • Technology category drives the highest revenue, but Tables consistently generate losses • Average discount of 15.62% significantly impacts margins beyond safe thresholds • Standard Class shipping delivers the best revenue-to-cost balance 📈 Dashboard Highlights ✔ Monthly Sales & Profit Trends ✔ Category & Sub-Category Profitability Analysis ✔ Discount vs Profit Impact Analysis ✔ Region-wise Profit Contribution ✔ Shipping Mode Performance ✔ Top & Bottom Performing Products 🛠 Tools & Technologies • Excel – Data cleaning, calculations & dashboard design • SQL – KPI aggregation, trend analysis & business queries • Power BI – Interactive visuals, DAX measures & storytelling 🎯 Business Value This dashboard enables businesses to: • Optimize pricing and discount strategies • Improve regional and product-level profitability • Shift from volume-driven to margin-driven growth • Make data-backed decisions with clarity and confidence 📌 Always open to feedback, collaboration, and data-driven discussions. #DataAnalytics #PowerBI #SQL #Excel #BusinessIntelligence #DashboardDesign #DataStorytelling